如果有一列有NaN,如何更改整行

2024-03-28 09:17:25 发布

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我有一个这样的数据帧

                    gauge       satellite
1979-06-23 18:00:00 6.700000    2.484378
1979-06-27 03:00:00 NaN         8.891460
1979-06-27 06:00:00 1.833333    4.053460
1979-06-27 09:00:00 NaN         2.876649
1979-07-31 18:00:00 6.066667    1.438324

我想得到这样一个数据帧

                    gauge       satellite
1979-06-23 18:00:00 6.700000    2.484378
1979-06-27 03:00:00 NaN         NaN
1979-06-27 06:00:00 1.833333    4.053460
1979-06-27 09:00:00 NaN         NaN
1979-07-31 18:00:00 6.066667    1.438324

Tags: 数据nangaugesatellite
3条回答

使用^{}添加nan

import numpy as np
df['satellite'] = np.where(df['gauge'].isnull(),np.nan,df['satellite'])

第二种解决方案

使用.locisnull

df.loc[df['guage'].isnull(),'satellite'] = np.nan

mask

df.mask(df.gauge.isna())

                        gauge  satellite
1979-06-23 18:00:00  6.700000   2.484378
1979-06-27 03:00:00       NaN        NaN
1979-06-27 06:00:00  1.833333   4.053460
1979-06-27 09:00:00       NaN        NaN
1979-07-31 18:00:00  6.066667   1.438324

我要做的reindex

df.dropna().reindex(df.index)

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