3° ENCUENTRO
2024-11-08
# Instalamos y/o cargamos paquetes
library("tidyverse")
library("readxl")IMPORTACIÓN DE DATOS
Función read_csv()
ALUMNOS_2024 <- read_csv("https://docs.google.com/spreadsheets/d/e/2PACX-1vTwVt48G81FHfD_K9jcVmhjN3otTkR0-5Y8mC23oaEOTmhiG4So0kjw6I0b2tkU5ilpehvlhqBjId9i/pub?output=csv")## Rows: 24 Columns: 5
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): Marca temporal, Género, ¿Qué tan difícil le resulta el aprendizaje ...
## dbl (2): Edad, ¿Cuántas asignaturas rendiste y aprobaste este año?
##
## 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.names(ALUMNOS_2024)## [1] "Marca temporal"
## [2] "Género"
## [3] "Edad"
## [4] "¿Qué tan difícil le resulta el aprendizaje del software R y RStudio?"
## [5] "¿Cuántas asignaturas rendiste y aprobaste este año?"Función read_excel()
MANDARINAS <- read_excel("MANDARINAS_2024.xlsx")glimpse(MANDARINAS)## Rows: 419
## Columns: 8
## $ N <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1…
## $ GRUPO <dbl> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ VARIEDAD <chr> "Clementina", "Clementina", "Clementina", "Clementina", …
## $ N_DE_FRUTO <dbl> 19, 9, 21, 8, 4, 30, 22, 23, 17, 27, 29, 14, 16, 13, 25,…
## $ PESO <dbl> 101, 122, 127, 126, 37, 139, 140, 130, 138, 142, 121, 15…
## $ DIAM_ECUAT <dbl> 64.2, 64.2, 64.7, 64.9, 65.9, 66.4, 67.1, 67.5, 68.2, 68…
## $ NIVEL_DE_DAÑO <dbl> 1, 0, 3, 3, 2, 2, 3, 1, 2, 2, 2, 1, 1, 2, 1, 1, 0, 1, 0,…
## $ COLOR <dbl> 4, 5, 4, 1, 5, 4, 4, 3, 3, 4, 4, 1, 1, 3, 4, 1, 4, 1, 5,…VISUALIZACIÓN DE DATOS
Cargamos la base de datos “iris”
Ordenamos la base de datos
IRIS <- iris %>%
rename(Longitud.Sepalo = Sepal.Length,
Ancho.Sepalo = Sepal.Width,
Longitud.Petalo = Petal.Length,
Ancho.Petalo = Petal.Width,
ESPECIE = Species)## Rows: 150
## Columns: 5
## $ Longitud.Sepalo <dbl> 5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4,…
## $ Ancho.Sepalo <dbl> 3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7,…
## $ Longitud.Petalo <dbl> 1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5,…
## $ Ancho.Petalo <dbl> 0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2,…
## $ ESPECIE <fct> setosa, setosa, setosa, setosa, setosa, setosa, setosa…Diagramas de dispersión
ggplot(IRIS, aes(Longitud.Petalo, Ancho.Petalo)) +
geom_point()
ggplot(IRIS, aes(Longitud.Petalo, Ancho.Petalo)) +
geom_point(shape = 25, fill = "yellow") # Para las formas 21 a 25, `fill =` controla el color de relleno de la forma.
También es posible modificar el tamaño de la forma seleccionada con
“size =”
ggplot(IRIS, aes(Longitud.Petalo, Ancho.Petalo)) +
geom_point(size = 4)
ggplot(IRIS, aes(Longitud.Petalo, Ancho.Petalo)) +
geom_point(color = "red")
Combinamos atributos
ggplot(IRIS, aes(Longitud.Petalo, Ancho.Petalo, shape = ESPECIE, color = ESPECIE)) +
geom_point(size= 3)
Gráfico de líneas
PP_77_22 <- read_excel("PP_77_22.xlsx")glimpse(PP_77_22)## Rows: 46
## Columns: 2
## $ ANIO <dbl> 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987,…
## $ PP <dbl> 666.4, 553.2, 675.7, 532.4, 528.7, 410.9, 569.2, 484.0, 610.2, 37…ggplot(PP_77_22, aes(ANIO, PP)) +
geom_line()
Renombramos variables
PP_77_22 <- PP_77_22 %>%
rename(AÑO = ANIO,
PRECIPITACION = PP)Visualizamos
PP_77_22## # A tibble: 46 × 2
## AÑO PRECIPITACION
## <dbl> <dbl>
## 1 1977 666.
## 2 1978 553.
## 3 1979 676.
## 4 1980 532.
## 5 1981 529.
## 6 1982 411.
## 7 1983 569.
## 8 1984 484
## 9 1985 610.
## 10 1986 379.
## # ℹ 36 more rowsCombinamos ambos argumentos…
ggplot(PP_77_22, aes(AÑO, PRECIPITACION)) +
geom_line(color = "blue", linetype = 3, lwd = 1 )
Histogramas
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_histogram()## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Cambiamos color de los contenedores.
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_histogram(color = "yellow")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Modificamos color y relleno de los contenedores.
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_histogram(color = "yellow", fill = "darkgreen")## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
A continuación pueden ver los nombres de algunos colores con la
función colors()
colors()## [1] "white" "aliceblue" "antiquewhite"
## [4] "antiquewhite1" "antiquewhite2" "antiquewhite3"
## [7] "antiquewhite4" "aquamarine" "aquamarine1"
## [10] "aquamarine2" "aquamarine3" "aquamarine4"
## [13] "azure" "azure1" "azure2"
## [16] "azure3" "azure4" "beige"
## [19] "bisque" "bisque1" "bisque2"
## [22] "bisque3" "bisque4" "black"
## [25] "blanchedalmond" "blue" "blue1"
## [28] "blue2" "blue3" "blue4"
## [31] "blueviolet" "brown" "brown1"
## [34] "brown2" "brown3" "brown4"
## [37] "burlywood" "burlywood1" "burlywood2"
## [40] "burlywood3" "burlywood4" "cadetblue"
## [43] "cadetblue1" "cadetblue2" "cadetblue3"
## [46] "cadetblue4" "chartreuse" "chartreuse1"
## [49] "chartreuse2" "chartreuse3" "chartreuse4"
## [52] "chocolate" "chocolate1" "chocolate2"
## [55] "chocolate3" "chocolate4" "coral"
## [58] "coral1" "coral2" "coral3"
## [61] "coral4" "cornflowerblue" "cornsilk"
## [64] "cornsilk1" "cornsilk2" "cornsilk3"
## [67] "cornsilk4" "cyan" "cyan1"
## [70] "cyan2" "cyan3" "cyan4"
## [73] "darkblue" "darkcyan" "darkgoldenrod"
## [76] "darkgoldenrod1" "darkgoldenrod2" "darkgoldenrod3"
## [79] "darkgoldenrod4" "darkgray" "darkgreen"
## [82] "darkgrey" "darkkhaki" "darkmagenta"
## [85] "darkolivegreen" "darkolivegreen1" "darkolivegreen2"
## [88] "darkolivegreen3" "darkolivegreen4" "darkorange"
## [91] "darkorange1" "darkorange2" "darkorange3"
## [94] "darkorange4" "darkorchid" "darkorchid1"
## [97] "darkorchid2" "darkorchid3" "darkorchid4"
## [100] "darkred" "darksalmon" "darkseagreen"
## [103] "darkseagreen1" "darkseagreen2" "darkseagreen3"
## [106] "darkseagreen4" "darkslateblue" "darkslategray"
## [109] "darkslategray1" "darkslategray2" "darkslategray3"
## [112] "darkslategray4" "darkslategrey" "darkturquoise"
## [115] "darkviolet" "deeppink" "deeppink1"
## [118] "deeppink2" "deeppink3" "deeppink4"
## [121] "deepskyblue" "deepskyblue1" "deepskyblue2"
## [124] "deepskyblue3" "deepskyblue4" "dimgray"
## [127] "dimgrey" "dodgerblue" "dodgerblue1"
## [130] "dodgerblue2" "dodgerblue3" "dodgerblue4"
## [133] "firebrick" "firebrick1" "firebrick2"
## [136] "firebrick3" "firebrick4" "floralwhite"
## [139] "forestgreen" "gainsboro" "ghostwhite"
## [142] "gold" "gold1" "gold2"
## [145] "gold3" "gold4" "goldenrod"
## [148] "goldenrod1" "goldenrod2" "goldenrod3"
## [151] "goldenrod4" "gray" "gray0"
## [154] "gray1" "gray2" "gray3"
## [157] "gray4" "gray5" "gray6"
## [160] "gray7" "gray8" "gray9"
## [163] "gray10" "gray11" "gray12"
## [166] "gray13" "gray14" "gray15"
## [169] "gray16" "gray17" "gray18"
## [172] "gray19" "gray20" "gray21"
## [175] "gray22" "gray23" "gray24"
## [178] "gray25" "gray26" "gray27"
## [181] "gray28" "gray29" "gray30"
## [184] "gray31" "gray32" "gray33"
## [187] "gray34" "gray35" "gray36"
## [190] "gray37" "gray38" "gray39"
## [193] "gray40" "gray41" "gray42"
## [196] "gray43" "gray44" "gray45"
## [199] "gray46" "gray47" "gray48"
## [202] "gray49" "gray50" "gray51"
## [205] "gray52" "gray53" "gray54"
## [208] "gray55" "gray56" "gray57"
## [211] "gray58" "gray59" "gray60"
## [214] "gray61" "gray62" "gray63"
## [217] "gray64" "gray65" "gray66"
## [220] "gray67" "gray68" "gray69"
## [223] "gray70" "gray71" "gray72"
## [226] "gray73" "gray74" "gray75"
## [229] "gray76" "gray77" "gray78"
## [232] "gray79" "gray80" "gray81"
## [235] "gray82" "gray83" "gray84"
## [238] "gray85" "gray86" "gray87"
## [241] "gray88" "gray89" "gray90"
## [244] "gray91" "gray92" "gray93"
## [247] "gray94" "gray95" "gray96"
## [250] "gray97" "gray98" "gray99"
## [253] "gray100" "green" "green1"
## [256] "green2" "green3" "green4"
## [259] "greenyellow" "grey" "grey0"
## [262] "grey1" "grey2" "grey3"
## [265] "grey4" "grey5" "grey6"
## [268] "grey7" "grey8" "grey9"
## [271] "grey10" "grey11" "grey12"
## [274] "grey13" "grey14" "grey15"
## [277] "grey16" "grey17" "grey18"
## [280] "grey19" "grey20" "grey21"
## [283] "grey22" "grey23" "grey24"
## [286] "grey25" "grey26" "grey27"
## [289] "grey28" "grey29" "grey30"
## [292] "grey31" "grey32" "grey33"
## [295] "grey34" "grey35" "grey36"
## [298] "grey37" "grey38" "grey39"
## [301] "grey40" "grey41" "grey42"
## [304] "grey43" "grey44" "grey45"
## [307] "grey46" "grey47" "grey48"
## [310] "grey49" "grey50" "grey51"
## [313] "grey52" "grey53" "grey54"
## [316] "grey55" "grey56" "grey57"
## [319] "grey58" "grey59" "grey60"
## [322] "grey61" "grey62" "grey63"
## [325] "grey64" "grey65" "grey66"
## [328] "grey67" "grey68" "grey69"
## [331] "grey70" "grey71" "grey72"
## [334] "grey73" "grey74" "grey75"
## [337] "grey76" "grey77" "grey78"
## [340] "grey79" "grey80" "grey81"
## [343] "grey82" "grey83" "grey84"
## [346] "grey85" "grey86" "grey87"
## [349] "grey88" "grey89" "grey90"
## [352] "grey91" "grey92" "grey93"
## [355] "grey94" "grey95" "grey96"
## [358] "grey97" "grey98" "grey99"
## [361] "grey100" "honeydew" "honeydew1"
## [364] "honeydew2" "honeydew3" "honeydew4"
## [367] "hotpink" "hotpink1" "hotpink2"
## [370] "hotpink3" "hotpink4" "indianred"
## [373] "indianred1" "indianred2" "indianred3"
## [376] "indianred4" "ivory" "ivory1"
## [379] "ivory2" "ivory3" "ivory4"
## [382] "khaki" "khaki1" "khaki2"
## [385] "khaki3" "khaki4" "lavender"
## [388] "lavenderblush" "lavenderblush1" "lavenderblush2"
## [391] "lavenderblush3" "lavenderblush4" "lawngreen"
## [394] "lemonchiffon" "lemonchiffon1" "lemonchiffon2"
## [397] "lemonchiffon3" "lemonchiffon4" "lightblue"
## [400] "lightblue1" "lightblue2" "lightblue3"
## [403] "lightblue4" "lightcoral" "lightcyan"
## [406] "lightcyan1" "lightcyan2" "lightcyan3"
## [409] "lightcyan4" "lightgoldenrod" "lightgoldenrod1"
## [412] "lightgoldenrod2" "lightgoldenrod3" "lightgoldenrod4"
## [415] "lightgoldenrodyellow" "lightgray" "lightgreen"
## [418] "lightgrey" "lightpink" "lightpink1"
## [421] "lightpink2" "lightpink3" "lightpink4"
## [424] "lightsalmon" "lightsalmon1" "lightsalmon2"
## [427] "lightsalmon3" "lightsalmon4" "lightseagreen"
## [430] "lightskyblue" "lightskyblue1" "lightskyblue2"
## [433] "lightskyblue3" "lightskyblue4" "lightslateblue"
## [436] "lightslategray" "lightslategrey" "lightsteelblue"
## [439] "lightsteelblue1" "lightsteelblue2" "lightsteelblue3"
## [442] "lightsteelblue4" "lightyellow" "lightyellow1"
## [445] "lightyellow2" "lightyellow3" "lightyellow4"
## [448] "limegreen" "linen" "magenta"
## [451] "magenta1" "magenta2" "magenta3"
## [454] "magenta4" "maroon" "maroon1"
## [457] "maroon2" "maroon3" "maroon4"
## [460] "mediumaquamarine" "mediumblue" "mediumorchid"
## [463] "mediumorchid1" "mediumorchid2" "mediumorchid3"
## [466] "mediumorchid4" "mediumpurple" "mediumpurple1"
## [469] "mediumpurple2" "mediumpurple3" "mediumpurple4"
## [472] "mediumseagreen" "mediumslateblue" "mediumspringgreen"
## [475] "mediumturquoise" "mediumvioletred" "midnightblue"
## [478] "mintcream" "mistyrose" "mistyrose1"
## [481] "mistyrose2" "mistyrose3" "mistyrose4"
## [484] "moccasin" "navajowhite" "navajowhite1"
## [487] "navajowhite2" "navajowhite3" "navajowhite4"
## [490] "navy" "navyblue" "oldlace"
## [493] "olivedrab" "olivedrab1" "olivedrab2"
## [496] "olivedrab3" "olivedrab4" "orange"
## [499] "orange1" "orange2" "orange3"
## [502] "orange4" "orangered" "orangered1"
## [505] "orangered2" "orangered3" "orangered4"
## [508] "orchid" "orchid1" "orchid2"
## [511] "orchid3" "orchid4" "palegoldenrod"
## [514] "palegreen" "palegreen1" "palegreen2"
## [517] "palegreen3" "palegreen4" "paleturquoise"
## [520] "paleturquoise1" "paleturquoise2" "paleturquoise3"
## [523] "paleturquoise4" "palevioletred" "palevioletred1"
## [526] "palevioletred2" "palevioletred3" "palevioletred4"
## [529] "papayawhip" "peachpuff" "peachpuff1"
## [532] "peachpuff2" "peachpuff3" "peachpuff4"
## [535] "peru" "pink" "pink1"
## [538] "pink2" "pink3" "pink4"
## [541] "plum" "plum1" "plum2"
## [544] "plum3" "plum4" "powderblue"
## [547] "purple" "purple1" "purple2"
## [550] "purple3" "purple4" "red"
## [553] "red1" "red2" "red3"
## [556] "red4" "rosybrown" "rosybrown1"
## [559] "rosybrown2" "rosybrown3" "rosybrown4"
## [562] "royalblue" "royalblue1" "royalblue2"
## [565] "royalblue3" "royalblue4" "saddlebrown"
## [568] "salmon" "salmon1" "salmon2"
## [571] "salmon3" "salmon4" "sandybrown"
## [574] "seagreen" "seagreen1" "seagreen2"
## [577] "seagreen3" "seagreen4" "seashell"
## [580] "seashell1" "seashell2" "seashell3"
## [583] "seashell4" "sienna" "sienna1"
## [586] "sienna2" "sienna3" "sienna4"
## [589] "skyblue" "skyblue1" "skyblue2"
## [592] "skyblue3" "skyblue4" "slateblue"
## [595] "slateblue1" "slateblue2" "slateblue3"
## [598] "slateblue4" "slategray" "slategray1"
## [601] "slategray2" "slategray3" "slategray4"
## [604] "slategrey" "snow" "snow1"
## [607] "snow2" "snow3" "snow4"
## [610] "springgreen" "springgreen1" "springgreen2"
## [613] "springgreen3" "springgreen4" "steelblue"
## [616] "steelblue1" "steelblue2" "steelblue3"
## [619] "steelblue4" "tan" "tan1"
## [622] "tan2" "tan3" "tan4"
## [625] "thistle" "thistle1" "thistle2"
## [628] "thistle3" "thistle4" "tomato"
## [631] "tomato1" "tomato2" "tomato3"
## [634] "tomato4" "turquoise" "turquoise1"
## [637] "turquoise2" "turquoise3" "turquoise4"
## [640] "violet" "violetred" "violetred1"
## [643] "violetred2" "violetred3" "violetred4"
## [646] "wheat" "wheat1" "wheat2"
## [649] "wheat3" "wheat4" "whitesmoke"
## [652] "yellow" "yellow1" "yellow2"
## [655] "yellow3" "yellow4" "yellowgreen"
Ajuste de los contenedores
- Ajustando el número de bins a través del argumento
bins. Usando este método especificamos el número de contenedores.
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_histogram(bins = 8, color = "gray", fill = "lightblue") +
theme_classic()
- Ajustando el ancho de los contenedores a través del argumento
binwidth. Con el segundo método, en lugar de especificar el número de bins, especificamos el ancho de los bins. Por ejemplo, establezcamos el ancho de cada contenedor en cien milímetros.
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_histogram(binwidth = 100, color = "red", fill = "blue") +
theme_classic()
Polígono de frecuencias
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_freqpoly(binwidth = 100)
Combinamos un histograma con un polígono de frecuencias
ggplot(PP_77_22, aes(PRECIPITACION)) +
geom_histogram(binwidth = 100, color = "yellow") +
geom_freqpoly(binwidth = 100, color = "red", linewidth = 1.5)
Gráfico de cajas
MANDARINAS <- read_excel("MANDARINAS_2024.xlsx")str(MANDARINAS)## tibble [419 × 8] (S3: tbl_df/tbl/data.frame)
## $ N : num [1:419] 1 2 3 4 5 6 7 8 9 10 ...
## $ GRUPO : num [1:419] 1 1 1 1 1 1 1 1 1 1 ...
## $ VARIEDAD : chr [1:419] "Clementina" "Clementina" "Clementina" "Clementina" ...
## $ N_DE_FRUTO : num [1:419] 19 9 21 8 4 30 22 23 17 27 ...
## $ PESO : num [1:419] 101 122 127 126 37 139 140 130 138 142 ...
## $ DIAM_ECUAT : num [1:419] 64.2 64.2 64.7 64.9 65.9 66.4 67.1 67.5 68.2 68.2 ...
## $ NIVEL_DE_DAÑO: num [1:419] 1 0 3 3 2 2 3 1 2 2 ...
## $ COLOR : num [1:419] 4 5 4 1 5 4 4 3 3 4 ...ggplot(MANDARINAS, aes(DIAM_ECUAT, VARIEDAD)) +
geom_boxplot()
ggplot(MANDARINAS, aes(DIAM_ECUAT, VARIEDAD, color = VARIEDAD)) +
geom_boxplot()
¿Y si agregamos la media muestral?
ggplot(MANDARINAS, aes(DIAM_ECUAT, VARIEDAD, color = VARIEDAD)) +
geom_boxplot() +
stat_summary(fun = mean, color = "black") # función para agregar la media muestral y asignarle color## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_segment()`).