This function takes a data frame, a categorical target variable and a list of ssv and produces a density plot of each ssv and each category of the target variable. The output is written as .png file into the current working directory. Also, summary statistics are provided. The files can be saved into the current working directory. Consider changing the working directory to a new empty folder before running if you want to save a copy of the plots.
categorical.freqplot(df, target, ssv = NULL,
outlier_removal_ssv = TRUE, savePlots = FALSE,
image_directory = tempdir())
Data frame to be analysed.
Categorical target varaible to be analysed.
A vector of suspected sources of variation. These are the variables
in df
which we believe might have an influence on the target variable and
will be tested. If no list of ssv is provided, the test will be performed
on all numeric variables.
Logical. Should outlier removal be performed for each ssv (default: TRUE
)?
Logical. If FALSE
(the default) frequency plots will be output to the standard plotting
device. If TRUE
, frequency plots will be saved to image_directory
as png files.
Directory to which plots should be saved. This is only used if savePlots = TRUE
and
defaults to the temporary directory of the current R session, i.e. tempdir()
. To save plots to the current
working directory set savePlots = TRUE
and image_directory = getwd()
.
The density plots of each category of target
against each ssv
are written as
.png file into the current working directory. Also, a data frame with the following
columns is output
Causes |
The ssv that were analysed. |
outliers_removed |
How many outliers (with respect to this ssv )
have been removed before drawing the plot? |
observations_retained |
After outlier removal was performed, how many observations were left and used to fit the model? |
Frequency plots for each ssv
against each category of the target
are produced and
svaed to current working directory. Also a data frame with summary statistics is produced,
see Value for details.
# NOT RUN {
categorical.freqplot(mtcars, target = "cyl")
# }
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