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
如何将所有负信用值移动到借方列(并删除空的贷方列)?
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
这将找到负值:
df.loc[df['Credit'] < 0]
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']]
谢谢!
最佳答案
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)
输出:
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
备注 : 如果
Debit
总是 Na
哪里Credit
是 <0
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)
关于python - 将条件值从一列复制到另一列,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/62011588/