This week's assignment will be broken into two parts:
Follow the instructions in this repository for downloading and installing Anaconda locally and creating a new Python environment.
Note: If you are unable to successfully install Python locally, you can also use the Binder link above to proceed with step 2. After loading Binder, a new Jupyter notebook can be created to complete Part 2.
However, local installation is still preferred, so please also contact me any problems encountered.
If running Python locally, start a Jupyter notebook by running the following command from the command line:
source activate musa
jupyter notebook
This will create the local Jupyter server. If it does not open in a browser, copy the link that is output by the command into your favorite browser. Once the server is running, you can create a new notebook and get started!
For help running the notebook, see the Jupyter documentation.
Use a Jupyter notebook to find the Philadelphia ZIP code with the largest average annual ZHVI value, for each year in the data set. The Zillow data is available in this repository: data/Zip_Zhvi_AllHomes.csv.
The Jupyter notebook should used pandas to load the data and analyze it. The following steps should be followed:
- Load the ZHVI data for each ZIP code, selecting only Philadelphia ZIP codes.
- Calculate the annual average ZHVI for each ZIP code in Philadelphia and each year.
- Identify the ZIP code with the maximum value for each year.
The final result should be the year and the ZIP code with the maximum value.
Please send your Jupyter notebook .ipynb
showing
your calculation for Part 2 above.
Files should be submitted to [email protected] by 9am on 1/30.