The Python snippets presented here applied to a set of dataframes from evaluation studies exemplify key analytical steps and replicable coding solutions for other assessments

Source from Pixabay

Programming languages meet social sciences


Data science stylistics

How to use R and Python to model data through different versions of regression analysis which represents an estimation task to produce predictions for different types of target variables

By author combining images from source 1, source 2 and source 3

1. Introduction to regression analysis


Data Science Stylistics

How to use R and Python to model neural network pathways and generate predictions for a set of predictors and target variables

By author combining images from source 1, source 2 and source 3

1. Introduction to neural networks


Data Science Stylistics

How to use R and Python to predict the probability of an event, based on prior knowledge of conditions that relate to it

By author combining images from source 1, source 2 and source 3


Data science stylistics

How to develop a decision tree in R and Python to represent for each internal node a “test” on an attribute, for each branch the outcome of the test, and for each leaf node a class label.


Data science stylistics

1. Meaning of partitioning in data science


Data science stylistics


Data science stylistics


Step 1: Upload relevant libraries

library(dplyr)
library(ggplot2)

Nicola Giordano

Cultivating an interest in applying data science to international humanitarian work and social sciences.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store