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NumPy/Pandas HOME
Welcome to the iwantcoding.com NumPy & Pandas Tutorial. NumPy + Pandas are the foundation of Python data work. Fast n-dimensional arrays, expressive tabular DataFrames, and an ecosystem that plugs into every plotting, ML, and stats library you’ll touch.
What this tutorial covers
| Chapter | You will learn |
|---|---|
| NumPy | ndarray, dtypes, creation, indexing / slicing, broadcasting, reshape, ufuncs, aggregations, np.random, linear algebra. |
| Pandas Basics | Series, DataFrame, read_csv / to_csv / Parquet, loc / iloc, filtering, assigning columns, missing data, dtypes, apply. |
| Pandas Power | groupby, merge / join / concat, pivot / melt, time series, rolling windows, categorical, .str, plotting, performance. |
| Examples | Cheatsheet, runnable snippets, quiz, exercises, bootcamp, certificate. |
Who this is for
- Data analysts & scientists.
- ML engineers wrangling features before training.
- Backend devs writing analytics jobs.
How to use this tutorial: read the chapter, run the example with Try it Yourself », do the exercise, then take the quiz at the bottom. Hit Mark complete when you're done — the sidebar will track your progress.
Example
Example
import numpy as np import pandas as pd print(np.__version__, pd.__version__)Try it Yourself »
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