I\'m making a bar plot and I want the colors of the bars to vary from red to blue according to a color gradient. I have a dimension of the data frame that tells me where on
It's pretty straight forward to create a barchart and set the bar colors according to a value from the dataframe. A colormap and a normalization instance help converting the values to colors, which are understood by the color
argument of matplotlib.Axes.bar
. The colorbar is then created from a ScalarMappable
using the same normalization and colormap as the bars.
import matplotlib.pyplot as plt
import matplotlib.colors
import numpy as np; np.random.seed(0)
import pandas as pd
x = np.arange(12)
y = np.random.rand(len(x))*51
c = np.random.rand(len(x))*3+1.5
df = pd.DataFrame({"x":x,"y":y,"c":c})
cmap = plt.cm.rainbow
norm = matplotlib.colors.Normalize(vmin=1.5, vmax=4.5)
fig, ax = plt.subplots()
ax.bar(df.x, df.y, color=cmap(norm(df.c.values)))
ax.set_xticks(df.x)
sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
sm.set_array([]) # only needed for matplotlib < 3.1
fig.colorbar(sm)
plt.show()
For using a custom colormap with bar plots see Barplot colored according a colormap?