The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
It is often said that data manipulation alone takes 50-70% time of a data science project.
The duration of this never-ending activity can be attributed to our opaqueness with datasets provided.
Functions in this package enable familiarity with the data.frame to further reduce coding errors and re-work.# The easiest way to get dplyr is to install from GitHub:
install.packages("dataframeexplorer", dependencies = T)
# Alternatively, you can install development version:
install.packages("devtools")
devtools::install_github("ashrithssreddy/dataframeexplorer")Functions: [x] Percentiles [x] Level of dataset Univariate Analysis Bivariate Analysis Show progress bar for level_of_dataset Run the level_of_dataset code in parallel for performance
Changes: Return value for all functions to be included into
documentation Message not printed in all codes
Default filename not consistent Outputs not refined Pep 8
formatting examples not consistent Comments not consistent across all
codes sink() to be run in glimpse_to_file upon an error Arguement
format to be used: dataset = dataset, output_filename =
“dataset_glimpse.txt” Throw a warning when duplicate column names
are found Level: Unsink when interrupted Add
instructions to interpretation of output
1. glimpse_to_file
glimpse_to_file(mtcars, "mtcars_glimpse.txt") or glimpse_to_file(mtcars, "C://Users/Desktop/mtcars_glimpse.txt")
Mail ashrithssreddy@gmail.com for suggestions with “dataframeexplorer” in subject line.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.