0 (October 9, 2015) 9 pandas: powerful Python data analysis toolkit, Release 0.17.0 loss of information, by specifying which columns/rows make up the MultiIndex in the header and index_col parameters deprecated and will be removed in a future version. Similar functionaility can be accessed thru the rpy2 project (GH9602) • Adding DatetimeIndex/PeriodIndex to another DatetimeIndex/PeriodIndex is being depre- read_stata to select whether to order im- ported categorical data (GH8836). See here for more information on importing categorical variables from Stata data files. • Added ability to export Categorical

name attribute can be a hashable type (GH12610) • Bug in .describe() resets categorical columns information (GH11558) • Bug where loffset argument was not applied when calling resample().count() on a timeseries However, when wrapped in a Series whose dtype is datetime64[ns] or timedelta64[ns], the dtype information is respected. In [1]: pd.Series([pd.NaT], dtype='project of the (NUMFocus organization). This will help ensure the success of development of pandas as a world-class open-source project. This is a minor bug-fix release

Python data analysis toolkit, Release 0.19.0 • Bug in .describe() resets categorical columns information (GH11558) • Bug where loffset argument was not applied when calling resample().count() on a timeseries However, when wrapped in a Series whose dtype is datetime64[ns] or timedelta64[ns], the dtype information is respected. In [1]: pd.Series([pd.NaT], dtype='project of the (NUMFocus organization). This will help ensure the success of development of pandas as a world-class open-source project. This is a minor bug-fix release

read_stata to select whether to order im- ported categorical data (GH8836). See here for more information on importing categorical variables from Stata data files. • Added ability to export Categorical 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 characters raises a ValueError. (GH7858) • read_stata and StataReader can import missing data information into a DataFrame by setting the argument convert_missing to True. When using this options, missing

keyword argument for specifying the types of specific columns (GH14295). See the io docs for more information. 1.3. v0.20.1 (May 5, 2017) 11 pandas: powerful Python data analysis toolkit, Release 0.20.3 000Z"},{"idx":2, ˓→"A":3,"B":"c","C":"2016-01-03T00:00:00.000Z"}]}' See IO: Table Schema for more information. Additionally, the repr for DataFrame and Series can now publish this JSON Table schema representation notebook and nteract more flexiblity in how they display pandas objects, since they have more information about the data. You must enable this by setting the display.html.table_schema option to True.

minor_axis=None, **kwargs) to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return The new methods re- quire scipy. Consult the Scipy reference guide and documentation for more information about when the various methods are appropriate. See the docs. Interpolate now also accepts a limit Your Google BigQuery Project ID # To find this, see your dashboard: # https://code.google.com/apis/console/b/0/?noredirect projectid = xxxxxxxxx; df = gbq.read_gbq(query, project_id = projectid) # Use

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424 4.5 Project Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . keyword argument for specifying the types of specific columns (GH14295). See the io docs for more information. In [11]: data = "a b\n1 2\n3 4" In [12]: pd.read_fwf(StringIO(data)).dtypes Out[12]: a int64 000Z"},{"idx":2, ˓→"A":3,"B":"c","C":"2016-01-03T00:00:00.000Z"}]}' See IO: Table Schema for more information. Additionally, the repr for DataFrame and Series can now publish this JSON Table schema representation

keyword argument for specifying the types of specific columns (GH14295). See the io docs for more information. In [11]: data = "a b\n1 2\n3 4" In [12]: pd.read_fwf(StringIO(data)).dtypes Out[12]: a int64 000Z"},{"idx":2, ˓→"A":3,"B":"c","C":"2016-01-03T00:00:00.000Z"}]}' See IO: Table Schema for more information. Additionally, the repr for DataFrame and Series can now publish this JSON Table schema representation notebook and nteract more flexiblity in how they display pandas objects, since they have more information about the data. You must enable this by setting the display.html.table_schema option to True.

characters raises a ValueError. (GH7858) • read_stata and StataReader can import missing data information into a DataFrame by setting the argument convert_missing to True. When using this options, missing minor_axis=None, **kwargs) to conform with other NDFrame objects. See Internal Refactoring for more information. • Series.argmin and Series.argmax are now aliased to Series.idxmin and Series.idxmax. These return The new methods re- quire scipy. Consult the Scipy reference guide and documentation for more information about when the various methods are appropriate. See the docs. Interpolate now also accepts a limit

in DatetimeIndex addition when adding a non-optimized DateOffset incorrectly dropping timezone information (GH30336) • Bug in DataFrame.drop() where attempting to drop non-existent values from a DatetimeIndex lambda function with named aggre- gation (GH27519) • Bug in DataFrame.groupby() losing column name information when grouping by a categorical column (GH28787) • Remove error raised due to duplicated input NumFOCUS sponsored project. This will help ensure the success of development of pandas as a world- class open-source project, and makes it possible to donate to the project. 2.2.5 Project governance The