?? Day 25 of 365: Pandas DataFrames ???? ??
Ajinkya Deokate
Data Scientist | Researcher | Author | Public Speaking Expert @PlanetSpark | Freelancer
Hey, data explorers!
Welcome to Day 25 of our #365DaysOfDataScience journey! ??
Today we’re diving into Pandas DataFrames—the backbone of data manipulation in Python. If you enjoyed working with Series, you’re going to love DataFrames. They’re like spreadsheets but with superpowers!
?? What We’ll Be Doing Today:
Introduction to DataFrames??
??- Learn how to create DataFrames from CSVs, dictionaries, and NumPy arrays.
Exploring DataFrames??
??- Use handy methods like .head() to preview data, .info() to get an overview, and .describe() to see basic statistics.
?? Learning Resources:
Read:??
??- Get a deeper understanding of DataFrames by reading Chapter 6 of "Python for Data Analysis."
Watch:??
领英推荐
??- Check out a Pandas DataFrame tutorial on YouTube to see them in action!
?? Today’s Task:
- Load a dataset (grab one from Kaggle or use your own) into a Pandas DataFrame.
- Explore the data by using:
??- .head() to see the first few rows.
??- .info() to check the structure of the DataFrame.
??- .describe() to get summary statistics for numerical columns.
Tip: Pandas make it easy to work with real-world data! Once you’ve loaded and explored your dataset, think about what insights you can extract with just these basic tools.
Let’s explore some datasets together and share our findings.
Happy DataFraming! ??
See You Soon!
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