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https://github.com/muhendis/data2gRaph

The data2gRaph project is a web-based data visualization tool that can also be used off-line.
https://github.com/muhendis/data2gRaph

bioconductor corrplot dt ggextra ggfortify ggplot ggplot2 r shiny shinyapps shinycssloaders shinydashboard

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The data2gRaph project is a web-based data visualization tool that can also be used off-line.

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# data2gRaph

Visualization is of great importance for data science and machine learning. Because it allows you to become aware of unnoticed details.

The data2gRaph project is a web-based data visualization tool that can also be used off-line. It consists of 3 parts:

> The first section visualizes statistical information.

> The second section visualizes using machine learning information.

> The third section visualizes create a mix plot using different plots.

#### [click to screenshots](https://github.com/muhendis/data2gRaph/tree/master/Example%20graph)

## Content of the the application

##### About

##### Input Data

##### Statistical Plots

Measures of Central Tendency

Measures of Dispersion

Covariance Matrix

Correlation Analyses

##### Unsupervised ML Plots

Principal Component Analysis

K-means Clustering

Hierarchical Clustering



##### Mix Plots

Scatter+Rug+Hist

Density+Densigram

Hexagonal+Boxplot

Complex Heatmap

## Installation steps
1. Download this pogram where you want to run it, [click to download](https://github.com/muhendis/data2gRaph/archive/master.zip)

2. Run the file named Packages_to_be_installed.R once for the required packages.

```
../data2gRaph/Packages_to_be_installed.R

```

## Running step

Run the file named app.R.

```
../data2gRaph/app.R
```

## Information about R, OS and attached or installed packages

```{R}
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.04.3 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so

locale:
[1] LC_CTYPE=tr_TR.UTF-8 LC_NUMERIC=C LC_TIME=tr_TR.UTF-8 LC_COLLATE=tr_TR.UTF-8 LC_MONETARY=tr_TR.UTF-8
[6] LC_MESSAGES=tr_TR.UTF-8 LC_PAPER=tr_TR.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=tr_TR.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] grid stats graphics grDevices utils datasets methods base

other attached packages:
[1] hexbin_1.28.0 ComplexHeatmap_2.2.0 ggExtra_0.9 ggpubr_0.2.4 magrittr_1.5 ggfortify_0.4.8
[7] viridis_0.5.1 viridisLite_0.3.0 reshape2_1.4.3 ggthemes_4.2.0 ggplot2_3.2.1 RColorBrewer_1.1-2
[13] corrplot_0.84 shinycssloaders_0.2.0 DT_0.10 shinydashboard_0.7.1 shiny_1.4.0

loaded via a namespace (and not attached):
[1] shape_1.4.4 circlize_0.4.8 GetoptLong_0.1.7 tidyselect_0.2.5 purrr_0.3.3 lattice_0.20-38
[7] colorspace_1.4-1 vctrs_0.2.0 miniUI_0.1.1.1 htmltools_0.4.0 rlang_0.4.1 later_1.0.0
[13] pillar_1.4.2 glue_1.3.1 withr_2.1.2 lifecycle_0.1.0 plyr_1.8.4 stringr_1.4.0
[19] munsell_0.5.0 ggsignif_0.6.0 gtable_0.3.0 htmlwidgets_1.5.1 GlobalOptions_0.1.1 fastmap_1.0.1
[25] httpuv_1.5.2 parallel_3.6.1 Rcpp_1.0.3 xtable_1.8-4 promises_1.1.0 scales_1.1.0
[31] backports_1.1.5 mime_0.7 gridExtra_2.3 rjson_0.2.20 png_0.1-7 digest_0.6.23
[37] stringi_1.4.3 dplyr_0.8.3 clue_0.3-57 tools_3.6.1 lazyeval_0.2.2 tibble_2.1.3
[43] cluster_2.1.0 crayon_1.3.4 tidyr_1.0.0 pkgconfig_2.0.3 zeallot_0.1.0 assertthat_0.2.1
[49] rstudioapi_0.10 R6_2.4.1 compiler_3.6.1
```

## Several screenshots of the application