pandas 将列从 str 转换为 float [英] Pandas convert column from str to float

问题描述

对于下面的数据框，我正在使用代码

For the below dataframe I am using the code

df['%'] = ((df['Code Lines'] / df['Code Lines'].sum()) * 100).round(2).astype(str) + '%'

输出

Language    # of Files  Blank Lines Comment Lines   Code Lines  % 
C++              15          66           35            354    6.13%
C/C++ Header      1           3            7              4    0.07%
Markdown          6           73           0            142    2.46%
Python           110         1998       2086           4982    86.27%
Tcl/Tk            1          14           18            273    4.73%
YAML              1           0            6             20    0.35%

我正在尝试将 str 转换为 float

I am trying to convert the str to float

df['%'] = df['% of Total (Code Only)'].astype('float64')

出现错误

文件"/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/dtypes/cast.py",第 730 行，在 astype_nansafe 中返回 arr.astype(dtype, copy=True) ValueError:无法将字符串转换为浮点数:'0.35%'

File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/dtypes/cast.py", line 730, in astype_nansafe return arr.astype(dtype, copy=True) ValueError: could not convert string to float: '0.35%'

有没有办法将列 % 保持为浮动以及符号 %

is there a way to maintain the column % as float along with sign %

推荐答案

Use str[:-1] for remove last value (%) by 使用 str 进行索引:

Use str[:-1] for remove last value (%) by indexing with str:

df['%'] = df['%'].str[:-1].astype('float64')

但如果可能的话更好的是:

But if possible better is:

df['%'] = ((df['Code Lines'] / df['Code Lines'].sum()) * 100).round(2)

<小时>

print (df)
       Language  # of Files  Blank  Lines Comment  Lines Code Lines      %
0           C++          15     66             35               354   6.13
1  C/C++ Header           1      3              7                 4   0.07
2      Markdown           6     73              0               142   2.46
3        Python         110   1998           2086              4982  86.27
4        Tcl/Tk           1     14             18               273   4.73
5          YAML           1      0              6                20   0.35

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