pandas pipe logo pandas pipe: start

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The code below demonstrates the importance of starting a pipeline with a copy of the original dataframe.

import pandas as pd

df = pd.read_csv('')

def start_pipeline(dataf):
    return dataf.copy()

def set_types(dataf):
    dataf['date'] = pd.to_datetime(dataf['date'])
    return dataf

df.pipe(start_pipeline).pipe(set_types).dtypes, df.dtypes

The main important thing to get right here is to make sure that we do not change the original dataframe as a side-effect.