Python Pandas Period.to_timestamp() Example

Getting started with Python to_timestamp using pandas

Pandas is an open-source library in Python. It provides ready-to-use high-performance data structures and data analysis tools. Pandas module runs on top of NumPy and it is popularly used for data science and data analytics. Apart from data manipulations, it can also be used to visualize the data using various plots.

Pandas module has many useful methods and one of them is to_timestamp() method. This method returns the Timestamp representation of the Period at the target frequency at the specified end of the period. A timestamp is a sequence of characters or encoded information identifying when a certain event occurred,

Advertisement

The simple syntax of the python to_timestamp method is as follows:

Period.to_timestamp()

Now let us jump into the practical part and understand how the to_timestam() method works in Python.

 

Example-1: Python to_timestamp() method with default parameter values

Before going to the implementation part, make sure that you have installed the pandas' module on your system. You can use the pip command to install the module. Once the installation is complete, import the module.

# importing pandas module
import pandas as pd

Let us first create a Period and then will use the to_timestamp() method to convert the period to a time stamp.

# Creating a time period
timePeriod = pd.Period(freq ='S', year = 2002, month = 3, day = 24,
                         hour = 2, minute = 1, second = 33)
  
# Print the Period object
print(timePeriod)

Output:

to_timestamp-data

This is now a Period, you can also verify by printing the type of the variable as shown below:

Advertisement
# printing the type of the variable
print(type(timePeriod))

Output:

Python-to_timestam

Periods can be used to check if a specific event occurs within a certain period. Basically, a Period represents an interval while a Timestamp represents a point in time. Now, let us convert the above Period into a time stamp.

# converting period to timestamp
timeStamp =timePeriod.to_timestamp()

# printing
print(timeStamp)

Output:

time-stamp

Let us also check the type to verify that it is now a time stamp.

# printing the type of the variable
print(type(timeStamp))

Output:

time-stamp-by-default

As you can see, we have converted a period into a time stamp using python. So far we have converted a Period into a time stamp using the default parameters of to_timestamp() method. Let us now look at its parameters as well.

Advertisement

 

Example-2: Python to_timestamp() with different parameter values

The to_timestamp() method takes an optional parameter known as frequency. It specifies the timestamp in the specified frequency. For example, "M" represents monthly frequency, and "T" represents minute frequency. Let us take an example and understand how the parameter in to_timestamp works. We will again create a Period and will convert the Period into a times stamp by specifying the frequency.

# Creating a time period
timePeriod = pd.Period(freq='S',year = 2002, month = 3, day = 24,
                         hour = 2, minute = 1, second = 33)

# T shows minutely frequency
timeStamp =timePeriod.to_timestamp(freq ="T")

# print
print(timeStamp)

Output:

time-stamp-freq-T

As you can see, the seconds have been assigned 00 because we specified frequency as minutes. If we will assign the frequency monthly, then hours, minutes, and seconds will be zeros.

# Creating a time period
timePeriod = pd.Period(freq='S',year = 2002, month = 3, day = 24,
                         hour = 2, minute = 1, second = 33)

# T shows minutely frequency
timeStamp =timePeriod.to_timestamp(freq ="M")

# print
print(timeStamp)

Output:

time-stamp-monthly

As you can see, hours, minutes and seconds have been assigned to zeros.

 

Example-3: Timestamp to DateTime

DateTime in Python is the combination between dates and times. Let us first create a timestamp and then we will convert it into Python Datetime.

Advertisement
# importing datetime module
from datetime import datetime

# creating a random number to have time stamp
timeStamp = 1446733073

# converting timestamp to datetime
dt= datetime.fromtimestamp(timestamp)

# printing
print(dt)
print(type(dt))

Output:

timestamp-to-date

As you can see, we have now created a Python DateTime from a time stamp.

 

Converting the date column into a Python timestamp

Now, we will jump into real-life examples and convert the column from a data frame into a Python timestamp. We will use a time series dataset about Electric Production from Kaggle which you can download from here. Let us first import the dataset and then we will print a few columns.

# importing dataset
data = pd.read_csv("Electric_Production.csv")

# printing 
print(data.head())

Output:

Data-set

As you can see, the dataset has two columns. we will only deal with the DATE column and will convert it into python to_timestamp.

# creating new row and converting the date into time stamp
data['new'] = data['DATE'].to_timestamp

We have created a new row and added the timestamp there. Let us print the dataset to confirm it.

Advertisement
# printing
print(data.head())

Output:

time-stamp-dataset

As you can see, we were able to create a new column that contains the time stamp.

 

Summary

pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It contains many useful methods and one of them is to_timestamp. In this short article, we discussed how we can use to_timstamp method by solving various examples. Moreover, we also learned how we can convert a timestamp into Python DateTime.

 

Further Reading

Python pandas convert datetime to timestamp effectively through dt accessor
pandas.DataFrame.to_timestamp

 

Didn't find what you were looking for? Perform a quick search across GoLinuxCloud

If my articles on GoLinuxCloud has helped you, kindly consider buying me a coffee as a token of appreciation.

Buy GoLinuxCloud a Coffee

For any other feedbacks or questions you can either use the comments section or contact me form.

Thank You for your support!!

Leave a Comment

X