Python Pandas Tutorial 03: How to load data from Google Sheets, Excel, .CSV, and PDFs (Google Colab
How to load data from Google Sheets, Excel, .CSV, and PDFs This video will explain how to ingest data into a Google Colab notebook, so that you can transform data using Python's Pandas data analytics library. Please note: these strategies will not work with other IDEs (such as PyCharm, VS Code, and/or Jupyter Notebook) because of the oAuth credentialing protocols. If you would like to use an external IDE to collect data from a Google Sheet, then check out this video: https://youtu.be/Jivt894fer4 Python is a programming language. You can implement Python in various environments including script files, notebooks, and terminal or command line. My preference is to code in a script file; my editor of choice is PyCharm. This lesson will take place in a notebook. I wanted to craft a tutorial that minimizes the barrier to entry so that you can overcome the friction that comes from learning something new. So I decided to use Google Colab, which is Google’s version of a Jupyter notebook. You will need a Google Account in order to access Colab but it’s completely free and easy to install. Pandas is a data analytics library. It’s called Pandas bc it stands for Panel Data, which means that it formats values in a row and column format similar to a spreadsheet. However, it is much more powerful than a spreadsheet and it will fundamentally change the way you approach data work.
How to load data from Google Sheets, Excel, .CSV, and PDFs This video will explain how to ingest data into a Google Colab notebook, so that you can transform data using Python's Pandas data analytics library. Please note: these strategies will not work with other IDEs (such as PyCharm, VS Code, and/or Jupyter Notebook) because of the oAuth credentialing protocols. If you would like to use an external IDE to collect data from a Google Sheet, then check out this video: https://youtu.be/Jivt894fer4 Python is a programming language. You can implement Python in various environments including script files, notebooks, and terminal or command line. My preference is to code in a script file; my editor of choice is PyCharm. This lesson will take place in a notebook. I wanted to craft a tutorial that minimizes the barrier to entry so that you can overcome the friction that comes from learning something new. So I decided to use Google Colab, which is Google’s version of a Jupyter notebook. You will need a Google Account in order to access Colab but it’s completely free and easy to install. Pandas is a data analytics library. It’s called Pandas bc it stands for Panel Data, which means that it formats values in a row and column format similar to a spreadsheet. However, it is much more powerful than a spreadsheet and it will fundamentally change the way you approach data work.