Description:

Typically it takes 60 to 80% of the time to collect required data, cleanse it and analyse in any data science project. It is very essential for one to be familiar with various tools/libraries available in python for doing data analysis and understanding the data. Data Visualisation helps to get hidden insights quickly . Data Visualisation is key for summarising and communicating your insights.

This hands on workshop's objective is to provide overview of the libraries and how to use them for various activities performed during the data analysis and visualisation

Following will be covered as part of this session

• How does data analysis fit in the life cycle of data science project
• Dealing with numpy arrays - quick overview Reading data using various formats and sources
• Data scrubbing/cleansing - dealing with missing values, data transformation
• Introduction to data visualisation and quick overview of libraries available Using visualisation to understand and communicate results
• Analysing one of the open source data set
• By the end of the session
  • Audience will have very good understanding of how to apply numpy, pandas to analyse, visualise understand and communicate the results
  • Scrub/Cleanse the data and prepare data set required for machine learning

Prerequisites:

Hands on exposure with basic python programming language

Software requirements:

Please install Anaconda ( https://www.anaconda.com/download/) with Python 3.6

Download the git hub repo - https://github.com/sdonapar/data_analysis_pythonwe would be using jupyter notebooks for this workshop

Content URLs:

https://github.com/sdonapar/data_analysis_python

Speaker Info:

I am a mechanical engineering graduate with 25+ years of experience in manufacturing and financial services domains, I have started my career as design engineer in hydraulic turbine manufacturing company. After spending 5 years, I have stated my IT journey at Aspect Development/i2 Technology. I have worked primarily on data scrubbing, modelling, analysis and data migration projects for supply chain management. I then joined technology services side of Fidelity, financial services company. I have been using python for last 6+ years for automation, data analysis, web development, etc. I am very excited about the endless opportunities that arise in day today work and application of python for solving problems, automating day to day activities. I am very passionate about teaching python to engineering students thru pythonexpress program. I conduct regular training sessions for data analys ( numpy, pandas and matplotlib) in my company.

I have done this workshop at couple of times at Bangalore Python meetup (BangPyPers) and also I have done this workshop at Pycon 2017 Delhi

Speaker Links:

github link - https://github.com/sdonapar

linkedin profile - https://www.linkedin.com/in/sasidonaparthi

twitter handle - @sdonapar