| Type: | Package |
| Title: | Data Insights Through Inbuilt R Shiny App |
| Version: | 0.4.2 |
| Description: | It builds dynamic R shiny based dashboards to analyze any CSV files. It provides simple dashboard design to subset the data, perform exploratory data analysis and preliminary machine learning (supervised and unsupervised). It also provides filters based on columns of interest. |
| Depends: | R (≥ 3.5.0), |
| Imports: | dplyr, shiny, shinydashboard, tm, wordcloud, corrplot, randomForest, RColorBrewer, caret, nnet, plotly |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| Config/testthat/edition: | 3 |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| NeedsCompilation: | no |
| Packaged: | 2025-02-03 14:15:51 UTC; RPUSH1 |
| Author: | Jayachandra N [aut, cre], Pushker Ravindra [aut] |
| Maintainer: | Jayachandra N <itsjay510@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-02-03 19:30:02 UTC |
Conf Matrix
Description
Calculates a cross-tabulation of observed and predicted classes with associated statistics.
Usage
confmatrix(actuals, preds)
Arguments
actuals |
a numeric vector |
preds |
a numeric vector |
Details
confmatrix
Value
A table same as caret::ConfusionMatrix
Author(s)
Jayachandra N
Examples
confmatrix(c(1,1,1,0), c(1,1,0,0))
Data Partition
Description
Partition data for training and test
Usage
dataPartition(df, train_data_perc)
Arguments
df |
data.frame which need to be devided into train and test subset |
train_data_perc |
numeric value between 1 to 100 |
Details
dataPartition
Value
list of length 2 which contains Train data and Test data
Author(s)
Jayachandra N
Examples
dataPartition(iris, 80)
Detect Class
Description
Detects class of given objects
Usage
detectClass(x)
Arguments
x |
a vector |
Details
detectClass
Value
type of the vector
Author(s)
Jayachandra N
Examples
detectClass(c(1,2,3))
detectClass(c("a","b"))
detectClass(iris$Species)
Exclude These
Description
Exclude an item from a set of items
Usage
excludeThese(set, items_to_exclude)
Arguments
set |
vector |
items_to_exclude |
vector to exclude from the whole set |
Details
excludeThese
Value
vector
Author(s)
Jayachandra N
Examples
excludeThese(1:10, 1)
Get Coefficients
Description
Get coefficients from the model summary
Usage
getCoefficients(model)
Arguments
model |
lm model |
Details
getCoefficients
Value
data.frame of coeffcients
Author(s)
Jayachandra N
Examples
model <- lm(Sepal.Length ~ ., iris) # A linear regression model
getCoefficients(model)
get Data Insights
Description
Get detailed insights about the data like number of rows, columns and some basic statistics such as mean
Usage
getDataInsight(temp)
Arguments
temp |
data frame |
Details
getDataInsight
Value
list of details of data
Author(s)
Jayachandra N
Examples
getDataInsight(mtcars)
getDataInsight(iris)
Get Freq Table
Description
Get frequency table for a given text
Usage
getFeqTable(text)
Arguments
text |
plain text or a paragraph |
Details
getFeqTable
Value
data frame of word and it's frequency.
Author(s)
Jayachandra N
Examples
getFeqTable("shinyr is Incredible!")
Get Library Report
Description
Get report on whether the given packages are installed on not
Usage
getLibraryReport(packages)
Arguments
packages |
Vector of package names |
Details
getLibraryReport
Value
data.frame, status of required packages and their installation status
Author(s)
Jayachandra N
Examples
getLibraryReport(c('dplyr', 'data.table'))
Get Most Repeated Value
Description
get most repeated value in a given vector.
Usage
getMostRepeatedValue(vec)
Arguments
vec |
Vector to calculate most repeated values |
Details
getMostRepeatedValue
Value
most repeated values in the given set of values
Author(s)
Jayachandra N
Examples
getMostRepeatedValue(c(1,2,3,3,3,2))
getMostRepeatedValue(c("R", "R", "Python", "Python", "R"))
Get Type
Description
getType
Usage
getType(vec)
Arguments
vec |
A vector of any choice, to detect between numeric or character |
Value
type of the given vector
Author(s)
Jayachandra N
Examples
getType(iris$Species)
getType(as.factor(c(1,0,1,1,0,NA,1, NULL)))
getType(as.factor(c(1, NULL,0,1,1,0,1,'a')))
getType(c(1,2,3,4, NA))
getType(letters[1:4])
getTypeOfColumns
Description
getTypeOfColumns
Usage
getTypeOfColumns(df)
Arguments
df |
data frame |
Value
Data frame of column name and it's type
Author(s)
Jayachandra N
Examples
getTypeOfColumns(mtcars)
getTypeOfColumns(iris)
Get Word Cloud
Description
Get word cloud for given table of words' frequencies
Usage
getWordCloud(d)
Arguments
d |
table of word's frequency |
Details
getWordCloud
Value
Word cloud plot
Examples
x <- getFeqTable("Hello! R is Great")
getWordCloud(x)
Get Character Cols
Description
Get character columns.
Usage
getcharacterCols(dat)
Arguments
dat |
data frame |
Details
getcharacterCols
Value
A Character vector of names of numeric columns of a given data frame
Author(s)
Jayachandra N
Examples
getcharacterCols(iris)
getcharacterCols(mtcars)
Get Numeric Cols
Description
Get all columns which are numeric.
Usage
getnumericCols(dat)
Arguments
dat |
data frame |
Details
getnumericCols
Value
Character vector of names of numeric columns of given data frame
Author(s)
Jayachandra N
Examples
getnumericCols(iris)
getnumericCols(mtcars)
Group By And Summarize
Description
Group by columns and summarize given data.
Usage
groupByandSumarize(df, grp_col, summarise_col, FUN = mean)
Arguments
df |
data frame |
grp_col |
column name to group |
summarise_col |
column name to summarize |
FUN |
function to summarize |
Details
groupByandSumarize
Value
summarized table
Author(s)
Jayachandra N
Examples
groupByandSumarize(mtcars, grp_col = c("am"), summarise_col = "hp",
FUN = "mean")
Impute My Data
Description
Impute for missing values in given column in a given data by given method.
Usage
imputeMyData(df, col, FUN)
Arguments
df |
data frame to impute |
col |
a column name of data frame to impute |
FUN |
a function to be used for imputing values one of(mean, median, sum, min, max) |
Details
imputeMyData
Value
data frame after imputing the values
Author(s)
Jayachandra N
Examples
x <- head(iris)
x$Sepal.Length[1] <- NA
imputeMyData(x, "Sepal.Length", "mean")
Make Var
Description
Make a variable from a given character vector.
Usage
make_var(prefix, var, suffix)
Arguments
prefix |
prefix character |
var |
character to convert |
suffix |
suffix character |
Details
make_var
Value
variable
Author(s)
Jayachandra N
Examples
make_var("", "Jay", "")
make_var("", "Incredible_India", "")
Missing Count
Description
Count the number of missing values in a vector.
Usage
missing_count(x)
Arguments
x |
vector |
Details
missing_count
Value
Number of missing values in the given set of values
Author(s)
Jayachandra N
Examples
missing_count(c(1,2,3))
missing_count(c(NA, 1, NA, "NULL", ""))
Multinomial
Description
Fit Multinomial Log-linear Models.
Usage
multinomial(eqn, df)
Arguments
eqn |
formula to build model |
df |
data frame |
Details
multinomial
Value
model
Author(s)
Jayachandra N
Examples
multinomial( Species ~ ., iris)
Plot Cor
Description
Plot correlation plot
Usage
plotCor(cor_dat, my_method)
Arguments
cor_dat |
Corelation matrix |
my_method |
method to plot, for example: circle |
Details
plotCor
Value
Corelation plot
Author(s)
Jayachandra N
Examples
cor_dat <- cor(mtcars)
plotCor(cor_dat, "circle")
Random Forest Model
Description
Build Random Forest Model.
Usage
randomForestModel(eqn, df)
Arguments
eqn |
formula |
df |
data.frame |
Details
randoMForestModel
Value
rf model
Author(s)
Jayachandra N
Examples
randomForestModel( Species ~ ., iris)
Regression Model Metrics
Description
Generate regression model metrics such as R-squared and MAPE.
Usage
regressionModelMetrics(actuals, predictions, model)
Arguments
actuals |
numeric vector of actual values |
predictions |
numeric vector of predictions |
model |
lm model object |
Details
regressionModelMetrics
Value
list
Author(s)
Jayachandra N
Examples
mod <- lm(formula = wt ~ ., data = mtcars)
predictions <- predict(mod, mtcars[,-6])
actuals <- mtcars[,6]
regressionModelMetrics(actuals = actuals,
predictions = predictions, model = mod)
shineMe
Description
An R shiny app for shinyr UI.
Usage
shineMe()
Details
shineMe
Value
shiny UI page
Author(s)
Jayachandra N
Examples
shineMe()
Split And Get
Description
Split a string by space and get
Usage
splitAndGet(x)
Arguments
x |
string to split into words |
Details
splitAndGet
Value
List of worrds
Author(s)
Jayachandra N
Examples
splitAndGet("R programming is awesome!")
Valid Sets
Description
Get a list of all datasets available as data.frame in R
Usage
valid_sets(package = NULL, cols = NULL)
Arguments
package |
package name to fetch inbuilt data sets example: "datasets" |
cols |
numeric to specify condition on how many columns should data frame have |
Details
valid_sets
Value
data frame all available datasets of class data frame
Author(s)
Pushker Ravindra
Jayachandra N
Examples
valid_sets()