Data Analysis with Python, Pandas and Numpy. Online .

Python for Data Analysis

Course summary

• Duration: One day
• Times: 11am – 5pm
• Location: Online or In Classroom
• Instructor-led: No training-bots in our classroom yet
• Joining Instructions: Full joining instructions will be sent ahead of the course.
• Certificate: PCWorkshops certificate is issued on completion
• Notes: Includes notes, exercises, code samples, some videos.
• Laptops: Bring your own device, download anaconda.com
• Installation assistance: Email us for assistance from our technical professional should you require help

Who should come?

• Anyone who need to manage or interact with lines and lines of data.
• Some basic experience working with data would be useful but is not required to follow the course.
• The course does not require any prior programming experience.
  
  Practical
• This course is hands-on and very practical. You will be given many examples and challenges to try out on your own

Key learning outcomes

At the end of this course, you will be able to:

• Easily summarise data trends from large data sets

About the course:

Python:

Python is one of the most popular programming languages and provides an excellent tool for business professionals, academics and researchers to analyse, manipulate and visualise data. It is simple, versatile, and, best of all, it’s for free!

This course:

Being a course covering data analytics techniques used in Python, the course is ideal for anyone who need to manage or interact with lines and lines of data.

This course is to make life easier, make the data easy, interesting, and very useful.We introduce Python as a data analytics tools, vs other tools. How is Python is different and better or worse that rather than for instance Excel and SQL.

We focus on techniques that will save much time at work, that will return results easier and quicker, and that will give additional, powerful results.

ChatGPT. We present the different use cases sets out how data analysis might change as a result of recent developments in Artificial Intelligence such as ChatGPT.

This course starts at the beginning but dives right into the technical side to give you an in-depth, thorough practical knowledge of the software as a data analytics tool.

Course Outline:

Session 1: Brief Revision of Python Basics.

Session 2: Data Structures, Data and Files

• Lists, Tuples, Sets.
• Dictionaries, Json Files.
• CSV files. Reading and writing Csv Files. The CSV module.
• Txt Files. Bytes and Unicode with files.

Session 3: Numpy:

• The Python Numpy Module: Working with arrays, array manipulation, string, math, arithmetic and statistical functions.

Session 4: Pandas:

• Pandas Series, Date/ Time Functionality. Time series.
• Pandas Data frames, Indexing, Sorting, Filter, Slicing, Iteration, Functions,
• Aggregation.

Session 5: Data Cleaning and preparation

• Random Sampling.
• Finding and filtering Missing data,
• Remove Duplicates,
• String objects, Regex.
• Replacing values.
• Transforming data using function and mapping,
• Renaming Axis Indexes,
• Discretization and Binning.

Session 6: Data Wrangling

• Hierarchical Indexing, Reorder, Sorting,
• Statistics,
• Data frame Joins, Merging, Concatenation, Overlap.
• Reshaping and pivoting.

Session 7: Plotting and Visualization

• Introducing to plotting data with MatPlotLib

Your trainer:

Sarah Barnard has been a software and database developer for 20+ years.

The founded, grew and sold 3 software training companies during this time.

She has published 5000+ educational programming scripts available under white label, 49 training manuals available on Shopify, manages a Udemy chanel and a Programming Languages Meetup group.