raw data css

multiplycsv.py

import pandas as pd
import numpy as np  
from datetime import datetime, timedelta

# Read the CSV file
df = pd.read_csv('Rawdata.csv')
# Define the start and end dates
start_date = datetime(2020, 1, 1) 
end_date = datetime(2024, 12, 31)
# Generate a list of dates within the specified range
date_array = [start_date + timedelta(days=x) for x in range((end_date - start_date).days + 1)]

# Convert the dates to the desired string format ('%d-%m-%Y')
date_array_str = [date.strftime('%d-%m-%Y') for date in date_array] 

# Create a dictionary to store the dataframes for each date
ndf = {}
frames = []
# Update the 'Date' column with the new dates
for each  in date_array_str:
    ndf[each] = df.copy()
    ndf[each]['Value'] = np.random.randint(500,20000, size=len(df))
    ndf[each]['Date'] = each
    frames.append(ndf[each])

print("for loop df done")
# Concatenate the dataframes     
result = pd.concat(frames)
# Save the updated Excel file
result.to_csv('Outdata.csv', index=False)
# check status with sh
#tag=$( tail -n 1 Outdata.csv )
#echo $tag