converting daily stock data to weekly-based via pandas in Python

Question

I\'ve got a DataFrame storing daily-based data which is as below:

Date              Open        High         Low       Close   Volume
2010-01-04         


        

Answer 1

I had the exact same question and found a great solution here.

https://www.techtrekking.com/how-to-convert-daily-time-series-data-into-weekly-and-monthly-using-pandas-and-python/

The weekly code is posted below.

import pandas as pd
import numpy as np

print('*** Program Started ***')

df = pd.read_csv('15-06-2016-TO-14-06-2018HDFCBANKALLN.csv')

# ensuring only equity series is considered
df = df.loc[df['Series'] == 'EQ']

# Converting date to pandas datetime format
df['Date'] = pd.to_datetime(df['Date'])
# Getting week number
df['Week_Number'] = df['Date'].dt.week
# Getting year. Weeknum is common across years to we need to create unique index by using year and weeknum
df['Year'] = df['Date'].dt.year

# Grouping based on required values
df2 = df.groupby(['Year','Week_Number']).agg({'Open Price':'first', 'High Price':'max', 'Low Price':'min', 'Close Price':'last','Total Traded Quantity':'sum'})
# df3 = df.groupby(['Year','Week_Number']).agg({'Open Price':'first', 'High Price':'max', 'Low Price':'min', 'Close Price':'last','Total Traded Quantity':'sum','Average Price':'avg'})
df2.to_csv('Weekly_OHLC.csv')
print('*** Program ended ***')