[El Camino College] Notebook: CalEnviroScreen Exploration

This notebook will put together everything you’ve learned so far and include new ways of interpreting data .

Learning Objectives¶

In this notebook, you will learn about:

insert learning objectives

Table of Contents¶

Introduction

1. Introduction ¶

→ Explore the data, observe how many rows/columns and what they correspond to
→ Subset different LA census tracts including El Camino’s (create interactive graph they can play around with)
→ Local rates of (asthma, pollution ) , LA wide rates, Cal state wide (ex. compare local to higher level state averages)

import numpy as np
import pandas as pd

enviro = pd.read_csv('cal_enviro_screen.csv')
enviro

Let’s take a look at El Camino College’s census tract data. Their tract # is 6037603702.

ecc = enviro[enviro['Census Tract'] == 6037603702]
ecc

2. Exploring by Region ¶

→ Split data into different neighborhoods of LA
→ Focus subsetting health outcomes (PM2.5, lead, groundwater threats, pollution burden, asthma), particularly in lower-income neighborhoods