Pandas: Create a stacked histograms plot of different columns

Last update on April 08 2025 12:47:39 (UTC/GMT +8 hours)

8. Stacked Histograms of Stock Prices

Write a Pandas program to create a stacked histograms plot of opening, closing, high, low stock prices of Alphabet Inc. between two specific dates.

Use the alphabet_stock_data.csv file to extract data.

alphabet_stock_data:

alphabet_stock_data Table

Sample Solution:

Python Code :

import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("alphabet_stock_data.csv")
start_date = pd.to_datetime('2020-4-1')
end_date = pd.to_datetime('2020-9-30')                         
df['Date'] = pd.to_datetime(df['Date']) 
new_df = (df['Date']>= start_date) & (df['Date']<= end_date)
df1 = df.loc[new_df]
df2 = df1[['Open','Close','High','Low']]
plt.figure(figsize=(25,25))
df2.plot.hist(stacked=True, bins=20)
plt.suptitle('Opening/Closing/High/Low stock prices of Alphabet Inc.,\n From 01-04-2020 to 30-09-2020', fontsize=12, color='blue')
plt.show()

Sample Output:

Click for download alphabet_stock_data.csv

For more Practice: Solve these Related Problems:

• Write a Pandas program to create a stacked histogram that combines opening, closing, high, and low prices into one plot.
• Write a Pandas program to generate a stacked histogram for the four price columns using different color shades for each.
• Write a Pandas program to build a stacked histogram that displays the relative frequency of each price type on a single axis.
• Write a Pandas program to produce a pivot table of price data and plot it as a stacked histogram to compare distributions.

Python Code Editor:

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