[![metacran downloads](https://cranlogs.r-pkg.org/badges/grand-total/funModeling)](https://cran.r-project.org/package=funModeling)
[![metacran downloads](https://cranlogs.r-pkg.org/badges/funModeling)](https://cran.r-project.org/package=funModeling)
# Hello!
This package contains a set of functions related to exploratory data analysis, data preparation, and model performance. It is used by people coming from business, research, and teaching (professors and students).
<img src="https://datascienceheroes.com/img/blog/funModeling_cover.png" alt="funModeling" width="400px"/>
<img src="https://s3.amazonaws.com/datascienceheroes.com/img/blog/funModeling_logo_hq.png" alt="funModeling" width="300px"/>
## Books
`funModeling` is intimately related to the _Data Science Live Book_ -Open Source- (2017) in the sense that most of its functionality is used to explain different topics addressed by the book.
<img src="https://livebook.datascienceheroes.com/introduction/data-science-live-book.png" alt="Data Science Live Book" width="300px"/>
Versions:
* EN: [Data Science Live Book](https://livebook.datascienceheroes.com/)
* ES: [Libro Vivo de Ciencia de Datos](https://librovivodecienciadedatos.ai)
In the _Download_ section, you can buy (name your price) a digital copy of the book in PDF, mobi and pub.
## Blog posts based on `funModeling`:
* [Exploratory Data Analysis in R (introduction)](https://blog.datascienceheroes.com/exploratory-data-analysis-in-r-intro/)
* [Automatic data types checking in predictive models](https://blog.datascienceheroes.com/automatic-data-types-checking-in-predictive-models/)
* [Fast data exploration for predictive modeling](https://blog.datascienceheroes.com/fast-data-exploration-for-predictive-modeling/)
* [New discretization method: Recursive information gain ratio maximization](https://blog.datascienceheroes.com/discretization-recursive-gain-ratio-maximization/)
## Official page
* [funModeling official webpage](http://pablo14.github.io/funModeling/)
* Check the vignette [here](http://pablo14.github.io/funModeling/articles/funModeling_quickstart.html).
## If you speak Spanish...
<img src="https://s3.amazonaws.com/datascienceheroes.com/img/blog/Logo_Datos_Vivos.png" alt="Escuela de Datos Vivos" width="250px"/>
You are invited to the [Escuela de Datos Vivos](https://escueladedatosvivos.ai/), a data school founded by the same funModeling / DSLB author. There you can find free and paid courses, blog post, youtube channel, using R and Python.
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R包:funModeling:数据清理、重要性变量分析和模型性能___下载.zip
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R包:funModeling:数据清理、重要性变量分析和模型性能___下载.zip (180个子文件)
docsearch.css 11KB
pkgdown.css 5KB
DESCRIPTION 1KB
.gitignore 119B
README.html 1.69MB
funModeling_quickstart.html 608KB
funModeling_quickstart.html 48KB
compare_df.html 18KB
prep_outliers.html 16KB
categ_analysis.html 14KB
index.html 13KB
data_integrity.html 11KB
desc_groups.html 10KB
index.html 9KB
gain_lift.html 9KB
profiling_num.html 9KB
cross_plot.html 9KB
discretize_df.html 9KB
discretize_get_bins.html 9KB
desc_groups_rank.html 9KB
status.html 9KB
auto_grouping.html 8KB
freq.html 8KB
coord_plot.html 8KB
df_status.html 8KB
equal_freq.html 8KB
convert_df_to_categoric.html 8KB
discretize_rgr.html 8KB
plotar.html 8KB
hampel_outlier.html 7KB
v_compare.html 7KB
data_integrity_model.html 7KB
get_sample.html 7KB
concatenate_n_vars.html 7KB
correlation_table.html 7KB
plot_num.html 7KB
tukey_outlier.html 7KB
infor_magic.html 7KB
entropy_2.html 7KB
var_rank_info.html 7KB
funModeling-package.html 6KB
information_gain.html 6KB
gain_ratio.html 6KB
fibonacci.html 6KB
range01.html 6KB
export_plot.html 6KB
data_country.html 6KB
LICENSE.html 6KB
heart_disease.html 6KB
data_golf.html 5KB
metadata_models.html 5KB
index.html 5KB
authors.html 5KB
404.html 5KB
pkgdown.js 3KB
docsearch.js 2KB
README.md 2KB
LICENSE.md 1KB
NAMESPACE 2KB
cluster_performance-1.png 129KB
profiling1-1.png 126KB
README-profiling1-1.png 126KB
profiling1-2.png 122KB
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performance-1.png 102KB
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unnamed-chunk-4-1.png 82KB
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density_histogram-1.png 75KB
freq-3.png 53KB
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README-profiling1-1.png 52KB
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freq-1.png 52KB
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distribution1-1.png 46KB
distribution1-2.png 45KB
README-performance-1.png 45KB
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README-distribution1-1.png 39KB
README-unnamed-chunk-3-1.png 38KB
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discre1.png 34KB
discre1.png 34KB
boxplot_analysis-1.png 30KB
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README-distribution1-1.png 16KB
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