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 packagesimport pandas as pd# creating a dataframe from the csv filedata = pd.DataFrame(pd.read_csv('timestamps.csv'))# viewing our dataframeprint("Original dataframe")display(data)# unit='s' to convert it into epoch timedata['Datetime'] = pd.to_datetime(data['timestamps'], unit='s')# checking our dataframe once againprint("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 packagesimport pandas as pdimport datetime# creating a dataframe from the csv filedata = pd.DataFrame(pd.read_csv('timestamps.csv'))# unit='s' to convert it into epoch timedata['Datetime'] = pd.to_datetime(data['timestamps'], unit='s')data['Modified Datetime'] = data['Datetime'].dt.strftime('%d-%m-%Y %H:%M')# checking our dataframe once againdisplay(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 packagesimport pandas as pd# unit='ms' to calculate the number# of millisecondsdate = pd.to_datetime(1550767605, unit = 'ms')# checking our dataframe once againprint(date) |
Output:
1970-01-18 22:46:07.605000
