Data science for all
For a long time, statistical and digital methods were restricted to hard sciences. Fortunately, historians and humanists can now benefit from data science as well. This webpage provides programming lessons on the use of data science in digital humanities. Learn to conduct efficient statistical analyses and show your insights with beautiful visualizations.
CODING LESSONS
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Checking normality in R
Learn what is and how to identify data that is normally distributed.
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Z score in R
Learn to calculate and visualize Z scores in R.
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Text Mining in Python - TF-IDF
Learn the difference between term frequency and TF-IDF and how to use them in Python.
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Visualizing Text Data
Learn to analyze and visualize text data
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What are the digital humanities?
Learn about what digital humanities really are and their applications.
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Changing ggplot colors with scale_color_brewer
Use RColorBrewer to choose professional color palettes.
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Use Matplotlib line plot to create clear and compelling visualizations
Use Matplotlib to plot and highlight elements in historical trends in 8 steps.
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R programming for climate data analysis and visualization
Learn the basics of linear regression models and how to use them to study the relationship between two variables.
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Climate Data Visualization
Would you like to contribute to raise awareness about global warming? In this lesson you will learn how to create your own ggplot2 themes to code compelling plots showing historical weather data.
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Where To Find And How To Load Historical Data
Learn 5 great websites to find reliable historical data and how to load it in R and Python.
*Cover images are all in public domain (available at Wikimedia Commons) or AI generated.