class: center, middle, inverse, title-slide .title[ # Procesamiento de datos con {tidyverse} ] .subtitle[ ## <a style="float:left"><br /> </div><br /> <hr color="#EB811B" size="1px" width="1125px"> ] .author[ ### <a href="https://linktr.ee/estacion_r"><img 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VVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWlPTgkAAAAABD0/7Ub7AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAM6Wdk0AAAiDSURBVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA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alt="estacion-R logo" style="width:320px;height:270px;"> </a> ] --- <style>:root{--panel-tab-active-foreground:#0051BA;--panel-tab-hover-foreground:#d22;--panel-tab-font-family:Roboto;}</style> # ¿Qué vimos? <br> ✅ Conceptos básicos de R (valores, vectores, data.framtes, funciones, objetos) <br> ✅ Cómo armar y organizar un proyecto de trabajo <br> ✅ Qué son los paquetes (o librerías) --- ## Hoja de Ruta .pull-left[ 📌 Flujo de trabajo en el Procesamiento de Datos <br> 📦 Paquete `{dplyr}` ``` 🔧 `select()` 🔧 `filter()` 🔧 `mutate()` 🔧 `rename()` 🔧 `arrange()` 🔧 `group_by()` 🔧 `summarise()` 🔧 `joins` ``` ] .pull-right[ 📌 La pipa (`|>` o `%>%`) <br> 📦 Paquete `{tidyr}` ``` 🔧 `pivot_longer()` 🔧 `pivot_wider()` ``` ] --- ## Configuración para esta clase <br> - Armar un proyeto de trabajo nuevo - Crear una carpeta en el llamada `datos` - Descargar la base de juguete [**relevamiento_indice_transparencia_2024.xlsx**](file:///home/pablote/Pablo/Proyectos/Estaci%C3%B3n%20R/Consultor%C3%ADa/intro_r_aaip/docs/datos/relevamiento_indice_transparencia_2024.xlsx) (Argentina) y ubicarla en la carpeta `datos` - Crear un **script** de trabajo. --- class: center, middle, inverse, hide-logo # Flujo de trabajo en el Procesamiento de Datos --- ## Flujo de trabajo en el Procesamiento de Datos <img src="data:image/png;base64,#../img/clase_3/proceso_ciencia_datos.jpg" width="60%" style="display: block; margin: auto;" /> --- class: center, middle, inverse, hide-logo # `{tidyverse}` --- ## ¿Qué es `{tidyverse}`? - Una colección de paquetes. - Comparten una filosofía acerca de los datos y la programación en R ("*tidy*" -*ordenado*-). - Tienen una coherencia para ser utilizados en conjunto. - Orientado a ser leído y escrito por y para seres humanos. - Una comunidad, basada en los principios del código abierto y trabajo colaborativo. --- ## ¿Qué es `{tidyverse}`? <img src="data:image/png;base64,#../img/clase_3/circuito_del_dato_tidy.png" width="60%" style="display: block; margin: auto;" /> --- ## `{tidyverse}` <br> - Instalación: ``` r install.packages("tidyverse") ``` --- ## `{tidyverse}` <br> - Cargo el paquete: ``` r library(tidyverse) ``` --- ## `{tidyverse}` - Nos evita tener que instalar uno por uno a cada paquete: ``` r install.packages("dplyr") install.packages("tidyr") install.packages("ggplot2") ``` <br> - Como también tener que convocarlos de a uno: ``` r library(dplyr) library(tidyr) library(ggplot2) ``` --- class: center, middle, hide-logo  --- ## Funciones del paquete dplyr: <br> | **Función** | **Acción** | |:--------------|--------------------------------------:| | `select()` | *selecciona o descarta variables* | | `filter()` | *selecciona filas* | | `mutate()` | *crea / edita variables* | | `rename()` | *renombra variables* | | `group_by()` | *segmenta en funcion de una variable* | | `summarize()` | *genera una tabla de resúmen* | --- class: center, middle, inverse, hide-logo # **select()** <html><hr color='#EB811B' size=1px width=1600px></html> <html><p style="color:white;" align:"left">Elige o descarta columnas de una base de datos</p></html> --- ## `select()` <br> - La función tiene la siguiente estructura: - Escribo la función --> Doy el primer argumento: la `base de datos` ``` r select(`base_de_datos`, variable1, variable2) ``` -- - Indico el segundo conjunto de argumentos: las `variables (columnas)` a seleccionar ``` r select(base_de_datos, `variable1, variable2`) ``` --- ## `select()` ``` r select(base_de_datos, * id, nombre) ``` <img src="data:image/png;base64,#../img/clase_3/select_presentacion.png" width="65%" style="display: block; margin: auto;" /> --- ## Caso práctico ```r # Cargo paquete library(rio) # Importo datos base_ind_transp <- import("datos/relevamiento_indice_transparencia_2024.xlsx") ``` <br> ``` r # Exploro la base colnames(base_ind_transp) [1] "Marca temporal" [2] "Período" [3] "Tipo de organismo" [4] "Universidades:" [5] "Empresas y Entes del Sector Público Nacional" [6] "Organismos descentralizados" [7] "Administración central y desconcentrada" [8] "1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)" [9] "1.b) ¿La información está actualizada? \n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [10] "1.c) ¿La información está disponible en la pestaña de transparencia?" [11] "2.a) ¿Informa los servicios y/o trámites que presta a la ciudadanía? (nombre, descripción y vínculo o link)\n\n- Si (servicios y/o trámites con los 3 requisitos)\n- Parcialmente (servicios y/o trámites con al menos 1 requisito)\n- No (no presenta información)\n- No corresponde (aclara que no cuenta con servicios y/o trámites)" [12] "2.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [13] "2.c) ¿La información está disponible en la pestaña de transparencia?" [14] "3.i.a) ¿Está completa la información sobre los 3 niveles de autoridades? (con nombre y apellido, cargo o función, DNI o CUIL)\n\n- Si (3 niveles jerárquicos con todos los requisitos)\n- Parcialmente (cumple con al menos un nivel de autoridad y/o requisito)\n- No (no presenta información)" [15] "3.i.b) ¿Está actualizada la información sobre las autoridades?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [16] "3.i.c) ¿Está disponible en la pestaña de transparencia?" [17] "3.ii.a) ¿El organismo presenta las designaciones de las autoridades de al menos 3 niveles jerárquicos?\n\n- Si (junto con todos los requisitos)\n- Parcialmente (al menos un nivel de autoridad y/o requisito)\n- No (no presenta información)" [18] "3.ii.b) ¿Las designaciones están actualizadas?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [19] "3.ii.c) ¿Las designaciones se encuentran disponibles en la pestaña de transparencia, y se pueden descargar o acceder al enlace de consulta?" [20] "4.i.a) ¿La planilla de personal está completa? (nombre y apellido, DNI o CUIL, escalafón, y modalidad de contratación - o redirige a la BIEP en forma completa)\n\n- Si (presenta una planilla con todos los requisitos)\n- Parcialmente (planilla con al menos uno de los campos requeridos)\n- No (no presenta planilla de personal / no funciona la BIEP)" [21] "4.i.b) ¿La planilla de personal está actualizada? \n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [22] "4.i.c) ¿La planilla de personal se encuentra disponible en la pestaña de transparencia y publicada en formato abierto y reutilizable?\n\n- Si (si cumple con ambos requisitos)\n- Parcialmente (al menos un requisito)\n- No (no presenta información)" [23] "4.ii.a) ¿Presenta un organigrama con la estructura del organismo? (formato .pdf, .jpg, imagen, o en el Mapa del Estado)" [24] "4.ii.b) ¿El organigrama se encuentra actualizado?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [25] "4.ii.c) ¿El organigrama se encuentra disponible en la pestaña de transparencia?" [26] "5.a) ¿El organismo presenta un listado con las DDJJ de 3 niveles de funcionarios/as? (deben estar bien rotuladas con nombre, apellido y cargo que desempeña). En caso que redirija a la Oficina Anticorrupción (OA) se tilda la opción \"Parcialmente\".\n\n- Si (de 3 niveles jerárquicos bien rotulados)\n- Parcialmente (al menos 1 nivel de autoridad / algún componente del rótulo / redirige a la Oficina Anticorrupción)\n- No (no presenta información / información con más de 3 años de antigüedad)" [27] "5.b) ¿Las DDJJ están actualizadas?\n\n- Actualizado (3 niveles de autoridades con DDJJ vigentes)\n- Parcialmente (1 o 2 niveles con DDJJ vigentes)\n- Desactualizado (ningún nivel de DDJJ vigentes)\n- Valor nulo (redirige la Oficina Anticorrupción)" [28] "5.c) ¿Están disponibles en la pestaña de transparencia y se pueden descargar?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información / redirige a la OA o se debe completar algún formulario de solicitud)" [29] "6.a) ¿La asignación mensual bruta y los convenios laborales están publicados?\n\n- Si (cumple la información solicitada)\n- Parcialmente (falta algún convenio o escala)\n- No (no presenta información / más de 3 años desactualizado)" [30] "6.b) ¿Están actualizadas?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [31] "6.c) ¿Se encuentran disponibles en la pestaña de transparencia, y a su vez, se pueden descargar?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [32] "7.a) ¿La información está completa? (presupuesto del año vigente y de dos años previos, junto con la ejecución presupuestaria)\n\n- Si (información completa)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [33] "7.b) ¿Presenta la ejecución presupuestaria del último trimestre?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [34] "7.c) ¿El presupuesto se encuentra disponible en la pestaña de transparencia y descargable en formato abierto?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [35] "8.a) ¿Las transferencias muestran toda la información que requiere este apartado?\n\n- Si (cumple con todos los requisitos)\n- Parcialmente (cumple con al menos 1 requisito)\n- No (no presenta información)\n- No corresponde (se explicita que no realiza transferencias)" [36] "8.b) ¿Esta sección está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [37] "8.c) ¿La información se encuentra disponible en la pestaña de transparencia, y descargable en formato abierto y reutilizable?\n\n- Si (cumple con todos los requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [38] "9.a) ¿Redirige al portal de compras y contrataciones del organismo? Organismos de la Adm. Central, Desconcentrada, y Descentralizada deben presentar a su vez el código del SAF para puntaje completo.\n\n- Si (cumple con toda la información)\n- Parcialmente (cumple con parte de la información)\n- No (no presenta información)" [39] "9.b) ¿La información está actualizada?\n\n- Actualizado (hasta 6 meses inclusive)\n- Parcialmente (mayor a 6 meses y hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [40] "9.c) ¿La información se encuentra disponible en la pestaña de transparencia y se puede descargar en formato abierto?\n\n- Si (cumple con todos los requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [41] "10.i.a) ¿Están publicados los informes de auditorías del año vigente y de dos años anteriores?\n\n- Si (cumple con todos los requisitos)\n- Parcialmente (al menos 1 año de informes)\n- No (no presenta información / redirige a SIGEN o formulario para completar)" [42] "10.i.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [43] "10.i.c) ¿La información se encuentra disponible en la pestaña de transparencia y se puede descargar en formato abierto?\n\n- Si (cumple con todos los requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no cumple algún requisito)" [44] "10.ii.a) ¿Presenta informes de evaluación?" [45] "10.ii.b) ¿La información está actualizada en forma anual?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [46] "10.ii.c) ¿La información se encuentra disponible en la pestaña de transparencia y se puede descargar en formato abierto?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos 1 requisito)\n- No (no cumple con ningún requisito)" [47] "11.a) ¿Cumple con todos los requisitos para solicitar información?\n\n- Si (cumple con la información solicitada)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [48] "11.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [49] "11.c) ¿La información está disponible en la pestaña de transparencia?" [50] "12.a) ¿Hay información del Responsable de Políticas de Transparencia?\n\n- Si (cumple con la información solicitada)\n- Parcialmente (al menos 1 requisito)\n- No (no presenta información)" [51] "12.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [52] "12.c) ¿La información está disponible en la pestaña de transparencia?" [53] "13.a) ¿Hay información acerca de espacios de participación ciudadana?" [54] "13.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [55] "13.c) ¿La información está disponible en la pestaña de transparencia?" [56] "14.a) ¿Se informa acerca de la dotación óptima del organismo?" [57] "14.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [58] "14.c) ¿La información se encuentra disponible en la pestaña de transparencia?" [59] "15.a) ¿Presenta información sobre las políticas de integridad?" [60] "15.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [61] "15.c) ¿La información está disponible en la pestaña de transparencia, y se puede descargar en formato abierto?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos un requisito)\n- No (no cumple)" [62] "16.a) ¿Presenta información sobre la planificación estratégica del organismo?" [63] "16.b)¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [64] "16.c) ¿La información está disponible en la pestaña de transparencia, y se puede descargar en formato abierto?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos un requisito)\n- No (no cumple)" [65] "17.a) ¿Hay datos estadísticos publicados?" [66] "17.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [67] "17.c) ¿La información está disponible en la pestaña de transparencia?" [68] "18.a) ¿Se informan las metas del organismo?" [69] "18.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [70] "18.c) ¿La información está disponible en la pestaña de transparencia?" [71] "19.a) ¿Están publicados los informes de gestión?" [72] "19.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [73] "19.c) ¿La información está disponible en la pestaña de transparencia, y se puede descargar en formato abierto?\n\n- Si (cumple con ambos requisitos)\n- Parcialmente (al menos un requisito)\n- No (no cumple)" [74] "El organismo relevado pertenece a:" [75] "20.a).[A] ¿Presenta información sobre las políticas prioritarias del organismo?" [76] "20.b).[A] ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [77] "20.c).[A] ¿La información está disponible en la pestaña de transparencia?" [78] "20.a).[E] ¿Presenta información sobre la autonomía financiera? Reflejado esquemáticamente como el % de dependencia de fondos estatales." [79] "20.b).[E] ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [80] "20.c).[E] ¿La información está disponible en la pestaña de transparencia?" [81] "20.a).[U] ¿La universidad explica su forma de gobierno?" [82] "20.b).[U] ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [83] "20.c).[U] ¿La información está disponible en la pestaña de transparencia?" [84] "Link del sitio web" [85] "Nombre y apellido de quien relevó" [86] "Fecha del relevamiento" ``` --- ## Caso práctico <br> - **Pedido:** Me han solicitado una base que contenga las variables de tiempo e identificacion del tipo de organismo <br> - Variables de trabajo: - *Marca temporal* - *Período* - *Tipo de organismo* --- ## Caso práctico - Selecciono las 3 columnas de interés ``` r library(tidyverse) *select(base_ind_transp, * "Marca temporal", "Período", "Tipo de organismo") Marca temporal Período 1 2024-04-17 11:13:21 ABRIL (Enero - Marzo 2024) 2 2024-04-17 11:30:18 ABRIL (Enero - Marzo 2024) 3 2024-04-17 11:41:42 ABRIL (Enero - Marzo 2024) 4 2024-04-17 12:07:43 ABRIL (Enero - Marzo 2024) 5 2024-04-17 12:16:02 ABRIL (Enero - Marzo 2024) 6 2024-04-18 10:43:08 ABRIL (Enero - Marzo 2024) 7 2024-04-18 13:28:00 ABRIL (Enero - Marzo 2024) 8 2024-04-18 15:15:45 ABRIL (Enero - Marzo 2024) 9 2024-04-18 15:43:58 ABRIL (Enero - Marzo 2024) 10 2024-04-18 16:17:35 ABRIL (Enero - Marzo 2024) 11 2024-04-18 16:22:17 ABRIL (Enero - Marzo 2024) 12 2024-04-19 11:52:02 ABRIL (Enero - Marzo 2024) 13 2024-05-17 15:43:45 ABRIL (Enero - Marzo 2024) 14 2024-05-24 15:08:49 ABRIL (Enero - Marzo 2024) 15 2024-06-04 17:24:11 JULIO (Abril - Junio 2024) 16 2024-06-05 14:31:24 JULIO (Abril - Junio 2024) 17 2024-06-25 17:21:51 1° Trimestre 2024 (Enero - Marzo) 18 2024-06-25 18:07:55 1° Trimestre 2024 (Enero - Marzo) 19 2024-06-26 13:03:55 1° Trimestre 2024 (Enero - Marzo) 20 2024-06-26 13:14:29 1° Trimestre 2024 (Enero - Marzo) 21 2024-06-26 16:40:46 1° Trimestre 2024 (Enero - Marzo) 22 2024-06-26 17:15:20 1° Trimestre 2024 (Enero - Marzo) 23 2024-06-28 09:37:02 1° Trimestre 2024 (Enero - Marzo) 24 2024-06-28 10:13:57 1° Trimestre 2024 (Enero - Marzo) 25 2024-06-28 11:02:31 1° Trimestre 2024 (Enero - Marzo) 26 2024-06-28 11:23:52 1° Trimestre 2024 (Enero - Marzo) 27 2024-06-28 13:22:24 1° Trimestre 2024 (Enero - Marzo) 28 2024-06-28 13:50:04 1° Trimestre 2024 (Enero - Marzo) 29 2024-06-28 15:46:03 1° Trimestre 2024 (Enero - Marzo) 30 2024-06-28 15:47:36 1° Trimestre 2024 (Enero - Marzo) 31 2024-06-28 16:00:41 1° Trimestre 2024 (Enero - Marzo) 32 2024-06-28 16:01:12 1° Trimestre 2024 (Enero - Marzo) 33 2024-06-28 16:48:30 1° Trimestre 2024 (Enero - Marzo) 34 2024-06-28 16:52:27 1° Trimestre 2024 (Enero - Marzo) 35 2024-06-28 17:37:29 1° Trimestre 2024 (Enero - Marzo) Tipo de organismo 1 Administración Central y Desconcentrada 2 Administración Central y Desconcentrada 3 Administración Central y Desconcentrada 4 Administración Central y Desconcentrada 5 Administración Central y Desconcentrada 6 Administración Central y Desconcentrada 7 Administración Central y Desconcentrada 8 Administración Central y Desconcentrada 9 Administración Central y Desconcentrada 10 Administración Central y Desconcentrada 11 Administración Central y Desconcentrada 12 Organismos Descentralizados 13 Universidades 14 Universidades 15 Empresas y Entes del Sector Público Nacional 16 Empresas y Entes del Sector Público Nacional 17 Organismos Descentralizados 18 Administración Central y Desconcentrada 19 Administración Central y Desconcentrada 20 Organismos Descentralizados 21 Organismos Descentralizados 22 Administración Central y Desconcentrada 23 Organismos Descentralizados 24 Organismos Descentralizados 25 Organismos Descentralizados 26 Organismos Descentralizados 27 Organismos Descentralizados 28 Empresas y Entes del Sector Público Nacional 29 Empresas y Entes del Sector Público Nacional 30 Universidades 31 Empresas y Entes del Sector Público Nacional 32 Organismos Descentralizados 33 Organismos Descentralizados 34 Administración Central y Desconcentrada 35 Administración Central y Desconcentrada ``` --- class: center, middle, inverse, hide-logo # La pipa --- ## Un operador llamado `pipa` <br> <br> .pull-left[ <br> ``` r base_de_datos |> funcion1 |> funcion2 |> funcion3 ``` ] .pull-right[  ] --- ## Un operador llamado `pipa` <br> - Pipa de **R base**: `|>` <br> - Pipa de **{magritr}**: `%>%` --- ## `select()` + La `pipa` #### Antes ``` r select(`base_ind_transp`, "Marca temporal", "Período", "Tipo de organismo") ``` -- #### Después ``` r `base_ind_transp` %>% select("Marca temporal", "Período", "Tipo de organismo") ``` --- class: middle, center, inverse, hide-logo # PREGUNTA --- ## Pregunta <br> * Cuál es la diferencia entre esta sentencia: ``` r select(base_ind_transp, "Marca temporal", "Período", "Tipo de organismo") ``` -- * Y esta sentencia: ``` r base_ind_transp_seleccion <- select(base_ind_transp, "Marca temporal", "Período", "Tipo de organismo") ``` --- ## Pregunta <br> * Cuál es la diferencia entre esta sentencia: ``` r select(base_ind_transp, "Marca temporal", "Período", "Tipo de organismo") ``` * Y esta sentencia: ``` r `base_ind_transp_seleccion` <- select(base_ind_transp, "Marca temporal", "Período", "Tipo de organismo") ``` --- ## Caso práctico - Selecciono las 3 columnas de interés ``` r library(tidyverse) base_ind_trans_seleccion <- base_ind_transp |> select("Marca temporal", "Período", "Tipo de organismo") ``` <br> - Chequeo las columnas del nuevo objeto ``` r colnames(base_ind_transp_seleccion) [1] "Marca temporal" "Período" "Tipo de organismo" ``` --- ## `select()` - *por posición* <br> 2. Selecciono ``` r base_ind_transp_seleccion_1 <- base_ind_transp |> select(1, 2, 3) ``` --- ## `select()` - *por posición* <br> 3. Chequeo ``` r colnames(base_ind_transp_seleccion_1) [1] "Marca temporal" "Período" "Tipo de organismo" ``` --- ## `select()` - *por posición (columnas consecutivas)* <br> ``` r base_ind_transp_seleccion_2 <- base_ind_transp |> select(1:3) ``` --- ## `select()` - *por posición (columnas consecutivas)* <br> ``` r base_ind_transp_seleccion_2 <- base_ind_transp |> select(1:3) ``` <br> ``` r colnames(base_ind_transp_seleccion_2) [1] "Marca temporal" "Período" "Tipo de organismo" ``` --- class: center, middle  --- ## `select()` - *Por patrones de texto* <br> **Funciones auxiliares:** - `starts_with()` --\> *empieza con...* - `ends_with()` --\> *termina con...* - `contains()` --\> *contiene...* --- ## `select()` + `starts_with()` <br> ``` r base_ind_transp_patron1 <- base_ind_transp |> select(starts_with("20")) ``` -- - Chequeo ``` r colnames(base_ind_transp_patron1) [1] "20.a).[A] ¿Presenta información sobre las políticas prioritarias del organismo?" [2] "20.b).[A] ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [3] "20.c).[A] ¿La información está disponible en la pestaña de transparencia?" [4] "20.a).[E] ¿Presenta información sobre la autonomía financiera? Reflejado esquemáticamente como el % de dependencia de fondos estatales." [5] "20.b).[E] ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [6] "20.c).[E] ¿La información está disponible en la pestaña de transparencia?" [7] "20.a).[U] ¿La universidad explica su forma de gobierno?" [8] "20.b).[U] ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [9] "20.c).[U] ¿La información está disponible en la pestaña de transparencia?" ``` --- ## `select()` + `starts_with()` <br> --- ## `select()` + `ends_with()` <br> ``` r base_ind_transp_patron2 <- base_ind_transp |> select(ends_with("actualización)")) ``` -- - Chequeo ``` r colnames(base_ind_transp_patron2) [1] "1.b) ¿La información está actualizada? \n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [2] "2.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [3] "3.i.b) ¿Está actualizada la información sobre las autoridades?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [4] "3.ii.b) ¿Las designaciones están actualizadas?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [5] "4.i.b) ¿La planilla de personal está actualizada? \n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [6] "4.ii.b) ¿El organigrama se encuentra actualizado?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [7] "6.b) ¿Están actualizadas?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [8] "7.b) ¿Presenta la ejecución presupuestaria del último trimestre?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [9] "8.b) ¿Esta sección está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [10] "9.b) ¿La información está actualizada?\n\n- Actualizado (hasta 6 meses inclusive)\n- Parcialmente (mayor a 6 meses y hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [11] "10.i.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [12] "10.ii.b) ¿La información está actualizada en forma anual?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [13] "11.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [14] "12.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [15] "13.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [16] "14.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [17] "15.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [18] "16.b)¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [19] "17.b) ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [20] "18.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [21] "19.b) ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [22] "20.b).[A] ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [23] "20.b).[E] ¿La información está actualizada?\n\n- Actualizado (hasta 3 meses inclusive)\n- Parcialmente (mayor a 3 meses y hasta 6 meses inclusive)\n- Desactualizado (mayor a 6 meses / no hay fecha de actualización)" [24] "20.b).[U] ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" ``` ## `select()` + `starts_with()` <br> --- class: center, middle  --- ## `select()` + `contains()` <br> ``` r base_ind_transp_patron3 <- base_ind_transp |> select(contains("[U]")) ``` -- - Chequeo ``` r colnames(base_ind_transp_patron3) [1] "20.a).[U] ¿La universidad explica su forma de gobierno?" [2] "20.b).[U] ¿La información está actualizada?\n\n- Actualizado (hasta 1 año inclusive)\n- Desactualizado (mayor a 1 año / no hay fecha de actualización)" [3] "20.c).[U] ¿La información está disponible en la pestaña de transparencia?" ``` --- class: center, middle  --- class: middle, center, inverse, hide-logo # LA COMBINACIÓN FINAL --- ## `select()` <br> ``` r base_ind_transp_tuto <- base_ind_transp |> select(Período, 4, starts_with("Link")) ``` -- ``` r colnames(base_ind_transp_tuto) [1] "Período" "Universidades:" "Link del sitio web" ``` --- class: center, middle, hide-logo  --- class: middle, center, inverse, hide-logo # Ejercitación grupal --- ## Ejercitación - Crear un objeto en donde importamos la base de datos del relevamiento de sujetos obligados - Seleccionar 3 variables de la base según el nombre de las mismas y guardar en otro objeto. - Seleccionar 3 variables de la base según la posición de las mismas y guardar en otro objeto. - Seleccionar todas las variables que **empiecen** con un patrón de texto (a elegir). --- class: middle, center, inverse, hide-logo # **filter()** <html><hr color='#EB811B' size=1px width=1600px></html> <html><p style="color:white;" align:"left">Elige o descarta columnas de una base de datos</p></html> --- ## `filter()` <br> - La función tiene la siguiente estructura: ``` r filter(base_de_datos, condicion) ``` <img src="data:image/png;base64,#../img/clase_3/filter_presentacion.png" width="65%" style="display: block; margin: auto;" /> --- ## `filter()` <br> - `Con pipe`, la función tiene la siguiente estructura: ``` r base_de_datos |> filter(Edad > 65) ``` <img src="data:image/png;base64,#../img/clase_3/filter_presentacion.png" width="65%" style="display: block; margin: auto;" /> --- ## Caso práctico - Debo realizar un análisis de la base de datos sólo para los sujetos obligados de tipo `Universidades`. <br> **Universo de análisis / Población de estudio:** - `Universidades` --- ## Caso práctico - Chequeo qué tipo de organismos existen en la base de trabajo -- ``` r unique(base_ind_transp$`Tipo de organismo`) [1] "Administración Central y Desconcentrada" [2] "Organismos Descentralizados" [3] "Universidades" [4] "Empresas y Entes del Sector Público Nacional" ``` --- ## Caso práctico - Aplico filtro ``` r library(tidyverse) base_filtrada <- base_ind_transp |> filter(`Tipo de organismo` == "Universidades") ``` -- - Chequeo filtro ``` r unique(base_filtrada$`Tipo de organismo`) [1] "Universidades" ``` --- ## `filter()` - Otra forma de chequeo: Contar casos ``` r base_ind_transp %>% count(`Tipo de organismo`) Tipo de organismo n 1 Administración Central y Desconcentrada 16 2 Empresas y Entes del Sector Público Nacional 5 3 Organismos Descentralizados 11 4 Universidades 3 ``` -- ``` r base_filtrada %>% count(`Tipo de organismo`) Tipo de organismo n 1 Universidades 3 ``` --- ## `filter()` .pull-left[ | Condición | Acción | |:----------|:--------------------| | `==` | *igual* | | `%in%` | *incluye* | | `!=` | *distinto* | | `>` | *mayor que* | | `<` | *menor que* | | `>=` | *mayor o igual que* | | `<=` | *menor o igual que* | ] .pull-right[ | Operador | Descripción | |:---------|:--------------------------------------------| | `&` | *y* - Cuando se cumplen ambas condiciones | | `┃` | *o* - Cuando se cumple una u otra condición | ] --- ## Caso práctico - Filtro múltiple <br> - Debo realizar un análisis de la base de datos para los sujetos obligados de tipo `Universidades` y `Organismos Descentralizados`. <br> --- ## Caso práctico - Filtro múltiple - Chequeo qué tipo de organismos existen en la base de trabajo -- ``` r unique(base_ind_transp$`Tipo de organismo`) [1] "Administración Central y Desconcentrada" [2] "Organismos Descentralizados" [3] "Universidades" [4] "Empresas y Entes del Sector Público Nacional" ``` --- ## Caso práctico - Filtro múltiple - Aplico filtro ``` r base_filtrada <- base_ind_transp |> filter(`Tipo de organismo` == "Universidades" | `Tipo de organismo` == "Organismos Descentralizados") ``` -- - Chequeo filtro ``` r unique(base_filtrada$`Tipo de organismo`) [1] "Organismos Descentralizados" "Universidades" ``` --- ## Caso práctico - Filtro múltiple - Operador `%in%` - Aplico filtro ``` r base_filtrada_operador_in <- base_ind_transp |> filter(`Tipo de organismo` %in% c("Universidades", "Organismos Descentralizados")) ``` -- - Chequeo filtro ``` r unique(base_filtrada_operador_in$`Tipo de organismo`) [1] "Organismos Descentralizados" "Universidades" ``` --- class: middle, center, inverse, hide-logo # **mutate()** <html><hr color='#EB811B' size=1px width=1600px></html> <html><p style="color:white;" align:"left">Crea / edita variables (columnas)</p></html> --- ## `mutate()` <br> - La función tiene la siguiente estructura: <br> ``` r base_de_datos %>% mutate(`var_nueva` = var_1 + var_2) ``` --- ## Caso práctico - Tenemos la siguiente tabla con los valores del **Índice de Transparencia**... - Queremos redondear los valores, para poder presentarlos ``` sujeto_obligado indice_transparencia 1 Instituto Nacional del Teatro 2.56560 2 Instituto Nacional del Cáncer 76.23423 3 Agencia de Planificación (APLA) 32.12312 4 Oficina Anticorrupción 89.10000 5 Fundación Miguel Lillo 65.21331 ``` --- ## Caso práctico ``` r base_resultados %>% mutate(redondeo = round(indice_transparencia, digits = 1)) ``` ``` sujeto_obligado indice_transparencia redondeo 1 Instituto Nacional del Teatro 2.56560 2.6 2 Instituto Nacional del Cáncer 76.23423 76.2 3 Agencia de Planificación (APLA) 32.12312 32.1 4 Oficina Anticorrupción 89.10000 89.1 5 Fundación Miguel Lillo 65.21331 65.2 ``` --- ## Caso práctico ``` r base_resultados %>% mutate(indice_transparencia = round(indice_transparencia, digits = 1)) ``` ``` sujeto_obligado indice_transparencia 1 Instituto Nacional del Teatro 2.6 2 Instituto Nacional del Cáncer 76.2 3 Agencia de Planificación (APLA) 32.1 4 Oficina Anticorrupción 89.1 5 Fundación Miguel Lillo 65.2 ``` --- ## `mutate()` + `case_when()` - `case_when()` = _"Siempre que..."_ - Quiero determinado valor en mi nueva variable, _siempre que_ ocurra cierta condición -- <br> ``` r base_de_datos %>% mutate(var_nueva = case_when(var_vieja == "a" `~` contenido_a, var_vieja == "b" `~` contenido_b)) ``` --- ## `mutate()` + `case_when()` - Recodificar variable `Periodo`: ``` r unique(base_ind_transp$Período) [1] "ABRIL (Enero - Marzo 2024)" "JULIO (Abril - Junio 2024)" [3] "1° Trimestre 2024 (Enero - Marzo)" ``` ``` r base_recod <- base_ind_transp %>% mutate(Período = case_when(Período == "ABRIL (Enero - Marzo 2024)" ~ "1er Trim", Período == "1° Trimestre 2024 (Enero - Marzo)" ~ "1er Trim", Período == "JULIO (Abril - Junio 2024)" ~ "2do Trim")) ``` -- ``` r unique(base_recod$Período) [1] "1er Trim" "2do Trim" ``` --- ## Limpieza de datos ``` r library(janitor) base_limpia <- base_ind_transp %>% select(`Universidades:`, `1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)`) %>% rename("universidades" = `Universidades:`, "1.a" = `1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)`) ``` -- ``` r colnames(base_limpia) [1] "universidades" "1.a" ``` --- class: middle, center, inverse, hide-logo # **group_by() + summarise()** <html><hr color='#EB811B' size=1px width=1600px></html> <html><p style="color:white;" align:"left">Agrupamiento / Cálculos</p></html> --- # `summarise()` - Caso: Quiero sumar el puntaje total para el ítem **1.a (_"¿Informa al menos uno de los elementos solicitados?"_)** -- Primero: Conocer la variable sobre la cuál voy a trabajar: - ¿Es numérica? - Está preparada para calcular? (recodificación, valores de texto o outliers, etc.) Veamos: --- # `summarise()` 1. Recodifico el nombre de la variable, para hacerla más amena de trabajar en el código ``` r base_trabajo <- base_ind_transp %>% select(Período, `Tipo de organismo`, `1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)`) %>% rename( "periodo" = Período, "tipo_organismo" = `Tipo de organismo`, "item_1a" = `1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)`) head(base_trabajo) periodo tipo_organismo item_1a 1 ABRIL (Enero - Marzo 2024) Administración Central y Desconcentrada Si 2 ABRIL (Enero - Marzo 2024) Administración Central y Desconcentrada Si 3 ABRIL (Enero - Marzo 2024) Administración Central y Desconcentrada Si 4 ABRIL (Enero - Marzo 2024) Administración Central y Desconcentrada Si 5 ABRIL (Enero - Marzo 2024) Administración Central y Desconcentrada Si 6 ABRIL (Enero - Marzo 2024) Administración Central y Desconcentrada No ``` --- # `summarise()` 2. Chequeo qué valores figuran en la variable: ``` r unique(base_trabajo$item_1a) [1] "Si" "No" ``` --- # `summarise()` 4. Recodifico la variable de texto a número (códigos), donde: "Si" == 1 y "No" == 2 ``` r base_trabajo <- base_trabajo %>% mutate(item_1a = case_when(item_1a == "Si" ~ 1, item_1a == "No" ~ 0)) unique(base_trabajo$item_1a) [1] 1 0 ``` --- # `summarise()` - ¡Todo listo para calcular! -- ``` r base_trabajo %>% summarise(suma_item = sum(item_1a)) suma_item 1 29 ``` -- ``` r base_trabajo %>% summarise(suma_item = sum(item_1a), media_item = mean(item_1a)) suma_item media_item 1 29 0.8285714 ``` --- # `group_by()` - Agrupa un data.frame por las categorías de una variable -- - Proteínas para el `summarise()` ``` r base_trabajo %>% group_by(variable) ``` --- # `group_by()` ``` r base_trabajo %>% group_by(tipo_organismo) %>% #<-- summarise(suma_item = sum(item_1a), media_item = mean(item_1a)) # A tibble: 4 × 3 tipo_organismo suma_item media_item <chr> <dbl> <dbl> 1 Administración Central y Desconcentrada 15 0.938 2 Empresas y Entes del Sector Público Nacional 4 0.8 3 Organismos Descentralizados 9 0.818 4 Universidades 1 0.333 ``` --- class: middle, center, logo-hide ## `tidyverse en acción` --- # `tidyverse` en acción ``` r base_trabajo <- base_ind_transp %>% select(Período, `Tipo de organismo`, `1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)`) %>% rename( "periodo" = Período, "tipo_organismo" = `Tipo de organismo`, "item_1a" = `1.a) ¿Informa al menos uno de los elementos solicitados? (misión, objetivos, o ambos)`) %>% mutate(item_1a = case_when(item_1a == "Si" ~ 1, item_1a == "No" ~ 0)) %>% group_by(tipo_organismo) %>% #<-- summarise(suma_item = sum(item_1a), media_item = mean(item_1a)) ``` --- # `tidyverse` en acción ``` r base_trabajo # A tibble: 4 × 3 tipo_organismo suma_item media_item <chr> <dbl> <dbl> 1 Administración Central y Desconcentrada 15 0.938 2 Empresas y Entes del Sector Público Nacional 4 0.8 3 Organismos Descentralizados 9 0.818 4 Universidades 1 0.333 ``` ---