[英]Fill NAN values of a column in dataframe from other dataframe pandas
i have a table in pandas df我在 pandas df 有一张桌子
main_id p_id_y score
1 1 123 0.617523
0 2 456 0.617523
0 3 789 NaN
0 4 987 NaN
1 5 654 NaN
also i have another dataframe df2.我还有另一个数据框df2。 which has the column's其中有列的
p_id score
123 1.3
456 4.6
789 0.4
987 1.1
654 3.2
i have to fill all the scores for all p_id_y which is NaN
with the respective score of p_id
in df2
.我必须用df2
中p_id
的相应分数填充所有p_id_y which is NaN
。
my final output should be.我的最终输出应该是。
main_id p_id_y score
1 1 123 0.617523
0 2 456 0.617523
0 3 789 0.4
0 4 987 1.1
1 5 654 3.2
Any ideas how to achieve that?任何想法如何实现这一目标? i was thinking to use this我想用这个
df['score'] = df['score'].fillna(something)
I think you can use combine_first
or fillna
, but first set_index
for align data:我认为您可以使用combine_first
或fillna
,但首先set_index
用于对齐数据:
df1 = df1.set_index('p_id_y')
df1['score'] = df1['score'].combine_first(df2.set_index('p_id')['score'])
#df1['score'] = df1['score'].fillna(df2.set_index('p_id')['score'])
print (df1.reset_index())
p_id_y main_id score
0 123 1 0.617523
1 456 2 0.617523
2 789 3 0.400000
3 987 4 1.100000
4 654 5 3.200000
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