Using pandas to_datetime with timestamps

Last Updated : 24 Nov, 2022

In this article, we are going to convert timestamps to datetime using the to_datetime() method from the pandas package. A timestamp is encoded information or a set of characters identifying when a certain event occurred, giving date and time of day, which can be accurate to a small fraction of a second.

Syntax:

pandas.to_datetime(arg, errors=’raise’, dayfirst=False, yearfirst=False, utc=None, box=True, format=None, exact=True, unit=None, infer_datetime_format=False, origin=’unix’, cache=False)

Parameters:

arg: An integer, string, float, list or dict object to convert in to Date time object.

dayfirst: Boolean value, places day first if True.

yearfirst: Boolean value, places year first if True.

utc: Boolean value, Returns time in UTC if True.

format: String input to tell position of day, month and year.

Example 1: Timestamps with to_datetime.

Here we are converting the CSV file into a dataframe using pandas.DataFrame() method after reading the contents of the file using pandas.read_csv(), the timestamps column from the data Dataframe is given as an argument in the to_datetime() for it to be converted into DateTime. unit=’s’ is used to convert the values of the timestamp column to epoch time after converting the values to DateTime it is stored in a column called ‘Datetime’ in the Dataframe.

File Used:

Code:

Python3

# import packages
import pandas as pd
 
# creating a dataframe from the csv file
data = pd.DataFrame(pd.read_csv('timestamps.csv'))
 
# viewing our dataframe
print("Original dataframe")
display(data)
 
# unit='s' to convert it into epoch time
data['Datetime'] = pd.to_datetime(data['timestamps'], 
                                  unit='s')
 
# checking our dataframe once again
print("Timestamps")
display(data)

Output:

Example 2: Formatting the Datetime column.

The code is just the same as the previous example, the add-on is formatting the ‘DateTime’ column. The Datetime column in the previous example can be further modified using strftime() which takes a string as an argument. strftime() returns an Index of formatted strings specified by date_format, which supports the same string format as the python standard library.

Syntax: strftime(format)

Code:

Python3

# import packages
import pandas as pd
import datetime
 
# creating a dataframe from the csv file
data = pd.DataFrame(pd.read_csv('timestamps.csv'))
 
# unit='s' to convert it into epoch time
data['Datetime'] = pd.to_datetime(data['timestamps'],
                                  unit='s')
 
data['Modified Datetime'] = data['Datetime'].dt.strftime('%d-%m-%Y %H:%M')
 
# checking our dataframe once again
display(data)

Output:

Example 3: Using unit=’ms’ in the to_datetime() method.

The pd.to_datetime() method with a timestamp as argument and unit=’ms’, calculating the number of milliseconds to the Unix epoch start.

Python3

# import packages
import pandas as pd
 
# unit='ms' to calculate the number 
# of milliseconds
date = pd.to_datetime(1550767605,
                      unit = 'ms')
 
# checking our dataframe once again
print(date)