Python Pandas: Data Manipulation and Analysis

Learn with real world examples of Python Pandas to analyse large data files. Create visual representations of your data.

What you'll learn

How-to install Python and Anaconda - the worlds largest Data Science platform.
How-to create a virtual environment using Conda.
How-to setup the Atom Text Editor.
How to clone a GitHub Repository in Atom Text Editor.
How-to create a new branch in Atom Text Editor.
Use Python Pandas to read in large data-sets such as stock price information, customer information, purchase information and more.
Use Pandas DataFrames to work with tabular data.
Inspect datasets to gain quick valuable insights.
Use conditional filtering to select relevant information from datasets.
Using NumPy and Pandas together.
Create Pandas DataFrames from scratch.
Create DataFrames from Python dictionaries.
Using Broadcasting with DataFrames.
Correctly labeling data and columns.
Data cleansing techniques.
Using Python Pandas to create graphical plots such as bar, line, area, scatter etc.
How-to analysis datasets using statistical methods such as min, mas, mean, std.
Create filters in your code to extract targeted data from large datasets.
How-to manage time data in Python with Pandas.
Correctly index time data and create DateTime indexes.
Partial String Indexing and slicing.
Resampling Pandas Time Data.
Method Chaining.
Separating and Resampling.


Requirements

You will need a desktop computer or laptop with Internet connection.
Some prior coding experience with Python would be beneficial or maybe a Python introduction course.
This course will walk you through installing all the necessary software and tools. Included is, how-to setup Python and Anaconda, how-to setup Atom Text Editor, how-to setup a virtual environment, how-to use GitHub and clone a repository.

Description

Python Pandas are one of the most used libraries in Python when it comes to data analysis and manipulation. Whether in finance, scientific fields, or data science, a familiarity with Pandas is a must have. This course teaches you how to work with real-world data sets for analyzing data in Python using Pandas. Not only will you learn how to manipulate and analyse data you will also learn powerful and easy to use visualization techniques for representing your data.

This course kicks off by showing you how to get up and running using GitHub, an essential skill in your coding career. Ideally, to get the best from this course you should have some Python programming experience.

Every piece of code and dataset used in this course is available to download for free from GitHub.

Without doubt this course will teach you the necessary skills to apply basic data science techniques which are use the world over by experienced data scientists and those who spend their working day in spreadsheets.

Who is the target audience?

Software Developers who have basic Python experience/knowledge and are looking to up-skill into the high demand area of Data Science.
Software Developers who work with spreadsheets and data-sets and would like to learn how to produce valuable insights from them.
Data Analyts operating in business who are looking to transition into Data Science by learning how to produce informative data-sets and graphs.