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Introduction to pandas (Summary)

Rodrigo Girão Serrão
Introduction to pandas Rodrigo Girão Serrão 02:25
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You have learned the fundamentals of collecting, organizing, and analyzing data with Python’s pandas library.

You now know how to:

  • Gather data from the web, such as scraping Wikipedia tables and loading them into pandas.
  • Read and write data in multiple formats including CSV, JSON, HTML, and Parquet.
  • Analyze, sort, and calculate statistics such as averages using built-in pandas methods.
  • Apply pandas to interpret and manipulate real-world datasets inside Jupyter notebooks.

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00:00 Congratulations on making it this far. This was a fairly short video course. It was definitely not enough for you to learn everything about pandas because pandas is a very mature tool that has been around for a while.

00:14 It has lots of different functionalities. It has lots of features that may or may not be useful to you and to your work. But even then, you did quite a lot.

00:25 This was a video course that was jam-packed with information because in this course you collected data from the internet using the urllib module, and you then used pandas to take the HTML you got from Wikipedia, and turned it into a DataFrame.

00:41 You also learned what is a DataFrame. You performed I/O operations with your data or on your DataFrame. You saved your data locally, and you read it back as a CSV file, but Pandas supports many other file formats, as you saw.

00:57 And you also analyzed your DataFrame with some pandas methods. You learned how to pick specific columns, how to drop rows that were not relevant for the particular analysis you were doing, and you then computed means and medians, and most importantly, you realized that you always have to check whether you have the right data and whether you’re computing the right thing.

01:20 This gave you an idea of what a data project might look like because you went through all of the steps from collecting data to arguably cleaning data because you had to get rid of some rows that were not relevant to computing the things you care about.

01:37 You did all of that, but at a small scale. If you want to keep learning, my best recommendation is that you check the pandas for Data Science learning path at Real Python.

01:48 Because it’s a learning path, it outlines exactly the steps you need to take in order to learn more about pandas the tool and data science the field. I’ve also included links for tutorials that you can read if you’re interested in web scraping specifically, which is the act of gathering data from web pages on the internet, and also a tutorial on Jupyter Notebooks, the interface you were using to develop your analysis.

02:16 I hope you learned a lot by going through this video course. I hope you have fun. My name is Rodrigo, and I hope to see you in the next one.

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