Python for Analysts (part 2)
Speaker: Laura Richter
Track: Data Science
Time: Oct 09 (Wed), 13:30
This is the second part of the 2 session tutorial, and follows on from Part 1.
Python has found a real niche in the data space, with a well established suite of data manipulation, analysis and visualisation tools. This tutorial will introduce Python as a data analysis tool. It is aimed at analysts, data scientists and developers who already have some data analysis and programming experience and want to add Python to their analysis tool belt.
We will begin with an introduction to Python and the Jupyter Notebook environment that we will be using in the tutorial. The majority of the tutorial will look at the core Python data modules NumPy and Pandas, covering data import and export, data manipulation, and statistics. We will also work with Python data visualisation modules, and look at Jupyter Notebooks as a tool for sharing and keeping a record of data analysis.
The tutorial will be interactive, with times for the attendees to work on tutorial material on their own laptops.
Setup requirements for the tutorial
In advance of the tutorial, please ensure you have all of the following in place:
The following software installed on the laptop you are using for the tutorial: Python 3.6 Jupyter notebooks (and optionally Jupyter lab)
A google account or a Microsoft account (for using either Google Colaboratory or Azure Notebooks)
Please contact me in advance if you need help installing software.