Question

我目前有一个如下所示的数据框表：

Day_Part    Start_Time    End_Time
Quarter 1   2014, 1, 1    2015, 3, 1
Quarter 2   2014, 3, 3    2014, 7, 3

列“Start_Time”和“End_Time”是pandas系列。我想将两列的数据类型转换为datetime。

我需要这两列具有datetime数据类型，因为在后面的代码块中，我说如果此列在此日期和此日期之间，那么我将其标记为Quarter 1.

*非常感谢任何帮助

Answer 1

您可以使用带有格式字符串的to_datetime（）来提取日期：

date = pd.to_datetime(df.Start_Time, format='%Y, %m, %d').dt.date

您还可以修改日期：

df[['Start_Time', 'End_Time']] = df[['Start_Time', 'End_Time']].apply(
    lambda x: pd.to_datetime(x, format='%Y, %m, %d').dt.date)

或者，您可以在阅读csv时转换为日期：

to_date = lambda x: pd.to_datetime(x, format='%Y, %m, %d').date()
converters = dict(Start_Time=to_date, End_Time=to_date)
df = pd.read_csv(StringIO(data), converters=converters)

一个可测试的例子：

import pandas as pd
from io import StringIO

data = u"""
Day_Part,Start_Time,End_Time
"Quarter 1","2014, 1, 1","2015, 3, 1"
"Quarter 2","2014, 3, 3","2014, 7, 3"
"""
df = pd.read_csv(StringIO(data))

# You can use `to_datetime()` with a format string to extract the date:
date = pd.to_datetime(df.Start_Time, format='%Y, %m, %d').dt.date

# The start month in the second row is 3
assert date[1].month == 3

# You can also modify in place
df[['Start_Time', 'End_Time']] = df[['Start_Time', 'End_Time']].apply(
    lambda x: pd.to_datetime(x, format='%Y, %m, %d').dt.date)

# The end month in the second row is 7
assert df.End_Time[1].month == 7

# You can convert to date when reading the csv
to_date = lambda x: pd.to_datetime(x, format='%Y, %m, %d').date()
converters = dict(Start_Time=to_date, End_Time=to_date)
df = pd.read_csv(StringIO(data), converters=converters)

# The end month in the first row is 3
assert df.End_Time[0].month == 3

Python：将dataframe列从Series转换为Datetime数据类型

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