![]() ![]() We can also create sentences by using our own defined word library which contains words of our choice and the faker will generate fake sentences using those words. We can also create our own sentences using the sentence function and text function. ![]() exp = Faker() for i in range(5): print(exp.name()) Let’s generate some data in the Japanese and Hindi language. We just need to mention the language we want. We can generate information according to different regions and localities in different languages. print('Name: ', exp.name()) print('Address: ',exp.address()) print('DOB: ',exp.date_of_birth()) Now we will use this variable to generate different attributes. Now we will explore different functions that are there in the Faker library, for this, we need to initiate the Faker function using a variable. ![]() from faker import Faker import pandas as pd b. We will explore different functions of faker so we will import faker also we will perform some operations on the dataset for which we need to import pandas. In order to explore faker we need to install it using pip install faker. The datasets generated can also be used to tune the machine learning model, validate the model, and to test the model. Faker data can also be used for learning purposes like performing different operations on different types of data types. Depending upon your need you can generate data that best fits your demand. It supports all major locations and languages which is beneficial for generating data based on locality.įaker data can be used to tune machine learning models, for stress testing a model, etc. Faker is an open-source python library that allows you to create your own dataset i.e you can generate random data with random attributes like name, age, location, etc. ![]()
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