Data Workshop with Vladimir #5

Więcej informacji o tym wydarzeniu dostępne jest w języku angielskim: Maybe you already know that data science includes several areas like statistics, programming and domain knowledge. But there’s a next one which is very important in real life – visualization. Next data workshop #5 will be about visualization. What you will learn:

• Right visualization is power in data science
• Fundamental perceptual principles
• Visualization depend on type of variables
• Exploratory data analysis
• Geographic visualization
• Practical overview libraries
• Visualization on real examples

During a workshop I will mention about several laws, e.g. Weber–Fechner law or Stevens' power law. About the speakers

• Vladimir

I like traveling, also in IT world. I worked in different areas in IT (with different technologies). A lot of things happened in this time… I don’t remember all of them, but last 3 years I spent my time learning data. I was involved in building infrastructure for Big Data, I prepared ETL (Hadoop stuff) and I analyzed data (sales forecasting) and so on. In my free time I learn from MOOC (Coursera, Udacity, edX and so on), books and I take participation on the Kaggle. I love challenges.

• Nikolay

I am new to IT world. I have started to learn programming and data science 1 year ago and I am very excited about this. Previously I worked in business administration and consulting for many years. Besides that I like books and music, I like to travel by car with my family and I like NHL (ice hockey) which I want now to look at as a data scientist not as just a spectator. Prerequisites

• Basic knowledge of python
• Three options:
  • Auto-magic via docker - https://github.com/dataworkshop/environment
  • Half-manual. The package manager “conda" - install through the Miniconda installer (http://conda.pydata.org/miniconda.html) or the Anaconda installer (https://www.continuum.io/downloads) + ggplot, seaborn, bokeh, gmplot, geoplotlib, folium, vincent, geopandas, matplotlib basemap
  • Totally manually. Install manually those packages: ipython, scikit-learn, pandas, matplotlib, ggplot, seaborn, bokeh, gmplot, geoplotlib, folium, vincent, geopandas, matplotlib basemap

Use this script to verify your environment: https://github.com/dataworkshop/prerequisite Please bring your laptop with you. Please come an hour before if you need help with setting up the environment!