问题
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?
回答1:
Pass param thousands=','
to read_csv to read those values as thousands:
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2:
Take a look at the read_csv documentation 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.
来源:https://stackoverflow.com/questions/37439933/pandas-reading-csv-data-formatted-with-comma-for-thousands-separator