How to Convert String to Datetime in Pandas

You can use the following methods to convert a string column to a datetime format in a pandas DataFrame:

Method 1: Convert One String Column to Datetime

df['col1'] = pd.to_datetime(df['col1'])

Method 2: Convert Multiple String Columns to Datetime

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

The following examples show how to use each of these methods in practice with the following pandas DataFrame:

import pandas as pd

#create DataFrame
df = pd.DataFrame({'task': ['A', 'B', 'C', 'D'],
                   'due_date': ['4-15-2022', '5-19-2022', '6-14-2022', '10-24-2022'],
                   'comp_date': ['4-14-2022', '5-23-2022', '6-24-2022', '10-7-2022']})

#view DataFrame
print(df)

  task   due_date  comp_date
0    A 2022-04-15 2022-04-14
1    B 2022-05-19 2022-05-23
2    C 2022-06-14 2022-06-24
3    D 2022-10-24 2022-10-07

#view data type of each column
print(df.dtypes)

task         object
due_date     object
comp_date    object
dtype: object

We can see that each column in the DataFrame currently has a data type of object, i.e. a string.

Example 1: Convert One String Column to Datetime

We can use the following syntax to convert the due_date column from a string to a datetime:

#convert due_date column to datetime
df['due_date'] = pd.to_datetime(df['due_date'])

#view updated DataFrame
print(df)

  task   due_date  comp_date
0    A 2022-04-15  4-14-2022
1    B 2022-05-19  5-23-2022
2    C 2022-06-14  6-24-2022
3    D 2022-10-24  10-7-2022

#view data type of each column
print(df.dtypes)

task                 object
due_date     datetime64[ns]
comp_date            object
dtype: object

We can see that the due_date column has been converted to a datetime while all other columns have remain unchanged.

Example 2: Convert Multiple String Columns to Datetime

We can use the following syntax to convert both the due_date and comp_date columns from a string to a datetime:

#convert due_date and comp_date columns to datetime
df[['due_date', 'comp_date']] = df[['due_date', 'comp_date']].apply(pd.to_datetime)

#view updated DataFrame
print(df)

  task   due_date  comp_date
0    A 2022-04-15 2022-04-14
1    B 2022-05-19 2022-05-23
2    C 2022-06-14 2022-06-24
3    D 2022-10-24 2022-10-07

#view data type of each column
print(df.dtypes)

task                 object
due_date     datetime64[ns]
comp_date    datetime64[ns]
dtype: object