Lecture 1 – Introduction

Data 6, Summer 2021

This is a Jupyter notebook. We'll write all of our code in this class in a Jupyter notebook.

Today, don't worry about how any of this works. Throughout the semester, we'll learn how each of these pieces work.

Note: The maps in this notebook will not load correctly in Safari if you're on a Mac; use Chrome.

from datascience import *
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
import plotly.graph_objects as go

California universities

Here, we'll load in data about all public universities in California. The data comes from this Wikipedia article.

uni = Table.read_table('data/california_universities.csv')

uni = uni.with_columns(
    'Enrollment', uni.apply(lambda s: int(s.replace(',', '')), 'Enrollment'),
    'Founded', uni.apply(lambda s: int(s.replace('*', '')), 'Founded')
)

Data is often stored in tables. In about a few weeks, we'll become very, very familiar with how tables work. But for now, let's just observe.

uni.show(15)

Name	City	County	Enrollment	Founded
University of California, Berkeley	Berkeley	Alameda	42519	1869
University of California, Davis	Davis	Yolo	39152	1905
University of California, Irvine	Irvine	Orange	35220	1965
University of California, Los Angeles	Los Angeles	Los Angeles	45428	1882
University of California, Merced	Merced	Merced	8544	2005
University of California, Riverside	Riverside	Riverside	23278	1954
University of California, San Diego	San Diego	San Diego	38798	1960
University of California, Santa Barbara	Santa Barbara	Santa Barbara	24346	1891
University of California, Santa Cruz	Santa Cruz	Santa Cruz	19700	1965
California State University Maritime Academy	Vallejo	Solano	1017	1929
California Polytechnic State University	San Luis Obispo	San Luis Obispo	21812	1901
California State Polytechnic University, Pomona	Pomona	Los Angeles	26443	1938
California State University, Bakersfield	Bakersfield	Kern	10493	1965
California State University Channel Islands	Camarillo	Ventura	7095	2002
California State University, Chico	Chico	Butte	17488	1887

... (17 rows omitted)

Let's start asking questions.

What's the largest public university in California?

uni.sort('Enrollment', descending = True)

Name	City	County	Enrollment	Founded
University of California, Los Angeles	Los Angeles	Los Angeles	45428	1882
University of California, Berkeley	Berkeley	Alameda	42519	1869
California State University, Fullerton	Fullerton	Orange	39774	1957
University of California, Davis	Davis	Yolo	39152	1905
University of California, San Diego	San Diego	San Diego	38798	1960
California State University, Northridge	Northridge	Los Angeles	38716	1958
California State University, Long Beach	Long Beach	Los Angeles	36846	1949
University of California, Irvine	Irvine	Orange	35220	1965
San Diego State University	San Diego	San Diego	34881	1897
San Jose State University	San Jose	Santa Clara	32828	1857

... (22 rows omitted)

uni.sort('Enrollment', descending = True).barh('Name', 'Enrollment')

What's the oldest public university in California? 🤔

uni.sort('Founded')

Name	City	County	Enrollment	Founded
San Jose State University	San Jose	Santa Clara	32828	1857
University of California, Berkeley	Berkeley	Alameda	42519	1869
University of California, Los Angeles	Los Angeles	Los Angeles	45428	1882
California State University, Chico	Chico	Butte	17488	1887
University of California, Santa Barbara	Santa Barbara	Santa Barbara	24346	1891
San Diego State University	San Diego	San Diego	34881	1897
San Francisco State University	San Francisco	San Francisco	29586	1899
California Polytechnic State University	San Luis Obispo	San Luis Obispo	21812	1901
University of California, Davis	Davis	Yolo	39152	1905
California State University, Fresno	Fresno	Fresno	24995	1911

... (22 rows omitted)

uni_copy = uni.sort('Founded').with_columns('Total Universities', np.arange(1, uni.num_rows + 1))
uni_copy.plot('Founded', 'Total Universities')

Let's add some spice.

fig = go.Figure()

fig.add_trace(
    go.Scatter(x = uni_copy.column('Founded'), 
               y = uni_copy.column('Total Universities'), 
               hovertext = uni_copy.column('Name'),
               mode = 'markers',
              )
)

fig.add_trace(
    go.Scatter(x = uni_copy.column('Founded'), 
               y = uni_copy.column('Total Universities'),
               line = dict(color = 'blue'),
              )
)

fig.update_layout(title = 'Total Number of Public Universities in California by Year',
                  xaxis_title = 'Year',
                  yaxis_title = 'Total Universities')

fig.show()