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Pandas: Create a histogram to visualize daily return distribution of a stock price


Write a Pandas program to create a histogram to visualize daily return distribution of Alphabet Inc. stock price between two specific dates.

Use the alphabet_stock_data.csv file to extract data.

alphabet_stock_data:


alphabet_stock_data Table

Date Open High Low Close Adj Close Volume
2020-04-01 1122 1129.689941 1097.449951 1105.619995 1105.619995 2343100
2020-04-02 1098.26001 1126.859985 1096.400024 1120.839966 1120.839966 1964900
2020-04-03 1119.015015 1123.540039 1079.810059 1097.880005 1097.880005 2313400
2020-04-06 1138 1194.660034 1130.939941 1186.920044 1186.920044 2664700
... ... ... ... ... ... ...
... ... ... ... ... ... ...
2020-09-29 1470.390015 1476.662964 1458.805054 1469.329956 1469.329956 978200
2020-09-30 1466.800049 1489.75 1459.880005 1469.599976 1469.599976 1700600

Sample Solution:

Python Code :

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
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[['Date', 'Adj Close']]
df3 = df2.set_index('Date')
daily_changes = df3.pct_change(periods=1)
sns.distplot(daily_changes['Adj Close'].dropna(),bins=100,color='purple')
plt.suptitle('Daily % return of Alphabet Inc. stock price,\n01-04-2020 to 30-09-2020', fontsize=12, color='black')
plt.grid(True)
plt.show()

Sample Output:

Pandas: Create a histogram to visualize daily return distribution of a stock price

Click for download alphabet_stock_data.csv

Python Code Editor:

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Previous: Write a Pandas program to plot the volatility over a period of time of Alphabet Inc. stock price between two specific dates.

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