问题:将Pandas列转换为DateTime

我在以字符串格式导入的pandas DataFrame中有一个字段。它应该是日期时间变量。如何将其转换为datetime列,然后根据日期进行过滤。

例:

  • 数据框名称:raw_data
  • 列名称:Mycol
  • 列中的值格式:“ 05SEP2014:00:00:00.000”

I have one field in a pandas DataFrame that was imported as string format. It should be a datetime variable. How do I convert it to a datetime column and then filter based on date.

Example:

  • DataFrame Name: raw_data
  • Column Name: Mycol
  • Value Format in Column: ’05SEP2014:00:00:00.000′

回答 0

使用该to_datetime函数,指定一种格式以匹配您的数据。

raw_data['Mycol'] =  pd.to_datetime(raw_data['Mycol'], format='%d%b%Y:%H:%M:%S.%f')

Use the to_datetime function, specifying a format to match your data.

raw_data['Mycol'] =  pd.to_datetime(raw_data['Mycol'], format='%d%b%Y:%H:%M:%S.%f')

回答 1

您可以使用DataFrame方法.apply()对Mycol中的值进行操作:

>>> df = pd.DataFrame(['05SEP2014:00:00:00.000'],columns=['Mycol'])
>>> df
                    Mycol
0  05SEP2014:00:00:00.000
>>> import datetime as dt
>>> df['Mycol'] = df['Mycol'].apply(lambda x: 
                                    dt.datetime.strptime(x,'%d%b%Y:%H:%M:%S.%f'))
>>> df
       Mycol
0 2014-09-05

You can use the DataFrame method .apply() to operate on the values in Mycol:

>>> df = pd.DataFrame(['05SEP2014:00:00:00.000'],columns=['Mycol'])
>>> df
                    Mycol
0  05SEP2014:00:00:00.000
>>> import datetime as dt
>>> df['Mycol'] = df['Mycol'].apply(lambda x: 
                                    dt.datetime.strptime(x,'%d%b%Y:%H:%M:%S.%f'))
>>> df
       Mycol
0 2014-09-05

回答 2

如果要转换的列不止一个,则可以执行以下操作:

df[["col1", "col2", "col3"]] = df[["col1", "col2", "col3"]].apply(pd.to_datetime)

If you have more than one column to be converted you can do the following:

df[["col1", "col2", "col3"]] = df[["col1", "col2", "col3"]].apply(pd.to_datetime)

回答 3

raw_data['Mycol'] =  pd.to_datetime(raw_data['Mycol'], format='%d%b%Y:%H:%M:%S.%f')

可以,但是会导致Python警告:试图在DataFrame的切片副本上设置一个值。尝试.loc[row_indexer,col_indexer] = value改用

我猜这是由于一些链接索引。

raw_data['Mycol'] =  pd.to_datetime(raw_data['Mycol'], format='%d%b%Y:%H:%M:%S.%f')

works, however it results in a Python warning of A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead

I would guess this is due to some chaining indexing.


回答 4

使用pandas to_datetime函数将列解析为DateTime。另外,通过使用infer_datetime_format=True,它将自动检测格式并将提到的列转换为DateTime。

import pandas as pd
raw_data['Mycol'] =  pd.to_datetime(raw_data['Mycol'], infer_datetime_format=True)

Use the pandas to_datetime function to parse the column as DateTime. Also, by using infer_datetime_format=True, it will automatically detect the format and convert the mentioned column to DateTime.

import pandas as pd
raw_data['Mycol'] =  pd.to_datetime(raw_data['Mycol'], infer_datetime_format=True)

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