Data Academy Subscription > Data with R > Basic Data Visualization in R
Course Description
In this course, you will learn and apply data visualization concepts for practical data science and interpretation. Data visualization is a general term describing any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends, and correlations that might go undetected in raw data become clearer through visualizations like bar plots, pie charts, histograms, boxplots, or line charts. You will learn the theoretical principles behind data visualization and you will use Exploratory Data Analysis (EDR) to examine the distribution of a single variables and the relationship between two variables.
Requirements
  • This course assumes knowledge of basic statistical terminology.
Instructor:
Minerva Singh
Minerva Singh is a PhD graduate from Cambridge University where she specialized in Tropical Ecology. She is also a part-time Data Scientist. As part of her research, she must carry out extensive data analysis, including spatial data analysis. For this purpose, she prefers to use a combination of freeware tools: R, QGIS, and Python. She does most of her spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing, and analysis. She also holds an MPhil degree in Geography and Environment from Oxford University. She has honed her statistical and data analysis skills through several MOOCs, including The Analytics Edge and Statistical. In addition to spatial data analysis, she is also proficient in statistical analysis, machine learning, and data mining.