如何用Pandas筛选Excel日期？筛选DateTime列代码报错求助

Hey there! Let's break down the two issues you're facing and fix them one by one.

1. Fixing the dt.date Syntax Error #

First up, the error in msft['Tested On']dt.date is just a tiny syntax mistake—you're missing a dot between the column reference and .dt. The correct syntax to access date components is:

msft['Tested On'].dt.date

This converts full datetime values to date-only objects (stripping off hours/minutes/seconds), which is essential for accurate date filtering.

2. Correctly Filtering for a Specific Date #

Your initial code df = msft[msft.Tested On == '2018-01-11'] likely failed because your Tested On column stores full datetime values (even if the time part isn't visible in Excel). Comparing directly to a date string only matches rows where the datetime is exactly 2018-01-11 00:00:00—most rows with that date but any other time won't be included.

Here are three reliable ways to capture all rows from 2018-01-11:

Method 1: Compare date objects #

Convert the datetime column to date objects and match against a date instance:

from datetime import date
target_date = date(2018, 1, 11)
df = msft[msft['Tested On'].dt.date == target_date]

Method 2: Floor datetime to day level #

Use .dt.floor('D') to strip the time component from datetime values, then compare to a timestamp:

import pandas as pd
target_timestamp = pd.Timestamp('2018-01-11')
df = msft[msft['Tested On'].dt.floor('D') == target_timestamp]

Method 3: Filter by date range #

This is often the most robust approach, as it captures all datetimes from midnight of the target date up to (but not including) midnight the next day:

start_date = '2018-01-11'
end_date = '2018-01-12'
df = msft[(msft['Tested On'] >= start_date) & (msft['Tested On'] < end_date)]

Quick Pre-Filter Check #

Before filtering, confirm your column is actually stored as datetime type with:

print(msft['Tested On'].dtype)

It should show something like datetime64[ns]. If not, convert it first using msft['Tested On'] = pd.to_datetime(msft['Tested On']).

内容的提问来源于stack exchange，提问作者gomathi subramanian