I am just learning data wrangling. Currently I am data wrangling a data frame of 6422 observation and 20 variables.
I have added an example to show my problem. I have several columns which have identical cases, which i want to summarize to 1 case (in the example column x1,x2,x3,x4 and row 1,2,3). The corresponding columns value1 (in the example 1,2,3) and value2 (in the example 7,8,9) should be manipulated in such a way that they are transformed into the same row.
My goal is to manipulate the data frame df1 into the data frame df7
df1 <- data.frame(x1,x2,x3,x4,stats.title,value1,value2)
# x1 x2 x3 x4 stats.title value1 value2
#1 A B C D I 1 7
#2 A B C D J 2 8
#3 A B C D K 3 9
#4 E F G H I 4 10
#5 E F G H J 5 11
#6 E F G H K 6 12
df 7 <- rbind(df5,df6)
# x1 x2 x3 x4 value1_I value1_J value1_K value2_I value2_J value2_K
#1 A B C D 1 2 3 7 8 9
#4 E F G H 4 5 6 10 11 12
Attached the example:
library(magrittr)
library(dplyr)
library(tidyr)
x1 <- rep(c("A","E"), each=3)
x2<- rep(c("B","F"), each=3)
x3<- rep(c("C","G"), each=3)
x4<- rep(c("D","H"), each=3)
stats.title <- rep(c("I","J","K"), times=2)
value1 <- (1:6)
value2 <- (7:12)
df1 <- data.frame(x1,x2,x3,x4,stats.title,value1,value2)
# x1 x2 x3 x4 stats.title value1 value2
#1 A B C D I 1 7
#2 A B C D J 2 8
#3 A B C D K 3 9
#4 E F G H I 4 10
#5 E F G H J 5 11
#6 E F G H K 6 12
df2 <- df1[1,] %>% select(-stats.title,-value1,-value2)
# x1 x2 x3 x4
#1 A B C D
df2.1 <- df1[4,] %>% select(-stats.title,-value1,-value2)
# x1 x2 x3 x4
#4 E F G H
df3 <- df1 %>% select(stats.title,value1,value2)
# stats.title value1 value2
#1 I 1 7
#2 J 2 8
#3 K 3 9
#4 I 4 10
#5 J 5 11
#6 K 6 12
df4 <- pivot_wider(df3[1:3,], names_from = stats.title, values_from = c("value1","value2"))
df4 <- as.data.frame(df4)
df4.1 <- pivot_wider(df3[4:6,], names_from = stats.title, values_from = c("value1","value2"))
df4.1 <- as.data.frame(df4.1)
df5 <- data.frame(df2,df4)
df6 <- data.frame(df2.1,df4.1)
df 7 <- rbind(df5,df6)
# x1 x2 x3 x4 value1_I value1_J value1_K value2_I value2_J value2_K
#1 A B C D 1 2 3 7 8 9
#4 E F G H 4 5 6 10 11 12
Thanks for the help in advance.
I tried the example shown above. Due to the fact that i have 6422 rows, i am searching for an effective way to manipulate the data frame.