Exploratory Data Analysis using Python

Workshop details

  • Python is a powerful programming language with many interesting data manipulation libraries, including scikit-learn, the one we use here for the Machine Learning workshops. However, before jumping to the ML workshops, it is indispensable that attendees become familiar with data analysis tools are the ones discussed here. Therefore, this workshop is directed to those wishing to get some hands-on introduction to exploratory data analysis in Python.

Learning objectives

  • How to import external datasets from the web directly to your programming code;

  • How to clear and standardize your dataset;

  • How to perform univariate, bivariate and multivariate analysis;

  • Plot different plot styles with different libraries.

Syllabus

  • Brief introduction to Python on Jupyter notebooks ;

  • Data Sourcing/Web Scraping;

  • Data cleaning:

Missing values treatment;

Standardization.

  • Univariate Analysis:

Listing Types of Variables;

Listing unique variables and plotting them;

Create multiple plots with numeric variables.

  • Bivariate analysis:

Bivariate numeric swarm plot (segmented);

Bivariate numeric box plot (segmented);

Bivariate scatter plot;

Bivariate hexagonal binning plot.

  • Multivariate analysis:

Multivariate scatter matrix;

Multivariated segmented pair-plot;

Correlation plot.

Format

  • Zoom live webinar: 1h live webinar with pre-recorded presentation split in two sessions of 30min each with a break of 5min between them. Attendees are welcome to join asynchronous live group discussion (Q&A) with the speaker on Discord during and after the scheduled session.

  • General discussion session: 1h Q&A recurrent pre-dated session booked for attendees of multiple slots of this workshop.

  • Recorded presentation: Attendees registering using a Google e-mail account, will have private access to the recorded webinars.

  • Certificate: all attendees checking-in and out of both 30min sessions will be entitled to receive a certificate of participation (PDF/PNG) that can be shared on your social media with credentials (QR-code) that can be verified on our website, with an option (extra fee) to register as a NFT asset with an unique address on the Ethereum blockchain.

Register using the form below