pandas 大熊猫读取以逗号分隔的千位分隔符格式的 CSV 数据

pandas reading CSV data formatted with comma for thousands separator

提问by EdChum

I am trying to create a dataframe in pandas using a CSV that is semicolon-delimited, and uses commas for the thousands separator on numeric data. Is there a way to read this in so that the type of the column is float and not string?

我正在尝试使用以分号分隔的 CSV 在 Pandas 中创建一个数据框，并使用逗号作为数字数据的千位分隔符。有没有办法读取它，以便列的类型是浮点数而不是字符串？

回答by EdChum

Pass param thousands=','to read_csvto read those values as thousands:

传递 param thousands=','toread_csv以将这些值读取为数千：

In [27]:
import pandas as pd
import io

t="""id;value
0;123,123
1;221,323,330
2;32,001"""
pd.read_csv(io.StringIO(t), thousands=r',', sep=';')

Out[27]:
   id      value
0   0     123123
1   1  221323330
2   2      32001

回答by Grr

Take a look at the read_csvdocumentation there is a keyword argument 'thousands' that you can pass the ',' into. Likewise if you had European data containing a '.' for the separator you could do the same.

查看read_csv文档，有一个关键字参数“千”，您可以将“,”传递给它。同样，如果您有包含 '.' 的欧洲数据。对于分隔符，您也可以这样做。