“Read & Process Files from Google Cloud Storage using Python | GCP Tutorial #6

In this video, you will learn how to read and process files directly from Google Cloud Storage using Python. Data Set Download https://drive.google.com/file/d/1DD6vmoA5-7Ucl5WcHmhX8jzVxnFc-ATr/view?usp=sharing We move beyond uploading files and start working with real cloud data, just like data analysts and data engineers do in real-world projects. This is one of the most important skills if you want to work in data analytics, data engineering, or cloud-based roles. What you will learn in this video: - How to connect Python with Google Cloud Storage - How to authenticate using a service account JSON key - How to access a bucket and read files from GCS - How to convert cloud data into a pandas DataFrame - How to perform basic data analysis Commands used: pip install google-cloud-storage pandas Python Code Covered: - Connecting to GCS using service account - Reading CSV file from bucket - Converting data into pandas DataFrame - Viewing and analyzing data Previous Videos: GCP Introduction GCS Setup and Upload using CLI Why this matters: In real companies, data is stored in the cloud. Knowing how to read and analyze that data directly using Python is a critical skill for any data professional. Subscribe for the full GCP playlist and upcoming hands-on projects. 0:00 Introduction 1:27 Installing Google Cloud Storage & Pandas libraries 2:07 Creating a Service Account & JSON key 4:30 Writing the Python code (Importing libraries) 5:17 Creating the GCS client 5:55 Accessing the GCS bucket 6:42 Accessing the file 7:26 Downloading and reading the data 8:06 Converting data into a pandas DataFrame 8:42 Printing and analyzing data 9:00 Troubleshooting access/permissions (403 error) 11:27 Data analysis (describe and value_counts) 13:00 Final summary and wrap-up #GCP #GoogleCloud #Python #DataAnalytics #CloudStorage #DataEngineering #Pandas #LearnPython