Less Code with More Comprehensive Results
Print a Correlation Matrix with Special Formatting
Proportionality Coefficients from Correlations
Read Specified Correlation Matrix
Create a Sequence of Numbered Variable Names with a Common Prefix and ...
Text Processing: Insert and Into a List
Text Processing: Convert a Number to a Word
Text Processing: Print Formatted Numbers
Text Processing: Add the Word Row to Case Labels that Could be Numeric
Text Processing: Capitalize First Letter of a Word
Text Processing: Wrap Words to Create New Lines From a Specified Line
Scatterplots including Time Series
Exploratory Factor Analysis and Multiple Indicator Measurement Model
Merge Two Data Frames Horizontally or Vertically
Analysis of Variance
Charts for One or Two Categorical Variables
Confirmatory Factor Analysis of a Multiple Indicator Measurement Model
Reflect Specified Variables in a Correlation Matrix
Correlation Analysis
Reorder Variables in a Correlation Matrix
Eigenvalue Plot of a Correlation Matrix
CountAll Descriptive Analysis of all Variables in the Data Frame
Display Contents of a Data File and Optional Variable Labels
Function . for Selecting Rows/Columns with base R Extract
Regression Analysis, ANOVA or t-test
Nest the Values of an Integer or Factor Variable
Create Factor Variables Across a Sequential Range or Vector of Variabl...
Sankey Flow Diagram (2- or 3-Stage) with Plotly
Hue, Chroma, Luminance (HCL) Color Wheel or Specified Colors
Run Interactive Shiny Data Visualizations
Kurtosis
Assign Variable Labels [Superseded by VariableLabels]
Logit Regression Analysis
order_by the Rows of a Data Frame
Create a Pivot (Summary) Table
Display a Portion of Output from a Saved List Object
Display All Text Output from a Saved List Object
Compute and Plot Normal Curve Probabilities over an Interval
Plot t-distribution Curve and Specified Cutoffs with Normal Curve
Plot a Normal Curve with Shaded Intervals by Standard Deviation
Analysis of Prop_test
Read Contents of a Data File with Optional Variable Labels and Feedbac...
Recode the Values of an Integer or Factor Variable
regPlot Analysis
Univariate and Grouped Displays for a Continuous Variable
Regression Analysis
Rename One or More Variables in a Data Frame
Rescale a Variable
Reshape a Wide-Form Data Frame to Long-Form
Pedagogical Binomial Simulation, Coin flips
Reshape a Long-Form Data Frame to Wide-Form
Save the last Plotly chart to a standalone HTML file
View the Upper and Left Corners of a Data Frame
Display All Named R Colors and Corresponding rgb Values
Display Color Palettes
Pedagogical Simulation for the Confidence Interval of the Mean
Pedagogical Simulation for the Central Limit Theorem
Pedagogical Simulation of Sample Means over Repeated Samples
Skew of a variable.
Seasonal and Trend Decomposition of a Time Series via Loess
Set the Default Color Theme and Other System Settings
Subset the Values of One or More Variables
Summary Statistics for One or Two Variables
Write the Contents of a Data Frame to an External File
Create Training and Testing Data
Deprecated: Transform the Values of an Integer or Factor Variable
Generic Method for t-test and Standardized Mean Difference with Enhanc...
Compute a Power Curve for a One or Two Group t-test
List the Values of a Variable
Create or Display Variable Labels
Each function replaces multiple standard R functions. For example, two function calls, Read() and CountAll(), generate summary statistics for all variables in the data frame, plus histograms and bar charts. Other functions provide data aggregation via pivot tables; comprehensive regression, ANOVA, and t-test; visualizations including integrated Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve; reading multiple data formats with the same call; variable labels; time series with aggregation and forecasting; color themes; and Trellis (facet) graphics. Also includes a confirmatory factor analysis of multiple-indicator measurement models, pedagogical routines for data simulation (e.g., Central Limit Theorem), generation and rendering of regression instructions for interpretative output, and both interactive construction of visualizations and interactive visualizations with plotly.