pandas.DataFrame.plot¶
- DataFrame.plot(frame=None, x=None, y=None, subplots=False, sharex=True, sharey=False, use_index=True, figsize=None, grid=None, legend=True, rot=None, ax=None, style=None, title=None, xlim=None, ylim=None, logx=False, logy=False, xticks=None, yticks=None, kind='line', sort_columns=False, fontsize=None, secondary_y=False, **kwds)¶
Make line or bar plot of DataFrame’s series with the index on the x-axis using matplotlib / pylab.
x : label or position, default None y : label or position, default None
Allows plotting of one column versus another- subplots : boolean, default False
- Make separate subplots for each time series
- sharex : boolean, default True
- In case subplots=True, share x axis
- sharey : boolean, default False
- In case subplots=True, share y axis
- use_index : boolean, default True
- Use index as ticks for x axis
- stacked : boolean, default False
- If True, create stacked bar plot. Only valid for DataFrame input
- sort_columns: boolean, default False
- Sort column names to determine plot ordering
- title : string
- Title to use for the plot
- grid : boolean, default None (matlab style default)
- Axis grid lines
- legend : boolean, default True
- Place legend on axis subplots
ax : matplotlib axis object, default None style : list or dict
matplotlib line style per column- kind : {‘line’, ‘bar’, ‘barh’, ‘kde’, ‘density’}
- bar : vertical bar plot barh : horizontal bar plot kde/density : Kernel Density Estimation plot
- logx : boolean, default False
- For line plots, use log scaling on x axis
- logy : boolean, default False
- For line plots, use log scaling on y axis
- xticks : sequence
- Values to use for the xticks
- yticks : sequence
- Values to use for the yticks
xlim : 2-tuple/list ylim : 2-tuple/list rot : int, default None
Rotation for ticks- secondary_y : boolean or sequence, default False
- Whether to plot on the secondary y-axis If dict then can select which columns to plot on secondary y-axis
- kwds : keywords
- Options to pass to matplotlib plotting method
ax_or_axes : matplotlib.AxesSubplot or list of them