我想，以取代hours在df与hours来自replacements对同时存在于两个dataframes项目编号：
import pandas as pd
df = pd.DataFrame({
'project_ids': [1, 2, 3, 4, 5],
'hours': [111, 222, 333, 444, 555],
'else' :['a', 'b', 'c', 'd', 'e']
})
replacements = pd.DataFrame({
'project_ids': [2, 5, 3],
'hours': [666, 999, 1000],
})
for project in replacements['project_ids']:
df.loc[df['project_ids'] == project, 'hours'] = replacements.loc[replacements['project_ids'] == project, 'hours']
print(df)
但是，只有项目 ID 3 获得正确分配 (1000)，但 2 和 5 均获得NaN：
projects hours else
0 1 111.0 a
1 2 NaN b
2 3 1000.0 c
3 4 444.0 d
4 5 NaN e
使用Series.map与其他Series通过创建replacements具有DataFrame.set_index：
s = replacements.set_index('project_ids')['hours']
df['hours'] = df['project_ids'].map(s).fillna(df['hours'])
print(df)
project_ids hours else
0 1 111.0 a
1 2 666.0 b
2 3 1000.0 c
3 4 444.0 d
4 5 999.0 e
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