In this course we introduce and learn to use some tools every journalist can adopt to produce graphics that can support or carry a story.LEARN MORE
R is getting more and more popular among Data Journalists worldwide. It can be used for complex statistics, but it can also be used to clean, join and superficially analyse data.
R is getting more and more popular among Data Journalists worldwide, as Timo Grossenbacher from SRF Data pointed out recently in a talk at useR!2017 conference in Brussels. Working as at Berliner Morgenpost’s Interactive Team, I can confirm that R indeed played an important role in many of our lately published projects, for example when we identified the strongholds of german parties. While we also use the software for more complex statistics from time to time, something that R helps us with on a near-daily basis is the act of cleaning, joining and superficially analysing data. Sometimes it’s just to briefly check if there is a story hiding in the data. But sometimes, the steps you will learn in this video tutorial are just the first part of a bigger, deeper data analysis.
The video tutorial will guide you through the standard steps I always take when getting the data for a potential new data driven project at the Morgenpost.
Module 1: Installing and getting to know the Software
• Section 1: Downloading R and RStudio
• Section 2: Structure and functionalities of RStudio
Module 2: Coding Basics
• Section 1: Basic calculations and comparisons in R
• Section 2: Using functions and conditional instructions
Module 3: Data Structures
• Section 1: Data Classes
• Section 2: Working with Data Sets
Module 4: Exploring the Tidyverse
• Section 1: Introduction to packages in R
• Section 2: The tidy data format
• Section 3: Manipulating data with dplyr Section 4: Visualising data with ggplot2