Pandas 数据框列的浮动百分比样式错误
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Pandas dataframe column of floats to percentage style error
提问by Solar
I am trying to convert a pandas dataframe column of floats to percentage style
我正在尝试将浮点数的 Pandas 数据框列转换为百分比样式
C
0.9977
0.1234
1.000
..
to
到
C
99.77%
12.34%
100%
...
To do this, I am doing:
为此，我正在做：
df['C'] = df['C'].map(lambda n: '{:.2%}'.format(n))
but I am getting the following error:
但我收到以下错误：
ValueError: Unknown format code '%' for object of type 'str'
I also tried '{:,.2%}'with the same error...
我也尝试'{:,.2%}'过同样的错误......
What I am doing wrong?
我做错了什么？
Thanks in advance!!
提前致谢！！
采纳答案by jezrael
First convert column to floats by astype:
首先将列转换为浮点数astype：
df['C'] = df['C'].astype(float).map(lambda n: '{:.2%}'.format(n))
Also solution should be simplify:
解决方案也应该简化：
df['C'] = df['C'].astype(float).map("{:.2%}".format)
EDIT:
编辑：
Problem is some non numeric values in column.
问题是列中有一些非数字值。
Replace non numeric to 0:
将非数字替换为0：
print (df)
C
0 0.9977
1 0.1234
2 Covered fraction
df['C'] = pd.to_numeric(df['C'], errors='coerce').fillna(0).map("{:.2%}".format)
print (df)
C
0 99.77%
1 12.34%
2 0.00%
Or remove rows with these values:
或删除具有这些值的行：
df['C'] = pd.to_numeric(df['C'], errors='coerce')
df = df.dropna(subset=['C'])
df['C'] = df['C'].astype(float).map("{:.2%}".format)
print (df)
C
0 99.77%
1 12.34%
回答by Mohit Motwani
You can also use df.style:
您还可以使用df.style：
df.style.format({'C': '{:.2%}'})
If your series data type is not an issue and want to use it as string try:
如果您的系列数据类型不是问题并且想将其用作字符串，请尝试：
df['C'] = df.C.apply(lambda x: f"{x[:x.find('.')+3]}%")
df
C
0 0.99%
1 0.12%
2 1.00%
OR if using python <3.6:
或者，如果使用 python <3.6：
df['C'] = df.C.apply(lambda x: x[:x.find('.')+3]+'%')
Using Jezrael's idea convert to numeric column and invalid strings as 0:
使用 Jezrael 的想法转换为数字列和无效字符串为 0：
df['C'] = pd.to_numeric(df['C'], errors='coerce').fillna(0)
df.style.format({'C': '{:.2%}'})
