[英]Copy conditional values from one column to another
Given a df like this:给定这样的df:
Date Category Debit Credit
2020-01-05 Utility 55.32 NA
2020-01-05 Movie 20.01 NA
2020-01-05 Payment NA -255.32
2020-01-05 Grocery 97.64 NA
How do I move all negative Credit values to the Debit column (and delete the empty Credit column)?如何将所有负信用值移动到借方列(并删除空的信用列)?
Date Category Debit
2020-01-05 Utility 55.32
2020-01-05 Movie 20.01
2020-01-05 Payment -255.32
2020-01-05 Grocery 97.64
This will find the negative values:这将找到负值:
df.loc[df['Credit'] < 0]
But this doesn't work (minimal pandas skills)但这不起作用(最小的 pandas 技能)
def creditmover():
If df.loc[df['Credit'] < 0]:
df.loc[df['Debit']]=df.loc[df['Credit']]
Thanks!谢谢!
According to your logic, you could do:根据你的逻辑,你可以这样做:
# where credit is < 0
s = df['Credit'] < 0
# copy the corresponding values
df.loc[s, 'Debit'] = df.loc[s, 'Credit']
# drop Credit
df = df.drop('Credit', axis=1)
Output: Output:
Date Category Debit
0 2020-01-05 Utility 55.32
1 2020-01-05 Movie 20.01
2 2020-01-05 Payment -255.32
3 2020-01-05 Grocery 97.64
Note : If Debit
is always Na
wherever Credit
is <0
and vise versa, then you can simply do:注意:如果在
Credit
<0
的情况下, Debit
始终为Na
,反之亦然,那么您可以简单地执行以下操作:
df['Debit'] = df['Debit'].fillna(df['Credit'])
df = df.drop('Credit', axis=1)
We can do pop
我们可以做
pop
df.loc[df.pop('Credit')<=0,'Debit']=df.Credit
df
Date Category Debit
0 2020-01-05 Utility 55.32
1 2020-01-05 Movie 20.01
2 2020-01-05 Payment -255.32
3 2020-01-05 Grocery 97.64
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