Two independent plots side by side for the same variable
SamrtEDA function to visualise two independ plots side by side for the same variable
In exploratory data analysis, it is common to want to make two
different plots for same variables. For example, a survey data may have
a large number of questions like age, gender, region etc. It includes
several categorical and numerical features. Suppose a analyst want to
see age variable distributions with gender and without gender in side by
side view. There is no direct functions available in any of the
statistical packages. Here is a way to achieve the same thing using R
using ggplot2 customized function ExpTwoPlots
Function definition:
ExpTwoPlots(
data,
plot_type = "numeric",
iv_variables = NULL,
target = NULL,
lp_geom_type = "boxplot",
lp_arg_list = list(),
rp_geom_type = "boxplot",
rp_arg_list = list(),
fname = NULL,
page = NULL,
theme = "Default"
)1. Plot Numerical independent variables - without target variable
Different use cases
target = "gear"
categorical_features <- c("vs", "carb") # we can add as many categorical variables
numeircal_features <- c("mpg", "qsec") # we can add as many numerical variables1.1 Left side Boxplot and Right side Histogram
num_1 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = NULL,
lp_arg_list = list(fill="orange"),
lp_geom_type = 'boxplot',
rp_arg_list = list(alpha=0.5, fill="white", color = "red", binwidth=1),
rp_geom_type = 'histogram',
page = c(2,1),
theme = "Default")
num_1## $`0`
1.2 Left side Histogram and Right side Density
num_2 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = NULL,
lp_arg_list = list(fill = "white",color = "red", binwidth=1),
lp_geom_type = 'histogram',
rp_arg_list = list(alpha=0.5, fill="red"),
rp_geom_type = 'density',
page = c(2,1),
theme = "Default")
num_2## $`0`
1.3 Left side Density and Right side Boxplot
num_3 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = NULL,
lp_arg_list = list(color = "red"),
lp_geom_type = 'density',
rp_arg_list = list(fill="orange"),
rp_geom_type = 'boxplot',
page = c(2,1),
theme = "Default")
num_3## $`0`
1.4 Left side qqplot and Right side Boxplot
num_4 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = NULL,
lp_arg_list = list(fill = "blue"),
lp_geom_type = 'qqplot',
rp_arg_list = list(fill="orange"),
rp_geom_type = 'boxplot',
page = c(2,1),
theme = "Default")
num_4## $`0`
2. Plot Numerical independent variables - with target variable
2.1 Left side Boxplot and Right side Histogram
num_21 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = "gear",
lp_arg_list = list(fill="pink"),
lp_geom_type = 'boxplot',
rp_arg_list = list(alpha=0.5, fill = c("grey", "orange", "lightblue"), binwidth=1),
rp_geom_type = 'histogram',
page = c(2,1),
theme = "Default")
num_21## $`0`
2.2 Left side Histogram and Right side Density
num_22 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = "gear",
lp_arg_list = list(fill = "white",color = "red", binwidth=1),
lp_geom_type = 'histogram',
rp_arg_list = list(alpha=0.5, fill = c("red", "orange", "pink")),
rp_geom_type = 'density',
page = c(2,1),
theme = "Default")
num_22## $`0`
2.3 Left side Density and Right side Boxplot
num_23 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = "gear",
lp_arg_list = list(fill = "grey"),
lp_geom_type = 'density',
rp_arg_list = list(fill = c("blue", "orange", "pink"), alpha=0.5),
rp_geom_type = 'boxplot',
page = c(2,1),
theme = "Default")
num_23## $`0`
2.4 Left side qqplot and Right side Density
num_24 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = "gear",
lp_arg_list = list(fill = "grey"),
lp_geom_type = 'qqplot',
rp_arg_list = list(fill = c("blue", "orange", "pink"), alpha=0.5),
rp_geom_type = 'density',
page = c(2,1),
theme = "Default")
num_24## $`0`
2.5 Left side Boxplot and Right side qqplot
num_25 <- ExpTwoPlots(mtcars,
plot_type = "numeric",
iv_variables = numeircal_features,
target = "gear",
lp_arg_list = list(fill = "orange"),
lp_geom_type = 'boxplot',
rp_arg_list = list(fill = c("blue", "green", "red"), alpha=0.5),
rp_geom_type = 'qqplot',
page = c(2,1),
theme = "Default")
num_25## $`0`
3. Plot categorical independent variables - without target variable
3.1 Left side donut chart and Right side bar chart
cat_1 <- ExpTwoPlots(mtcars,
plot_type = "categorical",
iv_variables = categorical_features,
target = NULL,
lp_arg_list = list(),
lp_geom_type = 'donut',
rp_arg_list = list(stat = 'identity'),
rp_geom_type = 'bar',
page = c(2,1),
theme = "Default")
cat_1## $`0`
3.2 Left side donut chart and Right side Pie chart
cat_2 <- ExpTwoPlots(mtcars,
plot_type = "categorical",
iv_variables = categorical_features,
target = NULL,
lp_arg_list = list(),
lp_geom_type = 'donut',
rp_arg_list = list(),
rp_geom_type = 'pie',
page = c(2,1),
theme = "Default")
cat_2## $`0`
3.3 Left side horizontal bar chart and Right side Pie chart
cat_3 <- ExpTwoPlots(mtcars,
plot_type = "categorical",
iv_variables = categorical_features,
target = NULL,
lp_arg_list = list(stat = 'identity'),
lp_geom_type = 'barh',
rp_arg_list = list(),
rp_geom_type = 'pie',
page = c(2,1),
theme = "Default")
cat_3## $`0`
4. Plot categorical independent variables - with target variable
4.1 Left side donut chart and Right side stacked bar chart
cat_41 <- ExpTwoPlots(mtcars,
plot_type = "categorical",
iv_variables = categorical_features,
target = 'gear',
lp_arg_list = list(),
lp_geom_type = 'donut',
rp_arg_list = list(stat = 'identity'),
rp_geom_type = 'bar',
page = c(2,1),
theme = "Default")
cat_41## $`0`
4.2 Left side donut chart and Right side horizontal stacked bar chart
cat_42 <- ExpTwoPlots(mtcars,
plot_type = "categorical",
iv_variables = categorical_features,
target = 'gear',
lp_arg_list = list(),
lp_geom_type = 'pie',
rp_arg_list = list(stat = 'identity'),
rp_geom_type = 'barh',
page = c(2,1),
theme = "Default")
cat_42## $`0`
- SamrtEDA function to visualise two independ plots side by side for the same variable
- 1. Plot Numerical independent variables - without target variable
- 2. Plot Numerical independent variables - with target variable
- 3. Plot categorical independent variables - without target variable
- 4. Plot categorical independent variables - with target variable