Introduction to Python and Data Analysis

Course Code: PYPDAI

Duration: 4 days

 
 
 
 

Introduction to Python and Data Analysis Course Overview

This course is an introduction to Python and its main data analysis libraries, Pandas and Matplotlib for delegates with some understanding of programming concepts. It is a two-part course, the first is an introduction to Python programming, the second introduces Python's data analysis tools. For the programming environment we use JupyterLab on the Anaconda platform. Anaconda is one of the most, if not the most, popular Data Science platforms.

Approach:

We believe in learning by doing and take a hands-on approach to training. Delegates are provided with all required resources, including data, and are expected to code along with the instructor. The objective is for delegates to reproduce the analysis in our manuals as well as gain a conceptual understanding of the methods.

Exercises and examples are used throughout the course to give practical hands-on experience with the techniques covered.

Course Objectives

This course aims to develop delegates skills in Python and its main data analysis libraries. On completion of the course they will have gained enough proficiency to allow them to apply these tools in their day to day data analysis activities.

Who will the Course Benefit?

This course is designed for anyone who wants to acquire basic proficiency in Python and its data analysis tools for use in their own work. It is for numerate people who are familiar with programming constructs but are not necessarily programmers who want to be able to do some data manipulation and visualization using Python.

Skills Gained

The delegate will learn and acquire skills as follows:

Python

  • Variables and data type
  • Inbuilt containers
  • If statements and loops
  • Functions

Pandas and Matplotlib

  • Read csv and excel format data into Pandas DataFrame objects
  • Fill-in missing values, group, manipulate and summarise tabular data
  • Plot bar chart, histograms and line graphs using Matplotlib
  • Use JupyterLab

Introduction to Python and Data Analysis Training Course

Course Introduction

  • Administration and Course Materials
  • Course Structure and Agenda
  • Delegate and Trainer Introductions

Session 1: INTRODUCTION

  • Python as an interpreted language
  • Script mode by example
  • Interactive mode
  • Statements
  • Comments
  • Whitespace and Indentation

Session 2: PYTHON: VARIABLES & SCALAR TYPES

  • Numerical types
  • Text
  • Boolean
  • Variables as references
  • The type() function

Session 3: OPERATORS & EXPRESSIONS

  • Arithmetic Operators
  • Assignment Operators
  • Comparison Operators
  • Logical Operators
  • Membership Operators

Session 4: CONTAINERS

  • Lists
  • Tuples
  • Sets
  • Dictionary

Introduction to Python and Data Analysis Training Course

Session 5: CONDITIONS & LOOPS

  • Basic if statement
  • Else clause
  • For loop
  • While loop
  • The range function
  • Iterating over a list
  • Break
  • Continue

Session 6: FUNCTIONS

  • inbuilt functions (len(), sum(), min(), max(), sorted())
  • defining functions
  • positional arguments
  • names arguments
  • default value arguments

Session 7: OBJECTS

  • What is a Class?
  • Data Attributes and Methods
  • A simple example
  • Some methods of inbuilt containers

Introduction to Python and Data Analysis Training Course

Session 8: INTRODUCTION TO DATAFRAMES

  • What is a DataFrame?
  • DataFrame attributes
  • Loading and writing DataFrames
  • Exploratory functions
  • Subsetting
  • Conditional subsetting
  • Adding and dropping columns
  • Inbuilt aggregating functions
  • Missing values

Introduction to Python and Data Analysis Training Course

Session 9: GROUPBY AND AGGREGATION: SPLIT-APPLY-COMBINE

  • Groupby one column and aggregate using single inbuilt function
  • Groupby two columns and aggregate using single inbuilt function
  • Groupby one column and aggregate using separate function for each column

Session 10: PLOTTING WITH MATPLOTLIB

  • Bar chart
  • Histogram
  • Line plot
Notes:
  • Course technical content is subject to change without notice.
  • Course content is structured as sessions, this does not strictly map to course timings. Concepts, content and practicals often span sessions.

Requirements

Delegates attending this course are expected to have the below Programming and Numeracy experience.

Programming:

  • Experience coding small programs that use variables, arrays or lists, conditional statements, loops and functions in some language. Skills and knowledge that can be acquired by attending our Introduction to Programming - Python course.

Numeracy:

  • Able to calculate and interpret averages, standard deviations and similar basic statistics.
  • Ability to read and understand charts and graphs.
  • Mathematics: GCSE or equivalent.

Pre-Requisite Courses

Further Learning

Course Reviews

Thoroughly positive experience throughout, including a smooth booking process. Fantastic and enthusiastic instruction from Stuart and a very comprehensive and well planned curriculum with strong supporting materials.

Robert - Higher Officer - Government - November 2024

Excellent course that has been very well delivered by Stuart. Stuart has great knowledge and delivered the course at an excellent pace.

Jordan - Power System ModellingEngineer - September 2024

Stuart was a brilliant trainer and really willing to support those at all levels. Thank you.

Kelly - Government - May 2024

A fully engaging course and at a suitable pace with a perfect mix of learning types (i.e. tutor and "hands on" practical). Thank you so much ... probably the best training course I've attended! It has given more an excellent grounded for further development.

Lee - Analyst - NHS - April 2024

The course was executed in the correct way to garner understanding of Python and has provided me with a substantial foundation with which I can use to further progress my understanding and use of Python.

Laith - Transport - March 2024

Excellent course giving a very good introduction to Python and Data Analysis. Initially did the online course supplied by the ONS, which gave a good intro, but this took those initial concepts and ran with them, giving excellent grounding and explaining the logic behind each process. Musie ran the course at exactly the right pace and reacted to questions and areas of interest well, happy to mould the course to our requirements and questions on-the-spot. Very much looking forward to taking this learning and seeing what I can do with it!

Simon - Data Analyst/Manager - Government

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Duration: 4 days

Price: £1,995.00 exc. VAT 


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