Python 将 Pandas DataFrame 中带逗号的数字字符串转换为浮点数
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Convert number strings with commas in pandas DataFrame to float
提问by pheon
I have a DataFrame that contains numbers as strings with commas for the thousands marker. I need to convert them to floats.
我有一个数据帧，其中包含数字作为字符串，千位标记用逗号表示。我需要将它们转换为浮点数。
a = [['1,200', '4,200'], ['7,000', '-0.03'], [ '5', '0']]
df=pandas.DataFrame(a)
I am guessing I need to use locale.atof. Indeed
我猜我需要使用 locale.atof。的确
df[0].apply(locale.atof)
works as expected. I get a Series of floats.
按预期工作。我得到了一系列的花车。
But when I apply it to the DataFrame, I get an error.
但是当我将它应用到 DataFrame 时，出现错误。
df.apply(locale.atof)
TypeError: ("cannot convert the series to ", u'occurred at index 0')
类型错误：（“无法将系列转换为”，你'发生在索引 0'）
and
和
df[0:1].apply(locale.atof)
gives another error:
给出另一个错误：
ValueError: ('invalid literal for float(): 1,200', u'occurred at index 0')
ValueError: ('float() 的文字无效: 1,200', u'occurred at index 0')
So, how do I convert this DataFrameof strings to a DataFrame of floats?
那么，如何将这个DataFrame字符串转换为浮点数的 DataFrame 呢？
采纳答案by Andy Hayden
If you're reading in from csvthen you can use the thousands arg:
df.read_csv('foo.tsv', sep='\t', thousands=',')
This method is likely to be more efficient than performing the operation as a separate step.
这种方法可能比将操作作为单独的步骤执行更有效。
You need to set the localefirst:
您需要先设置语言环境：
In [ 9]: import locale
In [10]: from locale import atof
In [11]: locale.setlocale(locale.LC_NUMERIC, '')
Out[11]: 'en_GB.UTF-8'
In [12]: df.applymap(atof)
Out[12]:
0 1
0 1200 4200.00
1 7000 -0.03
2 5 0.00
回答by shen ke
You may use the pandas.Series.str.replacemethod:
您可以使用pandas.Series.str.replace方法：
df.iloc[:,:].str.replace(',', '').astype(float)
This method can remove or replace the comma in the string.
此方法可以删除或替换字符串中的逗号。
回答by ghollah kioko
You can convert one column at a time like this :
您可以像这样一次转换一列：
df['colname'] = df['colname'].str.replace(',', '').astype(float)
