DataFrame.plot.hist(by=None, bins=10, **kwds) [source] Histogram New in version 0.17.0. Parameters: by : string or sequence Column in the DataFrame to group by. bins: integer, default 10 Number of histogram bins to be used **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.plot.hexbin(x, y, C=None, reduce_C_function=None, gridsize=None, **kwds) [source] Hexbin plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. C : label or position, optional The value at each (x, y) point. reduce_C_function : callable, optional Function of one argument that reduces all the values in a bin to a single number (e.g. mean, max, sum, std). gridsize : int, optional Number of bins. **kwds : optional Keyword ar

DataFrame.plot.density(**kwds) [source] Kernel Density Estimate plot New in version 0.17.0. Parameters: **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.plot.box(by=None, **kwds) [source] Boxplot New in version 0.17.0. Parameters: by : string or sequence Column in the DataFrame to group by. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.plot.barh(x=None, y=None, **kwds) [source] Horizontal bar plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.plot.bar(x=None, y=None, **kwds) [source] Vertical bar plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.plot.area(x=None, y=None, **kwds) [source] Area plot New in version 0.17.0. Parameters: x, y : label or position, optional Coordinates for each point. **kwds : optional Keyword arguments to pass on to pandas.DataFrame.plot(). Returns: axes : matplotlib.AxesSubplot or np.array of them

DataFrame.plot(x=None, y=None, kind='line', ax=None, subplots=False, sharex=None, sharey=False, layout=None, figsize=None, use_index=True, title=None, grid=None, legend=True, style=None, logx=False, logy=False, loglog=False, xticks=None, yticks=None, xlim=None, ylim=None, rot=None, fontsize=None, colormap=None, table=False, yerr=None, xerr=None, secondary_y=False, sort_columns=False, **kwds) [source] Make plots of DataFrame using matplotlib / pylab. New in version 0.17.0: Each plot kind has

DataFrame.pivot_table(data, values=None, index=None, columns=None, aggfunc='mean', fill_value=None, margins=False, dropna=True, margins_name='All') [source] Create a spreadsheet-style pivot table as a DataFrame. The levels in the pivot table will be stored in MultiIndex objects (hierarchical indexes) on the index and columns of the result DataFrame Parameters: data : DataFrame values : column to aggregate, optional index : column, Grouper, array, or list of the previous If an array is pas

DataFrame.pivot(index=None, columns=None, values=None) [source] Reshape data (produce a ?pivot? table) based on column values. Uses unique values from index / columns to form axes of the resulting DataFrame. Parameters: index : string or object, optional Column name to use to make new frame?s index. If None, uses existing index. columns : string or object Column name to use to make new frame?s columns values : string or object, optional Column name to use for populating new frame?s va