Learn Python for data analysis and visualization by building real world Python programs that analyze large datasets.

All Levels, — Video: 4.5 hours Other: 39 mins, 70 lectures

Average rating 4.5/5 (4.5)

Course requirements:

A working computer (Windows, Mac, or Linux)
 No prior knowledge of Python is required

Course description:

This Python course will get you up and running with using Python for data analysis and visualization. You will learn how to handle, analyze and visualize data in Python by actually completing two big data analysis projects, one demonstrated through videos and another laid out through six exercises.

The course assumes you have no prior knowledge of Python, so you also get to learn the basics of Python in the first two sections of the course. However, if you already know Python, the first two sections can serve as a refresher before you jump into the data analysis and visualization part.

In the course you will learn to use Python third-party data analysis libraries such as Pandas, Matplotlib, Seaborn, just to mention a few and tools to boost your productivity such as Spyder and Jupyter.

As you progress through the course, you will be guided step by step on building a program that uses real world data containing hundreds of files and millions of records. You will learn to write Python code that downloads, extracts, cleans, manipulates, aggregates and visualizes these datasets using Python. Apart from following the video screencasts, you will also be required to write your own Python scripts from scratch for completing a data analysis project on income data.

Full details
 Build 10 advanced Python scripts which together make up a data analysis and visualization program.
 Solve six exercises related to processing, analyzing and visualizing US income data with Python.
 Learn the fundamental blocks of the Python programming language such as variables, datatypes, loops, conditionals, functions and more.
 Use Python to batch download files from FTP sites, extract, rename and store remote files locally.
 Import data into Python for analysis and visualization from various sources such as CSV and delimited TXT files.
 Keep the data organized inside Python in easily manageable pandas dataframes.
 Merge large datasets taken from various data file formats.
 Create pivot tables in Python out of large datasets.
 Perform various operations among data columns and rows.
 Query data from Python pandas dataframes.
 Export data from Python into various formats such as TXT, CSV, Excel, HTML and more.
 Use Python to perform various visualizations such as time series, plots, heatmaps, and more.
 Create KML Google Earth files out of CSV files.

Full details
 Those who come from any technology field that deals with any kind of data.
 Those who want to leverage the power of the Python programming language for handling data.
 Those who need to learn Python basics and want to quickly advance their skills by learning how to perform data cleaning, analysis and visualization with Python — all in one single course.
 Those who want to switch from programming languages such as Java, C, R, Matlab, etc. to Python.

Full details


“Contents are good but the audio is hard to hear.” (Das Narayanadas)
“Too early yet, but looking forward to learning much more! Ardit is excellent at getting back to you and questions you have in email…much better then most professors/instructors I have had. Thanks, Ardit!” (Troy Lundquist)
“This course is flawless.
 The teaching method of introducing a new concept, gradually building on it and everything fall in place in the end is simple yet powerful. It made it so easy for me to grasp and practise the whole course material.
 Thanks for upgrading my python skills in such a simple yet remarkable manner. See you in the next course” (James E)

About Instructor:

Ardit Sulce

Ardit received his master’s degree in Geospatial Technologies from the Institute of Geoinformatics at University of Muenster, Germany. He also holds a Bachelor’s degree in Geodetic Engineering.
 Ardit offers his expertise in Python development on Upwork where he has worked with companies such as the Swiss in-Terra, Center for Conservation Geography, and Rapid Intelligence. He is the founder of PythonHow where he authors written tutorials about the Python programming language.

Instructor Other Courses:

The Python Mega Course: Build 10 Python Applications
Python for Beginners with Examples
Introduction to GIS
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