This repository contains the Homework directories for PUI class 2016.
The hw questions can be found here in the HWX repos. https://github.com/fedhere/PUI2016_fb55
Setting up GitHub, Using Unix enviornment variable, alias, PEP8 and style standards, using jupyter notebook
Write python scripts to stream real-time bus data from MTA through the MTA Bus Time interface using API to access the data. Using csv files within pandas and handling datetime data within pandas.
Write an ipython notebook that demonstrates visually in a data-driven way the Central Limit Theorem. Analysis of citibike data. Implementing Z-test.
Literature choices of statistical tests. Reproduce the analysis of the Hard to Employ program in NY. Tests of correlation using the scipy package with citibike data.
Compare Tests for Goodness of fit on Citibike data. Line fitting and data munging with income gender bias.Practice formulating the null hypothesis
Testing the postulate that "Light is a proxy for occupancy, and that occupancy is a good predictor of energy consumption".
Make visulizations
Analysis of 311 call complaints for community districts in respect of income and internet and mobile infrastructure.
TIME SERIES ANALYSIS: Goal: Find outliers, trends and periodicity in the MTA turnstile data
Geospatial Analysis of Citibike data.
Use GeoPandas to plot NYC Boroughs and locating a location on the map. Analysis of NYC business changes using clustering.
Using SQL within python to access data. Spatial analyses of NYC hospital asthma dismissal counts.
Investigation of citibike ridership with income Objective: relate the citibike ridership to income.
Identify specific socio-echonomic changes in NYC over 10 years.