Exercise 1 | Introduction & Logistics
Max Pellert
IS 616: Large Scale Data Analysis and
Visualization
Let’s get your basic setups running!
ðŸ›
R
Install R
https://cran.r-project.org/
Use RStudio
https://posit.co/products/open-source/rstudio/
Install R packges
install.packages()
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R packages
data.table
ggplot2
tidyverse
quanteda
...
Usually, functions in R are well-documented, just run any function
name prefixed with ? to get help if you are stuck.
Visualization and R
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Python
Install Spyder
https://www.spyder-ide.org/
Use pip as package manager
https://pip.pypa.io/en/stable/installation/
after installing pip, install packages with `pip install`
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Python packages
wordshiftgraphs
matplotlib
seaborne
altair
nltk
spacy
pytorch
transformers
...
Python Package Index (PyPI) (https://pypi.org/) usually also provides links to
package documentations
Visualization and Python
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Visualization and Python
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R vs. Python?
In this course, you are free to use either
The popularity of one over the other is currently largely determined
by disciplinary tastes and traditions (econ more towards R, computer
science more towards Python) and this course has a interdisciplinary
audience
They are both non-commercial and have dedicated communities
R may still have an edge in concise statistical computing and also
visualization, but Python caught up a lot
Python is a general purpose language and the de-facto standard in
deep learning
To do
Catch up on using your favorite visualization package
Take special care to check out all ways to customize your plots,
e.g.
How to change the theme of a plot
How to set custom axis limits
How to set custom axis ticks and labels
…
You will need those skills later in the course
To do
Also start refreshing your data wrangeling skills
How to load data in
How to handle most common preprocessing steps
…
It is obvious that you need those skills to able to do
data visualization
