The code provided by @amance is already optimized for performance and readability. However, I can suggest a few minor improvements to make it even better:

1. Add type hints for the function parameters:

def between_new(identifier: str, df1: pd.DataFrame, start_date: str, end_date: str, df2: pd.DataFrame, event_date: str) -> pd.Series:

This makes it clear what types of data are expected as input and what type of output is expected.

2. Use a more descriptive variable name instead of df_out:

merged_df = df3.merge(df_temp, on=identifier)

This makes the code easier to read and understand.

3. Remove the unnecessary set_index('event_index') call:

return merged_df[['event_index', 'final_index']].drop(columns='event_index')

This simplifies the output and removes unnecessary indexing.

Here’s the updated code:

import pandas as pd

def between_new(identifier: str, df1: pd.DataFrame, start_date: str, end_date: str, df2: pd.DataFrame, event_date: str) -> pd.Series:
    df_temp = df1.reset_index().rename(columns={'index':'final_index'})[[identifier, 'final_index', start_date, end_date]]
    merged_df = df2.merge(df_temp, on=identifier)
    return merged_df[['event_index', 'final_index']].drop(columns='event_index')

Overall, the code is already well-optimized and easy to understand. These minor improvements are just suggestions for further improvement.

Last modified on 2023-07-11