Public Pre-K in New York City - Data Scientist Final Project

Projects Portfolio Project: Data Scientist Final
1

Hi everyone,

I’m excited to share my final project for the Codecademy Data Scientist career path. I decided to look at the effects of Universal Pre-K, a public policy introduced in New York City in 2014, on the number of public pre-K sites offered across the city. I looked at data from the 2013-2014 school year and compared it with the 2018-2019 school year (the last full school year before the beginning of the COVID-19 pandemic).

This project took me about 15 hours to finish.

I’ve included a link below. Please let me know if you have any thoughts or questions!

https://github.com/eric-mosher/Codecademy-Data-Science-Final-Project/blob/main/New%20York%20City%20Public%20Pre-K%20Data%20Survey.ipynb

Best regards,
Eric

1 Like
2

Your repo is set to “private”.

3

Thanks, it should be publicly viewable now.

Eric

4

Cool project! Congrats on finishing it.
Good use of the text markdown cells to explain each of your steps so someone with no knowledge of the data could follow along.

A few things:

  • Where is the data from? US Census/ACS? Open Data NYC? It’s good practice to list the source of the data (and a link) at the top of the notebook.

  • One small thing that might be helpful is if you just printed out the first 5 rows of each df so the viewer could see how the data looks. ex: school2013.head().

  • Also, in cell 67, which bars are 2013? blue? (and obv. the orange bars are 2018.)
    Adding a legend might help there…for clarity’s sake.
    https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.legend.html#matplotlib.pyplot.legend
    Or, you could use the “hue” parameter in Seaborn to add a legend. ie:

ax = sns.barplot(x='Borough', y='no. of programs', 
hue= "year", data = pd.concat([school2013, school2018])) #or something like that.

https://seaborn.pydata.org/generated/seaborn.barplot.html

Good work!