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fillna on Series or DataFrame with no arguments is no longer valid code. You must either specify a fill value or an interpolation method: In [25]: s = Series([np.nan, 1., 2., np.nan, 4]) In [26]: s Out[26]: rows of a dataframe as tuples (GH818) • Add ability to pass fill_value and method to DataFrame and Series align method (GH806, GH807) • Add fill_value option to reindex, align methods (GH784) • Enable concat columns 7.3.5 panelnd The panelnd docs. Construct a 5D panelnd 7.4 Missing Data The missing data docs. Fill forward a reversed timeseries In [1]: df = pd.DataFrame(np.random.randn(6,1), index=pd.date_range(’2013-08-01’

fillna on Series or DataFrame with no arguments is no longer valid code. You must either specify a fill value or an interpolation method: In [25]: s = Series([np.nan, 1., 2., np.nan, 4]) In [26]: s Out[26]: rows of a dataframe as tuples (GH818) • Add ability to pass fill_value and method to DataFrame and Series align method (GH806, GH807) • Add fill_value option to reindex, align methods (GH784) • Enable concat columns 7.3.5 panelnd The panelnd docs. Construct a 5D panelnd 7.4 Missing Data The missing data docs. Fill forward a reversed timeseries In [1]: df = pd.DataFrame(np.random.randn(6,1), index=pd.date_range(’2013-08-01’

whichever version of openpyxl is installed. (GH7177) • DataFrame.fillna can now accept a DataFrame as a fill value (GH8377) • Passing multiple levels to stack() will now work when multiple level numbers are NaT properly (GH7261) • Bug in PeriodIndex.min/max results in int (GH7609) • Bug in resample where fill_method was ignored if you passed how (GH2073) 44 Chapter 1. What’s New pandas: powerful Python data fillna on Series or DataFrame with no arguments is no longer valid code. You must either specify a fill value or an interpolation method: In [25]: s = Series([np.nan, 1., 2., np.nan, 4]) In [26]: s Out[26]:

whichever version of openpyxl is installed. (GH7177) • DataFrame.fillna can now accept a DataFrame as a fill value (GH8377) • Passing multiple levels to stack() will now work when multiple level numbers are NaT properly (GH7261) • Bug in PeriodIndex.min/max results in int (GH7609) • Bug in resample where fill_method was ignored if you passed how (GH2073) • Bug in TimeGrouper doesn’t exclude column specified fillna on Series or DataFrame with no arguments is no longer valid code. You must either specify a fill value or an interpolation method: In [25]: s = Series([np.nan, 1., 2., np.nan, 4]) In [26]: s Out[26]:

(GH10393) • Add a limit_direction keyword argument that works with limit to enable interpolate to fill NaN values forward, backward, or both (GH9218, GH10420, GH11115) In [47]: ser = pd.Series([np.nan can easily be replaced by using the add and mul methods: DataFrame.add(other, fill_value=0) and DataFrame.mul(other, fill_value=1.) (GH10735). • TimeSeries deprecated in favor of Series (note that this 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

rows of a dataframe as tuples (GH818) • Add ability to pass fill_value and method to DataFrame and Series align method (GH806, GH807) • Add fill_value option to reindex, align methods (GH784) • Enable concat b 2 False c 3 True d NaN False When inserting a scalar value, it will naturally be propagated to fill the column: In [283]: df['foo'] = 'bar' In [284]: df Out[284]: one flag foo a 1 False #### 6.3.2 Missing data / operations with fill values In Series and DataFrame (though not yet in Panel), the arithmetic functions have the option of inputting a fill_value, namely a value to substitute when

rows of a dataframe as tuples (GH818) • Add ability to pass fill_value and method to DataFrame and Series align method (GH806, GH807) • Add fill_value option to reindex, align methods (GH784) • Enable concat b 2 False c 3 True d NaN False When inserting a scalar value, it will naturally be propagated to fill the column: In [283]: df['foo'] = 'bar' In [284]: df Out[284]: one flag foo a 1 False #### 6.3.2 Missing data / operations with fill values In Series and DataFrame (though not yet in Panel), the arithmetic functions have the option of inputting a fill_value, namely a value to substitute when

height = rx.height) page.show_pdf_page( page.rect, # fill all new page with the image src, # input document spage.number, # input page Content extraction for accessibility: Allowed Page extraction: Not Allowed Commenting: Allowed Fill form fields: Allowed Sign digital signatures: Allowed Creation of template pages: Not Allowed redact rect = [0, 0, 200, 200] # Add a redaction annotation which will have a red fill color page.add_redact_annot(rect, fill=(1, 0, 0)) # Apply the redactions to the current page, but ignore vector graphics

rows of a dataframe as tuples (#818) • Add ability to pass fill_value and method to DataFrame and Series align method (#806, #807) • Add fill_value option to reindex, align methods (#784) • Enable concat b 2 False c 3 True d NaN False When inserting a scalar value, it will naturally be propagated to fill the column: In [283]: df['foo'] = 'bar' In [284]: df Out[284]: one flag foo a 1 False #### 6.3.2 Missing data / operations with fill values In Series and DataFrame (though not yet in Panel), the arithmetic functions have the option of inputting a fill_value, namely a value to substitute when