Question

我使用

创建数据框

df3 = np.round(df2[["All"]]/df['Gender'].count()*100, 2).rename(columns={"All":'%'})

我希望在每个号码后添加%。我该怎么做？ df：

Third party unique identifier   Qsex    Gender
9ea3e3cb6719f3d336d324c446f486bd    1    male
d1b69bc4cccf0afef66debf4e3f0643e    2    female
f574fc585db0cddef88306ef6f32da59    1    male
8bc0a586bf0abec653c29cf4160753f9    1    male
7c22b56929378ec2eb3a536b4f4bc4e0    2    female
23d8433168c46d57a271a6b979037094    1    male
5743b7eec1b018572b6c5b44542a67a5    2    female
f176289325aa4a6fa56c0179e9cbd101    1    male
c729933ff7db798ae07c59d971f40a70    1    male

df2

    Qsex      1.0    2.0     All
Gender                      
Female      0  72342   72342
Male    51537      0   51537
All     51537  72342  123879

Answer 1

我认为您需要首先将normalize添加到crosstab，然后round，将100添加到多个，转换为string并最后添加% }：

df2 = pd.crosstab(df.Gender, df.Qsex, margins=True, normalize=True)
        .round(2)
        .mul(100)
        .astype(str) + '%'

print (df2)
Qsex        1      2     All
Gender                      
female   0.0%  33.0%   33.0%
male    67.0%   0.0%   67.0%
All     67.0%  33.0%  100.0%

因为如果仅使用astype(str) + '%'：

df2 = pd.crosstab(df.Gender, df.Qsex, margins=True).astype(str) + '%'
print (df2)
Qsex     1   2 All
Gender            
female  0%  3%  3%
male    6%  0%  6%
All     6%  3%  9%

熊猫：将符号附加到列中的单元格

1 个答案: