Pandas Read_Excel 日期时间转换器
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Pandas Read_Excel Datetime Converter
提问by MattR
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
使用 Python 3.6 和 Pandas 0.19.2：您如何读取 excel 文件并将列直接从 更改为日期时间read_excel？类似于关于转换器和 dtypes 的这个问题。但我想在某个专栏中阅读datetime
I want to change this:
我想改变这个：
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
into something like:
df1 = pd.read_excel(file, dtypes= {'COLUMN': datetime})
变成类似的东西：
df1 = pd.read_excel(file, dtypes= {'COLUMN': datetime})
The code does not error, but in my example, COLUMNis still a dtype of int64after calling print(df1['COLUMN'].dtype)
代码没有错误，但在我的例子中，COLUMN仍然是int64调用后的dtypeprint(df1['COLUMN'].dtype)
I have tried using np.datetime64instead 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.
我试过使用np.datetime64代替datetime. 我也试过使用 converters=代替dtypes=但无济于事。这可能有点挑剔，但在我的代码中实现将是一个很好的功能。
回答by EdChum
Typically reading excel sheets will use the dtypes defined in the excel sheets but you cannot specify the dtypes like in read_csvfor example. You can provide a convertersarg for which you can pass a dict of the column and func to call to convert the column:
通常，读取 excel 表将使用 excel 表中定义的 dtypes，但您不能指定 dtypes read_csv，例如。您可以提供一个convertersarg，您可以为其传递列的 dict 和 func 以调用以转换列：
df1 = pd.read_excel(file, converters= {'COLUMN': pd.to_datetime})
