![]() ![]() Use a seaborn figure-level plot, and use the col or row parameter.groupby object.ĭfg = dfm.groupby('variable') # get data for each unique value in the first columnįor (group, data), color, ax in zip(dfg, colors, axes):ĭata.plot(kind='density', ax=ax, color=color, title=group, legend=False) This is similar to 2., except it zips color and axes to a.Each object must be the same length.įig, axes = plt.subplots(nrows=2, ncols=2, figsize=(10, 6)) # define the figure and subplotsĬols = df.columns # create a list of dataframe columns to useĬolors = # list of colors for each subplot, otherwise all subplots will be one colorįor col, color, ax in zip(cols, colors, axes):ĭf.plot(kind='density', ax=ax, color=color, label=col, title=col)įig.delaxes(axes) # delete the empty subplotģ. Any variables applying to each axes, that need to be iterate through, are combined with.It's easiest to collapse the subplot array of Axes into one dimension with. ![]()
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