How to list the available data sets in R

Problem

We want to list the available data sets in R.

Solution

1. List all available data sets

data()

Data sets in package ‘datasets’:

AirPassengers           Monthly Airline Passenger Numbers 1949-1960
BJsales                 Sales Data with Leading Indicator
BJsales.lead (BJsales)
                        Sales Data with Leading Indicator
BOD                     Biochemical Oxygen Demand
CO2                     Carbon Dioxide Uptake in Grass Plants
ChickWeight             Weight versus age of chicks on different diets
DNase                   Elisa assay of DNase
EuStockMarkets          Daily Closing Prices of Major European Stock
                        Indices, 1991-1998
Formaldehyde            Determination of Formaldehyde
HairEyeColor            Hair and Eye Color of Statistics Students
...                    ...

2. List all available data sets, including those packages not currently loaded.

data(package = .packages(all.available = TRUE))

Data sets in package ‘aqp’:

amarillo                Amarillo Soils
ca630                   Soil Data from the Central Sierra Nevada Region
                        of California
munsell                 Munsell to sRGB Lookup Table for Common Soil
                        Colors
rruff.sample            Sample XRD Patterns
soil_minerals           Munsell Colors of Common Soil Minerals
sp1                     Soil Profile Data Example 1
sp2                     Honcut Creek Soil Profile Data
sp3                     Soil Profile Data Example 3
sp4                     Soil Chemical Data from Serpentinitic Soils of
                        California
sp5                     Sample Soil Database #5
sp6                     Soil Physical and Chemical Data from
                        Manganiferous Soils

Data sets in package ‘beeswarm’:

breast                  Lymph-node-negative primary breast tumors

3. List all available data sets of a specific package

data(package = "ISLR")

Data sets in package ‘ISLR’:

Auto                    Auto Data Set
Caravan                 The Insurance Company (TIC) Benchmark
Carseats                Sales of Child Car Seats
College                 U.S. News and World Report's College Data
Credit                  Credit Card Balance Data
Default                 Credit Card Default Data
Hitters                 Baseball Data
Khan                    Khan Gene Data
NCI60                   NCI 60 Data
OJ                      Orange Juice Data
Portfolio               Portfolio Data
Smarket                 S&P Stock Market Data
Wage                    Mid-Atlantic Wage Data
Weekly                  Weekly S&P Stock Market Data

References

• data{utils}

Increase the number of recent workbooks shown in Excel

Problem

By default Excel shows a list of the last 25 workbooks opened. How can we increase that number?

Solution

Click File, Options, Advanced, scroll down to the Display section, and increase the number of recent workbooks (the maximum is 50).

Create, modify and delete validation lists in Excel with VBA

Problem

We want to create, edit or delete validation lists in Excel using VBA.

Solución

• Creating a validation list

For the range $A$2:$A$5 we create a validation list based on $C$2:$C$5.

Sub Create_list()
    With Range("$A$2:$A$5").Validation
        .Delete
        .Add Type:=xlValidateList, _
        AlertStyle:=xlValidAlertStop, Operator:= _
        xlBetween, Formula1:="=$C$2:$C$5"
    End With
End Sub


• Modifying a validation list

For the range $A$2:$A$5 we modify the validation list source now based on $E$2:$E$5.

Sub Modify_list()
    With Range("$A$2:$A$5").Validation
        .Delete
        .Add Type:=xlValidateList, _
        AlertStyle:=xlValidAlertStop, Operator:= _
        xlBetween, Formula1:="=$E$2:$E$5"
    End With
End Sub


• Deleting a validation list

We delete the validation lists for the specified range.

Sub Delete_list()
    With Range("$A$2:$A$5").Validation
        .Delete        
    End With
End Sub

If instead of a range, we'd like to apply the code to a selection:

'Replace Range("$A$2:$A$5").Validation for
Selection.Validation

References

• Validation.Modify method

Crear, borrar y editar listas de validación en Excel con VBA

Problema

Queremos crear, editar o borrar listas de validación en Excel mediante VBA.

Solución

• Creación de una lista de validación - Creamos para el rango $A$2:$A$5 una lista de validación basada en $C$2:$C$5.

Sub Crear_lista()
    With Range("$A$2:$A$5").Validation
        .Delete
        .Add Type:=xlValidateList, _
        AlertStyle:=xlValidAlertStop, Operator:= _
        xlBetween, Formula1:="=$C$2:$C$5"
    End With
End Sub


• Edición de una lista de validación - Editamos el rango con la nueva lista de validación, en nuestro ejemplo $E$2:$E$5.

Sub Editar_lista()
    With Range("$A$2:$A$5").Validation
        .Delete
        .Add Type:=xlValidateList, _
        AlertStyle:=xlValidAlertStop, Operator:= _
        xlBetween, Formula1:="=$E$2:$E$5"
    End With
End Sub


• Borramos la lista de validación del rango - Borramos las listas de validación del rango seleccionado.

Sub Borrar_lista()
    With Range("$A$2:$A$5").Validation
        .Delete        
    End With
End Sub

Si en lugar de un rango queremos aplicarlo una selección:

'Reemplazamos Range("$A$2:$A$5").Validation por 
Selection.Validation

Get Windows user name in VBA

Problem

We'd like to retrieve the current Windows user name in VBA. For instance, based on that value, we could track access, enable login, or personalize the information displayed in our files.

Solution

1. We open the Microsoft Visual Basic Editor: Alt+F11.
2. We copy the following subroutine.

Sub username()
MsgBox Environ("UserName")
End Sub

3. We run it pressing F5.
4. A message box will display the name of the current user.

We can type the following expression into the Immediate window:

?Environ("Username")

We can store the user name in a cell.

Sub usuario()
Sheets("Hoja1").Range("A1") = Environ("UserName")
End Sub

How to remove space between axis and plot area in ggplot2

Problem

We want to remove the space between the axis and the plotting area. The space between the axis and the tick marks.

# data
set.seed(0)
the.df <- data.frame( x = rnorm(800, 50, 10), group = rep(letters[1:8], each = 100))

# Original plot
p <- ggplot(the.df) + 
  stat_density(aes(x = x, linetype = group), geom = "line", position = "identity") +
  xlim(10, 90) + ylim(0, 0.06) +
  scale_linetype_manual(values = c("11", "12", "13", "14", "21", "22", "23", "24")) +
  geom_segment(aes(x = 10, y = 0, xend = 90, yend = 0)) +
  geom_segment(aes(x = 10, y = 0, xend = 10, yend = 0.06))

Solution

Two alternatives

Scale continuous an expand

Instead of xlim(10, 90) + ylim(0, 0.06) we use a continous scale for both axis scale_x_continuous y scale_x_continuous, specifying expand = c(0, 0).

p <- ggplot(the.df) + 
  stat_density(aes(x = x, linetype = group), geom = "line", position = "identity") +
  scale_linetype_manual(values = c("11", "12", "13", "14", "21", "22", "23", "24")) +
  scale_x_continuous(limits=c(10, 90), expand = c(0, 0)) +
  scale_y_continuous(limits=c(0, 0.06), expand = c(0, 0)) +
  geom_segment(aes(x = 10, y = 0, xend = 90, yend = 0)) +
  geom_segment(aes(x = 10, y = 0, xend = 10, yend = 0.06))

coord_cartesian

We can user coord_cartesian instead of scale_x_continuous y scale_x_continuous.

p <- ggplot(the.df) + 
  stat_density(aes(x = x, linetype = group), geom = "line", position = "identity") +
  scale_linetype_manual(values = c("11", "12", "13", "14", "21", "22", "23", "24")) +
  geom_segment(aes(x = 10, y = 0, xend = 90, yend = 0)) +
  geom_segment(aes(x = 10, y = 0, xend = 10, yend = 0.06))+
  coord_cartesian(xlim = c(10, 90), ylim = c(0, .06))

Another example

uniq <- structure(list(year = c(1986L, 1987L, 1991L, 1992L, 1993L, 1994L, 1995L, 1996L, 1997L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 1986L, 1987L, 1991L, 1992L, 1993L, 1994L, 1995L, 1996L, 1997L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 1986L, 1987L, 1991L, 1992L, 1993L, 1994L, 1995L, 1996L, 1997L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L), uniq.loc = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("u.1", "u.2", "u.3"), class = "factor"), uniq.n = c(1, 1, 1, 2, 5, 4, 2, 16, 16, 10, 15, 14, 8, 12, 20, 11, 17, 30, 17, 21, 22, 19, 34, 44, 56, 11, 0, 0, 3, 3, 7, 17, 12, 21, 18, 10, 12, 9, 7, 11, 25, 14, 11, 17, 12, 24, 59, 17, 36, 50, 59, 12, 0, 0, 0, 1, 4, 6, 3, 3, 9, 3, 4, 2, 5, 2, 12, 6, 8, 8, 3, 2, 9, 5, 20, 7, 10, 8), uniq.p = c(100, 100, 25, 33.3, 31.2, 14.8, 11.8, 40, 37.2, 43.5, 48.4, 56, 40, 48, 35.1, 35.5, 47.2, 54.5, 53.1, 44.7, 24.4, 46.3, 37.8, 43.6, 44.8, 35.5, 0, 0, 75, 50, 43.8, 63, 70.6, 52.5, 41.9, 43.5, 38.7, 36, 35, 44, 43.9, 45.2, 30.6, 30.9, 37.5, 51.1, 65.6, 41.5, 40, 49.5, 47.2, 38.7, 0, 0, 0, 16.7, 25, 22.2, 17.6, 7.5, 20.9, 13, 12.9, 8, 25, 8, 21.1, 19.4, 22.2, 14.5, 9.4, 4.3, 10, 12.2, 22.2, 6.9, 8, 25.8)), .Names = c("year", "uniq.loc", "uniq.n", "uniq.p"), class = "data.frame", row.names = c(NA, -78L))

Original plot

ggplot(data = uniq) + 
  geom_area(aes(x = year, y = uniq.p, fill = uniq.loc), stat = "identity", position = "stack") +
  scale_x_continuous(limits=c(1986,2014)) +
  scale_y_continuous(limits=c(0,101)) +
  theme_bw()

Plot without spaces

# Scale_x_continuous y expand = c(0, 0)
ggplot(data = uniq) + 
  geom_area(aes(x = year, y = uniq.p, fill = uniq.loc), stat = "identity", position = "stack") +
  scale_x_continuous(limits=c(1986,2014), expand = c(0, 0)) +
  scale_y_continuous(limits=c(0,101), expand = c(0, 0)) +
  theme_bw() + theme(panel.grid=element_blank(), panel.border=element_blank())

 # coord_cartesian
ggplot(data = uniq) +  
  geom_area(aes(x = year, y = uniq.p, fill = uniq.loc), stat = "identity", position = "stack") +  
  coord_cartesian(xlim = c(1986,2014), ylim = c(0,101))+
  theme_bw() + theme(panel.grid=element_blank(), panel.border=element_blank())

References

• How to remove extra space beyond xlim and ylim in ggplot?
• How to remove space between axis & area-plot in ggplot2?

How to change the stacking order in a stacked bar chart in ggplot2

Problem

We want to control the stacking order of a stacked bar created with ggplot2.

• Original chart
By default the bars are stacked in alphabetical order based on the variable passed on to the argument fill.

library(reshape2)
library(ggplot2)
ra.melt <- melt(ra)
p <- ggplot(ra.melt, aes(x = variable, y = value))
p + geom_bar(aes(fill = quality), stat = "identity") + 
  labs(x = "group", y = "percentage (%)")

We double-check the levels of the variable quality.

levels(ra.melt$quality)

 [1] "A"     "B"     "C"     "D"     "E"     "F"    
 [7] "G"     "H"     "I"     "J"     "K"     "L"    
[13] "M"     "other"

• Data

ra <- structure(list(quality = structure(c(2L, 6L, 13L, 1L, 7L, 5L, 
10L, 4L, 3L, 9L, 11L, 12L, 8L, 14L), .Label = c("A", "B", "C", 
"D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "other"), class = "factor"), GY = c(25.5932389, 13.9567819, 11.7333, 8.6439, 7.8351008, 
    8.29, 6.059643, 3.8608517, 4.3277, 3.1710598, 1.2021144, 
    1.0986329, 0.9369271, 3.2907496), TH = c(23.0215577, 15.8975387, 
    10.5075, 7.8888, 8.8121504, 8.276, 6.4356378, 3.9147685, 
    5.4838, 3.9339386, 1.3921565, 0.742406, 0.8795013, 2.8142444
    ), SZ = c(21.217152, 16.0363831, 11.154, 8.5094, 7.945884, 
    10.2717, 5.4962929, 4.1381946, 5.1141, 3.4053352, 1.8472827, 
    1.0648934, 0.9792861, 2.820096), DZ = c(23.7548859, 14.4732136, 
    12.1292, 10.4722, 8.0838209, 7.0575, 5.144598, 4.174118, 
    5.4004, 3.1940577, 1.4427867, 1.1323864, 0.8986281, 2.6422047
    ), FP = c(19.9848602, 16.420735, 12.9683, 11.2059, 7.5143706, 
    6.8747, 5.8653262, 5.5412901, 4.182, 3.5347168, 1.3838249, 
    0.8811604, 0.8585596, 2.7842562)), .Names = c("quality", 
"GY", "TH", "SZ", "DZ", "FP"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14"))

   quality         GY         TH         SZ         DZ         FP
1        B 25.5932389 23.0215577 21.2171520 23.7548859 19.9848602
2        F 13.9567819 15.8975387 16.0363831 14.4732136 16.4207350
3        M 11.7333000 10.5075000 11.1540000 12.1292000 12.9683000
4        A  8.6439000  7.8888000  8.5094000 10.4722000 11.2059000
5        G  7.8351008  8.8121504  7.9458840  8.0838209  7.5143706
6        E  8.2900000  8.2760000 10.2717000  7.0575000  6.8747000
7        J  6.0596430  6.4356378  5.4962929  5.1445980  5.8653262
8        D  3.8608517  3.9147685  4.1381946  4.1741180  5.5412901
9        C  4.3277000  5.4838000  5.1141000  5.4004000  4.1820000
10       I  3.1710598  3.9339386  3.4053352  3.1940577  3.5347168
11       K  1.2021144  1.3921565  1.8472827  1.4427867  1.3838249
12       L  1.0986329  0.7424060  1.0648934  1.1323864  0.8811604
13       H  0.9369271  0.8795013  0.9792861  0.8986281  0.8585596
14   other  3.2907496  2.8142444  2.8200960  2.6422047  2.7842562

Solution

• Stacked in the data frame's original order

ra.melt$quality <- factor(ra.melt$quality, levels = ra$quality)
p <- ggplot(ra.melt, aes(x = variable, y = value))
p + geom_bar(aes(fill = quality), stat = "identity") + 
    labs(x = "group", y = "percentage (%)")

factor(ra.melt$quality, levels = ra$quality)

 [1] B     F     M     A     G     E     J     D    
 [9] C     I     K     L     H     other B     F    
[17] M     A     G     E     J     D     C     I    
[25] K     L     H     other B     F     M     A    
[33] G     E     J     D     C     I     K     L    
[41] H     other B     F     M     A     G     E    
[49] J     D     C     I     K     L     H     other
[57] B     F     M     A     G     E     J     D    
[65] C     I     K     L     H     other
Levels: B F M A G E J D C I K L H other

• In reverse order

ra.melt$quality <- factor(ra.melt$quality, levels = rev(ra$quality))
p <- ggplot(ra.melt, aes(x = variable, y = value))
p + geom_bar(aes(fill = quality), stat = "identity") +  
    labs(x = "group", y = "percentage (%)")

factor(ra.melt$quality, levels = rev(ra$quality))

 [1] B     F     M     A     G     E     J     D    
 [9] C     I     K     L     H     other B     F    
[17] M     A     G     E     J     D     C     I    
[25] K     L     H     other B     F     M     A    
[33] G     E     J     D     C     I     K     L    
[41] H     other B     F     M     A     G     E    
[49] J     D     C     I     K     L     H     other
[57] B     F     M     A     G     E     J     D    
[65] C     I     K     L     H     other
Levels: other H L K I C D J E G A M F B

Alternatively we can use the function fct_rev

library(forcats)
p <- ggplot(ra.melt, aes(x = variable, y = value))
p + geom_bar(aes(fill = fct_rev(quality)), stat = "identity") + 
  labs(x = "group", y = "percentage (%)")

• If we'd like to reverse the stacked order but but keeping the order of the legend, we use the argument position_stack(reverse = TRUE)

p <- ggplot(ra.melt, aes(x = variable, y = value))
p + geom_bar(aes(fill = fct_rev(quality)), stat = "identity", position = position_stack(reverse = TRUE)) + labs(x = "group", y = "percentage (%)")

Referencias

• geom_bar
• stacking bars
• stackoverflow

Related posts

• How to reorder bar charts with ggplot2

Cómo reordenar diagramas de barras en ggplot2

Problema

Queremos reodernar las barras de un diagrama de barras creado con ggplot2. En nuestro ejemplo, se puede observar que las barras no están ni en orden ascendente o descendente.

library(tidyverse)
ggplot(df, aes(x = Position)) + geom_bar()

Data frame

df <- structure(list(Position = structure(c(3L, 3L, 1L, 1L, 1L, 2L), .Label = c("Defense", 
"Striker", "Zoalkeeper"), class = "factor"), Name = structure(c(2L, 
1L, 3L, 5L, 4L, 6L), .Label = c("Frank", "James", "Jean", "John", 
"Steve", "Tim"), class = "factor")), class = "data.frame", row.names = c(NA, 
-6L))

    Position  Name
1 Zoalkeeper James
2 Zoalkeeper Frank
3    Defense  Jean
4    Defense Steve
5    Defense  John
6    Striker   Tim

Solución

Una alternativa es usar reorder para reordenar los niveles del factor. En orden ascendente (n) o descendente (-n) en función del conteo de la columna Position.

• Orden ascendente

df %>%
  count(Position) %>%
  ggplot(aes(x = reorder(Position, n), y = n)) +
  geom_bar(stat = 'identity') +
  xlab("Position")

• Orden descendente

df %>%
  count(Position) %>%
  ggplot(aes(x = reorder(Position, -n), y = n)) +
  geom_bar(stat = 'identity') +
  xlab("Position")

Entradas relacionadas

• Cambiar el orden de un diagrama de barras apiladas con ggplot2

Referencias

• stackoverflow