Nube de datos: mayo 2019

2019-05-23

How to apply a function across rows in R

Problem

We'd like to apply a function across rows in R. In our example, we will add two columns calculating the minimum and the median for each row.

df <- structure(list(V1 = c(5L, 4L, 7L), V2 = c(8L, 9L, 3L), V3 = c(12L, 
5L, 9L)), .Names = c("V1", "V2", "V3"), class = "data.frame", row.names = c(NA, 
-3L))

Solution

dplyr

library(dplyr)
# Using the piper operator %>%
df %>% 
  rowwise() %>% 
  mutate(min= min(V1, V2, V3), median = median(c(V1, V2, V3)))
# Without the pipe operator %>%
mutate(rowwise(df), min = min(V1, V2, V3), median = median(c(V1, V2, V3)))

Source: local data frame [3 x 5]
Groups: 

     V1    V2    V3   min median
  (int) (int) (int) (int)  (int)
1     5     8    12     5      8
2     4     9     5     4      5
3     7     3     9     3      7

Base R

df$min <- apply(df, 1, min)
df$median <- apply(df[, 1:3], 1, median)

  V1 V2 V3 min median
1  5  8 12   5      8
2  4  9  5   4      5
3  7  3  9   3      7

Spanish version

References

stackoverflow

2019-05-11

How to create boxplots grouping into intervals x-axis values using R?

Problem

We want to create boxplots grouping into intervals the values of the x-axis, like in the example below.

Solution

Data

We generate random data and a sequence to create the intervals.

set.seed(12)
y <- rnorm(1000)
x <- rnorm(1000)
rng <- seq(-3, 3, 0.5)

Base

boxplot(y ~ cut(x, breaks = rng),las=2)

If we'd like to include not available data (NAs), we use the function addNA:

boxplot(y ~ addNA(cut(x, breaks = rng)), las = 2)

ggplot2

First we create data frame with the intervals.

library(ggplot2)
df <- data.frame(x = cut(x, breaks = rng), y = y)
ggplot(data = df, aes(x = x, y = y)) + geom_boxplot(aes(fill = x))

Spanish version

References

stackoverflow

2019-05-09

How to make barplot bars with the same bar width in R

Title

Problem

We have three barplots with a different number of bars in each of them, and we want them to have the same bar width.

par(mfrow=c(1,3));
par(mar=c(9,6,4,2)+0.1);
barcenter1<- barplot(c(1,2,3,4,5));
mtext("Average Emergent", side=2, line=4);
par(mar=c(9,2,4,2)+0.1);
barcenter2<- barplot(c(1,2,3));
par(mar=c(9,2,4,2)+0.1);
barcenter3<- barplot(c(1,2,3,4,5,6,7));

Solution

First try

Using the arguments xlim = c(0, 1), width = 0.1 the problem is partially corrected. However, you can notice that the bar width is not exactly the same.

width - optional vector of bar widths. Re-cycled to length the number of bars drawn. Specifying a single value will have no visible effect unless xlim is specified.

par(mfrow = c(1, 3))
par(mar = c(9, 6, 4, 2) + 0.1)
barcenter1 <- barplot(c(1, 2, 3, 4, 5), xlim = c(0, 1), width = 0.1)
mtext("Average Emergent", side = 2, line = 4)
par(mar = c(9, 2, 4, 2) + 0.1)
barcenter2 <- barplot(c(1, 2, 3), xlim = c(0, 1), width = 0.1)
par(mar = c(9, 2, 4, 2) + 0.1)
barcenter1 <- barplot(c(1, 2, 3, 4, 5, 6, 7), xlim = c(0, 1), width = 0.1)

Second try/li>

We add zeros as placeholders.

par(mfrow = c(1, 1)) # Reiniciamos los parámetros gráficos
df <- data.frame(barcenter1 = c(1, 2, 3, 4, 5, 0, 0), 
                 barcenter2 = c(1, 2, 3, 0, 0, 0, 0), 
                 barcenter3 = c(1, 2, 3, 4, 5, 6, 7))
barplot(as.matrix(df), beside = TRUE)

With ggplot2:

df <- data.frame(x = c(1, 2, 3, 4, 5, 1, 2, 3, 1, 2, 3, 4, 5, 6, 7), 
                 y = c(rep("bar1", 5), rep("bar2", 3), rep("bar3", 7)))                                                                                         
library(ggplot2)
ggplot(data = df, aes(x = x, y = x)) + 
  geom_bar(stat = "identity") + 
  facet_grid(~y)

Alternative

If instead of three separate barplots we'd like to plot them with an empty space between them, we plot a single barplot with two NAs as delimiters. Si en lugar de tres gráficos propiamente dichos queremos mostrarlos sin que haya separación por las barras en blanco entre ellas, creamos un gráfico único con espacio con dos separaciones por NAs.

x <- c(1, 2, 3, 4, 5, NA, 1, 2, 3, NA, 1, 2, 3, 4, 5, 6, 7)
barplot(x)

References

2019-05-07

Plot a continuous series with ggplot2

Problem

When we try to plot a continuous series, in our example WS (Winter Solstice), ggplot2 connects the last winter data point in March to the first winter data point in December.

Data

library(ggplot2)

getSeason <- function(DATES) {
#found here https://stackoverflow.com/questions/9500114/find-which-season-a-particular-date-belongs-to
WS <- as.Date("2012-12-15", format = "%Y-%m-%d") # Winter Solstice
SE <- as.Date("2012-3-15",  format = "%Y-%m-%d") # Spring Equinox
SS <- as.Date("2012-6-15",  format = "%Y-%m-%d") # Summer Solstice
FE <- as.Date("2012-9-15",  format = "%Y-%m-%d") # Fall Equinox

# Convert dates from any year to 2012 dates
d <- as.Date(strftime(DATES, format="2012-%m-%d"))

ifelse (d >= WS | d < SE, "Winter",
  ifelse (d >= SE & d < SS, "Spring",
    ifelse (d >= SS & d < FE, "Summer", "Fall")))
}

zz <- sample(1:10000,365)/1000
dag <- seq(as.Date("2014-01-01"), as.Date("2014-12-31"), by = "day")
seas <-  getSeason(dag)
test <- data.frame(zz,dag,seas)

ggplot(data=test, aes(x=dag,ymax=zz,ymin=0,fill=seas))+
geom_ribbon()

Solution

We can solve it by subsetting our data in two, above and below WS, and plotting two layers with geom_ribbon. Thus you convert the continuous WS series into two discrete sections.

library(dplyr)
ggplot() +
  geom_ribbon(data = filter(test, dag >= "2014-12-15") ,
              aes(x = dag, ymax = zz, ymin = 0, fill = seas)) +
  geom_ribbon(data = filter(test, dag < "2014-12-15") ,
              aes(x = dag, ymax = zz, ymin = 0, fill = seas))

Results

References

2019-05-06

Filter between two dates in R with dplyr

Problem

We'd like to filter between two dates in R using the package dplyr.

    Patch       Date Prod_DL
1    BVG1   9/4/2015    3.43
2   BVG11  9/11/2015    3.49
3   BVG12  9/18/2015    3.45
4   BVG13  12/6/2015    3.57
5   BVG14 12/13/2015    3.43
6   BVG15 12/20/2015    3.47

Data

df <- read.table(
  text = "Patch,Date,Prod_DL
  BVG1,9/4/2015,3.43
  BVG11,9/11/2015,3.49
  BVG12,9/18/2015,3.45
  BVG13,12/6/2015,3.57
  BVG14,12/13/2015,3.43
  BVG15,12/20/2015,3.47",
  sep = ",",
  stringsAsFactors = FALSE,
  header = TRUE,
  row.names = NULL
)

Solution

Alternative 1

We properly format the column containing the dates, originally a character column, and filter between the two dates.

library("dplyr")
df$Date <-as.Date(df$Date,"%m/%d/%Y")
df %>%
  select(Patch, Date, Prod_DL) %>%
  filter(Date > "2015-09-04" & Date < "2015-09-18")

    Patch       Date Prod_DL
1   BVG11 2015-09-11    3.49

Alternative 2

We properly format the column containing the dates and use the function between: 'This is a shortcut for x >= left & x <= right, implemented efficiently in C++ for local values, and translated to the appropriate SQL for remote tables.' We need to change the days to account for the = sign on both sides, and to use as.Date, explanation here.

df$Date <- as.Date(df$Date, "%m/%d/%Y")
df %>% 
  select(Patch, Date, Prod_DL) %>%
  filter(between(Date, as.Date("2015-09-05"), as.Date("2015-09-17")))

    Patch       Date Prod_DL
1   BVG11 2015-09-11    3.49

Spanish version

References

stackoverflow

2019-05-04

Read data from URL in R

Problem

How can we read data from an URL in R? We have a URL pointing to a text file, and we'd like to read it directly in R without previously downloading it to our computer.

http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv

Solution

We just need to pass the URL string inside the appropriate function. Apart from read.csv from the base package, I include a couple of examples from two popular packages: data.table y readr.

Base

ad <- read.csv("http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv")
head(ad)

  X    TV radio newspaper sales
1 1 230.1  37.8      69.2  22.1
2 2  44.5  39.3      45.1  10.4
3 3  17.2  45.9      69.3   9.3
4 4 151.5  41.3      58.5  18.5
5 5 180.8  10.8      58.4  12.9
6 6   8.7  48.9      75.0   7.2

data.table

library(data.table)
ad <- fread("http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv")
head(ad)

V1    TV radio newspaper sales
1:  1 230.1  37.8      69.2  22.1
2:  2  44.5  39.3      45.1  10.4
3:  3  17.2  45.9      69.3   9.3
4:  4 151.5  41.3      58.5  18.5
5:  5 180.8  10.8      58.4  12.9
6:  6   8.7  48.9      75.0   7.2

readr

library(readr)
ad <- read_csv("http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv")
head(ad)

# A tibble: 6 x 5
     X1    TV radio newspaper sales
          
1     1 230.1  37.8      69.2  22.1
2     2  44.5  39.3      45.1  10.4
3     3  17.2  45.9      69.3   9.3
4     4 151.5  41.3      58.5  18.5
5     5 180.8  10.8      58.4  12.9
6     6   8.7  48.9      75.0   7.2

Spanish version

References

2019-05-03

Drop unused levels from a factor in R

Problem

If we filter a data frame containing a factor and then perform any operation, such as creating a contingency table, R will still show the unused levels. Subsetting does not in general drop unused levels.

df <- data.frame(name = c("a", "a", "a", "b", "b", "c", "c", "c", "c"), x = 1:9)
library(dplyr)
aa <-  df %>%
  group_by(name) %>%
  filter(n() < 4) %>% 
  droplevels()
table(aa$name)

In our example, the level c is still included in the results. We'd like to remove it and display only the used levels a and b.

# Resultado
a b c 
3 2 0
# Resultado deseado
a b 
3 2

Solution

There are two alternatives, the function droplevels or factor.

table(droplevels(aa$name))
table(factor(aa$name))

If we are using dplyr and the pipe operator:

aa <-  df %>%
  group_by(name) %>%
  filter(n() < 4) %>% 
  droplevels()
table(aa$name)

# Better still
df %>%
  group_by(name) %>%
  filter(n() < 4) %>% 
  droplevels() %>% 
  {table(.$name)}

Spanish version

2019-05-23

Problem

Solution

Related posts

References

2019-05-11

Problem

Solution

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2019-05-09

Problem

Solution

References

2019-05-07

Problem

Solution

Results

References

2019-05-06

Problem

Solution

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References

2019-05-04

Problem

Solution

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References

2019-05-03

Problem

Solution

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References