![]() ![]() We can see that we have a legend with colors but not the variable names. Our first attempt to add legends did not work well. Plt.savefig("scatterplot_colored_by_variable_legend_first_try_matplotlib_Python.png", Plt.legend(handles=scatter.legend_elements(), Scatter = plt.scatter(df.culmen_length_mm, In legend(), we specify title and handles by extracting legend elements from the plot. We provide the Pandas data frame and the variables for x and y argument to scatterplot function. Note that one could also use other functions like regplot. We can try to add legend to the scatterplot colored by a variable, by using legend() function in Matplotlib. import plotly.express as px df px.data.iris() fig px.scatter(df, x'sepalwidth', y'sepallength', color'species', symbol 'species') fig.show() 2 2.5 3 3.5 4 4.5 4.5 5 5.5 6 6.5 7 7. 1 gapmindergapminder ( 2002,1962) Scatterplot with Seaborn Default Colors Seaborn has a handy function named scatterplot to make scatter plots in Python. Add Color to Scatterplot by variable in Matplotlib Adding legend to Matplotlib scatte plot ![]() Note that the scatter plot colored by a variable is missing legend to describe the meaning of the clusters we see. Plt.savefig("scatterplot_point_colored_by_variable_matplotlib_Python.png", ![]() We use “c” argument in scatter() function to color data points by species variable in the dataframe.Ĭ=df.species.astype('category').cat.codes) ![]()
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