In matplotlib, set the vertical axis on the left side of the histogram to frequency and the vertical axis on the right side to relative frequency (maybe a wicked way)

What to do in this article

This is the sequel to this article. com / kanedaq / items / 1e7a0e52363224c08980)

Histogram with matplotlib

--The vertical axis on the left is the frequency (default of matplotlib) --The vertical axis on the right is the relative frequency (total height of columns = 1)

And draw. However, it may be an evil way.

Reference page (Thank you)

[python] How to draw a graph with two axes on the left and right with matplotlib

Source code (Jupyter Notebook) and drawing results

The number of data is 7,500, and it is a normal random number with an average value of 50 and a standard deviation of 10. First, try running the following Python code.

#%%

import numpy as np
import matplotlib.pyplot as plt


#%%

#Data creation
μ = 50
σ = 10
data = [ np.random.normal(μ, σ) for i in range(7500) ]


#%%

#Number of classes
num_bins = 20

#Graph drawing
fig = plt.figure(figsize=(12, 8))
plt.legend()
plt.xlabel('x', fontsize=18)
plt.title('null', fontsize=18)

# (1)Histogram with frequency on the vertical axis
ax1 = fig.add_subplot(111)
ax1.set_ylabel('frequency', fontsize=18)
ax1.grid(True, color="dimgray")
ax1.set_axisbelow(True)    #Move grid to the back
ax1.hist(data, bins=num_bins, rwidth=0.5, align="mid")

# (2)Histogram with relative frequency on the vertical axis
ax2 = ax1.twinx()
ax2.set_ylabel('relative frequency', fontsize=18)
ax2.grid(True, color="lightgrey", linestyle="--")
ax2.set_axisbelow(True)    #Move grid to the back
weights = np.ones_like(data) / len(data)
ax2.hist(data, bins=num_bins, weights=weights, rwidth=0.5, align="right", color="red")

The vertical axis = frequency column is drawn in the default color, and the vertical axis = relative frequency column is drawn in red, side by side. People confirm that the heights of both of them look the same </ font> (The reason why they are evil ...)

# (3) (1)Adjust the appearance of
ax3 = ax1.twinx()
ax3.set_yticklabels([]) 
ax3.hist(data, bins=num_bins, rwidth=0.5, align="mid")

#%%

import numpy as np
import matplotlib.pyplot as plt


#%%

#Data creation
μ = 50
σ = 10
data = [ np.random.normal(μ, σ) for i in range(7500) ]


#%%

#Number of classes
num_bins = 20

#Graph drawing
fig = plt.figure(figsize=(12, 8))
plt.legend()
plt.xlabel('x', fontsize=18)
plt.title('null', fontsize=18)

# (1)Histogram with frequency on the vertical axis
ax1 = fig.add_subplot(111)
ax1.set_ylabel('frequency', fontsize=18)
ax1.grid(True, color="dimgray")
ax1.set_axisbelow(True)    #Move grid to the back
ax1.hist(data, bins=num_bins, rwidth=0.5, align="mid")

# (2)Histogram with relative frequency on the vertical axis
ax2 = ax1.twinx()
ax2.set_ylabel('relative frequency', fontsize=18)
ax2.grid(True, color="lightgrey", linestyle="--")
ax2.set_axisbelow(True)    #Move grid to the back
weights = np.ones_like(data) / len(data)
ax2.hist(data, bins=num_bins, weights=weights, rwidth=0.5, align="right")

# (3) (1)Adjust the appearance of
ax3 = ax1.twinx()
ax3.set_yticklabels([]) 
ax3.hist(data, bins=num_bins, rwidth=0.5, align="mid")