Pandas数据帧的两列条件和替换

Question

我有一个数据帧，我想在其中放置过滤器或条件，特别是对于两列。如果值没有通过阈值，请更改值，将其更改为零。我知道我可以通过转换到单独的数据帧来完成过滤和合并。如果有其他有效的方法，请建议我。

import pandas as pd
df = pd.DataFrame({"User": ["user1", "user2", "user2", "user3", "user2", "user1"],
"Amount": [10.0, 1.0, 8.0, 2, 7.5, 8.0],
"Amount2": [1, 5.0, 8.0, 10.5, 0, 8.0]})

我想要的输出>2阈值

User  Amount  Amount2
user1    10.0      0.0
user2     0.0      5.0
user2     8.0      8.0
user3     0.0     10.5
user2     7.5      0.0
user1     8.0      8.0

Answer 1

您可以将2到2以下的clip值替换为2到0

df[['Amount', 'Amount2']] = df[['Amount', 'Amount2']].clip(lower=2).replace(2, 0)

print(df)
User  Amount  Amount2
0  user1    10.0      0.0
1  user2     0.0      5.0
2  user2     8.0      8.0
3  user3     0.0     10.5
4  user2     7.5      0.0
5  user1     8.0      8.0

Answer 2

您可以使用numpy.where一次处理所有需要的列：

# select desired columns (here based on name)
cols = df.filter(like='Amount').columns
# it's also possible to manually set them
# cols = ['Amount', 'Amount2']
df[cols] = np.where(df[cols].le(2), 0, df[cols])  # or .lt(2) for <

更新的df:

User  Amount  Amount2
0  user1    10.0      0.0
1  user2     0.0      5.0
2  user2     8.0      8.0
3  user3     0.0     10.5
4  user2     7.5      0.0
5  user1     8.0      8.0

Answer 3

threshold = 2
df.loc[(df['Amount'] < threshold),'Amount'] = 0
df.loc[(df['Amount2'] < threshold),'Amount2'] = 0

Answer 4

您可以使用np.where:

import numpy as np
df['Amount'] = np.where(df['Amount'] < 2,0, df['Amount'])
df['Amount2'] = np.where(df['Amount2'] < 2,0, df['Amount2'])

或者，如果您的数据帧中只有以下列：

df = df.where(df < 2, 0)