| Index | index by Group | index by Distribution | index by Vendor | index by creation date | index by Name | Mirrors | Help | Search |
| Name: python3-pandas | Distribution: SUSE Linux Enterprise 15 SP3 |
| Version: 0.23.4 | Vendor: openSUSE |
| Release: bp153.1.1 | Build date: Sat Feb 27 23:04:04 2021 |
| Group: Development/Libraries/Python | Build host: armbuild01 |
| Size: 28969435 | Source RPM: python-pandas-0.23.4-bp153.1.1.src.rpm |
| Packager: https://bugs.opensuse.org | |
| Url: http://pandas.pydata.org/ | |
| Summary: Python module for working with "relational" or "labeled" data | |
pandas is a Python package providing flexible and expressive data structures for working with "relational" or "labeled" data. Documentation is located at http://pandas.pydata.org/pandas-docs/stable/ .
BSD-3-Clause
* Wed Aug 08 2018 jengelh@inai.de
- Ensure neutrality of description. Remove future visions.
Use noun phrase in summary.
* Sat Aug 04 2018 toddrme2178@gmail.com
- Update to 0.23.4
* Python 3.7 with Windows gave all missing values for rolling variance calculations (:issue:`21813`)
* Bug where calling :func:`DataFrameGroupBy.agg` with a list of functions including ``ohlc`` as the non-initial element would raise a ``ValueError`` (:issue:`21716`)
* Bug in ``roll_quantile`` caused a memory leak when calling ``.rolling(...).quantile(q)`` with ``q`` in (0,1) (:issue:`21965`)
* Bug in :func:`Series.clip` and :func:`DataFrame.clip` cannot accept list-like threshold containing ``NaN`` (:issue:`19992`)
* Sat Jul 14 2018 arun@gmx.de
- update to version 0.23.3:
* This release fixes a build issue with the sdist for Python 3.7
(GH21785) There are no other changes.
* Sat Jul 07 2018 arun@gmx.de
- update to version 0.23.2:
* Fixed Regressions
+ Fixed regression in to_csv() when handling file-like object
incorrectly (GH21471)
+ Re-allowed duplicate level names of a MultiIndex. Accessing a
level that has a duplicate name by name still raises an error
(GH19029).
+ Bug in both DataFrame.first_valid_index() and
Series.first_valid_index() raised for a row index having
duplicate values (GH21441)
+ Fixed printing of DataFrames with hierarchical columns with long
names (GH21180)
+ Fixed regression in reindex() and groupby() with a MultiIndex or
multiple keys that contains categorical datetime-like values
(GH21390).
+ Fixed regression in unary negative operations with object dtype
(GH21380)
+ Bug in Timestamp.ceil() and Timestamp.floor() when timestamp is
a multiple of the rounding frequency (GH21262)
+ Fixed regression in to_clipboard() that defaulted to copying
dataframes with space delimited instead of tab delimited
(GH21104)
* Build Changes
+ The source and binary distributions no longer include test data
files, resulting in smaller download sizes. Tests relying on
these data files will be skipped when using
pandas.test(). (GH19320)
* Bug Fixes
* Conversion
+ Bug in constructing Index with an iterator or generator
(GH21470)
+ Bug in Series.nlargest() for signed and unsigned integer dtypes
when the minimum value is present (GH21426)
* Indexing
+ Bug in Index.get_indexer_non_unique() with categorical key
(GH21448)
+ Bug in comparison operations for MultiIndex where error was
raised on equality / inequality comparison involving a
MultiIndex with nlevels == 1 (GH21149)
+ Bug in DataFrame.drop() behaviour is not consistent for unique
and non-unique indexes (GH21494)
+ Bug in DataFrame.duplicated() with a large number of columns
causing a ‘maximum recursion depth exceeded’ (GH21524).
* I/O
+ Bug in read_csv() that caused it to incorrectly raise an error
when nrows=0, low_memory=True, and index_col was not None
(GH21141)
+ Bug in json_normalize() when formatting the record_prefix with
integer columns (GH21536)
* Categorical
+ Bug in rendering Series with Categorical dtype in rare
conditions under Python 2.7 (GH21002)
* Timezones
+ Bug in Timestamp and DatetimeIndex where passing a Timestamp
localized after a DST transition would return a datetime before
the DST transition (GH20854)
+ Bug in comparing DataFrame`s with tz-aware :class:`DatetimeIndex
columns with a DST transition that raised a KeyError (GH19970)
* Timedelta
+ Bug in Timedelta where non-zero timedeltas shorter than 1
microsecond were considered False (GH21484)
* Wed Jun 13 2018 toddrme2178@gmail.com
- Update to 0.23.1
+ Fixed Regressions
* Reverted change to comparing a Series holding datetimes and a datetime.date object
* Reverted the ability of to_sql() to perform multivalue inserts as this caused regression in certain cases (GH21103). In the future this will be made configurable.
* Fixed regression in the DatetimeIndex.date and DatetimeIndex.time attributes in case of timezone-aware data: DatetimeIndex.time returned a tz-aware time instead of tz-naive (GH21267) and DatetimeIndex.date returned incorrect date when the input date has a non-UTC timezone (GH21230).
* Fixed regression in pandas.io.json.json_normalize() when called with None values in nested levels in JSON, and to not drop keys with value as None (GH21158, GH21356).
* Bug in to_csv() causes encoding error when compression and encoding are specified (GH21241, GH21118)
* Bug preventing pandas from being importable with -OO optimization (GH21071)
* Bug in Categorical.fillna() incorrectly raising a TypeError when value the individual categories are iterable and value is an iterable (GH21097, GH19788)
* Fixed regression in constructors coercing NA values like None to strings when passing dtype=str (GH21083)
* Regression in pivot_table() where an ordered Categorical with missing values for the pivot’s index would give a mis-aligned result (GH21133)
* Fixed regression in merging on boolean index/columns (GH21119).
+ Performance Improvements
* Improved performance of CategoricalIndex.is_monotonic_increasing(), CategoricalIndex.is_monotonic_decreasing() and CategoricalIndex.is_monotonic() (GH21025)
* Improved performance of CategoricalIndex.is_unique() (GH21107)
+ Bug fixes
* Groupby/Resample/Rolling
> Bug in DataFrame.agg() where applying multiple aggregation functions to a DataFrame with duplicated column names would cause a stack overflow (GH21063)
> Bug in pandas.core.groupby.GroupBy.ffill() and pandas.core.groupby.GroupBy.bfill() where the fill within a grouping would not always be applied as intended due to the implementations’ use of a non-stable sort (GH21207)
> Bug in pandas.core.groupby.GroupBy.rank() where results did not scale to 100% when specifying method='dense' and pct=True
> Bug in pandas.DataFrame.rolling() and pandas.Series.rolling() which incorrectly accepted a 0 window size rather than raising (GH21286)
* Data-type specific
> Bug in Series.str.replace() where the method throws TypeError on Python 3.5.2 (:issue: 21078)
> Bug in Timedelta: where passing a float with a unit would prematurely round the float precision (:issue: 14156)
> Bug in pandas.testing.assert_index_equal() which raised AssertionError incorrectly, when comparing two CategoricalIndex objects with param check_categorical=False (GH19776)
* Sparse
> Bug in SparseArray.shape which previously only returned the shape SparseArray.sp_values (GH21126)
* Indexing
> Bug in Series.reset_index() where appropriate error was not raised with an invalid level name (GH20925)
> Bug in interval_range() when start/periods or end/periods are specified with float start or end (GH21161)
> Bug in MultiIndex.set_names() where error raised for a MultiIndex with nlevels == 1 (GH21149)
> Bug in IntervalIndex constructors where creating an IntervalIndex from categorical data was not fully supported (GH21243, issue:21253)
> Bug in MultiIndex.sort_index() which was not guaranteed to sort correctly with level=1; this was also causing data misalignment in particular DataFrame.stack() operations (GH20994, GH20945, GH21052)
* Plotting
> New keywords (sharex, sharey) to turn on/off sharing of x/y-axis by subplots generated with pandas.DataFrame().groupby().boxplot() (:issue: 20968)
* I/O
> Bug in IO methods specifying compression='zip' which produced uncompressed zip archives (GH17778, GH21144)
> Bug in DataFrame.to_stata() which prevented exporting DataFrames to buffers and most file-like objects (GH21041)
> Bug in read_stata() and StataReader which did not correctly decode utf-8 strings on Python 3 from Stata 14 files (dta version 118) (GH21244)
> Bug in IO JSON read_json() reading empty JSON schema with orient='table' back to DataFrame caused an error (GH21287)
* Reshaping
> Bug in concat() where error was raised in concatenating Series with numpy scalar and tuple names (GH21015)
> Bug in concat() warning message providing the wrong guidance for future behavior (GH21101)
* Other
> Tab completion on Index in IPython no longer outputs deprecation warnings (GH21125)
> Bug preventing pandas being used on Windows without C++ redistributable installed (GH21106)
* Mon May 21 2018 toddrme2178@gmail.com
- Update dependencies
* Thu May 17 2018 tchvatal@suse.com
- Update to 0.23.0:
* Round-trippable JSON format with ‘table’ orient.
* Instantiation from dicts respects order for Python 3.6+.
* Dependent column arguments for assign.
* Merging / sorting on a combination of columns and index levels.
* Extending Pandas with custom types.
* Excluding unobserved categories from groupby.
* Changes to make output shape of DataFrame.apply consistent.
* Thu May 17 2018 tchvatal@suse.com
- Do not bother generating pandas doc if it is already in both
html and pdf provided by upstream, just point to the URL
* Thu Jan 11 2018 tchvatal@suse.com
- Drop commented code to allow us py3 only build
* Wed Jan 03 2018 arun@gmx.de
- specfile:
* update copyright year
- update to version 0.22.0:
* Pandas 0.22.0 changes the handling of empty and all-NA sums and
products. The summary is that
+ The sum of an empty or all-NA Series is now 0
+ The product of an empty or all-NA Series is now 1
+ We’ve added a min_count parameter to .sum() and .prod()
controlling the minimum number of valid values for the result to
be valid. If fewer than min_count non-NA values are present, the
result is NA. The default is 0. To return NaN, the 0.21
behavior, use min_count=1.
* Sat Dec 16 2017 arun@gmx.de
- update to version 0.21.1:
* Highlights include:
+ Temporarily restore matplotlib datetime plotting
functionality. This should resolve issues for users who
implicitly relied on pandas to plot datetimes with
matplotlib. See here.
+ Improvements to the Parquet IO functions introduced in
0.21.0. See here.
* Improvements to the Parquet IO functionality
+ DataFrame.to_parquet() will now write non-default indexes when
the underlying engine supports it. The indexes will be preserved
when reading back in with read_parquet() (GH18581).
+ read_parquet() now allows to specify the columns to read from a
parquet file (GH18154)
+ read_parquet() now allows to specify kwargs which are passed to
the respective engine (GH18216)
* Other Enhancements
+ Timestamp.timestamp() is now available in Python 2.7. (GH17329)
+ Grouper and TimeGrouper now have a friendly repr output
(GH18203).
* Deprecations
+ pandas.tseries.register has been renamed to
pandas.plotting.register_matplotlib_converters`() (GH18301)
* Performance Improvements
+ Improved performance of plotting large series/dataframes
(GH18236).
* Conversion
+ Bug in TimedeltaIndex subtraction could incorrectly overflow
when NaT is present (GH17791)
+ Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex
could fail to overflow (GH18020)
+ Bug in IntervalIndex.copy() when copying and IntervalIndex with
non-default closed (GH18339)
+ Bug in DataFrame.to_dict() where columns of datetime that are
tz-aware were not converted to required arrays when used with
orient='records', raising"TypeError` (GH18372)
+ Bug in DateTimeIndex and date_range() where mismatching tz-aware
start and end timezones would not raise an err if end.tzinfo is
None (GH18431)
+ Bug in Series.fillna() which raised when passed a long integer
on Python 2 (GH18159).
* Indexing
+ Bug in a boolean comparison of a datetime.datetime and a
datetime64[ns] dtype Series (GH17965)
+ Bug where a MultiIndex with more than a million records was not
raising AttributeError when trying to access a missing attribute
(GH18165)
+ Bug in IntervalIndex constructor when a list of intervals is
passed with non-default closed (GH18334)
+ Bug in Index.putmask when an invalid mask passed (GH18368)
+ Bug in masked assignment of a timedelta64[ns] dtype Series,
incorrectly coerced to float (GH18493)
* I/O
+ Bug in class:~pandas.io.stata.StataReader not converting
date/time columns with display formatting addressed
(GH17990). Previously columns with display formatting were
normally left as ordinal numbers and not converted to datetime
objects.
+ Bug in read_csv() when reading a compressed UTF-16 encoded file
(GH18071)
+ Bug in read_csv() for handling null values in index columns when
specifying na_filter=False (GH5239)
+ Bug in read_csv() when reading numeric category fields with high
cardinality (GH18186)
+ Bug in DataFrame.to_csv() when the table had MultiIndex columns,
and a list of strings was passed in for header (GH5539)
+ Bug in parsing integer datetime-like columns with specified
format in read_sql (GH17855).
+ Bug in DataFrame.to_msgpack() when serializing data of the
numpy.bool_ datatype (GH18390)
+ Bug in read_json() not decoding when reading line deliminted
JSON from S3 (GH17200)
+ Bug in pandas.io.json.json_normalize() to avoid modification of
meta (GH18610)
+ Bug in to_latex() where repeated multi-index values were not
printed even though a higher level index differed from the
previous row (GH14484)
+ Bug when reading NaN-only categorical columns in HDFStore
(GH18413)
+ Bug in DataFrame.to_latex() with longtable=True where a latex
multicolumn always spanned over three columns (GH17959)
* Plotting
+ Bug in DataFrame.plot() and Series.plot() with DatetimeIndex
where a figure generated by them is not pickleable in Python 3
(GH18439)
* Groupby/Resample/Rolling
+ Bug in DataFrame.resample(...).apply(...) when there is a
callable that returns different columns (GH15169)
+ Bug in DataFrame.resample(...) when there is a time change (DST)
and resampling frequecy is 12h or higher (GH15549)
+ Bug in pd.DataFrameGroupBy.count() when counting over a
datetimelike column (GH13393)
+ Bug in rolling.var where calculation is inaccurate with a
zero-valued array (GH18430)
* Reshaping
+ Error message in pd.merge_asof() for key datatype mismatch now
includes datatype of left and right key (GH18068)
+ Bug in pd.concat when empty and non-empty DataFrames or Series
are concatenated (GH18178 GH18187)
+ Bug in DataFrame.filter(...) when unicode is passed as a
condition in Python 2 (GH13101)
+ Bug when merging empty DataFrames when np.seterr(divide='raise')
is set (GH17776)
* Numeric
+ Bug in pd.Series.rolling.skew() and rolling.kurt() with all
equal values has floating issue (GH18044)
+ Bug in TimedeltaIndex subtraction could incorrectly overflow
when NaT is present (GH17791)
+ Bug in DatetimeIndex subtracting datetimelike from DatetimeIndex
could fail to overflow (GH18020)
* Categorical
+ Bug in DataFrame.astype() where casting to ‘category’ on an
empty DataFrame causes a segmentation fault (GH18004)
+ Error messages in the testing module have been improved when
items have different CategoricalDtype (GH18069)
+ CategoricalIndex can now correctly take a
pd.api.types.CategoricalDtype as its dtype (GH18116)
+ Bug in Categorical.unique() returning read-only codes array when
all categories were NaN (GH18051)
+ Bug in DataFrame.groupby(axis=1) with a CategoricalIndex
(GH18432)
* String
+ Series.str.split() will now propogate NaN values across all
expanded columns instead of None (GH18450)
* Mon Oct 30 2017 arun@gmx.de
- specfile:
* updated minimum numpy version to 1.9.0 (see setup.py)
- update to version 0.21.0:
* Highlights include:
+ Integration with Apache Parquet, including a new top-level
read_parquet() function and DataFrame.to_parquet() method, see
here.
+ New user-facing pandas.api.types.CategoricalDtype for specifying
categoricals independent of the data, see here.
+ The behavior of sum and prod on all-NaN Series/DataFrames is now
consistent and no longer depends on whether bottleneck is
installed, see here.
+ Compatibility fixes for pypy, see here.
+ Additions to the drop, reindex and rename API to make them more
consistent, see here.
+ Addition of the new methods DataFrame.infer_objects (see here)
and GroupBy.pipe (see here).
+ Indexing with a list of labels, where one or more of the labels
is missing, is deprecated and will raise a KeyError in a future
version, see here.
* full list at http://pandas.pydata.org/pandas-docs/stable/whatsnew.html
* Sat Sep 23 2017 arun@gmx.de
- update to version 0.20.3:
* bug fix release, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-20-3-july-7-2017
for complete changelog
- changes from version 0.20.2:
* bug fix release, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-20-2-june-4-2017
for complete changelog
* Thu May 18 2017 toddrme2178@gmail.com
- Update to version 0.20.1
Highlights include:
* New ``.agg()`` API for Series/DataFrame similar to the
groupby-rolling-resample API's
* Integration with the ``feather-format``, including a new
top-level ``pd.read_feather()`` and ``DataFrame.to_feather()``
method
* The ``.ix`` indexer has been deprecated
* ``Panel`` has been deprecated
* Addition of an ``IntervalIndex`` and ``Interval`` scalar type
* Improved user API when grouping by index levels in ``.groupby()``
* Improved support for ``UInt64`` dtypes
* A new orient for JSON serialization, ``orient='table'``, that
uses the Table Schema spec and that gives the possibility for
a more interactive repr in the Jupyter Notebook
* Experimental support for exporting styled DataFrames
(``DataFrame.style``) to Excel
* Window binary corr/cov operations now return a MultiIndexed
``DataFrame`` rather than a ``Panel``, as ``Panel`` is now
deprecated
* Support for S3 handling now uses ``s3fs``
* Google BigQuery support now uses the ``pandas-gbq`` library
* Mon May 08 2017 toddrme2178@gmail.com
- Fix dateutil dependency
* Tue Apr 25 2017 toddrme2178@gmail.com
- Implement single-spec version.
* Thu Mar 30 2017 toddrme2178@gmail.com
- update to version 0.19.2:
* Enhancements
The pd.merge_asof(), added in 0.19.0, gained some improvements:
+ pd.merge_asof() gained left_index/right_index and
left_by/right_by arguments (GH14253)
+ pd.merge_asof() can take multiple columns in by parameter and
has specialized dtypes for better performace (GH13936)
* Performance Improvements
+ Performance regression with PeriodIndex (GH14822)
+ Performance regression in indexing with getitem (GH14930)
+ Improved performance of .replace() (GH12745)
+ Improved performance Series creation with a datetime index and
dictionary data (GH14894)
* Bug Fixes
+ Compat with python 3.6 for pickling of some offsets (GH14685)
+ Compat with python 3.6 for some indexing exception types
(GH14684, GH14689)
+ Compat with python 3.6 for deprecation warnings in the test
suite (GH14681)
+ Compat with python 3.6 for Timestamp pickles (GH14689)
+ Compat with dateutil==2.6.0; segfault reported in the testing
suite (GH14621)
+ Allow nanoseconds in Timestamp.replace as a kwarg (GH14621)
+ Bug in pd.read_csv in which aliasing was being done for
na_values when passed in as a dictionary (GH14203)
+ Bug in pd.read_csv in which column indices for a dict-like
na_values were not being respected (GH14203)
+ Bug in pd.read_csv where reading files fails, if the number of
headers is equal to the number of lines in the file (GH14515)
+ Bug in pd.read_csv for the Python engine in which an unhelpful
error message was being raised when multi-char delimiters were
not being respected with quotes (GH14582)
+ Fix bugs (GH14734, GH13654) in pd.read_sas and
pandas.io.sas.sas7bdat.SAS7BDATReader that caused problems when
reading a SAS file incrementally.
+ Bug in pd.read_csv for the Python engine in which an unhelpful
error message was being raised when skipfooter was not being
respected by Python’s CSV library (GH13879)
+ Bug in .fillna() in which timezone aware datetime64 values were
incorrectly rounded (GH14872)
+ Bug in .groupby(..., sort=True) of a non-lexsorted MultiIndex
when grouping with multiple levels (GH14776)
+ Bug in pd.cut with negative values and a single bin (GH14652)
+ Bug in pd.to_numeric where a 0 was not unsigned on a
downcast='unsigned' argument (GH14401)
+ Bug in plotting regular and irregular timeseries using shared
axes (sharex=True or ax.twinx()) (GH13341, GH14322).
+ Bug in not propogating exceptions in parsing invalid datetimes,
noted in python 3.6 (GH14561)
+ Bug in resampling a DatetimeIndex in local TZ, covering a DST
change, which would raise AmbiguousTimeError (GH14682)
+ Bug in indexing that transformed RecursionError into KeyError or
IndexingError (GH14554)
+ Bug in HDFStore when writing a MultiIndex when using
data_columns=True (GH14435)
+ Bug in HDFStore.append() when writing a Series and passing a
min_itemsize argument containing a value for the index (GH11412)
+ Bug when writing to a HDFStore in table format with a
min_itemsize value for the index and without asking to append
(GH10381)
+ Bug in Series.groupby.nunique() raising an IndexError for an
empty Series (GH12553)
+ Bug in DataFrame.nlargest and DataFrame.nsmallest when the index
had duplicate values (GH13412)
+ Bug in clipboard functions on linux with python2 with unicode
and separators (GH13747)
+ Bug in clipboard functions on Windows 10 and python 3 (GH14362,
GH12807)
+ Bug in .to_clipboard() and Excel compat (GH12529)
+ Bug in DataFrame.combine_first() for integer columns (GH14687).
+ Bug in pd.read_csv() in which the dtype parameter was not being
respected for empty data (GH14712)
+ Bug in pd.read_csv() in which the nrows parameter was not being
respected for large input when using the C engine for parsing
(GH7626)
+ Bug in pd.merge_asof() could not handle timezone-aware
DatetimeIndex when a tolerance was specified (GH14844)
+ Explicit check in to_stata and StataWriter for out-of-range
values when writing doubles (GH14618)
+ Bug in .plot(kind='kde') which did not drop missing values to
generate the KDE Plot, instead generating an empty
plot. (GH14821)
+ Bug in unstack() if called with a list of column(s) as an
argument, regardless of the dtypes of all columns, they get
coerced to object (GH11847)
- update to version 0.19.1:
* Performance Improvements
+ Fixed performance regression in factorization of Period data
(GH14338)
+ Fixed performance regression in Series.asof(where) when where is
a scalar (GH14461)
+ Improved performance in DataFrame.asof(where) when where is a
scalar (GH14461)
+ Improved performance in .to_json() when lines=True (GH14408)
+ Improved performance in certain types of loc indexing with a
MultiIndex (GH14551).
* Bug Fixes
+ Source installs from PyPI will now again work without cython
installed, as in previous versions (GH14204)
+ Compat with Cython 0.25 for building (GH14496)
+ Fixed regression where user-provided file handles were closed in
read_csv (c engine) (GH14418).
+ Fixed regression in DataFrame.quantile when missing values where
present in some columns (GH14357).
+ Fixed regression in Index.difference where the freq of a
DatetimeIndex was incorrectly set (GH14323)
+ Added back pandas.core.common.array_equivalent with a
deprecation warning (GH14555).
+ Bug in pd.read_csv for the C engine in which quotation marks
were improperly parsed in skipped rows (GH14459)
+ Bug in pd.read_csv for Python 2.x in which Unicode quote
characters were no longer being respected (GH14477)
+ Fixed regression in Index.append when categorical indices were
appended (GH14545).
+ Fixed regression in pd.DataFrame where constructor fails when
given dict with None value (GH14381)
+ Fixed regression in DatetimeIndex._maybe_cast_slice_bound when
index is empty (GH14354).
+ Bug in localizing an ambiguous timezone when a boolean is passed
(GH14402)
+ Bug in TimedeltaIndex addition with a Datetime-like object where
addition overflow in the negative direction was not being caught
(GH14068, GH14453)
+ Bug in string indexing against data with object Index may raise
AttributeError (GH14424)
+ Corrrecly raise ValueError on empty input to pd.eval() and
df.query() (GH13139)
+ Bug in RangeIndex.intersection when result is a empty set
(GH14364).
+ Bug in groupby-transform broadcasting that could cause incorrect
dtype coercion (GH14457)
+ Bug in Series.__setitem__ which allowed mutating read-only
arrays (GH14359).
+ Bug in DataFrame.insert where multiple calls with duplicate
columns can fail (GH14291)
+ pd.merge() will raise ValueError with non-boolean parameters in
passed boolean type arguments (GH14434)
+ Bug in Timestamp where dates very near the minimum (1677-09)
could underflow on creation (GH14415)
+ Bug in pd.concat where names of the keys were not propagated to
the resulting MultiIndex (GH14252)
+ Bug in pd.concat where axis cannot take string parameters 'rows'
or 'columns' (GH14369)
+ Bug in pd.concat with dataframes heterogeneous in length and
tuple keys (GH14438)
+ Bug in MultiIndex.set_levels where illegal level values were
still set after raising an error (GH13754)
+ Bug in DataFrame.to_json where lines=True and a value contained
a } character (GH14391)
+ Bug in df.groupby causing an AttributeError when grouping a
single index frame by a column and the index level
(:issue`14327`)
+ Bug in df.groupby where TypeError raised when
pd.Grouper(key=...) is passed in a list (GH14334)
+ Bug in pd.pivot_table may raise TypeError or ValueError when
index or columns is not scalar and values is not specified
(GH14380)
* Sun Oct 23 2016 toddrme2178@gmail.com
- update to version 0.19.0:
(long changelog, see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-19-0-october-2-2016)
* Highlights include:
+ merge_asof() for asof-style time-series joining
+ .rolling() is now time-series aware
+ read_csv() now supports parsing Categorical data
+ A function union_categorical() has been added for combining
categoricals
+ PeriodIndex now has its own period dtype, and changed to be more
consistent with other Index classes
+ Sparse data structures gained enhanced support of int and bool
dtypes
+ Comparison operations with Series no longer ignores the index,
see here for an overview of the API changes.
+ Introduction of a pandas development API for utility functions
+ Deprecation of Panel4D and PanelND. We recommend to represent
these types of n-dimensional data with the xarray package.
+ Removal of the previously deprecated modules pandas.io.data,
pandas.io.wb, pandas.tools.rplot.
- specfile:
* require python3-Cython
* Split documentation into own subpackage to speed up build.
* Remove buildrequires for optional dependencies to speed up build.
- Remove unneeded patches:
* 0001_disable_experimental_msgpack_big_endian.patch ^
* 0001_respect_byteorder_in_statareader.patch
* Tue Jul 12 2016 antoine.belvire@laposte.net
- Update to 0.8.1:
* .groupby(...) has been enhanced to provide convenient syntax
when working with .rolling(..), .expanding(..) and
.resample(..) per group.
* pd.to_datetime() has gained the ability to assemble dates
from a DataFrame.
* Method chaining improvements.
* Custom business hour offset.
* Many bug fixes in the handling of sparse.
* Expanded the Tutorials section with a feature on modern pandas,
courtesy of @TomAugsb (GH13045).
- Changes from 0.8.0:
* Moving and expanding window functions are now methods on Series
and DataFrame, similar to .groupby.
* Adding support for a RangeIndex as a specialized form of the
Int64Index for memory savings.
* API breaking change to the .resample method to make it more
.groupby like.
* Removal of support for positional indexing with floats, which
was deprecated since 0.14.0. This will now raise a TypeError.
* The .to_xarray() function has been added for compatibility with
the xarray package.
* The read_sas function has been enhanced to read sas7bdat files.
* Addition of the .str.extractall() method, and API changes to
the .str.extract() method and .str.cat() method.
* pd.test() top-level nose test runner is available (GH4327).
* Fri Feb 26 2016 tbechtold@suse.com
- Require python-python-dateutil. package was renamed
* Tue Feb 09 2016 aplanas@suse.com
- Add 0001_respect_byteorder_in_statareader.patch
Fix StataReader in big endian architectures
https://github.com/pydata/pandas/issues/11282
- Add 0001_disable_experimental_msgpack_big_endian.patch
Skip experimental msgpack test in big endian systems
* Wed Feb 03 2016 aplanas@suse.com
- Remove non-needed BuildRequires
- Update Requires from documentation
- Update Recommends from documentation
- Add tests in %check section
* Mon Nov 30 2015 toddrme2178@gmail.com
- update to version 0.17.1:
(for full changelog see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-17-1-november-21-2015)
Highlights include:
* Support for Conditional HTML Formatting, see here
* Releasing the GIL on the csv reader & other ops, see here
* Fixed regression in DataFrame.drop_duplicates from 0.16.2, causing
incorrect results on integer values (GH11376)
* Mon Oct 12 2015 toddrme2178@gmail.com
- update to version 0.17.0:
(for full changelog see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-17-0-october-9-2015)
Highlights:
* Release the Global Interpreter Lock (GIL) on some cython
operations, see here
* Plotting methods are now available as attributes of the .plot
accessor, see here
* The sorting API has been revamped to remove some long-time
inconsistencies, see here
* Support for a datetime64[ns] with timezones as a first-class
dtype, see here
* The default for to_datetime will now be to raise when presented
with unparseable formats, previously this would return the
original input. Also, date parse functions now return consistent
results. See here
* The default for dropna in HDFStore has changed to False, to store
by default all rows even if they are all NaN, see here
* Datetime accessor (dt) now supports Series.dt.strftime to generate
formatted strings for datetime-likes, and Series.dt.total_seconds
to ge nerate each duration of the timedelta in seconds. See here
* Period and PeriodIndex can handle multiplied freq like 3D, which
corresponding to 3 days span. See here
* Development installed versions of pandas will now have PEP440
compliant version strings (GH9518)
* Development support for benchmarking with the Air Speed Velocity
library (GH8361)
* Support for reading SAS xport files, see here
* Documentation comparing SAS to pandas, see here
* Removal of the automatic TimeSeries broadcasting, deprecated since
0.8.0, see here
* Display format with plain text can optionally align with Unicode
East Asian Width, see here
* Compatibility with Python 3.5 (GH11097)
* Compatibility with matplotlib 1.5.0 (GH11111)
* Mon Jun 29 2015 toddrme2178@gmail.com
- update to version 0.16.2:
(see http://pandas.pydata.org/pandas-docs/stable/whatsnew.html#v0-16-2-june-12-2015)
* Highlights
+ A new pipe method
+ Documentation on how to use numba with pandas
* Enhancements
+ Added rsplit to Index/Series StringMethods (GH10303)
+ Removed the hard-coded size limits on the DataFrame HTML
representation in the IPython notebook, and leave this to
IPython itself (only for IPython v3.0 or greater). This
eliminates the duplicate scroll bars that appeared in the
notebook with large frames (GH10231).
Note that the notebook has a toggle output scrolling feature to
limit the display of very large frames (by clicking left of the
output). You can also configure the way DataFrames are displayed
using the pandas options, see here here.
+ axis parameter of DataFrame.quantile now accepts also index and
column. (GH9543)
* API Changes
+ Holiday now raises NotImplementedError if both offset and
observance are used in the constructor instead of returning an
incorrect result (GH10217).
* Performance Improvements
+ Improved Series.resample performance with dtype=datetime64[ns]
(GH7754)
+ Increase performance of str.split when expand=True (GH10081)
* Bug Fixes
+ Bug in Series.hist raises an error when a one row Series was
given (GH10214)
+ Bug where HDFStore.select modifies the passed columns list
(GH7212)
+ Bug in Categorical repr with display.width of None in Python 3
(GH10087)
+ Bug in to_json with certain orients and a CategoricalIndex would
segfault (GH10317)
+ Bug where some of the nan funcs do not have consistent return
dtypes (GH10251)
+ Bug in DataFrame.quantile on checking that a valid axis was
passed (GH9543)
+ Bug in groupby.apply aggregation for Categorical not preserving
categories (GH10138)
+ Bug in to_csv where date_format is ignored if the datetime is
fractional (GH10209)
+ Bug in DataFrame.to_json with mixed data types (GH10289)
+ Bug in cache updating when consolidating (GH10264)
+ Bug in mean() where integer dtypes can overflow (GH10172)
+ Bug where Panel.from_dict does not set dtype when specified
(GH10058)
+ Bug in Index.union raises AttributeError when passing
array-likes. (GH10149)
+ Bug in Timestamp‘s’ microsecond, quarter, dayofyear, week and
daysinmonth properties return np.int type, not built-in
int. (GH10050)
+ Bug in NaT raises AttributeError when accessing to daysinmonth,
dayofweek properties. (GH10096)
+ Bug in Index repr when using the max_seq_items=None setting
(GH10182).
+ Bug in getting timezone data with dateutil on various platforms
( GH9059, GH8639, GH9663, GH10121)
+ Bug in displaying datetimes with mixed frequencies; display ‘ms’
datetimes to the proper precision. (GH10170)
+ Bug in setitem where type promotion is applied to the entire
block (GH10280)
+ Bug in Series arithmetic methods may incorrectly hold names
(GH10068)
+ Bug in GroupBy.get_group when grouping on multiple keys, one of
which is categorical. (GH10132)
+ Bug in DatetimeIndex and TimedeltaIndex names are lost after
timedelta arithmetics ( GH9926)
+ Bug in DataFrame construction from nested dict with datetime64
(GH10160)
+ Bug in Series construction from dict with datetime64 keys
(GH9456)
+ Bug in Series.plot(label="LABEL") not correctly setting the
label (GH10119)
+ Bug in plot not defaulting to matplotlib axes.grid setting
(GH9792)
+ Bug causing strings containing an exponent, but no decimal to be
parsed as int instead of float in engine='python' for the read_csv
parser (GH9565)
+ Bug in Series.align resets name when fill_value is specified
(GH10067)
+ Bug in read_csv causing index name not to be set on an empty
DataFrame (GH10184)
+ Bug in SparseSeries.abs resets name (GH10241)
+ Bug in TimedeltaIndex slicing may reset freq (GH10292)
+ Bug in GroupBy.get_group raises ValueError when group key
contains NaT (GH6992)
+ Bug in SparseSeries constructor ignores input data name
(GH10258)
+ Bug in Categorical.remove_categories causing a ValueError when
removing the NaN category if underlying dtype is floating-point
(GH10156)
+ Bug where infer_freq infers timerule (WOM-5XXX) unsupported by
to_offset (GH9425)
+ Bug in DataFrame.to_hdf() where table format would raise a
seemingly unrelated error for invalid (non-string) column
names. This is now explicitly forbidden. (GH9057)
+ Bug to handle masking empty DataFrame (GH10126).
+ Bug where MySQL interface could not handle numeric table/column
names (GH10255)
+ Bug in read_csv with a date_parser that returned a datetime64
array of other time resolution than [ns] (GH10245)
+ Bug in Panel.apply when the result has ndim=0 (GH10332)
+ Bug in read_hdf where auto_close could not be passed (GH9327).
+ Bug in read_hdf where open stores could not be used (GH10330).
+ Bug in adding empty DataFrame``s, now results in a ``DataFrame
that .equals an empty DataFrame (GH10181).
+ Bug in to_hdf and HDFStore which did not check that complib
choices were valid (GH4582, GH8874).
* Tue May 19 2015 toddrme2178@gmail.com
- Update to version 0.16.1
* Highlights
- Support for a ``CategoricalIndex``, a category based index
- New section on how-to-contribute to pandas
- Revised "Merge, join, and concatenate" documentation,
including graphical examples to make it easier to understand
each operations
- New method sample for drawing random samples from Series,
DataFrames and Panels.
- The default Index printing has changed to a more uniform
format
- BusinessHour datetime-offset is now supported
* Enhancements
- BusinessHour`offset is now supported, which represents
business hours starting from 09:00 - 17:00 on BusinessDay by
default.
- DataFrame.diff now takes an axis parameter that determines the
direction of differencing
- Allow clip, clip_lower, and clip_upper to accept array-like
arguments as thresholds (This is a regression from 0.11.0).
These methods now have an axis parameter which determines
how the Series or DataFrame will be aligned with the
threshold(s).
- DataFrame.mask() and Series.mask() now support same keywords
as where
- drop function can now accept errors keyword to suppress
ValueError raised when any of label does not exist in the
target data.
- Allow conversion of values with dtype datetime64 or timedelta64
to strings using astype(str)
- get_dummies function now accepts sparse keyword. If set to
True, the return DataFrame is sparse, e.g. SparseDataFrame.
- Period now accepts datetime64 as value input.
- Allow timedelta string conversion when leading zero is
missing from time definition, ie 0:00:00 vs 00:00:00.
- Allow Panel.shift with axis='items'
- Trying to write an excel file now raises NotImplementedError
if the DataFrame has a MultiIndex instead of writing a broken
Excel file.
- Allow Categorical.add_categories to accept Series or np.array.
- Add/delete str/dt/cat accessors dynamically from __dir__.
- Add normalize as a dt accessor method.
- DataFrame and Series now have _constructor_expanddim property
as overridable constructor for one higher dimensionality
data. This should be used only when it is really needed
- pd.lib.infer_dtype now returns 'bytes' in Python 3 where
appropriate.
- We introduce a CategoricalIndex, a new type of index object
that is useful for supporting indexing with duplicates. This
is a container around a Categorical (introduced in v0.15.0)
and allows efficient indexing and storage of an index with a
large number of duplicated elements. Prior to 0.16.1,
setting the index of a DataFrame/Series with a category
dtype would convert this to regular object-based Index.
- Series, DataFrames, and Panels now have a new method:
pandas.DataFrame.sample. The method accepts a specific number
of rows or columns to return, or a fraction of the total
number or rows or columns. It also has options for sampling
with or without replacement, for passing in a column for
weights for non-uniform sampling, and for setting seed values
to facilitate replication.
- The following new methods are accesible via .str accessor to
apply the function to each values.
+ capitalize()
+ swapcase()
+ normalize()
+ partition()
+ rpartition()
+ index()
+ rindex()
+ translate()
- Added StringMethods (.str accessor) to Index
- split now takes expand keyword to specify whether to expand
dimensionality. return_type is deprecated.
* API changes
- When passing in an ax to df.plot( ..., ax=ax), the sharex
kwarg will now default to False.
- Add support for separating years and quarters using dashes,
for example 2014-Q1.
- pandas.DataFrame.assign now inserts new columns in
alphabetical order. Previously the order was arbitrary.
- By default, read_csv and read_table will now try to infer
the compression type based on the file extension. Set
compression=None to restore the previous behavior
(no decompression).
- The string representation of Index and its sub-classes have
now been unified. These will show a single-line display if
there are few values; a wrapped multi-line display for a lot
of values (but less than display.max_seq_items; if lots of
items > display.max_seq_items) will show a truncated display
(the head and tail of the data). The formatting for
MultiIndex is unchanges (a multi-line wrapped display). The
display width responds to the option display.max_seq_items,
which is defaulted to 100.
* Deprecations
- Series.str.split's return_type keyword was removed in favor
of expand
* Performance Improvements
- Improved csv write performance with mixed dtypes, including
datetimes by up to 5x
- Improved csv write performance generally by 2x
- Improved the performance of pd.lib.max_len_string_array
by 5-7x
* Bug Fixes
- Bug where labels did not appear properly in the legend of
DataFrame.plot(), passing label= arguments works, and Series
indices are no longer mutated.
- Bug in json serialization causing a segfault when a frame had
zero length.
- Bug in read_csv where missing trailing delimiters would cause
segfault.
- Bug in retaining index name on appending
- Bug in scatter_matrix draws unexpected axis ticklabels
- Fixed bug in StataWriter resulting in changes to input
DataFrame upon save.
- Bug in transform causing length mismatch when null entries
were present and a fast aggregator was being used
- Bug in equals causing false negatives when block order
differed
- Bug in grouping with multiple pd.Grouper where one is
non-time based
- Bug in read_sql_table error when reading postgres table with
timezone
- Bug in DataFrame slicing may not retain metadata
- Bug where TimdeltaIndex were not properly serialized in fixed
HDFStore
- Bug with TimedeltaIndex constructor ignoring name when given
another TimedeltaIndex as data.
- Bug in DataFrameFormatter._get_formatted_index with not
applying max_colwidth to the DataFrame index
- Bug in .loc with a read-only ndarray data source
- Bug in groupby.apply() that would raise if a passed user
defined function either returned only None (for all input).
- Always use temporary files in pytables tests
- Bug in plotting continuously using secondary_y may not show
legend properly.
- Bug in DataFrame.plot(kind="hist") results in TypeError when
DataFrame contains non-numeric columns
- Bug where repeated plotting of DataFrame with a DatetimeIndex
may raise TypeError
- Bug in setup.py that would allow an incompat cython version
to build
- Bug in plotting secondary_y incorrectly attaches right_ax
property to secondary axes specifying itself recursively.
- Bug in Series.quantile on empty Series of type Datetime or
Timedelta
- Bug in where causing incorrect results when upcasting was
required
- Bug in FloatArrayFormatter where decision boundary for
displaying "small" floats in decimal format is off by one
order of magnitude for a given display.precision
- Fixed bug where DataFrame.plot() raised an error when both
color and style keywords were passed and there was no color
symbol in the style strings
- Not showing a DeprecationWarning on combining list-likes with
an Index
- Bug in read_csv and read_table when using skip_rows parameter
if blank lines are present.
- Bug in read_csv() interprets index_col=True as 1
- Bug in index equality comparisons using == failing on
Index/MultiIndex type incompatibility
- Bug in which SparseDataFrame could not take nan as a column
name
- Bug in to_msgpack and read_msgpack zlib and blosc compression
support
- Bug GroupBy.size doesn't attach index name properly if
grouped by TimeGrouper
- Bug causing an exception in slice assignments because
length_of_indexer returns wrong results
- Bug in csv parser causing lines with initial whitespace plus
one non-space character to be skipped.
- Bug in C csv parser causing spurious NaNs when data started
with newline followed by whitespace.
- Bug causing elements with a null group to spill into the
final group when grouping by a Categorical
- Bug where .iloc and .loc behavior is not consistent on empty
dataframes
- Bug in invalid attribute access on a TimedeltaIndex
incorrectly raised ValueError instead of AttributeError
- Bug in unequal comparisons between categorical data and a
scalar, which was not in the categories (e.g.
Series(Categorical(list("abc"), ordered=True)) > "d". This
returned False for all elements, but now raises a TypeError.
Equality comparisons also now return False for == and True
for !=.
- Bug in DataFrame __setitem__ when right hand side is a
dictionary
- Bug in where when dtype is datetime64/timedelta64, but dtype
of other is not
- Bug in MultiIndex.sortlevel() results in unicode level name
breaks
- Bug in which groupby.transform incorrectly enforced output
dtypes to match input dtypes.
- Bug in DataFrame constructor when columns parameter is set,
and data is an empty list
- Bug in bar plot with log=True raises TypeError if all values
are less than 1
- Bug in horizontal bar plot ignores log=True
- Bug in PyTables queries that did not return proper results
using the index
- Bug where dividing a dataframe containing values of type
Decimal by another Decimal would raise.
- Bug where using DataFrames asfreq would remove the name of
the index.
- Bug causing extra index point when resample BM/BQ
- Changed caching in AbstractHolidayCalendar to be at the
instance level rather than at the class level as the latter
can result in unexpected behaviour.
- Fixed latex output for multi-indexed dataframes
- Bug causing an exception when setting an empty range using
DataFrame.loc
- Bug in hiding ticklabels with subplots and shared axes when
adding a new plot to an existing grid of axes
- Bug in transform and filter when grouping on a categorical
variable
- Bug in transform when groups are equal in number and dtype to
the input index
- Google BigQuery connector now imports dependencies on a
per-method basis.
- Updated BigQuery connector to no longer use deprecated
oauth2client.tools.run()
- Bug in subclassed DataFrame. It may not return the correct
class, when slicing or subsetting it.
- Bug in .median() where non-float null values are not handled
correctly
- Bug in Series.fillna() where it raises if a numerically
convertible string is given
* Tue Mar 24 2015 toddrme2178@gmail.com
- update to version 0.16.0:
* Highlights:
- DataFrame.assign method
- Series.to_coo/from_coo methods to interact with scipy.sparse
- Backwards incompatible change to Timedelta to conform the .seconds
attribute with datetime.timedelta
- Changes to the .loc slicing API to conform with the behavior of .ix
- Changes to the default for ordering in the Categorical constructor
- Enhancement to the .str accessor to make string operations easier
- The pandas.tools.rplot, pandas.sandbox.qtpandas and pandas.rpy
modules are deprecated. We refer users to external packages like
seaborn, pandas-qt and rpy2 for similar or equivalent functionality
* New features
- Inspired by dplyr's mutate verb, DataFrame has a new assign method.
- Added SparseSeries.to_coo and SparseSeries.from_coo methods for
converting to and from scipy.sparse.coo_matrix instances.
- Following new methods are accesible via .str accessor to apply the
function to each values. This is intended to make it more consistent with
standard methods on strings: isalnum(), isalpha(), isdigit(), isdigit(),
isspace(), islower(), isupper(), istitle(), isnumeric(), isdecimal(),
find(), rfind(), ljust(), rjust(), zfill()
- Reindex now supports method='nearest' for frames or series with a
monotonic increasing or decreasing index.
- The read_excel() function's sheetname argument now accepts a list and
None, to get multiple or all sheets respectively. If more than one sheet
is specified, a dictionary is returned.
- Allow Stata files to be read incrementally with an iterator; support for
long strings in Stata files.
- Paths beginning with ~ will now be expanded to begin with the user's home
directory.
- Added time interval selection in get_data_yahoo.
- Added Timestamp.to_datetime64() to complement Timedelta.to_timedelta64().
- tseries.frequencies.to_offset() now accepts Timedelta as input.
- Lag parameter was added to the autocorrelation method of Series, defaults
to lag-1 autocorrelation.
- Timedelta will now accept nanoseconds keyword in constructor.
- SQL code now safely escapes table and column names.
- Added auto-complete for Series.str.<tab>, Series.dt.<tab> and
Series.cat.<tab>.
- Index.get_indexer now supports method='pad' and method='backfill' even
for any target array, not just monotonic targets.
- Index.asof now works on all index types.
- A verbose argument has been augmented in io.read_excel(), defaults to
False. Set to True to print sheet names as they are parsed.
- Added days_in_month (compatibility alias daysinmonth) property to
Timestamp, DatetimeIndex, Period, PeriodIndex, and Series.dt.
- Added decimal option in to_csv to provide formatting for non-'.' decimal
separators
- Added normalize option for Timestamp to normalized to midnight
- Added example for DataFrame import to R using HDF5 file and rhdf5
library.
* Backwards incompatible API changes
- In v0.16.0, we are restoring the API to match that of datetime.timedelta.
Further, the component values are still available through the .components
accessor. This affects the .seconds and .microseconds accessors, and
removes the .hours, .minutes, .milliseconds accessors. These changes
affect TimedeltaIndex and the Series .dt accessor as well.
- The behavior of a small sub-set of edge cases for using .loc have
changed. Furthermore we have improved the content of the error messages
that are raised:
+ Slicing with .loc where the start and/or stop bound is not found in
the index is now allowed; this previously would raise a KeyError. This
makes the behavior the same as .ix in this case. This change is only
for slicing, not when indexing with a single label.
+ Allow slicing with float-like values on an integer index for .ix.
Previously this was only enabled for .loc:
+ Provide a useful exception for indexing with an invalid type for that
index when using .loc. For example trying to use .loc on an index of
type DatetimeIndex or PeriodIndex or TimedeltaIndex, with an integer
(or a float).
- In prior versions, Categoricals that had an unspecified ordering
(meaning no ordered keyword was passed) were defaulted as ordered
Categoricals. Going forward, the ordered keyword in the Categorical
constructor will default to False. Ordering must now be explicit.
Furthermore, previously you *could* change the ordered attribute of a
Categorical by just setting the attribute, e.g. cat.ordered=True; This is
now deprecated and you should use cat.as_ordered() or cat.as_unordered().
These will by default return a **new** object and not modify the
existing object.
- Index.duplicated now returns np.array(dtype=bool) rather than
Index(dtype=object) containing bool values.
- DataFrame.to_json now returns accurate type serialisation for each column
for frames of mixed dtype
- DatetimeIndex, PeriodIndex and TimedeltaIndex.summary now output the same
format.
- TimedeltaIndex.freqstr now output the same string format as
DatetimeIndex.
- Bar and horizontal bar plots no longer add a dashed line along the info
axis. The prior style can be achieved with matplotlib's axhline or
axvline methods.
- Series accessors .dt, .cat and .str now raise AttributeError instead of
TypeError if the series does not contain the appropriate type of data.
This follows Python's built-in exception hierarchy more closely and
ensures that tests like hasattr(s, 'cat') are consistent on both Python
2 and 3.
- Series now supports bitwise operation for integral types. Previously even
if the input dtypes were integral, the output dtype was coerced to bool.
- During division involving a Series or DataFrame, 0/0 and 0//0 now give
np.nan instead of np.inf.
- Series.values_counts and Series.describe for categorical data will now
put NaN entries at the end.
- Series.describe for categorical data will now give counts and frequencies
of 0, not NaN, for unused categories
- Due to a bug fix, looking up a partial string label with
DatetimeIndex.asof now includes values that match the string, even if
they are after the start of the partial string label. Old behavior:
* Deprecations
- The rplot trellis plotting interface is deprecated and will be removed
in a future version. We refer to external packages like
seaborn for similar but more refined functionality.
- The pandas.sandbox.qtpandas interface is deprecated and will be removed
in a future version.
We refer users to the external package pandas-qt.
- The pandas.rpy interface is deprecated and will be removed in a future
version.
Similar functionaility can be accessed thru the rpy2 project
- Adding DatetimeIndex/PeriodIndex to another DatetimeIndex/PeriodIndex is
being deprecated as a set-operation. This will be changed to a TypeError
in a future version. .union() should be used for the union set operation.
- Subtracting DatetimeIndex/PeriodIndex from another
DatetimeIndex/PeriodIndex is being deprecated as a set-operation. This
will be changed to an actual numeric subtraction yielding a
TimeDeltaIndex in a future version. .difference() should be used for
the differencing set operation.
* Removal of prior version deprecations/changes
- DataFrame.pivot_table and crosstab's rows and cols keyword arguments were
removed in favor
of index and columns
- DataFrame.to_excel and DataFrame.to_csv cols keyword argument was removed
in favor of columns
- Removed convert_dummies in favor of get_dummies
- Removed value_range in favor of describe
* Performance Improvements
- Fixed a performance regression for .loc indexing with an array or
list-like.
- DataFrame.to_json 30x performance improvement for mixed dtype frames.
- Performance improvements in MultiIndex.duplicated by working with labels
instead of values
- Improved the speed of nunique by calling unique instead of value_counts
- Performance improvement of up to 10x in DataFrame.count and
DataFrame.dropna by taking advantage of homogeneous/heterogeneous dtypes
appropriately
- Performance improvement of up to 20x in DataFrame.count when using a
MultiIndex and the level keyword argument
- Performance and memory usage improvements in merge when key space exceeds
int64 bounds
- Performance improvements in multi-key groupby
- Performance improvements in MultiIndex.sortlevel
- Performance and memory usage improvements in DataFrame.duplicated
- Cythonized Period
- Decreased memory usage on to_hdf
* Bug Fixes
- Changed .to_html to remove leading/trailing spaces in table body
- Fixed issue using read_csv on s3 with Python 3
- Fixed compatibility issue in DatetimeIndex affecting architectures where
numpy.int_ defaults to numpy.int32
- Bug in Panel indexing with an object-like
- Bug in the returned Series.dt.components index was reset to the default
index
- Bug in Categorical.__getitem__/__setitem__ with listlike input getting
incorrect results from indexer coercion
- Bug in partial setting with a DatetimeIndex
- Bug in groupby for integer and datetime64 columns when applying an
aggregator that caused the value to be
changed when the number was sufficiently large
- Fixed bug in to_sql when mapping a Timestamp object column (datetime
column with timezone info) to the appropriate sqlalchemy type.
- Fixed bug in to_sql dtype argument not accepting an instantiated
SQLAlchemy type.
- Bug in .loc partial setting with a np.datetime64
- Incorrect dtypes inferred on datetimelike looking Series & on .xs slices
- Items in Categorical.unique() (and s.unique() if s is of dtype category)
now appear in the order in which they are originally found, not in sorted
order. This is now consistent with the behavior for other dtypes in pandas.
- Fixed bug on big endian platforms which produced incorrect results in
StataReader.
- Bug in MultiIndex.has_duplicates when having many levels causes an
indexer overflow
- Bug in pivot and unstack where nan values would break index alignment
- Bug in left join on multi-index with sort=True or null values.
- Bug in MultiIndex where inserting new keys would fail.
- Bug in groupby when key space exceeds int64 bounds.
- Bug in unstack with TimedeltaIndex or DatetimeIndex and nulls.
- Bug in rank where comparing floats with tolerance will cause inconsistent
behaviour.
- Fixed character encoding bug in read_stata and StataReader when loading
data from a URL.
- Bug in adding offsets.Nano to other offets raises TypeError
- Bug in DatetimeIndex iteration, related to, fixed in
- Bugs in resample around DST transitions. This required fixing offset
classes so they behave correctly on DST transitions.
- Bug in binary operator method (eg .mul()) alignment with integer levels.
- Bug in boxplot, scatter and hexbin plot may show an unnecessary warning
- Bug in subplot with layout kw may show unnecessary warning
- Bug in using grouper functions that need passed thru arguments (e.g.
axis), when using wrapped function (e.g. fillna),
- DataFrame now properly supports simultaneous copy and dtype arguments in
constructor
- Bug in read_csv when using skiprows on a file with CR line endings with
the c engine.
- isnull now detects NaT in PeriodIndex
- Bug in groupby .nth() with a multiple column groupby
- Bug in DataFrame.where and Series.where coerce numerics to string
incorrectly
- Bug in DataFrame.where and Series.where raise ValueError when string
list-like is passed.
- Accessing Series.str methods on with non-string values now raises
TypeError instead of producing incorrect results
- Bug in DatetimeIndex.__contains__ when index has duplicates and is not
monotonic increasing
- Fixed division by zero error for Series.kurt() when all values are equal
- Fixed issue in the xlsxwriter engine where it added a default 'General'
format to cells if no other format wass applied. This prevented other
row or column formatting being applied.
- Fixes issue with index_col=False when usecols is also specified in
read_csv.
- Bug where wide_to_long would modify the input stubnames list
- Bug in to_sql not storing float64 values using double precision.
- SparseSeries and SparsePanel now accept zero argument constructors (same
as their non-sparse counterparts).
- Regression in merging Categorical and object dtypes
- Bug in read_csv with buffer overflows with certain malformed input files
- Bug in groupby MultiIndex with missing pair
- Fixed bug in Series.groupby where grouping on MultiIndex levels would
ignore the sort argument
- Fix bug in DataFrame.Groupby where sort=False is ignored in the case of
Categorical columns.
- Fixed bug with reading CSV files from Amazon S3 on python 3 raising a
TypeError
- Bug in the Google BigQuery reader where the 'jobComplete' key may be
present but False in the query results
- Bug in Series.values_counts with excluding NaN for categorical type
Series with dropna=True
- Fixed mising numeric_only option for DataFrame.std/var/sem
- Support constructing Panel or Panel4D with scalar data
- Series text representation disconnected from `max_rows`/`max_columns`.
- Series number formatting inconsistent when truncated.
- A Spurious SettingWithCopy Warning was generated when setting a new item
in a frame in some cases
* Mon Jan 12 2015 toddrme2178@gmail.com
- update to version 0.15.2:
* API changes:
- Indexing in MultiIndex beyond lex-sort depth is now supported,
though a lexically sorted index will have a better
performance. (GH2646)
- Bug in unique of Series with category dtype, which returned all
categories regardless whether they were "used" or not (see
GH8559 for the discussion). Previous behaviour was to return all
categories.
- Series.all and Series.any now support the level and skipna
parameters. Series.all, Series.any, Index.all, and Index.any no
longer support the out and keepdims parameters, which existed
for compatibility with ndarray. Various index types no longer
support the all and any aggregation functions and will now raise
TypeError. (GH8302).
- Allow equality comparisons of Series with a categorical dtype
and object dtype; previously these would raise TypeError
(GH8938)
- Bug in NDFrame: conflicting attribute/column names now behave
consistently between getting and setting. Previously, when both
a column and attribute named y existed, data.y would return the
attribute, while data.y = z would update the column (GH8994)
- Timestamp('now') is now equivalent to Timestamp.now() in that it
returns the local time rather than UTC. Also, Timestamp('today')
is now equivalent to Timestamp.today() and both have tz as a
possible argument. (GH9000)
- Fix negative step support for label-based slices (GH8753)
* Enhancements:
- Added ability to export Categorical data to Stata (GH8633). See
here for limitations of categorical variables exported to Stata
data files.
- Added flag order_categoricals to StataReader and read_stata to
select whether to order imported categorical data (GH8836). See
here for more information on importing categorical variables
from Stata data files.
- Added ability to export Categorical data to to/from HDF5
(GH7621). Queries work the same as if it was an object
array. However, the category dtyped data is stored in a more
efficient manner. See here for an example and caveats
w.r.t. prior versions of pandas.
- Added support for searchsorted() on Categorical class (GH8420).
- Added the ability to specify the SQL type of columns when
writing a DataFrame to a database (GH8778). For example,
specifying to use the sqlalchemy String type instead of the
default Text type for string columns.
- Series.all and Series.any now support the level and skipna
parameters (GH8302).
- Panel now supports the all and any aggregation
functions. (GH8302).
- Added support for utcfromtimestamp(), fromtimestamp(), and
combine() on Timestamp class (GH5351).
- Added Google Analytics (pandas.io.ga) basic documentation
(GH8835).
- Timedelta arithmetic returns NotImplemented in unknown cases,
allowing extensions by custom classes (GH8813).
- Timedelta now supports arithemtic with numpy.ndarray objects of
the appropriate dtype (numpy 1.8 or newer only) (GH8884).
- Added Timedelta.to_timedelta64() method to the public API
(GH8884).
- Added gbq.generate_bq_schema() function to the gbq module
(GH8325).
- Series now works with map objects the same way as generators
(GH8909).
- Added context manager to HDFStore for automatic closing
(GH8791).
- to_datetime gains an exact keyword to allow for a format to not
require an exact match for a provided format string (if its
False). exact defaults to True (meaning that exact matching is
still the default) (GH8904)
- Added axvlines boolean option to parallel_coordinates plot
function, determines whether vertical lines will be printed,
default is True
- Added ability to read table footers to read_html (GH8552).
- to_sql now infers datatypes of non-NA values for columns that
contain NA values and have dtype object (GH8778).
* Performance:
- Reduce memory usage when skiprows is an integer in read_csv
(GH8681)
- Performance boost for to_datetime conversions with a passed
format=, and the exact=False (GH8904)
* Bug fixes:
- Bug in concat of Series with category dtype which were coercing
to object. (GH8641)
- Bug in Timestamp-Timestamp not returning a Timedelta type and
datelike-datelike ops with timezones (GH8865)
- Made consistent a timezone mismatch exception (either tz
operated with None or incompatible timezone), will now return
TypeError rather than ValueError (a couple of edge cases only),
(GH8865)
- Bug in using a pd.Grouper(key=...) with no level/axis or level
only (GH8795, GH8866)
- Report a TypeError when invalid/no paramaters are passed in a
groupby (GH8015)
- Bug in packaging pandas with py2app/cx_Freeze (GH8602, GH8831)
- Bug in groupby signatures that didn’t include *args or **kwargs
(GH8733).
- io.data.Options now raises RemoteDataError when no expiry dates
are available from Yahoo and when it receives no data from Yahoo
(GH8761), (GH8783).
- Unclear error message in csv parsing when passing dtype and
names and the parsed data is a different data type (GH8833)
- Bug in slicing a multi-index with an empty list and at least one
boolean indexer (GH8781)
- io.data.Options now raises RemoteDataError when no expiry dates
are available from Yahoo (GH8761).
- Timedelta kwargs may now be numpy ints and floats (GH8757).
- Fixed several outstanding bugs for Timedelta arithmetic and
comparisons (GH8813, GH5963, GH5436).
- sql_schema now generates dialect appropriate CREATE TABLE
statements (GH8697)
- slice string method now takes step into account (GH8754)
- Bug in BlockManager where setting values with different type
would break block integrity (GH8850)
- Bug in DatetimeIndex when using time object as key (GH8667)
- Bug in merge where how='left' and sort=False would not preserve
left frame order (GH7331)
- Bug in MultiIndex.reindex where reindexing at level would not
reorder labels (GH4088)
- Bug in certain operations with dateutil timezones, manifesting
with dateutil 2.3 (GH8639)
- Regression in DatetimeIndex iteration with a Fixed/Local offset
timezone (GH8890)
- Bug in to_datetime when parsing a nanoseconds using the %f
format (GH8989)
- io.data.Options now raises RemoteDataError when no expiry dates
are available from Yahoo and when it receives no data from Yahoo
(GH8761), (GH8783).
- Fix: The font size was only set on x axis if vertical or the y
axis if horizontal. (GH8765)
- Fixed division by 0 when reading big csv files in python 3
(GH8621)
- Bug in outputing a Multindex with to_html,index=False which
would add an extra column (GH8452)
- Imported categorical variables from Stata files retain the
ordinal information in the underlying data (GH8836).
- Defined .size attribute across NDFrame objects to provide compat
with numpy >= 1.9.1; buggy with np.array_split (GH8846)
- Skip testing of histogram plots for matplotlib <= 1.2 (GH8648).
- Bug where get_data_google returned object dtypes (GH3995)
- Bug in DataFrame.stack(..., dropna=False) when the DataFrame’s
columns is a MultiIndex whose labels do not reference all its
levels. (GH8844)
- Bug in that Option context applied on __enter__ (GH8514)
- Bug in resample that causes a ValueError when resampling across
multiple days and the last offset is not calculated from the
start of the range (GH8683)
- Bug where DataFrame.plot(kind='scatter') fails when checking if
an np.array is in the DataFrame (GH8852)
- Bug in pd.infer_freq/DataFrame.inferred_freq that prevented
proper sub-daily frequency inference when the index contained
DST days (GH8772).
- Bug where index name was still used when plotting a series with
use_index=False (GH8558).
- Bugs when trying to stack multiple columns, when some (or all)
of the level names are numbers (GH8584).
- Bug in MultiIndex where __contains__ returns wrong result if
index is not lexically sorted or unique (GH7724)
- BUG CSV: fix problem with trailing whitespace in skipped rows,
(GH8679), (GH8661), (GH8983)
- Regression in Timestamp does not parse ‘Z’ zone designator for
UTC (GH8771)
- Bug in StataWriter the produces writes strings with 244
characters irrespective of actual size (GH8969)
- Fixed ValueError raised by cummin/cummax when datetime64 Series
contains NaT. (GH8965)
- Bug in Datareader returns object dtype if there are missing
values (GH8980)
- Bug in plotting if sharex was enabled and index was a
timeseries, would show labels on multiple axes (GH3964).
- Bug where passing a unit to the TimedeltaIndex constructor
applied the to nano-second conversion twice. (GH9011).
- Bug in plotting of a period-like array (GH9012)
- Update copyright year
* Sun Nov 09 2014 toddrme2178@gmail.com
- Updated to version 0.15.1:
+ API changes
- Represent ``MultiIndex`` labels with a dtype that utilizes memory based
on the level size.
- ``groupby`` with ``as_index=False`` will not add erroneous extra columns
to result (:issue:`8582`):
- ``groupby`` will not erroneously exclude columns if the column name
conflics with the grouper name (:issue:`8112`):
- ``concat`` permits a wider variety of iterables of pandas objects to be
passed as the first parameter (:issue:`8645`):
- ``s.dt.hour`` and other ``.dt`` accessors will now return ``np.nan`` for
missing values (rather than previously -1), (:issue:`8689`)
- support for slicing with monotonic decreasing indexes, even if ``start``
or ``stop`` is not found in the index (:issue:`7860`):
- added Index properties `is_monotonic_increasing` and
`is_monotonic_decreasing` (:issue:`8680`).
- pandas now also registers the ``datetime64`` dtype in matplotlib's units
registry to plot such values as datetimes.
+ Enhancements
- Added option to select columns when importing Stata files (:issue:`7935`)
- Qualify memory usage in ``DataFrame.info()`` by adding ``+`` if it is a
lower bound (:issue:`8578`)
- Raise errors in certain aggregation cases where an argument such as
``numeric_only`` is not handled (:issue:`8592`).
- Added support for 3-character ISO and non-standard country codes in
:func:``io.wb.download()`` (:issue:`8482`)
- :ref:`World Bank data requests <remote_data.wb>` now will warn/raise
based on an ``errors`` argument, as well as a list of hard-coded country
codes and the World Bank's JSON response.
- Added option to ``Series.str.split()`` to return a ``DataFrame`` rather
than a ``Series`` (:issue:`8428`)
- Added option to ``df.info(null_counts=None|True|False)`` to override the
default display options and force showing of the null-counts
(:issue:`8701`)
+ Bug Fixes
- Bug in unpickling of a ``CustomBusinessDay`` object (:issue:`8591`)
- Bug in coercing ``Categorical`` to a records array, e.g.
``df.to_records()`` (:issue:`8626`)
- Bug in ``Categorical`` not created properly with ``Series.to_frame()``
(:issue:`8626`)
- Bug in coercing in astype of a ``Categorical`` of a passed
``pd.Categorical`` (this now raises ``TypeError`` correctly),
(:issue:`8626`)
- Bug in ``cut``/``qcut`` when using ``Series`` and ``retbins=True``
(:issue:`8589`)
- Bug in writing Categorical columns to an SQL database with ``to_sql``
(:issue:`8624`).
- Bug in comparing ``Categorical`` of datetime raising when being compared
to a scalar datetime (:issue:`8687`)
- Bug in selecting from a ``Categorical`` with ``.iloc`` (:issue:`8623`)
- Bug in groupby-transform with a Categorical (:issue:`8623`)
- Bug in duplicated/drop_duplicates with a Categorical (:issue:`8623`)
- Bug in ``Categorical`` reflected comparison operator raising if the first
argument was a numpy array scalar (e.g. np.int64) (:issue:`8658`)
- Bug in Panel indexing with a list-like (:issue:`8710`)
- Compat issue is ``DataFrame.dtypes`` when
``options.mode.use_inf_as_null`` is True (:issue:`8722`)
- Bug in ``read_csv``, ``dialect`` parameter would not take a string
(:issue: `8703`)
- Bug in slicing a multi-index level with an empty-list (:issue:`8737`)
- Bug in numeric index operations of add/sub with Float/Index Index with
numpy arrays (:issue:`8608`)
- Bug in setitem with empty indexer and unwanted coercion of dtypes
(:issue:`8669`)
- Bug in ix/loc block splitting on setitem (manifests with integer-like
dtypes, e.g. datetime64) (:issue:`8607`)
- Bug when doing label based indexing with integers not found in the index
for non-unique but monotonic indexes (:issue:`8680`).
- Bug when indexing a Float64Index with ``np.nan`` on numpy 1.7
(:issue:`8980`).
- Fix ``shape`` attribute for ``MultiIndex`` (:issue:`8609`)
- Bug in ``GroupBy`` where a name conflict between the grouper and columns
would break ``groupby`` operations (:issue:`7115`, :issue:`8112`)
- Fixed a bug where plotting a column ``y`` and specifying a label would
mutate the index name of the original DataFrame (:issue:`8494`)
- Fix regression in plotting of a DatetimeIndex directly with matplotlib
(:issue:`8614`).
- Bug in ``date_range`` where partially-specified dates would incorporate
current date (:issue:`6961`)
- Bug in Setting by indexer to a scalar value with a mixed-dtype `Panel4d`
was failing (:issue:`8702`)
- Bug where ``DataReader``'s would fail if one of the symbols passed was
invalid. Now returns data for valid symbols and np.nan for invalid
(:issue:`8494`)
- Bug in ``get_quote_yahoo`` that wouldn't allow non-float return values
(:issue:`5229`).
* Mon Oct 20 2014 toddrme2178@gmail.com
- Update to 0.15.0, highlights:
- Drop support for numpy < 1.7.0
- The Categorical type was integrated as a first-class
pandas type
- New scalar type Timedelta, and a new index type TimedeltaIndex
- New DataFrame default display for df.info() to
include memory usage
- New datetimelike properties accessor .dt for Series
- Split indexing documentation into Indexing and Selecting Data and
MultiIndex / Advanced Indexing
- Split out string methods documentation into Working with Text Data
- read_csv will now by default ignore blank lines when parsing
- API change in using Indexes in set operations
- Internal refactoring of the Index class to no longer
sub-class ndarray
- dropping support for PyTables less than version 3.0.0,
and numexpr less than version 2.1
- Update minimum dependency versions of
python-numpy, python-tables, and python-numexpr
/usr/lib/python3.6/site-packages/pandas /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info/PKG-INFO /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info/SOURCES.txt /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info/dependency_links.txt /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info/not-zip-safe /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info/requires.txt /usr/lib/python3.6/site-packages/pandas-0.23.4-py3.6.egg-info/top_level.txt /usr/lib/python3.6/site-packages/pandas/__init__.py /usr/lib/python3.6/site-packages/pandas/__pycache__ /usr/lib/python3.6/site-packages/pandas/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/_version.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/_version.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/conftest.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/conftest.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/json.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/json.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/lib.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/lib.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/parser.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/parser.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/testing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/testing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/tslib.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/__pycache__/tslib.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/_libs /usr/lib/python3.6/site-packages/pandas/_libs/__init__.py /usr/lib/python3.6/site-packages/pandas/_libs/__pycache__ /usr/lib/python3.6/site-packages/pandas/_libs/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/_libs/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/_libs/algos.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/groupby.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/hashing.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/hashtable.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/index.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/indexing.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/internals.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/interval.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/join.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/json.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/lib.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/missing.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/ops.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/parsers.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/properties.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/reduction.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/reshape.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/skiplist.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/sparse.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/testing.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslib.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/__init__.py /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/__pycache__ /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/ccalendar.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/conversion.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/fields.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/frequencies.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/nattype.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/np_datetime.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/offsets.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/parsing.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/period.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/resolution.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/strptime.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/timedeltas.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/timestamps.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/tslibs/timezones.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/window.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_libs/writers.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/_version.py /usr/lib/python3.6/site-packages/pandas/api /usr/lib/python3.6/site-packages/pandas/api/__init__.py /usr/lib/python3.6/site-packages/pandas/api/__pycache__ /usr/lib/python3.6/site-packages/pandas/api/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/api/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/api/extensions /usr/lib/python3.6/site-packages/pandas/api/extensions/__init__.py /usr/lib/python3.6/site-packages/pandas/api/extensions/__pycache__ /usr/lib/python3.6/site-packages/pandas/api/extensions/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/api/extensions/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/api/types /usr/lib/python3.6/site-packages/pandas/api/types/__init__.py /usr/lib/python3.6/site-packages/pandas/api/types/__pycache__ /usr/lib/python3.6/site-packages/pandas/api/types/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/api/types/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat /usr/lib/python3.6/site-packages/pandas/compat/__init__.py /usr/lib/python3.6/site-packages/pandas/compat/__pycache__ /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/chainmap.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/chainmap.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/chainmap_impl.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/chainmap_impl.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/pickle_compat.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/compat/__pycache__/pickle_compat.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat/chainmap.py /usr/lib/python3.6/site-packages/pandas/compat/chainmap_impl.py /usr/lib/python3.6/site-packages/pandas/compat/numpy /usr/lib/python3.6/site-packages/pandas/compat/numpy/__init__.py /usr/lib/python3.6/site-packages/pandas/compat/numpy/__pycache__ /usr/lib/python3.6/site-packages/pandas/compat/numpy/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/compat/numpy/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat/numpy/__pycache__/function.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/compat/numpy/__pycache__/function.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/compat/numpy/function.py /usr/lib/python3.6/site-packages/pandas/compat/pickle_compat.py /usr/lib/python3.6/site-packages/pandas/computation /usr/lib/python3.6/site-packages/pandas/computation/__init__.py /usr/lib/python3.6/site-packages/pandas/computation/__pycache__ /usr/lib/python3.6/site-packages/pandas/computation/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/computation/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/computation/__pycache__/expressions.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/computation/__pycache__/expressions.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/computation/expressions.py /usr/lib/python3.6/site-packages/pandas/conftest.py /usr/lib/python3.6/site-packages/pandas/core /usr/lib/python3.6/site-packages/pandas/core/__init__.py /usr/lib/python3.6/site-packages/pandas/core/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/accessor.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/accessor.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/algorithms.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/algorithms.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/apply.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/apply.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/base.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/base.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/categorical.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/categorical.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/common.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/common.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/config.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/config.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/config_init.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/config_init.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/datetools.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/datetools.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/frame.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/frame.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/generic.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/generic.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/index.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/index.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/indexing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/indexing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/internals.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/internals.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/missing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/missing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/nanops.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/nanops.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/ops.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/ops.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/panel.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/panel.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/resample.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/resample.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/series.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/series.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/sorting.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/sorting.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/strings.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/strings.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/window.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/__pycache__/window.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/accessor.py /usr/lib/python3.6/site-packages/pandas/core/algorithms.py /usr/lib/python3.6/site-packages/pandas/core/api.py /usr/lib/python3.6/site-packages/pandas/core/apply.py /usr/lib/python3.6/site-packages/pandas/core/arrays /usr/lib/python3.6/site-packages/pandas/core/arrays/__init__.py /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__/base.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__/base.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__/categorical.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/arrays/__pycache__/categorical.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/arrays/base.py /usr/lib/python3.6/site-packages/pandas/core/arrays/categorical.py /usr/lib/python3.6/site-packages/pandas/core/base.py /usr/lib/python3.6/site-packages/pandas/core/categorical.py /usr/lib/python3.6/site-packages/pandas/core/common.py /usr/lib/python3.6/site-packages/pandas/core/computation /usr/lib/python3.6/site-packages/pandas/core/computation/__init__.py /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/align.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/align.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/check.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/check.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/common.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/common.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/engines.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/engines.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/eval.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/eval.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/expr.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/expr.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/expressions.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/expressions.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/ops.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/ops.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/pytables.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/pytables.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/scope.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/__pycache__/scope.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/computation/align.py /usr/lib/python3.6/site-packages/pandas/core/computation/api.py /usr/lib/python3.6/site-packages/pandas/core/computation/check.py /usr/lib/python3.6/site-packages/pandas/core/computation/common.py /usr/lib/python3.6/site-packages/pandas/core/computation/engines.py /usr/lib/python3.6/site-packages/pandas/core/computation/eval.py /usr/lib/python3.6/site-packages/pandas/core/computation/expr.py /usr/lib/python3.6/site-packages/pandas/core/computation/expressions.py /usr/lib/python3.6/site-packages/pandas/core/computation/ops.py /usr/lib/python3.6/site-packages/pandas/core/computation/pytables.py /usr/lib/python3.6/site-packages/pandas/core/computation/scope.py /usr/lib/python3.6/site-packages/pandas/core/config.py /usr/lib/python3.6/site-packages/pandas/core/config_init.py /usr/lib/python3.6/site-packages/pandas/core/datetools.py /usr/lib/python3.6/site-packages/pandas/core/dtypes /usr/lib/python3.6/site-packages/pandas/core/dtypes/__init__.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/base.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/base.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/cast.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/cast.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/common.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/common.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/concat.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/concat.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/dtypes.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/dtypes.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/generic.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/generic.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/inference.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/inference.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/missing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/__pycache__/missing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/dtypes/api.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/base.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/cast.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/common.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/concat.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/dtypes.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/generic.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/inference.py /usr/lib/python3.6/site-packages/pandas/core/dtypes/missing.py /usr/lib/python3.6/site-packages/pandas/core/frame.py /usr/lib/python3.6/site-packages/pandas/core/generic.py /usr/lib/python3.6/site-packages/pandas/core/groupby /usr/lib/python3.6/site-packages/pandas/core/groupby/__init__.py /usr/lib/python3.6/site-packages/pandas/core/groupby/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/groupby/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/groupby/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/groupby/__pycache__/groupby.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/groupby/__pycache__/groupby.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/groupby/groupby.py /usr/lib/python3.6/site-packages/pandas/core/index.py /usr/lib/python3.6/site-packages/pandas/core/indexes /usr/lib/python3.6/site-packages/pandas/core/indexes/__init__.py /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/accessors.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/accessors.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/base.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/base.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/category.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/category.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/datetimelike.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/datetimelike.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/datetimes.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/datetimes.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/frozen.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/frozen.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/interval.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/interval.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/multi.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/multi.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/numeric.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/numeric.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/period.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/period.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/range.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/range.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/timedeltas.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/__pycache__/timedeltas.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/indexes/accessors.py /usr/lib/python3.6/site-packages/pandas/core/indexes/api.py /usr/lib/python3.6/site-packages/pandas/core/indexes/base.py /usr/lib/python3.6/site-packages/pandas/core/indexes/category.py /usr/lib/python3.6/site-packages/pandas/core/indexes/datetimelike.py /usr/lib/python3.6/site-packages/pandas/core/indexes/datetimes.py /usr/lib/python3.6/site-packages/pandas/core/indexes/frozen.py /usr/lib/python3.6/site-packages/pandas/core/indexes/interval.py /usr/lib/python3.6/site-packages/pandas/core/indexes/multi.py /usr/lib/python3.6/site-packages/pandas/core/indexes/numeric.py /usr/lib/python3.6/site-packages/pandas/core/indexes/period.py /usr/lib/python3.6/site-packages/pandas/core/indexes/range.py /usr/lib/python3.6/site-packages/pandas/core/indexes/timedeltas.py /usr/lib/python3.6/site-packages/pandas/core/indexing.py /usr/lib/python3.6/site-packages/pandas/core/internals.py /usr/lib/python3.6/site-packages/pandas/core/missing.py /usr/lib/python3.6/site-packages/pandas/core/nanops.py /usr/lib/python3.6/site-packages/pandas/core/ops.py /usr/lib/python3.6/site-packages/pandas/core/panel.py /usr/lib/python3.6/site-packages/pandas/core/resample.py /usr/lib/python3.6/site-packages/pandas/core/reshape /usr/lib/python3.6/site-packages/pandas/core/reshape/__init__.py /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/concat.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/concat.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/melt.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/melt.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/merge.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/merge.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/pivot.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/pivot.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/reshape.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/reshape.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/tile.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/tile.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/util.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/__pycache__/util.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/reshape/api.py /usr/lib/python3.6/site-packages/pandas/core/reshape/concat.py /usr/lib/python3.6/site-packages/pandas/core/reshape/melt.py /usr/lib/python3.6/site-packages/pandas/core/reshape/merge.py /usr/lib/python3.6/site-packages/pandas/core/reshape/pivot.py /usr/lib/python3.6/site-packages/pandas/core/reshape/reshape.py /usr/lib/python3.6/site-packages/pandas/core/reshape/tile.py /usr/lib/python3.6/site-packages/pandas/core/reshape/util.py /usr/lib/python3.6/site-packages/pandas/core/series.py /usr/lib/python3.6/site-packages/pandas/core/sorting.py /usr/lib/python3.6/site-packages/pandas/core/sparse /usr/lib/python3.6/site-packages/pandas/core/sparse/__init__.py /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/array.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/array.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/frame.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/frame.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/scipy_sparse.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/scipy_sparse.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/series.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/__pycache__/series.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/sparse/api.py /usr/lib/python3.6/site-packages/pandas/core/sparse/array.py /usr/lib/python3.6/site-packages/pandas/core/sparse/frame.py /usr/lib/python3.6/site-packages/pandas/core/sparse/scipy_sparse.py /usr/lib/python3.6/site-packages/pandas/core/sparse/series.py /usr/lib/python3.6/site-packages/pandas/core/strings.py /usr/lib/python3.6/site-packages/pandas/core/tools /usr/lib/python3.6/site-packages/pandas/core/tools/__init__.py /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/datetimes.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/datetimes.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/numeric.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/numeric.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/timedeltas.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/__pycache__/timedeltas.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/tools/datetimes.py /usr/lib/python3.6/site-packages/pandas/core/tools/numeric.py /usr/lib/python3.6/site-packages/pandas/core/tools/timedeltas.py /usr/lib/python3.6/site-packages/pandas/core/util /usr/lib/python3.6/site-packages/pandas/core/util/__init__.py /usr/lib/python3.6/site-packages/pandas/core/util/__pycache__ /usr/lib/python3.6/site-packages/pandas/core/util/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/util/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/util/__pycache__/hashing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/core/util/__pycache__/hashing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/core/util/hashing.py /usr/lib/python3.6/site-packages/pandas/core/window.py /usr/lib/python3.6/site-packages/pandas/errors /usr/lib/python3.6/site-packages/pandas/errors/__init__.py /usr/lib/python3.6/site-packages/pandas/errors/__pycache__ /usr/lib/python3.6/site-packages/pandas/errors/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/errors/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/formats /usr/lib/python3.6/site-packages/pandas/formats/__init__.py /usr/lib/python3.6/site-packages/pandas/formats/__pycache__ /usr/lib/python3.6/site-packages/pandas/formats/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/formats/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/formats/__pycache__/style.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/formats/__pycache__/style.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/formats/style.py /usr/lib/python3.6/site-packages/pandas/io /usr/lib/python3.6/site-packages/pandas/io/__init__.py /usr/lib/python3.6/site-packages/pandas/io/__pycache__ /usr/lib/python3.6/site-packages/pandas/io/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/clipboards.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/clipboards.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/common.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/common.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/date_converters.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/date_converters.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/excel.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/excel.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/feather_format.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/feather_format.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/gbq.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/gbq.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/html.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/html.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/packers.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/packers.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/parquet.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/parquet.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/parsers.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/parsers.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/pickle.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/pickle.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/pytables.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/pytables.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/s3.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/s3.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/sql.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/sql.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/stata.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/__pycache__/stata.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/api.py /usr/lib/python3.6/site-packages/pandas/io/clipboard /usr/lib/python3.6/site-packages/pandas/io/clipboard/__init__.py /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__ /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/clipboards.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/clipboards.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/exceptions.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/exceptions.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/windows.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/__pycache__/windows.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/clipboard/clipboards.py /usr/lib/python3.6/site-packages/pandas/io/clipboard/exceptions.py /usr/lib/python3.6/site-packages/pandas/io/clipboard/windows.py /usr/lib/python3.6/site-packages/pandas/io/clipboards.py /usr/lib/python3.6/site-packages/pandas/io/common.py /usr/lib/python3.6/site-packages/pandas/io/date_converters.py /usr/lib/python3.6/site-packages/pandas/io/excel.py /usr/lib/python3.6/site-packages/pandas/io/feather_format.py /usr/lib/python3.6/site-packages/pandas/io/formats /usr/lib/python3.6/site-packages/pandas/io/formats/__init__.py /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__ /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/console.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/console.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/css.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/css.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/csvs.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/csvs.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/excel.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/excel.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/format.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/format.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/html.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/html.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/latex.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/latex.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/printing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/printing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/style.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/style.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/terminal.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/__pycache__/terminal.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/formats/console.py /usr/lib/python3.6/site-packages/pandas/io/formats/css.py /usr/lib/python3.6/site-packages/pandas/io/formats/csvs.py /usr/lib/python3.6/site-packages/pandas/io/formats/excel.py /usr/lib/python3.6/site-packages/pandas/io/formats/format.py /usr/lib/python3.6/site-packages/pandas/io/formats/html.py /usr/lib/python3.6/site-packages/pandas/io/formats/latex.py /usr/lib/python3.6/site-packages/pandas/io/formats/printing.py /usr/lib/python3.6/site-packages/pandas/io/formats/style.py /usr/lib/python3.6/site-packages/pandas/io/formats/templates /usr/lib/python3.6/site-packages/pandas/io/formats/templates/html.tpl /usr/lib/python3.6/site-packages/pandas/io/formats/terminal.py /usr/lib/python3.6/site-packages/pandas/io/gbq.py /usr/lib/python3.6/site-packages/pandas/io/html.py /usr/lib/python3.6/site-packages/pandas/io/json /usr/lib/python3.6/site-packages/pandas/io/json/__init__.py /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__ /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/json.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/json.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/normalize.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/normalize.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/table_schema.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/json/__pycache__/table_schema.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/json/json.py /usr/lib/python3.6/site-packages/pandas/io/json/normalize.py /usr/lib/python3.6/site-packages/pandas/io/json/table_schema.py /usr/lib/python3.6/site-packages/pandas/io/msgpack /usr/lib/python3.6/site-packages/pandas/io/msgpack/__init__.py /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__ /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__/_version.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__/_version.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__/exceptions.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/msgpack/__pycache__/exceptions.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/msgpack/_packer.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/io/msgpack/_unpacker.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/io/msgpack/_version.py /usr/lib/python3.6/site-packages/pandas/io/msgpack/exceptions.py /usr/lib/python3.6/site-packages/pandas/io/packers.py /usr/lib/python3.6/site-packages/pandas/io/parquet.py /usr/lib/python3.6/site-packages/pandas/io/parsers.py /usr/lib/python3.6/site-packages/pandas/io/pickle.py /usr/lib/python3.6/site-packages/pandas/io/pytables.py /usr/lib/python3.6/site-packages/pandas/io/s3.py /usr/lib/python3.6/site-packages/pandas/io/sas /usr/lib/python3.6/site-packages/pandas/io/sas/__init__.py /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__ /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sas7bdat.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sas7bdat.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sas_constants.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sas_constants.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sas_xport.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sas_xport.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sasreader.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/__pycache__/sasreader.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/io/sas/_sas.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/io/sas/sas7bdat.py /usr/lib/python3.6/site-packages/pandas/io/sas/sas_constants.py /usr/lib/python3.6/site-packages/pandas/io/sas/sas_xport.py /usr/lib/python3.6/site-packages/pandas/io/sas/sasreader.py /usr/lib/python3.6/site-packages/pandas/io/sql.py /usr/lib/python3.6/site-packages/pandas/io/stata.py /usr/lib/python3.6/site-packages/pandas/json.py /usr/lib/python3.6/site-packages/pandas/lib.py /usr/lib/python3.6/site-packages/pandas/parser.py /usr/lib/python3.6/site-packages/pandas/plotting /usr/lib/python3.6/site-packages/pandas/plotting/__init__.py /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__ /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_compat.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_compat.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_converter.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_converter.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_core.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_core.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_misc.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_misc.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_style.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_style.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_timeseries.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_timeseries.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_tools.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/plotting/__pycache__/_tools.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/plotting/_compat.py /usr/lib/python3.6/site-packages/pandas/plotting/_converter.py /usr/lib/python3.6/site-packages/pandas/plotting/_core.py /usr/lib/python3.6/site-packages/pandas/plotting/_misc.py /usr/lib/python3.6/site-packages/pandas/plotting/_style.py /usr/lib/python3.6/site-packages/pandas/plotting/_timeseries.py /usr/lib/python3.6/site-packages/pandas/plotting/_tools.py /usr/lib/python3.6/site-packages/pandas/testing.py /usr/lib/python3.6/site-packages/pandas/tools /usr/lib/python3.6/site-packages/pandas/tools/__init__.py /usr/lib/python3.6/site-packages/pandas/tools/__pycache__ /usr/lib/python3.6/site-packages/pandas/tools/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tools/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tools/__pycache__/merge.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tools/__pycache__/merge.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tools/__pycache__/plotting.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tools/__pycache__/plotting.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tools/merge.py /usr/lib/python3.6/site-packages/pandas/tools/plotting.py /usr/lib/python3.6/site-packages/pandas/tseries /usr/lib/python3.6/site-packages/pandas/tseries/__init__.py /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__ /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/api.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/api.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/converter.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/converter.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/frequencies.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/frequencies.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/holiday.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/holiday.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/offsets.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/offsets.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/plotting.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/tseries/__pycache__/plotting.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/tseries/api.py /usr/lib/python3.6/site-packages/pandas/tseries/converter.py /usr/lib/python3.6/site-packages/pandas/tseries/frequencies.py /usr/lib/python3.6/site-packages/pandas/tseries/holiday.py /usr/lib/python3.6/site-packages/pandas/tseries/offsets.py /usr/lib/python3.6/site-packages/pandas/tseries/plotting.py /usr/lib/python3.6/site-packages/pandas/tslib.py /usr/lib/python3.6/site-packages/pandas/types /usr/lib/python3.6/site-packages/pandas/types/__init__.py /usr/lib/python3.6/site-packages/pandas/types/__pycache__ /usr/lib/python3.6/site-packages/pandas/types/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/types/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/types/__pycache__/common.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/types/__pycache__/common.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/types/__pycache__/concat.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/types/__pycache__/concat.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/types/common.py /usr/lib/python3.6/site-packages/pandas/types/concat.py /usr/lib/python3.6/site-packages/pandas/util /usr/lib/python3.6/site-packages/pandas/util/__init__.py /usr/lib/python3.6/site-packages/pandas/util/__pycache__ /usr/lib/python3.6/site-packages/pandas/util/__pycache__/__init__.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/__init__.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_decorators.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_decorators.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_depr_module.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_depr_module.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_doctools.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_doctools.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_print_versions.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_print_versions.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_test_decorators.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_test_decorators.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_tester.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_tester.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_validators.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/_validators.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/decorators.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/decorators.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/testing.cpython-36.opt-1.pyc /usr/lib/python3.6/site-packages/pandas/util/__pycache__/testing.cpython-36.pyc /usr/lib/python3.6/site-packages/pandas/util/_decorators.py /usr/lib/python3.6/site-packages/pandas/util/_depr_module.py /usr/lib/python3.6/site-packages/pandas/util/_doctools.py /usr/lib/python3.6/site-packages/pandas/util/_move.cpython-36m-arm-linux-gnueabihf.so /usr/lib/python3.6/site-packages/pandas/util/_print_versions.py /usr/lib/python3.6/site-packages/pandas/util/_test_decorators.py /usr/lib/python3.6/site-packages/pandas/util/_tester.py /usr/lib/python3.6/site-packages/pandas/util/_validators.py /usr/lib/python3.6/site-packages/pandas/util/decorators.py /usr/lib/python3.6/site-packages/pandas/util/testing.py /usr/share/doc/packages/python3-pandas /usr/share/doc/packages/python3-pandas/README.rst /usr/share/doc/packages/python3-pandas/RELEASE.md /usr/share/licenses/python3-pandas /usr/share/licenses/python3-pandas/LICENSE
Generated by rpm2html 1.8.1
Fabrice Bellet, Tue Jul 9 15:33:36 2024