pandas 熊猫从 csv 读取数据帧，索引为字符串，而不是 int
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/31813500/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
Pandas read dataframe from csv with index as string, not int
提问by Quentin
My csv file is as following :
我的 csv 文件如下：
INDEX, VAL
04016170,22
04206261,11
0420677,11
df = pd.read_csv('data.csv', index_col='INDEX')
df = pd.read_csv('data.csv', index_col='INDEX')
How can I force pandas to read the index as string and not as integer (to preserve the first 0) ?
如何强制Pandas将索引读取为字符串而不是整数（以保留第一个0）？
回答by EdChum
You can pass the dtypeas a param this will map the column to the passed dtype:
您可以将dtype作为参数传递，这会将列映射到传递的数据类型：
In [130]:
import io
import pandas as pd
t="""INDEX,VAL
04016170,22
04206261,11
0420677,11"""
df = pd.read_csv(io.StringIO(t), index_col='VAL', dtype={'INDEX':str})
df
Out[130]:
INDEX
VAL
22 04016170
11 04206261
11 0420677
In [131]:
df.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 3 entries, 22 to 11
Data columns (total 1 columns):
INDEX 3 non-null object
dtypes: object(1)
memory usage: 48.0+ bytes
EDIT
编辑
OK, you can do it this way, there is a bug here when you explicitly set the index_colin read_csv, so you have to load the csv in first and then call set_indexafter loading:
好的，你可以这样做，当你显式设置index_colin 时read_csv，这里有一个错误，所以你必须先加载 csv ，然后set_index在加载后调用：
In [134]:
df = pd.read_csv(io.StringIO(t), dtype={'INDEX':str})
df = df.set_index('INDEX')
df
Out[134]:
VAL
INDEX
04016170 22
04206261 11
0420677 11
回答by themachinist
Another solution in two lines:
两行的另一种解决方案：
df = pd.read_csv('data.csv',index_col=0)
df.index = [str(x) for x in df.index]
or
或者
df.index = df.index.astype(str)
