This lesson is an introduction to Exploratory Data Analysis using two powerful Python libraries: pandas and seaborn. Pandas provides flexible and powerful data structures, while seaborn allows us to almost effortlessly generate beautiful visualizations of our data.
We will play around with the Titanic dataset from Kaggle, which you can download here (we will only use the train.csv file).
The lesson will be a mixture of live coding demonstrations and questions for you to jump right into the nitty-gritty. It will use a Jupyter Notebook (running Python 3). You can view and download the notebook here. The full notebook containing the live demonstrations and solutions to the questions will be posted after the workshop.
Don't forget to bring your own laptop.
Time and Place
Where: Room D1.112, Science Park 904
When: Tuesday, October 24th, 2017 at 17:00 PM
Required Preparation
Prior knowledge
The lesson assumes basic knowledge of Python.
Software Dependencies
A working Python distribution. You can install Anaconda for an all-in-one setup. Before the lesson, download the Jupyter notebook of the class and the dataset, and place them in the same directory.
Description
This lesson is an introduction to Exploratory Data Analysis using two powerful Python libraries: pandas and seaborn. Pandas provides flexible and powerful data structures, while seaborn allows us to almost effortlessly generate beautiful visualizations of our data.
We will play around with the Titanic dataset from Kaggle, which you can download here (we will only use the
train.csvfile).The lesson will be a mixture of live coding demonstrations and questions for you to jump right into the nitty-gritty. It will use a Jupyter Notebook (running Python 3). You can view and download the notebook here. The full notebook containing the live demonstrations and solutions to the questions will be posted after the workshop.
Don't forget to bring your own laptop.
Time and Place
Where: Room D1.112, Science Park 904 When: Tuesday, October 24th, 2017 at 17:00 PM
Required Preparation
Prior knowledge
The lesson assumes basic knowledge of Python.
Software Dependencies
A working Python distribution. You can install Anaconda for an all-in-one setup. Before the lesson, download the Jupyter notebook of the class and the dataset, and place them in the same directory.