bar labeling in matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('ggplot')
x = ['Nuclear', 'Hydro', 'Gas', 'Oil', 'Coal', 'Biofuel']
energy = [5, 6, 15, 22, 24, 8]
x_pos = [i for i, _ in enumerate(x)]
plt.bar(x_pos, energy, color='green')
plt.xlabel("Energy Source")
plt.ylabel("Energy Output (GJ)")
plt.title("Energy output from various fuel sources")
plt.xticks(x_pos, x)
plt.show()bar chart in python
import numpy as npimport matplotlib.pyplot as plt# data to plotn_groups = 4means_frank = (90, 55, 40, 65)means_guido = (85, 62, 54, 20)# create plotfig, ax = plt.subplots()index = np.arange(n_groups)bar_width = 0.35opacity = 0.8rects1 = plt.bar(index, means_frank, bar_width,alpha=opacity,color='b',label='Frank')rects2 = plt.bar(index + bar_width, means_guido, bar_width,alpha=opacity,color='g',label='Guido')plt.xlabel('Person')plt.ylabel('Scores')plt.title('Scores by person')plt.xticks(index + bar_width, ('A', 'B', 'C', 'D'))plt.legend()plt.tight_layout()plt.show()Grouped bar chart with labels
fig, ax = plt.subplots(figsize=(12, 8))
x = np.arange(len(df.job.unique()))
# Define bar width. We'll use this to offset the second bar.
bar_width = 0.4
# Note we add the `width` parameter now which sets the width of each bar.
b1 = ax.bar(x, df.loc[df['sex'] == 'men', 'count'],
width=bar_width)
# Same thing, but offset the x by the width of the bar.
b2 = ax.bar(x + bar_width, df.loc[df['sex'] == 'women', 'count'],
width=bar_width)Copyright © 2021 Codeinu
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