Handle Dates in Python using Pandas date time function

In this blog we will look at function which are used to handle dates in Python¶

Step 1: Importing Libraries¶

In [1]:

import pandas as pd
import numpy as np

Step 2: Creating Sample date¶

In [3]:

dt_val = "20 Jan 2022"
dt_val

Out[3]:

'20 Jan 2022'

In [7]:

# If we look at the data type, it is basically a string
type(dt_val)

Out[7]:

str

Step 3: Using data_time from Pandas to convert it into a date¶

In [13]:

dt_val_2 = pd.Series(dt_val)
dt_val_2

Out[13]:

0    20 Jan 2022
dtype: object

In [17]:

dt_val_3 = pd.to_datetime(dt_val_2)
dt_val_3

Out[17]:

0   2022-01-20
dtype: datetime64[ns]

Step 4: Other date strings that can be handled¶

In [18]:

other_val = pd.Series(['22/09/2020','22-09-2020','20200922','2020-09-22T13:25'])
other_val

Out[18]:

0          22/09/2020
1          22-09-2020
2            20200922
3    2020-09-22T13:25
dtype: object

All the date mentioned in the above series are object(basically text values).Lets convert them into date format using date_time function¶

In [21]:

other_val_dt=pd.to_datetime(other_val)
other_val_dt

Out[21]:

0   2020-09-22 00:00:00
1   2020-09-22 00:00:00
2   2020-09-22 00:00:00
3   2020-09-22 13:25:00
dtype: datetime64[ns]

In the next couple of blogs we will look at how to extract month, year and date from date string.We will also look at the parser package to handle dates¶