vinsinraw / dsce_bac Goto Github PK

19th, 20th & 21st April, 2pm - 5pm

If you run into issues while installing the softwares required for the workshop, please reach out to us @ [email protected] or 7259970037.

Materials for the workshop. Please install all the required softwares and download the data sets and scripts from this repository before the workshop. The final version of the materials will be available by 6 PM Wednesday (18/04/2018). Please ensure that you download them before coming to the workshop.

• Workshop Material Download Demo

R can be installed from the R project website. Please install the latest version 3.4.4.

• R Download Demo
• R Installation Demo

Download and install Rtools from here.

RStudio IDE can be installed from the RStudio website. Install the free desktop version.

• RStudio Download Demo
• RStudio Installation Demo

Below are a list of R packages required for the workshop:

• readr
• readxl
• haven
• dplyr
• ggplot2
• magrittr
• descriptr
• skimr

• inferr
• olsrr
• blorr
• rmarkdown
• knitr
• devtools
• forcats
• caret

Once you download the workshop materials, run the script (package_download.R) in the R folder to download the above packages as shown in the below video:

• R Packages Installation Demo

To test if a package has been correctly installed or not, type library(packagename) in the RStudio console. For example, to test if readr package has been installed, type library(readr) in the RStudio console. If the package has not been installed correctly, you will get the following error message:

Error in library(readr) : there is no package called ‘readr’

There will be no error message if the package has been correctly installed.

Download and install the Anaconda distribution from their website. We will use Jupyter Notebook for the python session.

• Anaconda Download Demo
• Anaconda Installation Demo

After installing the Anaconda distribution for Python, open the Command Prompt (type cmd) or Windows Powershell (type powershell) and type jupyter notebook.

• Jupyter Notebook Demo

• Quick tour of R & RStudio
• Importing data into R
• Data Wrangling
• Data Visualization
• Exploratory Data Analysis
• Linear Regression
• Logistic Regression

• Data Wrangling with Pandas
• Data Visualization
  • matplotlib
  • bokeh
  • plotly
• Modeling with statsmodels

• Rstudio Webinars
• RStudio Cheat Sheets
• tidyverse
• R Bloggers
• R Weekly