Computer Labs

Note

Please bring your own laptop if you can. Although the university does provide computers (in the computer rooms), it makes a lot of sense for you to bring your own laptop. There’s a good chance that your own laptop is faster and more flexible to configure. Also, you can take your laptop home with you and continue your econometrics work there.

Before you attend your first computer lab (which starts in week 2), please prepare your computer by following the explanation given in How to run Python.

If you do not have your own laptop: don’t worry! You can use the PCs in the computer rooms and we will explain to you how to set up a powerful cloud computer that you can even access remotely (for example, if you have your own PC at home). Instructions are in How to run Python.

We will help and assist you with the computer setup during the first computer labs (in week 2).

Datasets

I will post data sets for our econometric work here.

Important

All coding this semester has to be done in Python. Do not use other software!

Also: Only use packages or libraries that were used during the weekly computer labs! Do not use any other packages or libraries. We understand that some of you may have some familiarity already with Python and perhaps would like to use different packages or libraries to work on our notebooks, but we do not permit this. Sorry.

Week 2

Before attending this week’s computer lab, make sure to prepare your computer by following the steps given in How to run Python.

  • Put the following Juypter notebook inside your notebooks folder: week_2.ipynb.

  • Launch Jupyter, like so:

    • Anaconda users: open Anaconda Navigator through which you can launch Jupyter. Do not double-click the week_2.ipynb file!

    • Colab users: go to your Google Drive wherever you have saved week_2.ipynb and double click on it. Then Google will automatically launch a Jupyter session for you.

  • Now you can work on the file by editing and executing code cells. You will learn how to this during this week’s lab.

Important

Make sure you downlaod the above notebook into your folder named notebooks as explained in my instructions given in How to run Python.

Also make sure you have saved the data set World Development Indicators into your folder datasets as explained in my instructions given in How to run Python.

Week 3

Important

Those of you using their own laptops: please use Anaconda instead of Colab!

  • Put the following Juypter notebook inside your notebooks folder: week_3.ipynb.

  • Launch Jupyter, like so:

    • Anaconda users: open Anaconda Navigator through which you can launch Jupyter. Do not double-click the week_3.ipynb file!

    • Colab users: go to your Google Drive wherever you have saved week_3.ipynb and double click on it. Then Google will automatically launch a Jupyter session for you.

  • Now you can work on the file by editing and executing code cells.

Week 4

Important

Those of you using their own laptops: please use Anaconda instead of Colab!

  • Put the following Juypter notebook inside your notebooks folder: week_4.ipynb.

  • Make sure to put the EarningsHeight csv-file into your datasets folder (see at top of this page)

  • Launch Jupyter, like so:

    • Anaconda users: open Anaconda Navigator through which you can launch Jupyter. Do not double-click the week_4.ipynb file!

    • Colab users: go to your Google Drive wherever you have saved week_4.ipynb and double click on it. Then Google will automatically launch a Jupyter session for you.

  • Now you can work on the file by editing and executing code cells.

Week 5

Important

Those of you using their own laptops: please use Anaconda instead of Colab!

  • Put the following Juypter notebook inside your notebooks folder: week_5.ipynb.

  • Make sure to put the EarningsHeight csv-file into your datasets folder (see at top of this page)

  • Launch Jupyter, like so:

    • Anaconda users: open Anaconda Navigator through which you can launch Jupyter. Do not double-click the week_5.ipynb file!

    • Colab users: go to your Google Drive wherever you have saved week_5.ipynb and double click on it. Then Google will automatically launch a Jupyter session for you.

  • Now you can work on the file by editing and executing code cells.

Week 6

  • Put the following Juypter notebook inside your notebooks folder: week_6.ipynb.

  • Make sure to put the Growth csv-file into your datasets folder (see at top of this page)

Week 7

  • Put the following Juypter notebook inside your notebooks folder: week_7.ipynb.

Week 8

  • Put the following Juypter notebook inside your notebooks folder: week_8.ipynb.

  • Make sure to put the Birthweight csv-file into your datasets folder (see at top of this page)

Week 9

  • Put the following Juypter notebook inside your notebooks folder: week_9.ipynb.

  • Make sure to put the LeadMortality csv-file into your datasets folder (see at top of this page)

Week 10

  • Put the following Juypter notebook inside your notebooks folder: week_10.ipynb.

  • Make sure to put the cpi_aus_2023 csv-file into your datasets folder (see at top of this page)

Week 11

  • Put the following Juypter notebook inside your notebooks folder: week_11.ipynb.

  • Make sure to put the cpi_aus_2023 csv-file into your datasets folder (see at top of this page)

Week 12

Note

This week we’re posting a Jupyter notebook that contains a complete worked solution. All you need to do is run the code cells to produce Python output. Your tutor will guide you through each and every step!

  • Put the following Juypter notebook inside your notebooks folder: week_12.ipynb.

  • Make sure to put the gdp_us_2023 csv-file into your datasets folder (see at top of this page)