Next steps

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# Next steps
### R for Data Science <a href='https://therbootcamp.github.io'> Basel R Bootcamp </a> <a href='https://therbootcamp.github.io/R4DS_2019Feb/'> </a>  <a href='https://therbootcamp.github.io'> </a>  <a href='mailto:therbootcamp@gmail.com'> </a>  <a href='https://www.linkedin.com/company/basel-r-bootcamp/'> </a>
### February 2019

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 <img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/by-sa.png" height=14 style="vertical-align: middle"/>
 
 <a href="https://therbootcamp.github.io/">
 
 
 www.therbootcamp.com
 
 
 </a>
 <a href="https://therbootcamp.github.io/">
 
 R For Data Science | February 2019
 
 </a>
 
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# Hello Data Scientist!

In 2 days, 6 sessions, and 16 hours you have come a long way.

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<img src="https://therbootcamp.github.io/R4DS_2019Feb/_sessions/Welcome/image/schedule.png" height="580" align="center">
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#  Data Scientist

> *80% of a data scientist’s valuable time is spent simply finding, cleaning, and organizing data, leaving only 20% to actually perform analysis.*

> Harvard Business Review

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<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/data_scientist_activities.jpg" height = 500> 
<a href="https://www.wsj.com">Wall Street Journal</a>

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# Stuff we didn't cover

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1. Networks 
2. Statistics 
3. Machine learning 
4. Text analysis 
5. Rcpp 
6. Forms

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<img src="https://i0.wp.com/www.pieceofk.fr/wp-content/uploads/2017/09/Rplot.png?zoom=2&w=450" width=380 align="center"> 
source <a href="https://www.r-bloggers.com/exploring-the-cran-social-network/">R-bloggers.com</a>

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# Networks

A <high>social graph</high> of package Co-authors using [`tidyverse`](https://cran.r-project.org/web/packages/tidyverse/index.html) plus [`ggraph`](https://cran.r-project.org/web/packages/ggraph/index.html), an extension for [`ggplot2`](https://cran.r-project.org/web/packages/ggplot2/index.html) for graphs (aka networks) and [`igraph`](https://cran.r-project.org/web/packages/igraph/index.html), an extremely powerful library for network analysis. Find the code and additional explanations [here](https://www.r-bloggers.com/exploring-the-cran-social-network/).

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 <img src="https://i1.wp.com/www.pieceofk.fr/wp-content/uploads/2017/09/Rplot04.png?zoom=2&w=450" width=450> 
 source <a href="https://www.r-bloggers.com/exploring-the-cran-social-network/">R-bloggers.com</a>
 ]

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 <img src="https://i1.wp.com/www.pieceofk.fr/wp-content/uploads/2017/09/Rplot02.png?zoom=2&w=450" width=450> 
 source <a href="https://www.r-bloggers.com/exploring-the-cran-social-network/">R-bloggers.com</a>
 ]

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# Stats

> "It's easy to lie with statistics; it is easier to lie without them."

> Frederick Mosteller

| Package| Description| 
|:------|:------------|
| [`stats`](https://www.rdocumentation.org/packages/stats/versions/3.5.1)  | Linear, generalized linear models, individual tests, and distributions.|
| [`lme4`](https://cran.r-project.org/web/packages/lme4/index.html), [`afex`](https://cran.r-project.org/web/packages/afex/index.html)  | Mixed-mode, hierarchical regression.|
| [`sem`](https://cran.r-project.org/web/packages/sem/index.html), [`lavaan`](https://cran.r-project.org/web/packages/lavaan/index.html), [`OpenMx`](https://cran.r-project.org/web/packages/OpenMx/index.html) | Structural equation modeling. |
| [`survival`](https://cran.r-project.org/web/packages/survival/index.html) | Survival analysis. |

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<img src="https://imgs.xkcd.com/comics/p_values_2x.png" height = 500> 
<a href="http://www.xkcd.com/">xkcd.com</a>

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# Bayesian statistics

> The subjectivist (i.e. Bayesian) states his judgements, whereas the objectivist sweeps them under the carpet by calling assumptions knowledge, and he basks in the glorious objectivity of science.

> I. J. Good

| Package| Description| 
|:------|:------------|
| [`BayesFactor`](https://cran.r-project.org/web/packages/BayesFactor/index.html), [`rstanarm`](https://cran.r-project.org/web/packages/rstanarm/index.html)  | Bayesian linear models. As easy as non-Bayesian methods. |
| [`rjags`](https://cran.r-project.org/web/packages/rjags/index.html), [`rstan`](https://cran.r-project.org/web/packages/rstan/index.html)  | Build flexible, hierarchical Bayesian models. |
| [`mcmc`](https://cran.r-project.org/web/packages/mcmc/index.html)| Metropolis algorithms. |
| [`bridgesampling`](https://cran.r-project.org/web/packages/mcmc/index.html)| Estimating marginal likelihoods using bridgesampling. |

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<img src="https://i.stack.imgur.com/tStr4.png" height=500> 
<a href="http://www.xkcd.com/">xkcd.com</a>

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# Machine learning

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| Package| Description| 
|:------|:------------|
| [`caret`](https://cran.r-project.org/web/packages/caret/index.html) | Umbrella package for diverse machine learning algorithms.|
| [`mlr`](https://cran.r-project.org/web/packages/mlr/index.html), [`e1071`](https://cran.r-project.org/web/packages/e1071/index.html), etc. | Other umbrella packages. |
| [`randomForest`](https://cran.r-project.org/web/packages/randomForest/index.html), [`rpart`](https://cran.r-project.org/web/packages/rpart/index.html), [`FFTrees`](https://cran.r-project.org/web/packages/FFTrees/index.html) | Decision trees. |
| [`cluster`](https://cran.r-project.org/web/packages/cluster/index.html), [`fastcluster`](https://cran.r-project.org/web/packages/fastcluster/index.html), [`cstab`](https://cran.r-project.org/web/packages/cstab/index.html), etc.| Cluster analysis.|
| [`forecast`](https://cran.r-project.org/web/packages/forecast/index.html), [`mgm`](https://cran.r-project.org/web/packages/mgm/index.html), [`timeSeries`](https://cran.r-project.org/web/packages/timeSeries/index.html), etc.| Time series models.|
| [`tensorflow`](https://cran.r-project.org/web/packages/tensorflow/index.html) | Deep learning.|

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# Text analysis

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<high>Sundar Pichai @ Google IO, May 2018</high>

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| Package| Description| 
|:------|:------------|
| [`tm`](https://cran.r-project.org/web/packages/tm/index.html), [`tidytext`](https://cran.r-project.org/package=tidytext)  | General text analysis packages  |
| [`stringr`](https://cran.r-project.org/web/packages/stringr/index.html), [`stringi`](https://cran.r-project.org/web/packages/stringi/index.html)  | String operations and regular expressions. |
| [`rvest`](https://cran.r-project.org/web/packages/rvest/index.html), [`XML`](https://cran.r-project.org/web/packages/XML/index.html)  | Scraping content of the internet|
| [`text2vec`](https://cran.r-project.org/web/packages/text2vec/index.html) | Vector representation of words. |
| [`SentimentAnalysis`](https://cran.r-project.org/web/packages/SentimentAnalysis/index.html) | Sentiment analysis.|
| [`twitteR`](https://cran.r-project.org/web/packages/twitteR/index.html), [`streamR`](https://cran.r-project.org/web/packages/streamR/index.html), [`jsonlite`](https://www.google.ch/search?q=cran+jsonlite&rlz=1C5CHFA_enDE745CH747&oq=cran+jsonlite&aqs=chrome.0.0j69i57.3551j0j4&sourceid=chrome&ie=UTF-8) | Streaming and parsing tweets. |
| [`Rfacebook`](https://cran.r-project.org/web/packages/Rfacebook/index.html) | Access to Facebook API. |

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# Rcpp

By now one of the most referenced R packages is Rcpp - <high>R's interface to C++</high>. With often relatively little effort due to <high>Rcpp sugar</high>, Rcpp can provide vast speed improvements, which many packages today rely on Rcpp in the background for <high>swift code execution</high>. Rcpp becomes particularly powerful, when supplemented with `BH`, which makes avaialble a collection <high>free, peer-reviewed C++ libraries</high>, and [RcppArmdillo](http://arma.sourceforge.net/), which available the high-performance <high>Armadillo</high> library for linear algebra methods.

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 <img src="https://classic105.s3.amazonaws.com/wp-content/uploads/2017/05/180207142-sugar.jpg" width=350> 
 source <a href="https://classic105.s3.amazonaws.com/wp-content/uploads/2017/05/180207142-sugar.jpg/">classic105.com</a>
]

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<img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/Rcpp.png" width=480> <br2>
 <a href="http://dirk.eddelbuettel.com/code/rcpp/Rcpp-quickref.pdf">Quick Reference Guide</a>
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# Google Forms & Maps

New packages also allow you to interact with [Google Maps](https://www.google.com/maps) and [Google Forms](https://docs.google.com/forms). Use `ggmap` to access Google Maps and `googlesheets` to access Google Forms.

```r
library(ggmap)
ggmap(get_map(c(7.588576, 47.559601),zoom=16))
```

 <img src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/basel.png" width=350>
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# How to continue

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1. Practice 
2. Read books 
3. Consult websites 
4. Attend R group 
5. Get consulting 
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<img border="0" alt="W3Schools" src="http://www.theunmanageableemployee.com/wp-content/uploads/2011/07/5cs-stones-cropped-11052730.jpg?w=112">
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# Books

Here is a very incomplete series of good books. They are ordered by complexity, beginning with user-friendly books on <high>learning statistics</high> in R and ending with books focusing on the more <high>advanced topics of the R language</high>.

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</table>

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# Websites

The web is a great place to learn about R.

[Google](www.google.com) or [Rseek](www.rseek.org), which is a wrapper around google to maximize hits related to R. However, most of the time Google works just fine. Just be sure to add *r* to the the search query.

Then you will most likely be redirected to one of two pages

[R-bloggers](www.r-bloggers.com) is a website on which R users inform each other on the newest developments. See, e.g., Nathaniel's [entry](https://www.r-bloggers.com/the-new-and-improved-pirateplot-now-with-themes/).

[Stackoverflow](www.r-bloggers.com) is a website on which R users exchange problems and solutions to problems. Try post something yourself. You will be amazed by the turnaround.

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 <a href="https://www.google.com/"><img border="0" alt="W3Schools" src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/google.png" height="100"></a><img border="0" alt="W3Schools" src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/comma.png" height="50"><a href="http://rseek.org/"><img border="0" alt="W3Schools" src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/rseek.png" height="100" style="margin-left:10px; margin-buttom:10px"></a> 
 <a href="https://www.r-bloggers.com/"><img border="0" alt="W3Schools" src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/rbloggers.png" height="105" style="margin-bottom:10px"></a> 
 <a href="https://stackoverflow.com/"><img border="0" alt="W3Schools" src="https://raw.githubusercontent.com/therbootcamp/therbootcamp.github.io/master/_sessions/_image/stackoverflow.png" height="105"></a>

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# Meet other R enthusiasts at...

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# Support & Consulting

Dr. Dirk Wulff 
<a href="www.dirkwulff.org">dirkwulff.org</a> 
<a href="https://github.com/dwulff">github.com/dwulff</a> 
packages: 
<a href="https://cran.r-project.org/web/packages/cstab/index.html">cstab</a>, 
<a href="https://cran.r-project.org/web/packages/mousetrap/index.html">mousetrap</a>, <a href="https://cran.r-project.org/web/packages/memnet/index.html">memnet <a href="https://github.com/dwulff/choicepp">choicepp
 
 
 </th>
 <th class="tg-yw4l"> 
 <a href="www.nathanieldphillips.com/"><img border="0" alt="W3Schools" src="https://therbootcamp.github.io/assets/img/nathaniel_square_small.png" height="230" style="border-radius:50%"></a>

Dr. Nathaniel Phillips 
<a href="www.nathanieldphillips.com/">nathanieldphillips.com</a> 
<a href="https://github.com/ndphillips">github.com/ndphillips</a> 
packages: 
<a href="https://github.com/ndphillips/yarrr">yarrr</a>, 
<a href="https://github.com/ndphillips/FFTrees">FFTrees</a></th>

Markus Steiner 
<a href="https://github.com/mdsteiner">github.com/mdsteiner</a> 
package: 
<a href="https://github.com/ndphillips/ShinyPsych">ShinyPsych 
</th>

Dr. Michael Schulte-M. 
<a href="www.schulte-mecklenbeck.com">schulte-mecklenbeck.com</a> 
<a href="https://github.com/schultem">github.com/schultem</a> 
</th>

</tr>

</table>

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# Next Bootcamps

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Statistics with R 
 
<img src="image/statistics.png" height="260px" width="480px"></img>

<high>2 days, April 6-7, 2019</high> 
</a>

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<a href = "https://advancedstudies.unibas.ch/courses/course/applied-machine-learning-with-r-208291">
 Applied Machine Learning with R 
 
<img src="image/machine_learning.png" height="260px" width="480px"></img>

]

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# Thank you

<a href="http://i.imgur.com/PgtvQar.png">Here is an R Joke.</a> 
And now one more thing...