pandas DataFrame essentials: loading, indexing, and selection

                  import pandas as pd

df = pd.read_csv(
    'orders.csv',
    parse_dates=['created_at'],
    dtype={
        'customer_id': 'int64',
        'country': 'string',
        'status': 'category',
    },
)

df.columns = (
    df.columns.str.strip()
    .str.lower()
    .str.replace(' ', '_', regex=False)
)

active_orders = df.loc[
    (df['status'] == 'paid') &
    (df['country'].isin(['US', 'CA'])),
    ['customer_id', 'created_at', 'total_amount']
].copy()

active_orders = active_orders.set_index('created_at').sort_index()
latest_orders = active_orders.last('30D')

print(latest_orders.head())
print(latest_orders.dtypes)