Package: SmartEDA 0.3.10

SmartEDA: Summarize and Explore the Data

Exploratory analysis on any input data describing the structure and the relationships present in the data. The package automatically select the variable and does related descriptive statistics. Analyzing information value, weight of evidence, custom tables, summary statistics, graphical techniques will be performed for both numeric and categorical predictors.

Authors:Dayanand Ubrangala [aut, cre], Kiran R [aut, ctb], Ravi Prasad Kondapalli [aut, ctb], Sayan Putatunda [aut, ctb]

SmartEDA_0.3.10.tar.gz
SmartEDA_0.3.10.zip(r-4.7)SmartEDA_0.3.10.zip(r-4.6)SmartEDA_0.3.10.zip(r-4.5)
SmartEDA_0.3.10.tgz(r-4.6-any)SmartEDA_0.3.10.tgz(r-4.5-any)
SmartEDA_0.3.10.tar.gz(r-4.7-any)SmartEDA_0.3.10.tar.gz(r-4.6-any)
SmartEDA_0.3.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
SmartEDA/json (API)

# Install 'SmartEDA' in R:
install.packages('SmartEDA', repos = c('https://daya6489.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/daya6489/smarteda/issues

Pkgdown/docs site:https://daya6489.github.io

On CRAN:

Conda:

analysisexploratory-data-analysis

7.20 score 44 stars 239 scripts 752 downloads 17 exports 69 dependencies

Last updated from:c823b69e2d. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE177
source / vignettesOK244
linux-release-x86_64NOTE183
macos-release-arm64NOTE140
macos-oldrel-arm64NOTE154
windows-develNOTE148
windows-releaseNOTE126
windows-oldrelNOTE113
wasm-releaseOK161

Exports:ExpCatStatExpCatVizExpCTableExpCustomStatExpDataExpInfoValueExpKurtosisExpNumStatExpNumVizExpOutliersExpOutQQExpParcoordExpReportExpSkewExpStatExpTwoPlotsExpWoeTable

Dependencies:askpassbase64encbslibcachemclicpp11crayoncurldata.tabledigestdplyrevaluatefarverfastmapfontawesomeforcatsfsgenericsGGallyggplot2ggstatsgluegridExtragtablehighrhmshtmltoolsISLRisobandjquerylibjsonliteknitrlabelinglifecyclelpSolvemagrittrMASSmemoisemimepatchworkpillarpkgconfigprettyunitsprogresspurrrqpdfR6rappdirsRColorBrewerRcpprlangrmarkdownS7samplingsassscalesstringistringrsystibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Summarize and Explore the Data
1. Introduction | Journal of Open Source Software Article | 2. Data | 2.1 Overview of the data | 2.2 Add summary statistics into Metadata ouput | 3. Exploratory data analysis (EDA) | 3.1 Example for case 1: Target variable is not defined | 3.1.1 Summary of numerical variables | Compute Weighted Summary Statistics for numerical variable | 3.1.2 Distributions of numerical variables | 3.1.3. Summary of categorical variables | 3.1.4. Distributions of categorical variables | 3.2 Example for case 2: Target variable is continuous | 3.2.1. Target variable | 3.2.2 Summary of numerical variables | 3.2.3 Distributions of numerical variables | 3.2.4. Summary of categorical variables | Compute Weighted Summary Statistics for categorical variable | 3.3 Example for case 3: Target variable is categorical | 3.3.1. Summary of categorical dependent variable | 3.3.2 Summary of numerical variables | 3.3.3 Distributions of Numerical variables | 3.3.4 Summary of categorical variables | 3.3.5. Distributions of categorical variables | 4. Quantile-quantile plot for numeric variables | 5. Parallel Co-ordinate plots | 5.1 Defualt ExpParcoord funciton | 5.2 With Stratified rows and selected columns only | 5.3 Without stratification | 5.4 Scale change | 5.5 Selected numeric variables | 5.6 Selected categorical variables | 6. Customized Summary Statistics | 7. Univariate outlier analysis | 7.1 Identifying outliers using Boxplot method | 7.2 Identifying outliers using 3 Standard Deviation method

Last update: 2024-01-30
Started: 2019-05-04

Two independent plots side by side for the same variable
SamrtEDA function to visualise two independ plots side by side for the same variable | 1. Plot Numerical independent variables - without target variable | 1.1 Left side Boxplot and Right side Histogram | 1.2 Left side Histogram and Right side Density | 1.3 Left side Density and Right side Boxplot | 1.4 Left side qqplot and Right side Boxplot | 2. Plot Numerical independent variables - with target variable | 2.1 Left side Boxplot and Right side Histogram | 2.2 Left side Histogram and Right side Density | 2.3 Left side Density and Right side Boxplot | 2.4 Left side qqplot and Right side Density | 2.5 Left side Boxplot and Right side qqplot | 3. Plot categorical independent variables - without target variable | 3.1 Left side donut chart and Right side bar chart | 3.2 Left side donut chart and Right side Pie chart | 3.3 Left side horizontal bar chart and Right side Pie chart | 4. Plot categorical independent variables - with target variable | 4.1 Left side donut chart and Right side stacked bar chart | 4.2 Left side donut chart and Right side horizontal stacked bar chart

Last update: 2021-06-22
Started: 2021-06-22

Custom table summarizing outcomes
1. Exploratory analysis - Custom tables, summary statistics | 1.1 Usage of ExpCustomStat function | 2. Categorical summaries | 2.1. Frequency table | 2.2. Crosstabulation (more than one categorical variable) | 2.3. Adding filters to tables | 3. Numerical summaries | 3.1. Numerical variable summary | 3.2. Adding filters to complete data (like base subset) | 3.3. Filter out unique value from all the numeric variables | 3.4. Adding filters at variable level | 4. Numerical summaries by category | 4.1. Variable summary report (One group variable) | 4.2. Variable summary report (More than One group variable) | 4.3. Variable summary report (More than One group variable) with filter | 5. Resahpe data | Example scripts | References

Last update: 2019-08-06
Started: 2019-05-04