fill_gaps_in_currency_rates.py

#!/usr/bin/python3

import sys

if len(sys.argv) != 3:
    print("Usage: fill_gaps_in_currency_rates.py input_file_rates_with_gaps.csv output_file_rates_corrected.csv")
    exit()
else:
    input_file = sys.argv[1]
    output_file = sys.argv[2]

import pandas as pd

df = pd.read_csv(input_file, header=None, names=['Date', 'Rate'], parse_dates=['Date'], dayfirst=True)

# Ensure the 'Date' column is in datetime format
df['Date'] = pd.to_datetime(df['Date'], dayfirst=True)

# Create a DataFrame with all dates in the range, including weekends
date_range = pd.date_range(start=df['Date'].min(), end=df['Date'].max())
all_dates_df = pd.DataFrame({'Date': date_range})

# Merge the original DataFrame with the full date range DataFrame to fill in missing dates
result_df = pd.merge(all_dates_df, df, on='Date', how='left')

# Forward-fill missing values
result_df['Rate'].fillna(method='ffill', inplace=True)

# Write the result to another CSV file with the original date format
result_df.to_csv(output_file, index=False, date_format='%d.%m.%Y', float_format='%.5f')

print(f"Result has been written to {output_file}")