<img src="https://i.imgur.com/OhTn0sc.png" width="50%" /><br> July 12, 2023 <img src="https://media0.giphy.com/media/3ov9jNziFTMfzSumAw/giphy.gif" /> Remember that assignments are *not graded*. Please follow the instructions below. # Exercise 1 Go to this [repository](https://github.com/brain-image-library/py-brain-inventory). Click on this box and select `2-populate-authors-file` ![](https://hackmd.io/_uploads/HyZM_82Fn.png) Then click on the `AUTHORS` file ![](https://hackmd.io/_uploads/Bk4uOI2Fn.png) to open the file. On the upper right select `Edit in place` ![](https://hackmd.io/_uploads/rkMauInt2.png) This will open an editor. Add your name under `SAMS Data Science Group 2023` ![](https://hackmd.io/_uploads/HybBtLnYn.png) and click ![](https://hackmd.io/_uploads/ByfOYUhKh.png) A window like this should open ![](https://hackmd.io/_uploads/HJ1sKIhY2.png) and click `Commit Changes`. Congratulations you have made your first contribution to an open source project! # Exercise 2 Have you selected a metric yet? If you want to add a metric to the repository first we need to make an issue ticket. Issue tickets are important to keep track of contributions. Click on ![](https://hackmd.io/_uploads/r1DM9Uhth.png) then ![](https://hackmd.io/_uploads/H1cmcIhF3.png) and select ![](https://hackmd.io/_uploads/r1AH582Fh.png) Complete the issue with the best of your knowledge. This information can be updated by any member of the team. For reference, take a look at this [issue](https://github.com/brain-image-library/py-brain-inventory/issues/3). If you feel confident taking charge of this issue, then assign it to yourself. Feel free to explore this [document](https://docs.google.com/document/d/185dzRZZNtSGaTPZpeRBy3vn5Y7tJh2Xuq-SbXmIjRZo/edit?usp=sharing) and add another metric on this list. # Exercise 3 Open up the Brain Image Library notebook we used last session. Import the data to the workspace by running the first few cells. Notice that one of the columns is named `affiliation` and has the named of different universities. I want you to explore two packages. * [universities](https://pypi.org/project/universities/). Figure out if this package beyond containing general information about the university if you can find the coordinates or the city it is located. * [folium](https://pypi.org/project/folium/). If you can find the coordinates or the city check if you can plot these on a map using folium. To install these packages on Google Colab run ``` !pip install universities !pip install folium ``` The exclamation sign (!) is needed. # Exercise 4 Want to be challenged? If so, then let me know I have a additional component of this project you can help with. It is related to reading and parsing log files. The concepts are very similar to munging the dataframe the difference is this file is not as clean as the dataframe I am providing you and will require extra work to figure it out.