如何设置列为日期索引? [英] how set column as date index?

问题描述

我的数据集如下:

       Date    Value
    1/1/1988    0.62
    1/2/1988    0.64
    1/3/1988    0.65
    1/4/1988    0.66
    1/5/1988    0.67
    1/6/1988    0.66
    1/7/1988    0.64
    1/8/1988    0.66
    1/9/1988    0.65
    1/10/1988   0.65
    1/11/1988   0.64
    1/12/1988   0.66
    1/13/1988   0.67
    1/14/1988   0.66
    1/15/1988   0.65
    1/16/1988   0.64
    1/17/1988   0.62
    1/18/1988   0.64
    1/19/1988   0.62
    1/20/1988   0.62
    1/21/1988   0.64
    1/22/1988   0.62
    1/23/1988   0.60

我使用此代码读取此数据

I used this code to read this data

df.set_index(df['Date'], drop=False, append=False, inplace=False, verify_integrity=False).drop('Date', 1)

但是问题是索引不是日期格式.那么问题是如何将此列设置为日期索引?

but the problem is index is not in date format. So the question is how to set this column as date index?

推荐答案

您的问题缺少适当的解释，但是您可以执行以下操作:

Your question lacked a proper explanation, but you can do the following:

In [75]:
# convert to datetime
df['Date'] = pd.to_datetime(df['Date'])
df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 23 entries, 0 to 22
Data columns (total 2 columns):
Date     23 non-null datetime64[ns]
Value    23 non-null float64
dtypes: datetime64[ns](1), float64(1)
memory usage: 448.0 bytes

In [76]:
# set the index
df.set_index('Date', inplace=True)
df.info()

<class 'pandas.core.frame.DataFrame'>
DatetimeIndex: 23 entries, 1988-01-01 to 1988-01-23
Data columns (total 1 columns):
Value    23 non-null float64
dtypes: float64(1)
memory usage: 368.0 bytes

因此，此处 to_datetime 将转换日期字符串为datetime dtype， set_index 您只需使用参数inplace=True

So here to_datetime will convert date strings to datetime dtype, set_index with param inplace=True is all you need,

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