Highlighting data

Improving Your Data Visualizations in Python

Nick Strayer

Instructor

about me

table to visualization

table to visualization part two

table to visualization part three

tools needed for course

Prereqs

Introduction to Data Visualization with Matplotlib

Introduction to Data Visualization with Seaborn

Python Data Science Toolbox (Part 2)

different visualization tools

pollution.head()

         city  year  month  day     CO   NO2     O3    SO2
0  Cincinnati  2012      1    1  0.245  20.0  0.030   4.20
1  Cincinnati  2012      1    2  0.185   9.0  0.025   6.35
2  Cincinnati  2012      1    3  0.335  31.0  0.025   4.25
3  Cincinnati  2012      1    4  0.305  25.0  0.016  17.15
4  Cincinnati  2012      1    5  0.345  21.0  0.016  11.05

pollution.city.unique()

[ 'Boston',    'Cincinnati',     'Denver',       'Des Moines', 
  'Fairbanks', 'Houston',        'Indianapolis', 'Long Beach', 
  'New York',  'Salt Lake City', 'Vandenberg Air Force Base' ]

basic scatter plot with highlighted point

scatter plot with unlabeled outlier

cinci_pollution = pollution[pollution.city == 'Cincinnati']

# Make an array of colors based upon if a row is a given day
cinci_colors = ['orangered' if day == 38 else 'steelblue' 
                for day in cinci_pollution.day]

# Plot with additional scatter plot argument facecolors 
p = sns.regplot(x='NO2',
                y='SO2',
                data = cinci_pollution,
                fit_reg=False, 
                scatter_kws={'facecolors': cinci_colors,'alpha': 0.7})

scatter plot with labeled outlier

Let's make some highlights!

Improving Your Data Visualizations in Python