avatarDr. Monica

Summary

This context provides a tutorial on extracting YouTube data to a CSV format using the YouTube Data API v3, detailing the steps to activate the API key, set up the extraction parameters, and save the data in Python.

Abstract

The provided text is a comprehensive guide on utilizing the YouTube Data API v3 to scrape video data from YouTube and export it to a CSV file. It begins by emphasizing the significance of YouTube as a data source due to its status as the largest video sharing platform. The tutorial outlines a three-step process: first, it instructs on how to obtain an API key from the Google Developer Console by creating a new project and enabling the YouTube Data API v3. Next, it guides the reader through the Python code required to install and import necessary libraries, set API parameters, and extract data such as likes, dislikes, and views. Finally, it explains how to convert the extracted data into a pandas DataFrame and save it as a CSV file for further analysis. The guide also includes images and links to a GitHub repository with the complete code example.

Opinions

  • The author suggests that data extraction from YouTube can be highly beneficial for various purposes, such as tracking channel popularity or analyzing video engagement metrics.
  • The guide implies that the process of obtaining an API key and setting up the YouTube Data API v3 is straightforward and accessible to developers with varying levels of expertise.
  • The inclusion of a GitHub repository link suggests that the author values practical examples and resources that can aid readers in applying the tutorial's instructions.
  • The guide promotes the use of Python for data extraction tasks, highlighting its efficiency and the availability of libraries that facilitate interaction with the YouTube API.
  • By mentioning the use of pandas to handle data, the author indicates a preference for this library for data manipulation and analysis in Python.

Extract YouTube data to CSV using YouTube API

Web scraping is extracting data from websites. It is a form of copying, in which specific data is gathered and copied from the web into a central local database or spreadsheet for later analysis or retrieval.

Since YouTube is the biggest video sharing website in the internet, extracting data from it can be very helpful, you can find the most popular channels, keeping track on the popularity of channels, recording likes, dislikes and views on videos and much more.

In this tutorial, you will learn how to extract data from YouTube videos using YouTube Data API v3 by google. Github.

Step 1: Activate the API key from Google Developer Console

The first thing you need to do is to extract the API key from Google Developer Console. In order to do so, you will need to activate your account for GDC with the following steps.

Create a New Project:

  • Login to Google with your account credentials.
  • Visit the Google developer dashboard, create a new project from the top of the page as in below image, click “Select a project”:
Google developer dashboard

Now Click on “New Project” as shown below and proceed.

Select a project window

After this, you will be automatically redirected to the Google APIs dashboard.

  • The next step is to activation of YouTube API, so for that navigate to the API & Services from the side panel.
  • Then click on Enable API & Services from the top of the page.
  • Search for Youtube and then select YouTube Data API v3.
Select YouTube Data API v3 page

After that Enable the API by clicking on the Enable as shown in the below figure.

Now again click on the API & Services and select credentials. Navigate to the Create Credentials from the top of the page in that select API key.

Credentials Page

  • Once clicked after some time a pop up will come with the message API key created from there you will get our API key as alphanumeric. Copy that and keep it safe for further use.
API key created

API key created. Keep the API handy, as you need to paste it the python code.

Step 2 — Extraction of Data from YouTube Channels

Install and import relevant libraries in Python

from apiclient.discovery import build #pip install google-api-python-client
from apiclient.errors import HttpError #pip install google-api-python-client
from oauth2client.tools import argparser #pip install oauth2client
import pandas as pd #pip install pandas

Step 3 — Set YouTube Search parameters

youTubeApiKey="AIzaSyAT7mKPxpkp66glGvzxnpryy0rOFT3r7XM" #Input your youTubeApiKey
youtube=build('youtube','v3',developerKey=youTubeApiKey)
channelId='UCt4t-jeY85JegMlZ-E5UWtA' #Input the channelID of Youtube that you want to extract data

The below snippet will convert each differently stored variable in the data frame.

snippetdata=youtube.channels().list(part='snippet',id=channelId).execute()
snippetdata

And finally using the function to save the data frame to CSV file.

Once you have the data in CSV files, you can easily perform the different analyses as per project requirements.

Enjoy Scrapping!

YouTube
Data Science
Machine Learning
Python
Artificial Intelligence
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