Author: web-admin

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Chapter 2: Pandas Getting Started

Pandas – Getting Started (realistic first day) Step 0 – What should you expect today? Today we want to reach this point: Know how to install & import pandas Understand what a DataFrame and...

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Chapter 3: Pandas Series

What is a Pandas Series, really? A Series is: A one-dimensional labeled array It has data values + an index (labels for each value) You can think of it as one column from a...

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Chapter 4: Pandas DataFrames

What is a Pandas DataFrame, really? (the most honest explanation) A DataFrame is: A 2-dimensional, labeled data structure It is many Series put side by side (each column is a Series) It has both...

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Chapter 5: Pandas Read CSV

Pandas – Reading CSV Files (the most common first real task) Almost every data project starts with: Python

But in real life, very few CSVs are clean and simple. That’s why we need...

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Chapter 6: Pandas Read JSON

What is JSON and why do we read it with pandas? JSON (JavaScript Object Notation) is one of the most common data formats today — especially when: Data comes from APIs (REST APIs, web...

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Chapter 7: Pandas Analyzing Data

Analyzing DataFrames in pandas (We are sitting together — I’m explaining slowly, showing realistic examples, running small pieces of code, and telling you why we do things this way and what analysts actually do...

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Chapter 8: Cleaning Data

Cleaning Data in pandas (Imagine we are sitting together — I’m showing you real messy data, explaining what usually goes wrong, why we clean in certain order, and how people actually clean datasets in...

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Chapter 9: Cleaning Empty Cells

How to clean / handle empty cells (missing values) in pandas. Imagine we are sitting together and I’m showing you real data on my screen. We will go slowly, understand why things are missing,...

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Chapter 10: Cleaning Wrong Format

cleaning data that is in the wrong format in pandas. Imagine we are sitting together with a laptop. I’m showing you a real messy dataset, explaining why these problems appear, how to recognize them...

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Chapter 11: Cleaning Wrong Data

Fixing Wrong Data” in pandas Imagine we are sitting together. I’m showing you a real dataset that came from a messy source (Excel sheets filled by different people, API responses, manual entries, etc.). We...