Add Legend to Seaborn point plot

Question

I am plotting multiple dataframes as point plot using seaborn. Also I am plotting all the dataframes on the same axis.

How would I add legend to the plot ?

My code takes each of the dataframe and plots it one after another on the same figure.

Each dataframe has same columns

date        count 2017-01-01  35 2017-01-02  43 2017-01-03  12 2017-01-04  27  

My code :

f, ax = plt.subplots(1, 1, figsize=figsize) x_col='date' y_col = 'count' sns.pointplot(ax=ax,x=x_col,y=y_col,data=df_1,color='blue') sns.pointplot(ax=ax,x=x_col,y=y_col,data=df_2,color='green') sns.pointplot(ax=ax,x=x_col,y=y_col,data=df_3,color='red') 

This plots 3 lines on the same plot. However the legend is missing. The documentation does not accept label argument .

One workaround that worked was creating a new dataframe and using hue argument.

df_1['region'] = 'A' df_2['region'] = 'B' df_3['region'] = 'C' df = pd.concat([df_1,df_2,df_3]) sns.pointplot(ax=ax,x=x_col,y=y_col,data=df,hue='region') 

But I would like to know if there is a way to create a legend for the code that first adds sequentially point plot to the figure and then add a legend.

Sample output :

Answer 1

I would suggest not to use seaborn pointplot for plotting. This makes things unnecessarily complicated.
Instead use matplotlib plot_date. This allows to set labels to the plots and have them automatically put into a legend with ax.legend().

import matplotlib.pyplot as plt import pandas as pd import seaborn as sns import numpy as np  date = pd.date_range("2017-03", freq="M", periods=15) count = np.random.rand(15,4) df1 = pd.DataFrame({"date":date, "count" : count[:,0]}) df2 = pd.DataFrame({"date":date, "count" : count[:,1]+0.7}) df3 = pd.DataFrame({"date":date, "count" : count[:,2]+2})  f, ax = plt.subplots(1, 1) x_col='date' y_col = 'count'  ax.plot_date(df1.date, df1["count"], color="blue", label="A", linestyle="-") ax.plot_date(df2.date, df2["count"], color="red", label="B", linestyle="-") ax.plot_date(df3.date, df3["count"], color="green", label="C", linestyle="-")  ax.legend()  plt.gcf().autofmt_xdate() plt.show() 

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In case one is still interested in obtaining the legend for pointplots, here a way to go:

sns.pointplot(ax=ax,x=x_col,y=y_col,data=df1,color='blue') sns.pointplot(ax=ax,x=x_col,y=y_col,data=df2,color='green') sns.pointplot(ax=ax,x=x_col,y=y_col,data=df3,color='red')  ax.legend(handles=ax.lines[::len(df1)+1], labels=["A","B","C"])  ax.set_xticklabels([t.get_text().split("T")[0] for t in ax.get_xticklabels()]) plt.gcf().autofmt_xdate()  plt.show() 

Answer 2

Old question, but there's an easier way.

sns.pointplot(x=x_col,y=y_col,data=df_1,color='blue') sns.pointplot(x=x_col,y=y_col,data=df_2,color='green') sns.pointplot(x=x_col,y=y_col,data=df_3,color='red') plt.legend(labels=['legendEntry1', 'legendEntry2', 'legendEntry3']) 

This lets you add the plots sequentially, and not have to worry about any of the matplotlib crap besides defining the legend items.