[FIXED] How to map colors to certain values in a heatmap with plt.hist2d function?

Issue

I am plotting a Faceted Grid of heatmaps using matplotlib.pyplot.hist2d as an argument to the map function of the seaborn.FacetGrid object, the problem is the color representation of values is not consistent across the different plots. How to map the color palette values to constant values for all the plots?

def hist2dgrid(x, y, **kwargs):
    palette = kwargs.pop('color')
    bins_x = np.arange(0,24+1.5,1.5)
    bins_y = np.arange(0,36+3,2)
    plt.hist2d(x, y, bins = [bins_x, bins_y], cmap = palette, cmin = 0.5)
    plt.colorbar(label='count')

g= sns.FacetGrid(data=df_clean,col='start_time_day_name',col_wrap = 3)
g.map(hist2dgrid, 'start_time_hour_decimal', 'avg_trip_speed_kmh',color='viridis_r');

Output is:

Solution

You should pass to matplotlib.pyplot.hist2d vmin and vmax parameters:

Result on a random dataset, without above parameters:

Result on the same dataset, with above parameters:

plt.hist2d(x, y, bins = [bins_x, bins_y], cmap = palette, cmin = 0.5, vmin = 30, vmax = 40)

Answered By - Zephyr