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I am trying to plot my data where it shows my predicted values superimposed with the actual data values. It does the job but the bar that represents the y value become ridiculously small and uninterpretable and the x-axis labels only show at the bottom of the last graph.

Bit of background- the class ids are essentially subplots of different graphs with different actual and predicted values. enter image description here

g = sns.catplot(data=plt_df,
                y='Outcome',
                            x='DT',
                            kind='bar',
                            ci=None,
                            hue='Outcome_Type',
                            row='CLASS_ID',
                            palette=sns.color_palette(['red', 'blue']),
                            height = 10,
                            aspect = 3.5)

            g.fig.subplots_adjust(hspace=1)
            fig, ax = plt.subplots(figsize=(20, 9))
            g.fig.suptitle("Distribution Plot Comparing Actual and Predicted Visits given caliberated Betas - " + describe_plot)
            
            g.set_xlabels('Drive Time (Mins')
            g.set_ylabels('Visits Percentage')
            plt.xticks(rotation= 90)
            plt.show()
SadJoe
  • 1

0 Answers0