Data Wrangling with Python

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Data is the new oil, but it comes crude. To do anything meaningful - modeling, visualization, machine learning, for predictive analysis – you first need to wrestle and wrangle with data. Data Wrangling with Python teaches you the essentials that will get you up and running with data wrangling in no time.

For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain.

The course starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The course will further help you grasp concepts through real-world examples and datasets.

Data Wrangling with Python takes a practical approach to equip beginners with the most essential data analysis tools in the shortest possible time. It contains multiple activities that use real-life business scenarios for you to practice and apply your new skills in a highly relevant context.

By the end of this course, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently.

Lesson 1: Introduction to Data Structure using Python

Python for Data Wrangling
Lists, Sets, Strings, Tuples, and Dictionaries

Lesson 2: Advanced Operations on Built-In Data Structure

Advanced Data Structures
Basic File Operations in Python

Lesson 3: Introduction to NumPy, Pandas, and Matplotlib

NumPy Arrays
Pandas DataFrames
Statistics and Visualization with NumPy and Pandas
Using NumPy and Pandas to Calculate Basic Descriptive Statistics on the DataFrame

Lesson 4: Deep Dive into Data Wrangling with Python