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expss (version 0.8.6)

Tables with Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics

Description

Package provides tabulation functions with support for 'SPSS'-style labels, multiple / nested banners, weights, multiple-response variables and significance testing. There are facilities for nice output of tables in 'knitr', R notebooks, 'Shiny' and 'Jupyter' notebooks. Proper methods for labelled variables add value labels support to base R functions and to some functions from other packages. Additionally, the package offers useful functions for data processing in marketing research / social surveys - popular data transformation functions from 'SPSS' Statistics ('RECODE', 'COUNT', 'COMPUTE', 'DO IF', etc.) and 'Excel' ('COUNTIF', 'VLOOKUP', etc.). Package is intended to help people to move data processing from 'Excel'/'SPSS' to R.

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Version

Install

install.packages('expss')

Monthly Downloads

9,257

Version

0.8.6

License

GPL (>= 2)

Maintainer

Gregory Demin

Last Published

January 24th, 2018

Functions in expss (0.8.6)

compare_proportions

Calculate significance (p-values) of differences between proportions/means

Count/sum/average/other functions on values that meet a criterion

Convert dichotomy data.frame/matrix to data.frame with category encoding

as.datatable_widget

Create an HTML table widget for usage with Shiny

Recode vector into numeric vector with value labels

Aggregate dataset by grouping variable(s).

Convert variable (possibly multiple choice question) to data.frame/matrix of dummy variables.

Convert data.frame/matrix to object of class 'etable'

Add rows to data.frame/matrix/table

Set variable labels/value labels on variables in the data.frame

Experimental functions for operations with default dataset

expss: Tables with Labels and Some Useful Functions from Spreadsheets and SPSS Statistics

Repeats the same transformations on a specified set of variables/values

drop_empty_rows

Drop empty (with all NA's) rows/columns from data.frame/table

Options for contolling behaviour of the package

Convert labelled variable to factor

htmlTable.etable

Outputting HTML tables in RStudio viewer/R Notebooks

Replace NA values in vector/data.frame/matrix/list with supplied value

Read an SPSS Data File

Objects exported from other packages

Criteria functions

Cross tabulation with support of labels, weights and multiple response variables.

Change, rearrange or consolidate the values of an existing/new variable. Inspired by RECODE command from SPSS.

Provides variables description for dataset

Compute proportions from numeric vector/matrix/data.frame

Create vector of characters from unquoted strings (variable names)

Keep or drop elements by name/criteria in data.frame/matrix

Match finds value in rows or columns/index returns value by index from rows or columns

Auxiliary functions to pass arguments to function by reference

Compute sum/mean/sd/median/max/min/custom function on rows/columns

Partially (inside blocks) sort tables/data.frames

Make data.frame without conversion to factors and without fixing names

Infix operations on vectors - append, diff, intersection, union, replication

Look up values in dictionary.

Create multiple response set/multiple dichotomy set from variables

Replace certain values with NA

Set or get variable label

Get variables/range of variables by name/by pattern.

Merge two tables/data.frames

Modify data.frame/modify subset of the data.frame

Replace data.frame/list names with corresponding variables labels.

Functions for custom tables construction

Drop variable label and value labels

Compute various weighted statistics

Subset (filter) data.frames/matrices/vectors/lists

Compute nested variable(-s) from several variables

tab_significance_options

Mark significant differences between columns of the table

Sort data.frames/matrices/vectors

Function over grouping variables (window function)

Write data with labels to file in R code or in SPSS syntax.

Cross-tabulation with custom summary function.

default_dataset

Get or set reference to default dataset. Experimental feature.

Simple frequencies with support of labels, weights and multiple response variables.

Make data.frame from text

Prepend values/variable names to value/variable labels

Data from product test of chocolate confectionary

Split character vector to matrix/split columns in data.frame

Splits data.frame into list of data.frames that can be analyzed separately

Set or get value labels

Replace vector/matrix/data.frame/list values with corresponding value labels.