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Tidying and Wrangling

Making data useful!

Zachary del Rosario (He/Him)

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Workshop Schedule

Extract

Wrangle + Tidy

Friday

Saturday

Visualize

Model

Sunday

Monday

Tabula +

WebPlotDigitizer

Python + Jupyter

Concepts

Execution

Concepts

Execution

Concepts

Fin

Focus

Live

Take-Home

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Tidying and Wrangling

Tidying: Reshaping to tidy data

Wrangling: Unit conversions, data types, invalid/missing values, etc.

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Why are these important? (In-chat)

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Survey Time!

Please fill out this survey:

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https://forms.gle/yWZkqDXWSyVDWm41A

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Don’t worry, I’ll wait….

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Looking Forward

Visualizing Tidy Data!

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Visualizing Tidy Data is Trivial

(

df_converted

>> ggplot(aes(“sigma_MPa”))

+ geom_density()

)

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Visualizing Tidy Data is Trivial

(

df_converted

>> ggplot(aes(“sigma_MPa”))

+ geom_density()

+ theme_minimal()

+ labs(

x=”Critical Stress (MPa)”,

y=”Density (-)”

)

)

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Tonight’s Exercise

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Tonight’s Notebook: Programmatic Data Operations

03_data_assignment

  • Pandas’ DataFrame
  • Grama pipelines
  • How to tidy and wrangle

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End of Today

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Feel free to contact me via email:�

    • Zach del Rosario: zdelrosario@olin.edu

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