pandas Read_Excel日期时间转换器 [英] Pandas Read_Excel Datetime Converter

问题描述

使用Python 3.6和Pandas 0.19.2：如何读取Excel文件并将列直接从 read_excel 更改为日期时间？类似于有关转换器和dtypes的问题。但是我想在特定列中读为 datetime

Using Python 3.6 and Pandas 0.19.2: How do you read in an excel file and change a column to datetime straight from read_excel? Similar to This Question about converters and dtypes. But I want to read in a certain column as datetime

我想更改此内容：

import pandas as pd
import datetime
import numpy as np

file = 'PATH_HERE'

df1 = pd.read_excel(file)

df1['COLUMN'] = pd.to_datetime(df1['COLUMN']) # <--- Line to get rid of

变成：
df1 = pd。 read_excel（file，dtypes = {'COLUMN'：datetime}）

代码没有错误，但在我的示例中为<$ c在调用 print（df1 ['COLUMN']。dtype）<之后，$ c> COLUMN 仍然是 int64 的dtype。 / code>

The code does not error, but in my example, COLUMN is still a dtype of int64 after calling print(df1['COLUMN'].dtype)

我尝试使用 np.datetime64 而不是 datetime 。我也尝试使用 converters = 代替 dtypes = ，但无济于事。

I have tried using np.datetime64 instead of datetime. I have also tried using converters= instead of dtypes= but to no avail. This may be nit picky, but would be a nice feature to implement in my code.

推荐答案

通常，阅读excel工作表会使用在excel工作表中定义的dtype，但是您不能像 read_csv 。您可以提供一个 转换器 arg，您可以为其传递列的字典和func来调用以转换列：

Typically reading excel sheets will use the dtypes defined in the excel sheets but you cannot specify the dtypes like in read_csv for example. You can provide a converters arg for which you can pass a dict of the column and func to call to convert the column:

df1 = pd.read_excel(file, converters= {'COLUMN': pd.to_datetime})

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