#install.packages("readxl")
library(readxl)
## Warning: package 'readxl' was built under R version 4.3.3
dataxlsx1 <- read_excel("dataexcel1.xlsx", sheet="data_inversion")
View((dataxlsx1))
#install.packages("foreign")
library(foreign)
## Warning: package 'foreign' was built under R version 4.3.3
#install.packages("haven")
library(haven)
## Warning: package 'haven' was built under R version 4.3.3
dataspss1<- read_sav("PERSONAS NSE.sav")
dataspss1
## # A tibble: 33,684 × 91
## regional ciudad zona sector vivienda hogar persona sexo edad reljefe
## <dbl+lb> <chr+lbl> <chr> <chr> <chr> <chr> <dbl> <dbl+l> <dbl> <dbl+l>
## 1 4 [Sur] 010… [Cue… 001 003 01 1 1 1 [Hom… 62 1 [Jef…
## 2 4 [Sur] 010… [Cue… 001 003 01 1 2 2 [Muj… 56 2 [Cón…
## 3 4 [Sur] 010… [Cue… 001 003 02 1 1 1 [Hom… 62 1 [Jef…
## 4 4 [Sur] 010… [Cue… 001 003 02 1 2 2 [Muj… 57 2 [Cón…
## 5 4 [Sur] 010… [Cue… 001 003 03 1 1 2 [Muj… 49 1 [Jef…
## 6 4 [Sur] 010… [Cue… 001 003 03 1 2 1 [Hom… 25 3 [Hij…
## 7 4 [Sur] 010… [Cue… 001 003 03 1 3 2 [Muj… 15 3 [Hij…
## 8 4 [Sur] 010… [Cue… 001 003 04 1 1 1 [Hom… 67 1 [Jef…
## 9 4 [Sur] 010… [Cue… 001 003 04 1 2 2 [Muj… 64 2 [Cón…
## 10 4 [Sur] 010… [Cue… 001 003 04 1 3 1 [Hom… 12 5 [Nie…
## # ℹ 33,674 more rows
## # ℹ 81 more variables: p05 <dbl+lbl>, p06 <dbl+lbl>, caso_01 <dbl+lbl>,
## # numtrab <dbl>, rama <dbl>, grupo <dbl>, catetrab <dbl+lbl>,
## # pertrabn <dbl+lbl>, caso07 <dbl+lbl>, caso08 <dbl+lbl>, caso09 <dbl+lbl>,
## # iess <dbl+lbl>, caso10b <dbl+lbl>, caso11 <dbl+lbl>, caso12 <dbl+lbl>,
## # caso13 <dbl+lbl>, nivinst <dbl+lbl>, anoinst <dbl>, caso15a <dbl+lbl>,
## # caso16a <dbl+lbl>, caso16b <dbl+lbl>, caso17a <dbl+lbl>, …
View(dataspss1)
#install.packages("foreign")
library(foreign)
datastata1<- read.dta("data_stata_card.dta")
## Warning in read.dta("data_stata_card.dta"): cannot read factor labels from
## Stata 5 files
head(datastata1)
## id nearc2 nearc4 educ age fatheduc motheduc weight momdad14 sinmom14 step14
## 1 2 0 0 7 29 NA NA 158413 1 0 0
## 2 3 0 0 12 27 8 8 380166 1 0 0
## 3 4 0 0 12 34 14 12 367470 1 0 0
## 4 5 1 1 11 27 11 12 380166 1 0 0
## 5 6 1 1 12 34 8 7 367470 1 0 0
## 6 7 1 1 12 26 9 12 380166 1 0 0
## reg661 reg662 reg663 reg664 reg665 reg666 reg667 reg668 reg669 south66 black
## 1 1 0 0 0 0 0 0 0 0 0 1
## 2 1 0 0 0 0 0 0 0 0 0 0
## 3 1 0 0 0 0 0 0 0 0 0 0
## 4 0 1 0 0 0 0 0 0 0 0 0
## 5 0 1 0 0 0 0 0 0 0 0 0
## 6 0 1 0 0 0 0 0 0 0 0 0
## smsa south smsa66 wage enroll KWW IQ married libcrd14 exper lwage expersq
## 1 1 0 1 548 0 15 NA 1 0 16 6.306275 256
## 2 1 0 1 481 0 35 93 1 1 9 6.175867 81
## 3 1 0 1 721 0 42 103 1 1 16 6.580639 256
## 4 1 0 1 250 0 25 88 1 1 10 5.521461 100
## 5 1 0 1 729 0 34 108 1 0 16 6.591674 256
## 6 1 0 1 500 0 38 85 1 1 8 6.214608 64
#install.packages("readr")
gapminder = readr::read_csv(file = "https://raw.githubusercontent.com/zief0002/miniature-garbanzo/main/data/gapminder.csv")
## Rows: 193 Columns: 8
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): country, region, income_level, co2_change
## dbl (4): income, life_exp, co2, population
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
head(gapminder)
## # A tibble: 6 × 8
## country region income income_level life_exp co2 co2_change population
## <chr> <chr> <dbl> <chr> <dbl> <dbl> <chr> <dbl>
## 1 Afghanistan Asia 2.03 Level 1 62.7 0.254 increase 37.2
## 2 Albania Europe 13.3 Level 3 78.4 1.59 increase 2.88
## 3 Algeria Africa 11.6 Level 3 76 3.69 increase 42.2
## 4 Andorra Europe 58.3 Level 4 82.1 6.12 decrease 0.077
## 5 Angola Africa 6.93 Level 2 64.6 1.12 decrease 30.8
## 6 Antigua and B… Ameri… 21 Level 3 76.2 5.88 increase 0.0963
data("iris")
View(iris)
#install.packages("tidyverse")
library("tidyverse")
## Warning: package 'tidyverse' was built under R version 4.3.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors