如何在Python DataFrame中判断date1列日期是否处于date2列日期的±10天范围内

Got it, let's walk through how to solve this problem step by step. The core goal is to verify if each date in the date1 column falls within a 10-day window (either before or after) the corresponding date in the date2 column.

Step 1: Convert date columns to datetime type #

First up, we need to turn those string dates into proper datetime objects—strings can't be used to calculate date differences reliably. We'll use pd.to_datetime() and explicitly set the format parameter since our dates follow the DD/MM/YYYY pattern.

Step 2: Calculate date differences and check the 10-day condition #

Once we have datetime-formatted columns, we can compute the absolute difference between date1 and date2, extract the number of days from that difference, and check if it's 10 or less.

Full code example #

import pandas as pd

# Create the sample DataFrame from your scenario
df = pd.DataFrame({
    'date1': ['13/08/2021'],
    'date2': ['21/08/2021']
})

# Convert string dates to datetime objects
df['date1'] = pd.to_datetime(df['date1'], format='%d/%m/%Y')
df['date2'] = pd.to_datetime(df['date2'], format='%d/%m/%Y')

# Add a new column with the boolean check result
df['within_10_days'] = abs(df['date1'] - df['date2']).dt.days <= 10

# Print the result
print(df['within_10_days'])

Why the sample returns True #

In your example, the difference between 13/08/2021 and 21/08/2021 is 8 days—this is well within the ±10 day range, so the output will be a Series with the value True.

This logic works for multiple rows too: it will check each pair of dates individually and return a boolean value for every entry in your DataFrame.

内容的提问来源于stack exchange，提问作者Souvik Pal