Looking at the farmers market data

Improving Your Data Visualizations in Python

Nick Strayer

Instructor

First explorations of a dataset

  • Take a broad view
  • Show as much info as possible
  • Don't fuss over appearances

A box opening

Improving Your Data Visualizations in Python

Using your head()

pollution.head()

Basic output of python head command with column types pointed out

Improving Your Data Visualizations in Python
# Just show median
pollution.describe(percentiles=[0.5]
                   # Describe all columns
                   include='all')

Output of Panda's describe function with categorical data summarized on top and continuous on bottom

Improving Your Data Visualizations in Python
pd.plotting.scatter_matrix(pollution, alpha = 0.2);

Dense scatter matrix of pollution data showing correlations between continuous columns

Improving Your Data Visualizations in Python

Scatter matrix of pollution data with scatter of CO and NO2 highlighted

Improving Your Data Visualizations in Python

Scatter matrix of pollution data marginal histograms on diagonal highlighted

Improving Your Data Visualizations in Python
markets.head()

First five rows of new farmer's market data with column types pointed out

Improving Your Data Visualizations in Python

Let's explore our data

Improving Your Data Visualizations in Python

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