Function reference • ExPanDaR

ExPanD app

Shiny-based app for interactive exploratory data analysis

ExPanD(): Explore Your Data (ExPanD)

Workflow functions

Functions, mostly also used by ExPanD, that facilitate a typical exploratory data analysis workflow

prepare_missing_values_graph(): Prepares a Graph Displaying Missing Values in Panel Data

treat_outliers(): Treats Outliers in Numerical Data

prepare_descriptive_table(): Prepares a Table of Descriptive Statistics

prepare_ext_obs_table(): Prepares a Table Displaying Extreme Observations

prepare_by_group_bar_graph(): Prepares a by Group Bar Graph

prepare_by_group_trend_graph(): Prepares a By Group Trend Graph

prepare_by_group_violin_graph(): Prepares a by Group Violin Graph

prepare_trend_graph(): Prepares a Trend Graph

prepare_quantile_trend_graph(): Prepares a Quantile Trend Graph

prepare_correlation_table(): Prepares a Correlation Table

prepare_correlation_graph(): Prepares a Correlation Graph

prepare_scatter_plot(): Prepares a Scatter Plot

prepare_regression_table(): Prepares a Regression Table

Data

Data set used to showcase the functionality of ExPanD. ‘russell_3000’ is a set of financial accounting and stock return data for a sample of U.S. firms that are members of the Russell 3000 index. ‘worldbank’ is a country year panel of macro-economic data provided by the World Bank API.

russell_3000: Annual Financial Accounting and Stock Return Data for a Sample of Russell 3000 Firms (2013-2016)

russell_3000_data_def: Data Definitions for russell_3000 Data Set

ExPanD_config_russell_3000: Default Configuration to use with ExPanD and the Russell 3000 Data Set

worldbank: A Snapshot of Macroeconomic Data as Provided by the World Bank API (1960 - 2018)

worldbank_data_def: Data Definitions for worldbank Data Set

worldbank_var_def: Variable Definitions to Construct an Analysis Sample Based on the worldbank Data Set

ExPanD_config_worldbank: Default Configuration to Use with ExPanD and the worldbank Data Set