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Learn Python for Data Analysis and Visualization

Real world examples of Python Pandas to analyse large data files. Create visual representations of your data.

Instructed by Tony Staunton

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  • How-to install Python and Anaconda - the worlds largest Data Science platform.
  • How-to create a virtual environment using Conda.
  • How-to setup the free 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.

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.

  • You will need a desktop computer or laptop with Internet connection.
  • Some prior coding experience with Python would be beneficial or maybe have done 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.
  • 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 Analysts operating in business who are looking to transition into Data Science by learning how to produce informative data-sets and graphs.
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Section 1 : Course Introduction

  • Lecture 1 :
  • Lecture 2 :
  • How to access the source code for this course

Section 2 : Setting up Python, Anaconda, Atom and GitHub

  • Lecture 1 :
  • Setting Python up with Anaconda
  • Lecture 2 :
  • Setting up Atom Text Editor
  • Lecture 3 :
  • Creating Virtual Environments
  • Lecture 4 :
  • How to Clone a GitHub Repository
  • Lecture 5 :
  • How to use the Atom Text Editor to push code to GitHub

Section 3 : Introduction to Python Pandas

  • Lecture 1 :
  • Introduction to Pandas
  • Pandas is a library built on top of Numpy. For those of you not familiar with Numpy it is a scientific computing package for Python. For more information on Numpy visit http://www.numpy.org/. - Using pandas you can read in datasets containing information such as: - Stock Price Information - Customer information - Purchase/Sales Information In the examples to come we will be reading datasets that are in the CSV format. The main use of Pandas is to read in data and then manipulate the rows and columns of that data. We can also use Pandas to quickly grab statistical information about our data.
  • Lecture 2 :
  • Introduction to DataFrames
  • A DataFrame is the main way that Pandas works with tabular data files. Tabular data files are files that arrange their data in rows and columns.
  • Lecture 3 :
  • Inspecting Data
  • Lecture 4 :
  • Conditional Filtering
  • Lecture 5 :
  • Using NumPy and Pandas Together
  • Lecture 6 :
  • Creating DataFrames from NumPy
  • Lecture 7 :
  • Creating DataFrames from Dictionaries
  • Lecture 8 :
  • Using Broadcasting in Pandas
  • Lecture 9 :
  • Labeling data in a DataFrame
  • Lecture 10 :
  • Building DataFrames with Broadcasting
  • Lecture 11 :
  • Cleansing, Importing and Exporting Data
  • Lecture 12 :
  • Creating Plots with Pandas

Section 4 : Visual Data Analysis

  • Lecture 1 :
  • Creating Graphs with Pandas Plot Lines
  • Lecture 2 :
  • Creating Graphs with Pandas Scatter Plots
  • Lecture 3 :
  • Creating Graphs with Pandas Bar Plots
  • Lecture 4 :
  • Statistical Exploratory Data Analysis
  • Lecture 5 :
  • Filtering Data

Section 5 : Managing Dates and Times with Python Pandas

  • Lecture 1 :
  • Introduction to Pandas DateTime
  • Lecture 2 :
  • Indexing Pandas Time Series
  • Lecture 3 :
  • Creating and using a DateTimeIndex
  • Lecture 4 :
  • Resampling Pandas Time Data
  • Lecture 5 :
  • Method Chaining
  • Lecture 6 :
  • Separating and Resampling
  • Lecture 7 :
  • Additional Filtering Methods
  • Lecture 8 :
  • Visualizing Pandas Time Data
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Tony Staunton,

Hi! I'm Tony. I love to read, write and teach and you could definitely call me a bit of geek. I love all things to do with programming, productivity, books, and the internet. Previously I have run my own software business and won several awards from, most innovative startup to best product. After finding out the hard way just how stressful growing a startup into a business can be I have researched all things to do with productivity and I love helping others become more productive and avoid the mistakes I have made. I'm passionate about teaching and I love to hear back from my students with any questions or ideas on how to improve my courses or create new ones. My courses teach you how to programme and become more productive and you will not believe the freedom that these skills can bring. Sign up and find out for yourself why so many people are taking and recommending my courses. I genuinely believe that I have something to offer you and if you don't agree, I'll happily refund your money.  Sign up to my courses and join me in this amazing adventure today.
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