Primero la Sección de Librerías de Funciones:

# rownames(installed.packages())
list.of.packages <- c(
"arm" , 
"broom" , 
"corrplot" , 
"cowplot" , 
"datasets" , 
"datasets" , 
"dplyr" , 
"eeptools" , 
"estimatr" , 
"FinCal" , 
"formatR" , 
"ggfortify" , 
"ggpubr" , 
"haven" , 
"Hmisc" , 
"infer" , 
"knitr" , 
"lmtest" , 
"margins" , 
"nycflights13" , 
"psych" , 
"readxl" , 
"reshape2" , 
"rms" , 
"skimr" , 
"stargazer" , 
"stringr" , 
"survival" , 
"tableone" , 
"tidyr" , 
"tidyverse" , 
"TTR" , 
"wooldridge" , 
"xlsx" 
)
has   <- list.of.packages %in% rownames(installed.packages())
if(any(!has)) install.packages(list.of.packages[!has])

Llamada a LIBRERIAS:

# library(arm) 
# library(broom) 
# library(corrplot) 
# library(cowplot) 
# library(datasets) 
library(dplyr) 
# library(eeptools) 
# library(estimatr) 
library(FinCal) 
# library(formatR) 
# library(ggfortify) 
# library(ggpubr) 
 library(ggplot2) 
# library(haven) #para la lectura de archivos DTA de Stata
# library(Hmisc) 
# library(infer) 
# library(knitr) 
# library(lmtest) 
# library(margins) 
# library(nycflights13) 
# library(psych) 
library(readxl) 
library(reshape2) #para hacer ReShape (Pivot Tables)
# library(rms) 
# library(skimr) 
# library(stargazer) 
# library(stringr) 
# library(survival) 
# library(tableone) 
library(tidyr) #para hacer ReShape (Pivot Tables)
library(tidyverse) 
library(TTR) #para las graficas de series de tiempo
# library(wooldridge) 
library(xlsx) #para exportar a Excel file

A partir de aquí la Sección de Importación de Datasets:

getwd() #get to show me the current Working Directory 
[1] "/cloud/project"
### Cargando BBDD: n5ay5qadfe7e1nnsv5s01oe1x62mq51j.csv ####
# Version de BBDD: 2021.09.24 v1
# RUTA: https://ibm.box.com/shared/static/

# code to download the dataset
#download.file("https://ibm.box.com/shared/static/n5ay5qadfe7e1nnsv5s01oe1x62mq51j.csv", destfile="movies-db.csv")

# CSV file,  Download datasets
download.file("https://ibm.box.com/shared/static/n5ay5qadfe7e1nnsv5s01oe1x62mq51j.csv", 
              destfile="movies-db.csv")
trying URL 'https://ibm.box.com/shared/static/n5ay5qadfe7e1nnsv5s01oe1x62mq51j.csv'
Content type 'text/csv' length 1424 bytes
==================================================
downloaded 1424 bytes
# XLS file,  Download datasets
download.file("https://ibm.box.com/shared/static/nx0ohd9sq0iz3p871zg8ehc1m39ibpx6.xls", 
              destfile="movies-db.xls")
trying URL 'https://ibm.box.com/shared/static/nx0ohd9sq0iz3p871zg8ehc1m39ibpx6.xls'
Content type 'application/vnd.ms-excel' length 15360 bytes (15 KB)
==================================================
downloaded 15 KB
movies_data <- read.csv("movies-db.csv", header=TRUE, sep=",")
#movies_data
(
my_data <- movies_data
)
NA
NA

REVISION RAPIDA DEL DATAFRAME:

#View(movies_data)
summary(movies_data) # Summary Estadístico.
     name                year        length_min        genre           average_rating  cost_millions        foreign   
 Length:30          Min.   :1936   Min.   : 81.00   Length:30          Min.   :5.200   Min.   :  0.400   Min.   :0.0  
 Class :character   1st Qu.:1988   1st Qu.: 99.25   Class :character   1st Qu.:7.925   1st Qu.:  3.525   1st Qu.:0.0  
 Mode  :character   Median :1998   Median :110.50   Mode  :character   Median :8.300   Median : 13.000   Median :0.0  
                    Mean   :1996   Mean   :116.80                      Mean   :8.103   Mean   : 22.300   Mean   :0.4  
                    3rd Qu.:2008   3rd Qu.:124.25                      3rd Qu.:8.500   3rd Qu.: 25.000   3rd Qu.:1.0  
                    Max.   :2015   Max.   :179.00                      Max.   :9.300   Max.   :165.000   Max.   :1.0  
 age_restriction
 Min.   : 0.00  
 1st Qu.:12.00  
 Median :14.00  
 Mean   :12.93  
 3rd Qu.:16.00  
 Max.   :18.00  
head(movies_data) # Primeros 6.
names(movies_data) # Names de columnas.
[1] "name"            "year"            "length_min"      "genre"           "average_rating"  "cost_millions"   "foreign"        
[8] "age_restriction"
print(is.data.frame(movies_data))
[1] TRUE
#attach(movies_data) #only if there is only 1 dataset 
# CONTENIDO DE TABLA:
# movies_data es la tabla con datos de películas.

A partir de aquí inicia el Cuerpo del Script:

21.09.25.R.Lab08-importingData

Función str (structure)

```{r CUERPO}
Error: attempt to use zero-length variable name
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