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[英]Remove rows in pandas dataframe if any of specific columns contains a specific value
[英]Pandas group by a specific value in any of given columns
鉴于熊猫数据框如下:
Partner1 Partner2 Interactions
0 Ann Alice 1
1 Alice Kate 8
2 Kate Tony 9
3 Tony Ann 2
我怎样才能按特定的合作伙伴分组,比如说找到安的互动总数?
就像是
gb = df.groupby(['Partner1'] or ['Partner2']).agg({'Interactions': 'sum'})
并得到答案:
Partner Interactions
Ann 3
Alice 9
Kate 17
Tony 11
您可以使用melt
一起groupby
。 第一次melt
:
df = pd.melt(df, id_vars='Interactions', value_vars=['Partner1', 'Partner2'], value_name='Partner')
这将给出:
Interactions variable Partner
0 1 Partner1 Ann
1 8 Partner1 Alice
2 9 Partner1 Kate
3 2 Partner1 Tony
4 1 Partner2 Alice
5 8 Partner2 Kate
6 9 Partner2 Tony
7 2 Partner2 Ann
现在,按Partner
分组并求和:
df.groupby('Partner')[['Interactions']].sum()
结果:
Partner Interactions
Alice 9
Ann 3
Kate 17
Tony 11
您可以自己合并数据帧:
# join the df to itself
join_df = df.merge(df, left_on='Partner1', right_on='Partner2', suffixes=('', '_'))
# get sum
join_df['InteractionsSum'] = join_df[['Interactions', 'Interactions_']].agg(sum, 1)
join_df = join_df[['Partner1', 'Interactions']].copy()
print(join_df)
Partner1 Interactions
0 Ann 1
1 Alice 8
2 Kate 9
3 Tony 2
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