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...
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...
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...
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...
Pandas – Reading CSV Files (the most common first real task) Almost every data project starts with: Python
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import pandas as pd df = pd.read_csv("some_file.csv") |
But in real life, very few CSVs are clean and simple. That’s why we need...
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...
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...
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...
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,...
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...
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...
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