Looking at the farmers market data IMP R OVIN G YOU R DATA VISU - - PowerPoint PPT Presentation

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looking at the farmers market data
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Looking at the farmers market data IMP R OVIN G YOU R DATA VISU - - PowerPoint PPT Presentation

Dec 27, 2022 415 likes •886 views

Looking at the farmers market data IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON Nick Stra y er Instr u ctor First e x plorations of a dataset Take a broad v ie w Sho w as m u ch info as possible Don ' t f u ss o v er appearances

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Looking at the farmers market data

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

Nick Strayer

Instructor

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

First explorations of a dataset

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

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Using your head()

pollution.head()

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

# Just show median pollution.describe(percentiles=[0.5] # Describe all columns include='all')

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON pd.plotting.scatter_matrix(pollution, alpha = 0.2);

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON markets.head()

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Let's explore our data

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

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Exploring the patterns

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

Nick Strayer

Instructor

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Digging in deeper

Investigating correlations Are correlations driven by confounding? Anything surprising?

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Target audiences

Shared with peers Be smart about design decisions Remember they aren't as familiar with data

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON sns.regplot('NO2', 'CO', ci=False, data=pollution, # Lower opacity of points scatter_kws={'alpha':0.2, 'color':'grey'} )

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Profiling patterns

Found interesting paern in data How to quickly explore and explain the paern? Use text!

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Using text scatters to id outliers

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON g = sns.scatterplot("SO2","CO", data=long_beach_avgs) # Iterate over the rows of our data for _, row in long_beach_avgs.iterrows(): # Unpack columns from row month, SO2, CO = row # Draw annotation in correct place g.annotate(month, (SO2,CO)) plt.title('Long Beach avg SO2 by CO')

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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Let's dig in

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

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Making your visualizations efficient

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

Nick Strayer

Instructor

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

What is efficient?

Reduce the eort needed to see story Re-organize plots to keep focus Improve 'ink' to info ratio Don't compromise the message

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

# Create a subplot w/ one row & two columns. f, (ax1, ax2) = plt.subplots(1, 2) # Pass each axes to respective plot sns.lineplot('month', 'NO2', 'year', ax=ax1, data=pol_by_month) sns.barplot('year', 'count', ax=ax2, data=obs_by_year)

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Clear unnecessary legends

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

sns.lineplot('month', 'NO2', 'year', ax=ax1, data=pol_by_month, palette='RdBu',) sns.barplot('year', 'count', 'year', ax=ax2, data=obs_by_year, palette='RdBu', dodge=False) # Remove legends for both plots ax1.legend_.remove() ax2.legend_.remove()

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Let's practice

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

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Tweaking your plots

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

Nick Strayer

Instructor

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Looking at the small things

Put yourself into the viewer's shoes

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Is the aesthetic appropriate?

Is the aesthetic appropriate for the context?

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Font-sizes

Is everything legible?

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Removing spines from plots

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Removing spines from plots

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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Let's tweak some plots

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

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Wrap-Up

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON

Nick Strayer

Instructor

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Using color responsibly

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

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IMPROVING YOUR DATA VISUALIZATIONS IN PYTHON

Going further

Blogs Flowing data Curated list of data visualizations. Datawrapper Blog Articles that dig deep into visualization techniques and mistakes. Twier #datavis An ongoing stream of cool projects and inspiration.

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Thank you!

IMP R OVIN G YOU R DATA VISU AL IZATION S IN P YTH ON