library(readxl)
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── 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
library(dplyr)
library(conflicted)
conflicts_prefer(dplyr::filter)
## [conflicted] Will prefer dplyr::filter over any other package.
Baseeuropa <- read_excel("BASEDEDATOS.xlsx")
dim(Baseeuropa) #dimensiones de la base
## [1] 655 21
str(Baseeuropa) #tipo de variable (categóricas o numéricas)
## tibble [655 × 21] (S3: tbl_df/tbl/data.frame)
## $ DATE : chr [1:655] "1970-01-31" "1970-02-28" "1970-03-31" "1970-04-30" ...
## $ TIME PERIOD : chr [1:655] "Jan 1970" "Feb 1970" "Mar 1970" "Apr 1970" ...
## $ OBS.VALUE : num [1:655] 7.75 7.9 8.11 8.07 8.24 ...
## $ OBS.STATUS : chr [1:655] "A" "A" "A" "A" ...
## $ OBS.COMMENT : logi [1:655] NA NA NA NA NA NA ...
## $ SERIES KEY : chr [1:655] "FM.M.U2.EUR.4F.BB.U2_10Y.YLD" "FM.M.U2.EUR.4F.BB.U2_10Y.YLD" "FM.M.U2.EUR.4F.BB.U2_10Y.YLD" "FM.M.U2.EUR.4F.BB.U2_10Y.YLD" ...
## $ TITLE : chr [1:655] "Euro Area 10 Years Government Benchmark Bond - Yield" "Euro Area 10 Years Government Benchmark Bond - Yield" "Euro Area 10 Years Government Benchmark Bond - Yield" "Euro Area 10 Years Government Benchmark Bond - Yield" ...
## $ FREQUENCY : chr [1:655] "M" "M" "M" "M" ...
## $ FREQUENCY (DESC.) : chr [1:655] "Monthly" "Monthly" "Monthly" "Monthly" ...
## $ REFERENCE AREA : chr [1:655] "U2" "U2" "U2" "U2" ...
## $ REFERENCE AREA (DESC.) : chr [1:655] "Euro area (changing composition) (U2)" "Euro area (changing composition) (U2)" "Euro area (changing composition) (U2)" "Euro area (changing composition) (U2)" ...
## $ CURRENCY : chr [1:655] "EUR" "EUR" "EUR" "EUR" ...
## $ CURRENCY (DESC.) : chr [1:655] "Euro (EUR)" "Euro (EUR)" "Euro (EUR)" "Euro (EUR)" ...
## $ FINANCIAL MARKET PROVIDER : chr [1:655] "4F" "4F" "4F" "4F" ...
## $ FINANCIAL MARKET PROVIDER (DESC.) : chr [1:655] "ECB (4F)" "ECB (4F)" "ECB (4F)" "ECB (4F)" ...
## $ FINANCIAL MARKET INSTRUMENT : chr [1:655] "BB" "BB" "BB" "BB" ...
## $ FINANCIAL MARKET INSTRUMENT (DESC.) : chr [1:655] "Benchmark bond (BB)" "Benchmark bond (BB)" "Benchmark bond (BB)" "Benchmark bond (BB)" ...
## $ FINANCIAL MARKET PROVIDER IDENTIFIER : chr [1:655] "U2_10Y" "U2_10Y" "U2_10Y" "U2_10Y" ...
## $ FINANCIAL MARKET PROVIDER IDENTIFIER (DESC.): chr [1:655] "Euro Area 10 Years Government Benchmark Bond (U2_10Y)" "Euro Area 10 Years Government Benchmark Bond (U2_10Y)" "Euro Area 10 Years Government Benchmark Bond (U2_10Y)" "Euro Area 10 Years Government Benchmark Bond (U2_10Y)" ...
## $ FINANCIAL MARKET DATA TYPE : chr [1:655] "YLD" "YLD" "YLD" "YLD" ...
## $ FINANCIAL MARKET DATA TYPE (DESC.) : chr [1:655] "Yield (YLD)" "Yield (YLD)" "Yield (YLD)" "Yield (YLD)" ...
names(Baseeuropa) #nombre de las variables en las columnas
## [1] "DATE"
## [2] "TIME PERIOD"
## [3] "OBS.VALUE"
## [4] "OBS.STATUS"
## [5] "OBS.COMMENT"
## [6] "SERIES KEY"
## [7] "TITLE"
## [8] "FREQUENCY"
## [9] "FREQUENCY (DESC.)"
## [10] "REFERENCE AREA"
## [11] "REFERENCE AREA (DESC.)"
## [12] "CURRENCY"
## [13] "CURRENCY (DESC.)"
## [14] "FINANCIAL MARKET PROVIDER"
## [15] "FINANCIAL MARKET PROVIDER (DESC.)"
## [16] "FINANCIAL MARKET INSTRUMENT"
## [17] "FINANCIAL MARKET INSTRUMENT (DESC.)"
## [18] "FINANCIAL MARKET PROVIDER IDENTIFIER"
## [19] "FINANCIAL MARKET PROVIDER IDENTIFIER (DESC.)"
## [20] "FINANCIAL MARKET DATA TYPE"
## [21] "FINANCIAL MARKET DATA TYPE (DESC.)"
head(Baseeuropa) #primeros 6 datos de la base
## # A tibble: 6 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1970-01-31 Jan 1970 7.75 A NA FM.M.U2.EUR.4… Euro…
## 2 1970-02-28 Feb 1970 7.90 A NA FM.M.U2.EUR.4… Euro…
## 3 1970-03-31 Mar 1970 8.11 A NA FM.M.U2.EUR.4… Euro…
## 4 1970-04-30 Apr 1970 8.07 A NA FM.M.U2.EUR.4… Euro…
## 5 1970-05-31 May 1970 8.24 A NA FM.M.U2.EUR.4… Euro…
## 6 1970-06-30 Jun 1970 8.45 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
tail(Baseeuropa) #últimos 6 datos de la base
## # A tibble: 6 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 2024-02-29 Feb 2024 3.02 A NA FM.M.U2.EUR.4… Euro…
## 2 2024-03-31 Mar 2024 2.95 A NA FM.M.U2.EUR.4… Euro…
## 3 2024-04-30 Apr 2024 3.07 A NA FM.M.U2.EUR.4… Euro…
## 4 2024-05-31 May 2024 3.12 A NA FM.M.U2.EUR.4… Euro…
## 5 2024-06-30 Jun 2024 3.17 A NA FM.M.U2.EUR.4… Euro…
## 6 2024-07-31 Jul 2024 3.11 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
media <- mean(Baseeuropa$OBS.VALUE)
print(media)
## [1] 6.548814
mediana <- median(Baseeuropa$OBS.VALUE)
print(mediana)
## [1] 6.18
percentiles <- quantile(Baseeuropa$OBS.VALUE, probs = c(0.25, 0.5, 0.75))
print(percentiles)
## 25% 50% 75%
## 3.62445 6.18000 9.64595
desviación <- sd(Baseeuropa$OBS.VALUE)
print(desviación)
## [1] 3.840756
coeficiente_variación <- (desviación / media) * 100
print(coeficiente_variación)
## [1] 58.64812
hist(Baseeuropa$OBS.VALUE, main="Histograma de distribución normal", xlab="Datos", ylab="Frecuencia", col="blue") #no existe distribución normal
summary(Baseeuropa$OBS.VALUE) #única variable numérica
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.0915 3.6244 6.1800 6.5488 9.6459 15.4353
#construiremos un diagrama con nuestra variable numérica
round(Baseeuropa$OBS.VALUE)
## [1] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8
## [26] 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9
## [51] 10 10 10 10 11 11 11 11 10 11 10 10 10 10 10 9 9 9 10 9 9 9 9 9 10
## [76] 10 10 10 10 10 10 11 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
## [101] 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 12 12 13 13 12
## [126] 12 12 12 12 13 13 13 13 13 14 14 15 15 15 15 15 15 15 15 15 15 15 14 14 15
## [151] 15 14 14 14 14 13 13 13 13 13 13 13 13 13 13 13 13 13 13 13 12 12 13 12 12
## [176] 12 12 12 11 11 11 11 11 11 11 11 11 11 11 10 10 10 10 10 9 9 8 9 9 8
## [201] 8 8 9 8 8 9 8 8 9 9 9 10 10 10 9 9 9 9 9 9 9 9 9 9 9
## [226] 9 9 9 9 9 10 10 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 11
## [251] 11 11 11 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10
## [276] 10 10 9 9 9 9 9 8 8 8 7 7 7 7 7 7 7 8 8 8 9 9 9 9 9
## [301] 9 9 9 9 9 9 9 8 8 8 8 8 7 8 8 8 7 8 7 7 7 7 6 6 6
## [326] 6 6 6 6 6 6 6 6 6 6 5 5 5 5 5 5 5 5 5 4 4 4 4 4 4
## [351] 4 4 4 5 5 5 5 5 5 5 6 6 5 5 6 5 5 5 5 5 5 5 5 5 5
## [376] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 4 4 4 4 4
## [401] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3
## [426] 3 3 3 3 3 4 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 5
## [451] 5 4 4 4 4 4 4 4 4 4 4 5 5 4 5 4 4 4 4 4 4 4 4 4 4
## [476] 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 4 4 4 4 4 5 4 4 5 4
## [501] 4 4 4 4 4 4 3 3 4 3 3 3 2 2 2 2 2 3 3 3 3 3 3 3 3
## [526] 3 3 3 3 3 3 3 3 2 2 2 2 2 2 1 1 1 1 1 1 2 2 1 1 1
## [551] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
## [576] 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 0 0 0 0 0 0
## [601] 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
## [626] 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 4 4 3 3 3 3
## [651] 3 3 3 3 3
diagrama1 <- table(round(Baseeuropa$OBS.VALUE))
barplot(diagrama1, col= "green") #podemos ver la frecuencia por intervalos
filtro1 <- filter(Baseeuropa, `TIME PERIOD` == "Jan 1970")
head(filtro1)
## # A tibble: 1 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1970-01-31 Jan 1970 7.75 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
filtro2 <- subset(Baseeuropa, DATE == "1974-08-31")
head(filtro2)
## # A tibble: 1 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1974-08-31 Aug 1974 10.7 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
filtro3 <- subset(Baseeuropa, TITLE == "Euro Area 10 Years Government Benchmark Bond - Yield")
head(filtro3)
## # A tibble: 6 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1970-01-31 Jan 1970 7.75 A NA FM.M.U2.EUR.4… Euro…
## 2 1970-02-28 Feb 1970 7.90 A NA FM.M.U2.EUR.4… Euro…
## 3 1970-03-31 Mar 1970 8.11 A NA FM.M.U2.EUR.4… Euro…
## 4 1970-04-30 Apr 1970 8.07 A NA FM.M.U2.EUR.4… Euro…
## 5 1970-05-31 May 1970 8.24 A NA FM.M.U2.EUR.4… Euro…
## 6 1970-06-30 Jun 1970 8.45 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
filtro4 <- subset(Baseeuropa, OBS.VALUE > 3)
head(filtro4)
## # A tibble: 6 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1970-01-31 Jan 1970 7.75 A NA FM.M.U2.EUR.4… Euro…
## 2 1970-02-28 Feb 1970 7.90 A NA FM.M.U2.EUR.4… Euro…
## 3 1970-03-31 Mar 1970 8.11 A NA FM.M.U2.EUR.4… Euro…
## 4 1970-04-30 Apr 1970 8.07 A NA FM.M.U2.EUR.4… Euro…
## 5 1970-05-31 May 1970 8.24 A NA FM.M.U2.EUR.4… Euro…
## 6 1970-06-30 Jun 1970 8.45 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
filtro5 <- subset(Baseeuropa, OBS.VALUE > 5 )
head(filtro5)
## # A tibble: 6 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1970-01-31 Jan 1970 7.75 A NA FM.M.U2.EUR.4… Euro…
## 2 1970-02-28 Feb 1970 7.90 A NA FM.M.U2.EUR.4… Euro…
## 3 1970-03-31 Mar 1970 8.11 A NA FM.M.U2.EUR.4… Euro…
## 4 1970-04-30 Apr 1970 8.07 A NA FM.M.U2.EUR.4… Euro…
## 5 1970-05-31 May 1970 8.24 A NA FM.M.U2.EUR.4… Euro…
## 6 1970-06-30 Jun 1970 8.45 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
tail(filtro5)
## # A tibble: 6 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 2002-02-28 Feb 2002 5.07 A NA FM.M.U2.EUR.4… Euro…
## 2 2002-03-31 Mar 2002 5.32 A NA FM.M.U2.EUR.4… Euro…
## 3 2002-04-30 Apr 2002 5.30 A NA FM.M.U2.EUR.4… Euro…
## 4 2002-05-31 May 2002 5.30 A NA FM.M.U2.EUR.4… Euro…
## 5 2002-06-30 Jun 2002 5.16 A NA FM.M.U2.EUR.4… Euro…
## 6 2002-07-31 Jul 2002 5.03 A NA FM.M.U2.EUR.4… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
filtro6 <- subset(Baseeuropa, OBS.VALUE>14)
print(filtro6)
## # A tibble: 16 × 21
## DATE `TIME PERIOD` OBS.VALUE OBS.STATUS OBS.COMMENT `SERIES KEY` TITLE
## <chr> <chr> <dbl> <chr> <lgl> <chr> <chr>
## 1 1981-05-31 May 1981 14.7 A NA FM.M.U2.EUR.… Euro…
## 2 1981-06-30 Jun 1981 14.9 A NA FM.M.U2.EUR.… Euro…
## 3 1981-07-31 Jul 1981 15.0 A NA FM.M.U2.EUR.… Euro…
## 4 1981-08-31 Aug 1981 15.2 A NA FM.M.U2.EUR.… Euro…
## 5 1981-09-30 Sep 1981 15.4 A NA FM.M.U2.EUR.… Euro…
## 6 1981-10-31 Oct 1981 15.2 A NA FM.M.U2.EUR.… Euro…
## 7 1981-11-30 Nov 1981 15.2 A NA FM.M.U2.EUR.… Euro…
## 8 1981-12-31 Dec 1981 14.9 A NA FM.M.U2.EUR.… Euro…
## 9 1982-01-31 Jan 1982 14.8 A NA FM.M.U2.EUR.… Euro…
## 10 1982-02-28 Feb 1982 14.9 A NA FM.M.U2.EUR.… Euro…
## 11 1982-03-31 Mar 1982 14.6 A NA FM.M.U2.EUR.… Euro…
## 12 1982-04-30 Apr 1982 14.5 A NA FM.M.U2.EUR.… Euro…
## 13 1982-05-31 May 1982 14.4 A NA FM.M.U2.EUR.… Euro…
## 14 1982-06-30 Jun 1982 14.6 A NA FM.M.U2.EUR.… Euro…
## 15 1982-07-31 Jul 1982 14.6 A NA FM.M.U2.EUR.… Euro…
## 16 1982-08-31 Aug 1982 14.2 A NA FM.M.U2.EUR.… Euro…
## # ℹ 14 more variables: FREQUENCY <chr>, `FREQUENCY (DESC.)` <chr>,
## # `REFERENCE AREA` <chr>, `REFERENCE AREA (DESC.)` <chr>, CURRENCY <chr>,
## # `CURRENCY (DESC.)` <chr>, `FINANCIAL MARKET PROVIDER` <chr>,
## # `FINANCIAL MARKET PROVIDER (DESC.)` <chr>,
## # `FINANCIAL MARKET INSTRUMENT` <chr>,
## # `FINANCIAL MARKET INSTRUMENT (DESC.)` <chr>,
## # `FINANCIAL MARKET PROVIDER IDENTIFIER` <chr>, …
PERIODO <- table(Baseeuropa$`TIME PERIOD`)
head(PERIODO)
##
## Apr 1970 Apr 1971 Apr 1972 Apr 1973 Apr 1974 Apr 1975
## 1 1 1 1 1 1
ESTADO <- table(Baseeuropa$OBS.STATUS)
head(ESTADO)
##
## A
## 655
table(Baseeuropa$`REFERENCE AREA`)
##
## U2
## 655
año1 <- table(Baseeuropa$OBS.VALUE[361:372]) #año 2000
head(año1)
##
## 5.068 5.3357 5.3454 5.3982 5.4138 5.4163
## 1 1 1 1 1 1
año2 <- table(Baseeuropa$DATE[601:612]) #año 2020
head(año2)
##
## 2020-01-31 2020-02-29 2020-03-31 2020-04-30 2020-05-31 2020-06-30
## 1 1 1 1 1 1
interés <- table(Baseeuropa$OBS.VALUE > 6.5)
head(interés)
##
## FALSE TRUE
## 333 322
G1 <- Baseeuropa$OBS.VALUE[1:12]
hist(G1, main = "Histograma del año 1970", xlab = "Interés compuesto", ylab = "Frecuencia", col = "lightgreen")
G2 <- Baseeuropa$OBS.VALUE[13:84]
barplot(G2, main = "1971-1976", ylab = "Interés compuesto", xlab = "jan1971-dec1976", col = "lightblue")
G3 <- Baseeuropa$OBS.VALUE[457:480]
barplot(G3, main = "2008-2009", ylab = "Interés compuesto", xlab= "jan2008-dec2009", col = "lightyellow")
G4 <- Baseeuropa$OBS.VALUE[601:612]
barplot(G4, main = "2020", ylab = "Interés compuesto", xlab= "jan-dec", col = "red")
G5 <- Baseeuropa$OBS.VALUE[601:655]
barplot(G5, main = "2020-PRESENTE", ylab = "Interés compuesto", col = "black")
N_A <- table(is.na(Baseeuropa))
N_A #La cantidad de TRUE es la cantidad de NA's en la base de datos
##
## FALSE TRUE
## 13100 655
#todos los NA's pertenecen a la variable "OBS.COMMENT"
boxplot(Baseeuropa$OBS.VALUE, main= "Identificación de valores atípicos", ylab= "Valores de Interés", col = "red")
plot(Baseeuropa$OBS.VALUE, main= "Identificación de valores atípicos", xlab = "1970-2024", ylab= "Valores de Interés")
#Posible datos atípicos
atípicos <- abs(Baseeuropa$OBS.VALUE) > media + desviación
print(table(atípicos))
## atípicos
## FALSE TRUE
## 554 101
#No existen datos atípicos