View source: R/Table-print-function.R
BSkySummaryStats | R Documentation |
Outputs the following numerical statistics: min, max, mean, median, sum, sd, stderror, iqr, quartiles. If quartiles is selected, you can specify the comma separated quartiles needed. In addition to these, the user can pass, a list of comma separated statistical function names for example var.
BSkySummaryStats(
data = NULL,
datasetColumnObjects = list(),
groupByColumnObjects = list(),
datasetName = c(),
stats = c(min = TRUE, max = TRUE, mean = TRUE, median = TRUE, quantiles = TRUE),
quantilesProbs = c(0, 0.25, 0.5, 0.75, 1),
additionalStats = c(),
maxsum = 30,
bSkyFormatAppRequest = FALSE,
ftable_change_variable_order = TRUE,
sublist_length = 3,
remove_rows_with_zero_count = FALSE,
no_row_column_headers = FALSE
)
datasetColumnObjects: |
selected scale variables (say Dataset$var1, Dataset$var2) |
groupByColumnObjects: |
one or more factor variables to group by (say Dataset$var3, Dataset$var4) |
statFunctionList: |
List of functions. The ones set to TRUE will be executed. (say min=TRUE, sd=TRUE) |
quantilesProbs: |
Probabilities of the quantiles |
additionalStats: |
Addition statistical function that user can pass ( say var) |
datasetName: |
Name of the dataset from which datasetColumnObjects and groupByColumnObjects are chosen |
An object of class "data.frame", giving the results for each function on each variable.
Dataset <- data.frame(Expenses=c(20,23,19,25,26), Sales=c(48,50,55,51,49), Gender=c('m','f','f','m','m'), Deptt=c('IT', 'Sales', 'IT','Sales','IT'), stringsAsFactors = TRUE)
Result_Numerical_Statistics_Analysis = BSkySummaryStats(datasetColumnObjects = list(Sales = Dataset$Sales, Expenses = Dataset$Expenses), groupByColumnObjects = list(Deptt= Dataset$Deptt), stats = c(min=FALSE,max=FALSE,mean=TRUE,median=TRUE,sum=FALSE,sd=FALSE,stderror=FALSE,iqr=FALSE,quantiles=FALSE),datasetName="Dataset" )
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