How to rename suffixes when joining tables in dplyr

Problem

When joining two tables with dplyr, the suffixes .x and .y will be added to the non-joined duplicate variables to disambiguate them. In our example, to the column mpg: mpg.x y mpg.y. How can override these suffixes?

library(dplyr) 
left_join(mtcars, mtcars[, c("mpg", 'cyl')], by = c("cyl")) %>% head()

Output

  mpg.x cyl disp  hp drat   wt  qsec vs am gear carb mpg.y
1    21   6  160 110  3.9 2.62 16.46  0  1    4    4  21.0
2    21   6  160 110  3.9 2.62 16.46  0  1    4    4  21.0
3    21   6  160 110  3.9 2.62 16.46  0  1    4    4  21.4
4    21   6  160 110  3.9 2.62 16.46  0  1    4    4  18.1
5    21   6  160 110  3.9 2.62 16.46  0  1    4    4  19.2
6    21   6  160 110  3.9 2.62 16.46  0  1    4    4  17.8

Solution

We can pass the argument suffix, a character vector of length 2 with the desired names. In our example, mpg_original (suffix _original) and mpg_new (suffix_new).

left_join(mtcars, mtcars[,c("mpg","cyl")], 
              by = c("cyl"), 
              suffix = c("_original", "_new")) %>% head()

Output

  mpg_original cyl disp  hp drat   wt  qsec vs am gear carb mpg_new
1           21   6  160 110  3.9 2.62 16.46  0  1    4    4    21.0
2           21   6  160 110  3.9 2.62 16.46  0  1    4    4    21.0
3           21   6  160 110  3.9 2.62 16.46  0  1    4    4    21.4
4           21   6  160 110  3.9 2.62 16.46  0  1    4    4    18.1
5           21   6  160 110  3.9 2.62 16.46  0  1    4    4    19.2
6           21   6  160 110  3.9 2.62 16.46  0  1    4    4    17.8

References

• stackoverflow
• Join two tbls together

Cómo representar una curva logarítmica en R

Problema

Queremos ajustar una curva logarítmica a un diagrama de dispersión.

library(ggplot2)
ggplot(mpg, aes(displ, hwy)) +
  geom_point()

Solución

Paquete base

plot(hwy ~ displ, mpg)
logEstimate <- lm(hwy ~ log(displ), data = mpg)
curve(coef(logEstimate)[1] + coef(logEstimate)[2] * log(x), add = TRUE)

ggplot2

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  stat_smooth(method = "lm", formula = y ~ log(x))

Referencias

• stackoverflow

How to plot a log curve in R

Problem

We want to fit a logarithmic curve to a scatterplot.

library(ggplot2)
ggplot(mpg, aes(displ, hwy)) +
  geom_point()

Solution

Base package

plot(hwy ~ displ, mpg)
logEstimate <- lm(hwy ~ log(displ), data = mpg)
curve(coef(logEstimate)[1] + coef(logEstimate)[2] * log(x), add = TRUE)

ggplot2

ggplot(mpg, aes(displ, hwy)) +
  geom_point() +
  stat_smooth(method = "lm", formula = y ~ log(x))

References

• stackoverflow

How to do cross join in R?

Problem

We want to calculate a cross join, the Cartesian product of rows from tables —or elements of a vector— in the join. In other words, we want to combine each row from the first table with each row from the second table.

Solution

Two vectors

• expand.grid

expand.grid(1:5, 1:5)

• merge

merge(1:5, 1:5)

• Cross join with sqldf

library(sqldf)
df1 <- data.frame(a = 1:5)
df2 <- df1
sqldf("SELECT df1.a, df2.a FROM df1 
      CROSS JOIN df2")

• Results

   x y
1  1 1
2  2 1
3  3 1
4  4 1
5  5 1
6  1 2
7  2 2
8  3 2
9  4 2
10 5 2
11 1 3
12 2 3
13 3 3
14 4 3
15 5 3
16 1 4
17 2 4
18 3 4
19 4 4
20 5 4
21 1 5
22 2 5
23 3 5
24 4 5
25 5 5

More than two vectors

• expand.grid.

a <- c('europe', 'asia')
b <- c('co2', 'temperature')
c <- c('min', 'max')
expand.grid(a, b, c)

    Var1        Var2 Var3
1 europe         co2  min
2   asia         co2  min
3 europe temperature  min
4   asia temperature  min
5 europe         co2  max
6   asia         co2  max
7 europe temperature  max
8   asia temperature  max

References

• Merge Two Data Frames
• Create a Data Frame from All Combinations of Factor Variables
• Generating Cartesian product of strings in R
• Getting all combinations in R, repetition allowed