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dlookr (version 0.3.9)

Tools for Data Diagnosis, Exploration, Transformation

Description

A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values and outliers and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and relationship between target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputates missing values and outliers, resolving skewness. And it creates automated reports that support these three tasks.

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Version

Install

install.packages('dlookr')

Monthly Downloads

2,427

Version

0.3.9

License

GPL-2 | file LICENSE

Maintainer

Choonghyun Ryu

Last Published

March 16th, 2019

Functions in dlookr (0.3.9)

diagnose_numeric

Diagnose data quality of numerical variables
diagnose_numeric.tbl_dbi

Diagnose data quality of numerical variables in the DBMS
find_class

Extract variable names or indices of a specific class
plot_normality.tbl_dbi

Plot distribution information of numerical data
plot_outlier

Plot outlier information of numerical data diagnosis
get_os

Finding Users Machine's OS
eda_report.tbl_dbi

Reporting the information of EDA for table of the DBMS
get_column_info

Describe column of table in the DBMS
normality

Performs the Shapiro-Wilk test of normality
diagnose.tbl_dbi

Diagnose data quality of variables in the DBMS
normality.tbl_dbi

Performs the Shapiro-Wilk test of normality
dlookr-package

dlookr: Tools for Data Diagnosis, Exploration, Transformation
diagnose_outlier

Diagnose outlier of numerical variables
diagnose_outlier.tbl_dbi

Diagnose outlier of numerical variables in the DBMS
find_skewness

Finding skewed variables
get_class

Extracting a class of variables
diagnose_report

Reporting the information of data diagnosis
imputate_na

Imputate Missing values
eda_report

Reporting the information of EDA
diagnose_report.tbl_dbi

Reporting the information of data diagnosis for table of the DBMS
plot.bins

Visualize Distribution for an "bins" object
imputate_outlier

Imputate Outliers
find_na

Finding variables including missing values
plot.optimal_bins

Visualize Distribution for an "optimal_bins" Object
plot_normality

Plot distribution information of numerical data
find_outliers

Finding variables including outliers
plot_correlate.tbl_dbi

Visualize correlation plot of numerical data
relate

Relationship between target variable and variable of interest
plot.relate

Visualize Information for an "relate" Object
summary.bins

Summarizing Binned Variable
plot.imputation

Visualize Information for an "imputation" Object
plot_outlier.tbl_dbi

Plot outlier information of numerical data diagnosis in the DBMS
print.relate

Summarizing relate information
transform

Data Transformations
target_by.tbl_dbi

Target by one column in the DBMS
target_by

Target by one variables
transformation_report

Reporting the information of transformation
plot.transform

Visualize Information for an "transform" Object
plot_correlate

Visualize correlation plot of numerical data
summary.imputation

Summarizing imputation information
summary.transform

Summarizing transformation information
describe

Compute descriptive statistic
diagnose_category

Diagnose data quality of categorical variables
describe.tbl_dbi

Compute descriptive statistic
diagnose

Diagnose data quality of variables
diagnose_category.tbl_dbi

Diagnose data quality of categorical variables in the DBMS
correlate

Compute the correlation coefficient between two numerical data
correlate.tbl_dbi

Compute the correlation coefficient between two numerical data
binning

Binning the Numeric Data
binning_by

Optimal Binning for Scoring Modeling