Please enable JavaScript.
Coggle requires JavaScript to display documents.
Exploratory Data Analysis (EDA) with R, image, http://r-statistics…
Exploratory Data Analysis (EDA) with R
Goals
Understand the data
Filter the data and create new features
Generate hypotheses and questions and answer them
Identify preprocessing steps for the modeling phase
Workflow
Collect and Import data
Data Wrangling
Tidy the data
Bring data into the right format
Deal with outliers
Handle missing values
Transform the data
Filtering
Create new features
Selecting
Joining
Visualization
Modelling
Test different models
Use models to answer your questions or validate hpyotheses
Communicate results
Visualization
Shiny
Fast & easy web-dashboards
Interactive visualization
Ggplot2
Objective (usually on of the following 8)
Correlation
Deviation
Ranking
Distribution
Composition
Change
Groups
Spatial
Type of data
Amount of variables to plot
Discrete or continuous?
Data Preprocessing / Wrangling
dplyr
purrr
Tidyverse packages
tibble
tidyr
dyplyr
ggplot2
readr
purrr
stringr
http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
http://www.sthda.com/english/wiki/be-awesome-in-ggplot2-a-practical-guide-to-be-highly-effective-r-software-and-data-visualization
