Python Data Essentials: Python Introduction
Get started with Python for data science — the basics, packages and core data structures.
This course introduces the fundamentals of Python applied to data science. It targets beginners who want to understand the key concepts needed to start working with data in Python.
Prerequisites: Basic understanding of what programming is.
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What's inside
7 sections- 1 Table of Contents
- 2 Module 1 — Course Overview
- 3 Module 2 — Python and Data Science
- 4 Module 3 — Python Basics
- 5 Module 4 — Packages and Data Structures
- 6 Reference Diagrams
- 7 Reference Tables
More Python Foundations & Data Analysis courses
View all 26Python Data Essentials: Programming Fundamentals
Conditionals, loops, functions and object-oriented basics to prepare for pandas and NumPy.
Up and Running with Pandas
Pandas fundamentals — representing, exploring and evaluating data programmatically.
Cleaning Data with Pandas
Practical data cleaning, correlation analysis and data preparation with pandas.
Normalize Data for Analysis with Pandas
Why and how to normalize data, from simple techniques to Gaussian normalization with pandas and scikit-learn.
Pandas Functions
Advanced pandas — merge, join, concatenate, binning, pivot, melt and crosstab.
Plotting Data with Pandas
The Python visualization ecosystem and creating charts directly from pandas.
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