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DATA VISUALIZATION WITH PYTHON

Event:
DATA VISUALIZATION WITH PYTHON
Start:
September 27, 2021 -
End:
October 1, 2021 -
Link:
Venue:
online
Details:

OVERVIEW

    In this course, we will be manipulating and visualizing data in Python using the data analysis library Pandas, along with the visualization libraries Matplotlib and Seaborn.We will be working with Jupyter notebooks, which make it easy to run code and generate visualizations in an interactive format.To set all of this up, you can download the Anaconda data science platform, which offers these libraries and other popular scientific Python tools pre-installed.

    INTENDED AUDIENCE

      This course is meant to be an introduction to data manipulation and visualization in Python. A basic knowledge of Python will be useful, but you do not otherwise need previous programming experience

      ASSUMED BACKGROUND

        This course is aimed at researchers and technical workers with a background in biology and a basic knowledge of Python (if you've taken the Introductory Python course then you have the Python knowledge; if you're not sure whether you know enough Python to benefit from this course then just drop us an email).

        PROGRAM

        Monday 2-8 pm Berlin time: Course introduction, setup and introduction to Pandas

         

        First we will get set up with Jupyter notebooks and go over how to configure the environment for data analysis and visualization, as well as how to import the Pandas and Matplotlib/Seaborn libraries.

         

        We will talk about the datasets that we will be looking at in this course, and how to read the data into Pandas.Then we will dive in to the basics of Pandas and talk about DataFrames and Series objects. DataFrames are the core data structure in Pandas,and are similar to spreadsheets with rows and columns.


        We will read in the course data and learn how to quickly summarize the data, and how to perform some basic data cleaning techniques such as handling duplicates, missing values, null types and outliers. We will go over working with dates in Pandas, as well as string manipulations. As part of this data exploration, we will look at how to quickly and easily generate some basic plots straight from Pandas.