Convert Pandas Column to DateTime

Question

I have one field in a pandas DataFrame that has been imported as a string format. It must be a datetime variable. How to convert it to datetime column and then filter by date.

Example:

• DataFrame Name: raw_data strong>
• Column Name: Mycol
• Column format value: '05SEP2014: 00: 00: 00.000'

Answer 1

Use the to_datetime function to to_datetime format that matches your data.

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

Answer 2

You can use the DataFrame .apply() method to work with 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 

Answer 3

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

works, however, this leads to a Python warning about the value trying to be set on the copy slice from the DataFrame. Use .loc[row_indexer,col_indexer] = value

I would suggest that this is due to some indexing of the chains.

Answer 4

 import pandas as pd df["MyCol"]=pd.to_datetime(df["MyCol"])