<p>支持anky\u 91所说的,sort\u values()在这里会很有帮助。你知道吗</p>
<pre><code>import pandas as pd
df = pd.read_csv('file.csv')
# >>> df
# label uId adId operTime siteId slotId contentId netType
# 0 0 u147333631 3887 2019-03-30 15:01:55.617 10 30 2137 1
# 1 0 u146930169 1462 2019-03-31 09:51:15.275 3 32 1373 1
# 2 0 u139816523 2084 2019-03-27 08:10:41.769 10 30 2336 1
# 3 0 u106546472 1460 2019-03-31 08:51:41.085 3 32 1371 4
# 4 0 u106642861 2295 2019-03-27 22:58:03.679 3 32 2567 4
sub_df = df[(df['operTime']>'2019-03-31') & (df['operTime']<'2019-04-01')]
# >>> sub_df
# label uId adId operTime siteId slotId contentId netType
# 1 0 u146930169 1462 2019-03-31 09:51:15.275 3 32 1373 1
# 3 0 u106546472 1460 2019-03-31 08:51:41.085 3 32 1371 4
final_df = sub_df.sort_values(by=['operTime'])
# >>> final_df
# label uId adId operTime siteId slotId contentId netType
# 3 0 u106546472 1460 2019-03-31 08:51:41.085 3 32 1371 4
# 1 0 u146930169 1462 2019-03-31 09:51:15.275 3 32 1373 1
</code></pre>
<p>我认为您也可以在这里使用datetimeindex;如果文件足够大,这可能是必要的。你知道吗</p>