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
- 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 enjoyed the course, very informative and a good balance between instruction and practical work.
Megan - Transport - March 2025
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
Public Scheduled Events
Classroom & Live Virtual Instructor-Led Training
Duration: 4 days
Price: £1,995.00 exc. VAT
Live Virtual Classroom
All the convenience and benefits of the classroom experience without the hassle and costs of travel and accommodation.
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