knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
This package demonstrates some of the ways we use R.
You can install the developmental version of nottshcOpenData
using:
# install.packages("devtools") devtools::install_github("CDU-data-science-team/nottshcOpenData")
You may also have to set up MySQL on your computer if it's not already installed, see https://db.rstudio.com/best-practices/drivers/ for more information.
This example demonstrates how the nottshcOpenData
package can be used to
1. connect to the server using connect_mysql()
1. query data from the database within R Studio using get_px_exp()
1. tidy the data on the database using tidy_px_exp()
, and
1. load the data into the global environment using dplyr::collect()
# Load public package library(nottshcOpenData)
# Create MySQL connection # Note, the driver name, here "MySQL ODBC 8.0 ANSI Driver", may differ on your computer conn_mysql_suce <- connect_mysql(database = "SUCE", driver = "MySQL ODBC 8.0 ANSI Driver")
# Get database (db_) connection for specified date range db_px_data <- get_px_exp(from = "2020-01-01", to = "2020-12-31") # Look at messy data db_px_data
# Tidy the data (on the database) # Next select some variables for this example db_px_data_tidy <- db_px_data %>% tidy_px_exp() %>% dplyr::select(key, comment_key, date, team_c, team_n, directorate, division, category, subcategory, comment_type, comment_txt, crit) # Look at tidy data db_px_data_tidy
In case the data needs to be loaded from the MySQL database into the global environment you can use the collect()
function from the dplyr
package.
# Collect tidy data df_px_data_tidy <- db_px_data_tidy %>% dplyr::collect()
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