使用 python 更改特定 Pandas 数据框列中的行值
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Change row values in specific pandas data frame column with python
提问by Saibottrenham
Following problem.
以下问题。
I have a data frame with the following format.
我有一个具有以下格式的数据框。
Col1 Col2 Col3 Col4
1 0 0 0 0
2 0 0 0 0
Furthermore, I have a List of values that match the column names:
此外，我有一个与列名匹配的值列表：
ColNameList1 = [Col1, Col3] #list for the first row
ColNameList2 = [Col3, Col4] #list for the second row
The target is to change the value of 0 to 1 for every column row match.
目标是将每个列行匹配的值从 0 更改为 1。
Col1 Col2 Col3 Col4
1 1 0 1 0
2 0 0 1 1
I did some intense research on the Pandas documentation and also google and stack overflow but it seems there is not a fitting solution for this problem.
我对 Pandas 文档以及谷歌和堆栈溢出做了一些深入的研究，但似乎没有合适的解决方案来解决这个问题。
As always any help is much appreciated.
与往常一样，非常感谢任何帮助。
回答by Allen
You can simply use loc and set values:
您可以简单地使用 loc 并设置值：
df.loc[1,ColNameList1]=1
df.loc[2,ColNameList2]=1
df
Out[10]:
Col1 Col2 Col3 Col4
1 1 0 1 0
2 0 0 1 1
