How to Plot Multiple Gamma Distributions in Python with Matplotlib – A Step-by-Step Guide

1. Introduction

A follower asked a Python visualization question. The original code read a CSV and plotted a single gamma curve, resulting in only one figure.

2. Implementation

A contributor provided a solution that loops over the CSV rows, plots each gamma distribution, and shows all curves together.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as st

result_parameter_peak = pd.read_csv("result_parameter_peak.csv", encoding="utf_8_sig")

plt.figure()
for i, alpha, beta in result_parameter_peak.itertuples():
    x = np.arange(0, 300, 1)
    y661 = st.gamma.pdf(x, alpha, scale=beta)
    plt.plot(x, y661, '-.')
    plt.xlabel('Time')
    plt.ylabel('Probility')
    plt.title('Distribution')
plt.show()

The final version adds labels to each curve and displays a legend.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as st

result_parameter_peak = pd.read_csv("result_parameter_peak.csv", encoding="utf_8_sig")

plt.figure()
for i, alpha, beta in result_parameter_peak.itertuples():
    x = np.arange(0, 300, 1)
    y661 = st.gamma.pdf(x, alpha, scale=beta)
    plt.plot(x, y661, '-.', label="α:" + str(alpha) + "β:" + str(beta))
    plt.xlabel('Time')
    plt.ylabel('Probility')
    plt.title('Distribution')
plt.legend()
plt.show()

3. Conclusion

The article demonstrates how to solve the Matplotlib plotting issue, providing clear code and visual results, and thanks the contributors for their ideas and code.