OUr task is to bring a dataframe into R. I choose the 2022 World Cup Predictions database. this dataframe will include a set of predictions of all the matches of the FIFA 2022 world cup. Some of the columns in the dataframe are: -Date -league ID -League -team1 -team2 -probabilities, and projections -Scores
wc_matches <- read.csv("C:/Users/vitug/Downloads/wc_matches.csv", header=FALSE)
View(wc_matches)Now I am going to focus on the teams and the predictions of each match ##
wc_matches$V4## [1] "team1" "Qatar" "England" "Senegal" "USA"
## [6] "Argentina" "Denmark" "Mexico" "France" "Morocco"
## [11] "Germany" "Spain" "Belgium" "Switzerland" "Uruguay"
## [16] "Portugal" "Brazil" "Wales" "Qatar" "Netherlands"
## [21] "England" "Tunisia" "Poland" "France" "Argentina"
## [26] "Japan" "Belgium" "Croatia" "Spain" "Cameroon"
## [31] "South Korea" "Brazil" "Portugal" "Netherlands" "Ecuador"
## [36] "Iran" "Wales" "Tunisia" "Australia" "Poland"
## [41] "Saudi Arabia" "Canada" "Croatia" "Costa Rica" "Japan"
## [46] "Ghana" "South Korea" "Serbia" "Cameroon" "Netherlands"
## [51] "Argentina" "France" "England" "Japan" "Brazil"
## [56] "Morocco" "Portugal" "Croatia" "Netherlands" "Morocco"
## [61] "England" "Argentina" "France" "Croatia" "Argentina"wc_matches$V13## [1] "score1" "0" "6" "0" "1" "1" "0" "0"
## [9] "4" "0" "1" "7" "1" "1" "0" "3"
## [17] "2" "0" "1" "1" "0" "0" "2" "2"
## [25] "2" "0" "0" "4" "1" "3" "2" "1"
## [33] "2" "2" "1" "0" "0" "1" "1" "0"
## [41] "1" "1" "0" "2" "2" "0" "2" "2"
## [49] "1" "3" "2" "3" "3" "1" "4" "0"
## [57] "6" "1" "2" "1" "1" "3" "2" "2"
## [65] "3"This is the dataframe that I was able to pull in R console,I would recommend to rename the columns so we can pull more acurate information from the dataframe