按列总和划分 Pandas 数据框中的列
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Divide Column in Pandas Dataframe by Sum of Column
提问by spacedinosaur10
I have a dataframe where I would like to divide each row within column A by the sum of column A and make that a new column within the dataframe.
我有一个数据框，我想将 A 列中的每一行除以 A 列的总和，并将其作为数据框中的一个新列。
Example:
Col A New Col
2 .22
3 .33
4 .44
Total = 9 1.00
I tried to sum Col A and then tried to divide by 'Total' but because Total is not a column but a row, it did not work. I just get NaN for each row within the new column.
我尝试对 Col A 求和，然后尝试除以“Total”，但因为 Total 不是一列而是一行，所以它不起作用。我只是为新列中的每一行获取 NaN。
df['New Col']= (df['ColA']/df.loc['Total'])
I know you can also probably integrate a sum calculation within the one line of code instead of creating a totals row as well but not sure how to do that and could not find anything online.
我知道你也可以在一行代码中集成一个总和计算，而不是创建一个总计行，但不知道如何做到这一点并且在网上找不到任何东西。
df['New Col']= (df['ColA']/df.sum())
Ideas?
想法？
回答by Steven G
df['new'] = df['ColA'] / df['ColA'].sum()
should work
应该管用
回答by Clade
回答by Andy
You are very close. You want to perform the sum()on the Col Aseries
你很亲近。你想sum()在Col A系列上表演
df['New Col'] = df['Col A']/df['Col A'].sum()
Results in a dataframe that looks like this:
结果是一个如下所示的数据框：
>>> df
Col A New Col
0 2 0.222222
1 3 0.333333
2 4 0.444444
Now if you do df.sum()you get a Series with the totals per column:
现在，如果你这样做，df.sum()你会得到一个每列总数的系列：
>>> df.sum()
Col A 9.0
New Col 1.0
dtype: float64
