Nociones básicas

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# Nociones básicas
## R y Python ⚔
### Duvan Nieves
### 20 mayo, 2020

---

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# ¿Por qué es importante aprender a programar?

Image credit: <a href="https://cdn.computerhoy.com/sites/navi.axelspringer.es/public/media/image/2019/06/lenguaje-programacion.jpg" target="_blank">Cdn</a>

---
# Lenguajes de programación

--
* Bajo Nivel `$^1$`
  * Lenguaje de máquina : Dificil de comprender por seres humanos [Binario].

--
* Alto nivel `$^2$`
  * Pueden ser escritos y comprendidos por seres humanos.
  * Se ejecutan en diversos SO y equipos

.footnote[
 [1](https://conociendoalgoritmo.weebly.com/uploads/4/0/2/6/40267963/1303635.png?390)

[2](https://www.multisoft.hu/wp-content/uploads/karrier.jpg) 
]

---
# Ranking

<center>Fuente : <a href="https://spectrum.ieee.org/" target="_blank">https://spectrum.ieee.org/</a> </center>

---
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background-position: 50% 50%
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# Lenguajes de alto nivel

---
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# ¿Por qué que aprendemos a programar?

Image credit: <a href="https://cde.2.trome.pe/ima/0/1/2/1/0/1210803.jpg" target="_blank">Cde</a>

---
background-image: url("Problemas.png")
background-size: cover
background-position: 25% 25%
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---
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# ¿Cómo funciona un algoritmo?

---
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# Programación y ciencia de datos

---

<center>
Image credit: <a href="https://cio.edu.umh.es/wp-content/uploads/sites/1274/2019/04/R-Python.png" target="_blank">Cio</a> 
</center>

---
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# Instalando R y Python 
# Windows

---
# Instalacion de [R](https://cran.r-project.org/bin/windows/base/)

![](R.gif)

---
# Instalacion de [Python](https://www.python.org/downloads/release/python-382/)

![](python.gif)

---
# Instalacion de [Anaconda](https://www.anaconda.com/products/individual)

![](anaconda.gif)

---
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# Instalando R
# Ubuntu

---
# Instalacion de R

* Podemos buscar r-base en synaptic ó

* Ejecutar en la consola o terminal :

```r
sudo apt install r-base
```

![](r-base.png)

---
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# Entornos de desarrollo

---
# Entorno para R (I)

* [Rstudio](https://rstudio.com/products/rstudio/download/)

![](Rstudio.gif)

---
# Entorno para R (II)

* [Rcommander](https://www.rcommander.com/)

Abrir R e instalar de la siguiente forma

```r
install.packages("Rcmdr")
```

---
# Entorno Python (I)

* [Jupyter](https://jupyter.org/)

Abrir Terminal:

Actualizar instalador de modulos de python

```r
pip3 install --upgrade pip
```

--
.pull-left[

Jupyter Notebook

```r
pip3 install jupyter
```

![](notebook.png)

]
.pull-right[

Jupyter Lab

```r
pip3 install jupyterlab
```

![](lab.png)
  
]

---
# Entorno Python (II)

* [Spyder](https://www.spyder-ide.org/)

Abrir Terminal:

```r
pip3 install spyder
```

---
# Entorno Python (III)

* [PyCharm](https://www.jetbrains.com/es-es/pycharm/)

![](pycharm.jpg)

---
# Opciones Online

.pull-left[

* [Rcloud](https://rstudio.cloud/)

* [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb)

* [Azure Notebook](https://notebooks.azure.com/)

* [Kaggle Notebook](https://www.kaggle.com/kernels)

* [IBM DataPlatform Notebooks](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/notebooks-parent.html)

* [CoCalc](https://cocalc.com/)

* [Datalore](https://datalore.io/)

]

.pull-right[

![](online_gif.gif) 
]

---
# Opciones Móviles

.pull-left[

.center[
[QPython 3L](https://play.google.com/store/apps/details?id=org.qpython.qpy3&hl=es_CO)

![](Qpython.webp)
]
]

.pull-right[

.center[
[Pydroid 3](https://play.google.com/store/apps/details?id=ru.iiec.pydroid3&hl=es_CO)

![](pydroid.webp)

]
]

---
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# ¿Que podemos hacer programando?

---
#Mapas (I)

---
#Mapas (II)

---
#Mapas (III)

```r
library(colmaps)
colmap(municipios[municipios@data$depto =='Santander',]) +
  ggtitle("Santander - Fronteras Municipales")
```

---
# Mapas animados

---
# Mapas interactivos

```r
library(leaflet)
leaflet() %>% addTiles() %>% 
  setView(-75.576576, 6.261493, zoom = 13.5)
```

<div id="htmlwidget-478a90f834c13539e38a" style="width:100%;height:360px;" class="leaflet html-widget"></div>
<script type="application/json" data-for="htmlwidget-478a90f834c13539e38a">{"x":{"options":{"crs":{"crsClass":"L.CRS.EPSG3857","code":null,"proj4def":null,"projectedBounds":null,"options":{}}},"calls":[{"method":"addTiles","args":["//{s}.tile.openstreetmap.org/{z}/{x}/{y}.png",null,null,{"minZoom":0,"maxZoom":18,"tileSize":256,"subdomains":"abc","errorTileUrl":"","tms":false,"noWrap":false,"zoomOffset":0,"zoomReverse":false,"opacity":1,"zIndex":1,"detectRetina":false,"attribution":"© <a href=\"http://openstreetmap.org\">OpenStreetMap<\/a> contributors, <a href=\"http://creativecommons.org/licenses/by-sa/2.0/\">CC-BY-SA<\/a>"}]}],"setView":[[6.261493,-75.576576],13.5,[]]},"evals":[],"jsHooks":[]}</script>

---
# Gráficos interactivos (I)

```r
library(plotly)
plot_ly(z = ~volcano) %>% add_surface()
```

<div id="htmlwidget-1ee0dbb8ddfdd1c7c408" style="width:100%;height:432px;" class="plotly html-widget"></div>
<script type="application/json" data-for="htmlwidget-1ee0dbb8ddfdd1c7c408">{"x":{"visdat":{"bb6731918cc":["function () 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---
# Gráficos interactivos (II)

```r
ggplotly(GGally::ggpairs(iris %>% select(-Species)))
```

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---
#Gráficos 3D animados

![](gif_Fig_1.gif)

---
#Mapas globales

![](sst.png)

---
class: inverse,center, middle
# Conceptos básicos

---
# Tipos de datos en R y Python (I)

--
.pull-left[

<center>Python</center>

<code class ='r hljs remark-code'>#String x = "Hola Amet" type(x)</code>

```

```

<code class ='r hljs remark-code'>#Complejos x = 3.14j type(x)</code>

```

```

]

.pull-right[

<code class ='r hljs remark-code'>#Carácteres x <- "Hola Amet" typeof(x)</code>

```

## [1] "character"

```

<code class ='r hljs remark-code'>#Complejos x <- 3.14i typeof(x)</code>

```

## [1] "complex"

```

]

---
# Tipos de datos en R y Python (II)

.pull-left[

<center>Python</center>

<code class ='r hljs remark-code'>#Numéricos x = 12 y = 12.0 type(x)</code>

```

```

```

```

]

.pull-right[

<code class ='r hljs remark-code'>#Numéricos x <- 12L y <- 12.0 typeof(x)</code>

```

## [1] "integer"

```

<code class ='r hljs remark-code'>typeof(y)</code>

```

## [1] "double"

```

]

---
# Tipos de datos en R y Python (III)

.pull-left[

<center>Python</center>

<code class ='r hljs remark-code'>#Boleano x = True type(x)</code>

```

```

]

.pull-right[

<code class ='r hljs remark-code'>#Lógicos x <- TRUE typeof(x)</code>

```

## [1] "logical"

```

]

---
# Objetos en R y Python (I)

--
 
.pull-left[
 
<center>Python</center>

<code class ='r hljs remark-code'>#Lista como vector x = list(range(1, 8)) x</code>

```

[1, 2, 3, 4, 5, 6, 7]

```

```

<code class ='r hljs remark-code'>#Posiciones x[0]</code>

```

```
  
]

.pull-right[

<code class ='r hljs remark-code'>#Vector x <- c(1:8) x</code>

```

## [1] 1 2 3 4 5 6 7 8

```

<code class ='r hljs remark-code'>length(x)</code>

```

## [1] 8

```

<code class ='r hljs remark-code'>#Posiciones x[1]</code>

```

## [1] 1

```
  
]

---
# Objetos en R y Python (II)

--
 
.pull-left[
 
<center>Python</center>

<code class ='r hljs remark-code'>#Matrices import numpy as np x=np.matrix([[1,2,3],[4,5,6]]) x</code>

```

matrix([[1, 2, 3],
        [4, 5, 6]])

```

<code class ='r hljs remark-code'>x.shape</code>

```

(2, 3)

```

<code class ='r hljs remark-code'>#Primera Fila x[0]</code>

```

matrix([[1, 2, 3]])

```

]

.pull-right[

<code class ='r hljs remark-code'>#Matrices x<-matrix(1:6,nrow=2,byrow=T) x</code>

```

##      [,1] [,2] [,3]
## [1,]    1    2    3
## [2,]    4    5    6

```

```

## [1] 2 3

```

<code class ='r hljs remark-code'>#Primera Fila x[1,]</code>

```

## [1] 1 2 3

```

]

---
# Objetos en R y Python (II)

.pull-left[

<code class ='r hljs remark-code'>#Primera Columna x[:,0]</code>

```

matrix([[1],
        [4]])

```

<code class ='r hljs remark-code'>#Segunda Fila, tercera columna x[1,2]</code>

```

]

.pull-right[

<code class ='r hljs remark-code'>#Primera #Columna x[,1]</code>

```

## [1] 1 4

```

<code class ='r hljs remark-code'>#Segunda Fila, tercera columna x[2,3]</code>

```

## [1] 6

```
  
]

---
# Objetos en R y Python (III)

--
 
.pull-left[
 
<center>Python</center>

<code class ='r hljs remark-code'>#Dataframes import pandas as pd df=pd.DataFrame({'col1':range(1,10+1),'col2':range(11,20+1)}) df</code>

```

col1  col2
0     1    11
1     2    12
2     3    13
3     4    14
4     5    15
5     6    16
6     7    17
7     8    18
8     9    19
9    10    20

```

]

.pull-right[

<code class ='r hljs remark-code'>#Dataframes df = data.frame(col1=c(1:10), col2=c(11:20)) df</code>

```

##    col1 col2
## 1     1   11
## 2     2   12
## 3     3   13
## 4     4   14
## 5     5   15
## 6     6   16
## 7     7   17
## 8     8   18
## 9     9   19
## 10   10   20

```
  
]

---
#Dudas de programación

.pull-left[

![](dudas1.jpg)
![](dudas2.png)
![](dudas3.png)

]

.pull-right[
1. [stackoverflow](https://es.stackoverflow.com/)
1. [StackExchange](https://spanish.stackexchange.com/)
1. [GitHub Community](https://github.community/)
1. [Quora](https://es.quora.com/)
1. [reddit](https://www.reddit.com/)

![](dudas4.jpg)
![](dudas5.png)

]

---
#Plataformas educativas

.pull-left[
1. [Datacamp](https://www.datacamp.com/)
1. [Coursera](https://es.coursera.org/)
1. [edx](https://www.edx.org/es)
1. [Udemy](https://www.udemy.com/)
1. [Lynda](https://www.lynda.com/)
]

.pull-right[
1. [Codecademy](https://www.codecademy.com/)
1. [Udacity](https://www.udacity.com/)
1. [w3schools](https://www.w3schools.com/)
1. [Programmr](http://www.programmr.com/)
1. [CODE AVENGERS](https://www.codeavengers.com/)

]

![](learn-to-code.jpg)

---
#Recursos

.pull-left[
* [R para principiantes](https://cran.r-project.org/doc/contrib/rdebuts_es.pdf)
* [Métodos estadísticos con R y R Commander](https://cran.r-project.org/doc/contrib/Saez-Castillo-RRCmdrv21.pdf)
* [Gráficos estadísticos con R](https://cran.r-project.org/doc/contrib/grafi3.pdf)
* [Cheat Sheet R](https://rstudio.com/resources/cheatsheets/)
* [R-Exercises](https://www.r-exercises.com/)
* [R for Data Science](https://es.r4ds.hadley.nz/)

]

.pull-right[
* [Practice Python](https://www.practicepython.org/)
* [Towards Data Science](https://towardsdatascience.com/)
* [TinyStats](https://tinystats.github.io/teacups-giraffes-and-statistics/01_introToR.html)
* [Aplicaciones ML](https://github.com/firmai/industry-machine-learning/blob/master/README.md)
* [Compilador online](https://rextester.com/)

]

---
#Comunidades

1. [Python Colombia](https://www.python.org.co/)
1. [PyLadies Medellín](https://www.meetup.com/es-ES/Python-Ladies-Medellin/)
1. [Women Who Code Medellín](https://www.womenwhocode.com/medellin)
1. [She Codes Angular Medellín](https://www.meetup.com/es-ES/Python-Ladies-Medellin/)
1. [R-Ladies Medellín](https://www.meetup.com/es/rladies-medellin/)
1. [DATA SCIENCE FEM](https://www.datasciencefem.com/)

---
class: center, middle

#Gracias!

![](avatarc.png)

.pull-down[

<a href="https://duvancho321.github.io/">
.white[ duvancho321.github.io]
</a>

<a href="https://twitter.com/DuvanNievesRui1">
.white[ @DuvanNievesRui1]
</a>

<a href="https://github.com/Duvancho321">
.white[ @Duvancho321]
</a>

<a href="https://rpubs.com/duvancho321_">
.white[ RPubs]
</a>

]