How to merge multiple variables and create a new data set? - r

Question

https://www.kaggle.com/nowke9/ipldata ----- Contains the IPL Data.
This is exploratory study performed for the IPL data set. (link for the data attached above) After merging both the files with "id" and "match_id", I have created four more variables namely total_extras, total_runs_scored, total_fours_hit and total_sixes_hit. Now I wish to combine these newly created variables into one single data frame. When I assign these variables into one single variable namely batsman_aggregate and selecting only the required columns, I am getting an error message.
library(tidyverse)
deliveries_tbl <- read.csv("deliveries_edit.csv")
matches_tbl <- read.csv("matches.csv")
combined_matches_deliveries_tbl <- deliveries_tbl %>%
left_join(matches_tbl, by = c("match_id" = "id"))
# Add team score and team extra columns for each match, each inning.
total_score_extras_combined <- combined_matches_deliveries_tbl%>%
group_by(id, inning, date, batting_team, bowling_team, winner)%>%
mutate(total_score = sum(total_runs, na.rm = TRUE))%>%
mutate(total_extras = sum(extra_runs, na.rm = TRUE))%>%
group_by(total_score, total_extras, id, inning, date, batting_team, bowling_team, winner)%>%
select(id, inning, total_score, total_extras, date, batting_team, bowling_team, winner)%>%
distinct(total_score, total_extras)%>%
glimpse()%>%
ungroup()
# Batsman Aggregate (Runs Balls, fours, six , Sr)
# Batsman score in each match
batsman_score_in_a_match <- combined_matches_deliveries_tbl %>%
group_by(id, inning, batting_team, batsman)%>%
mutate(total_batsman_runs = sum(batsman_runs, na.rm = TRUE))%>%
distinct(total_batsman_runs)%>%
glimpse()%>%
ungroup()
# Number of deliveries played .
balls_faced <- combined_matches_deliveries_tbl %>%
filter(wide_runs == 0)%>%
group_by(id, inning, batsman)%>%
summarise(deliveries_played = n())%>%
ungroup()
# Number of 4 and 6s by a batsman in each match.
fours_hit <- combined_matches_deliveries_tbl %>%
filter(batsman_runs == 4)%>%
group_by(id, inning, batsman)%>%
summarise(fours_hit = n())%>%
glimpse()%>%
ungroup()
sixes_hit <- combined_matches_deliveries_tbl %>%
filter(batsman_runs == 6)%>%
group_by(id, inning, batsman)%>%
summarise(sixes_hit = n())%>%
glimpse()%>%
ungroup()
batsman_aggregate <- c(batsman_score_in_a_match, balls_faced, fours_hit, sixes_hit)%>%
select(id, inning, batsman, total_batsman_runs, deliveries_played, fours_hit, sixes_hit)
The error message is displayed as:-
Error: `select()` doesn't handle lists.
The required output is the data set created newly constructed variables.

Answer 1

You'll have to join those four tables, not combine using c.
And the join type is left_join so that all batsman are included in the output. Those who didn't face any balls or hit any boundaries will have NA, but you can easily replace these with 0.
I've ignored the by since dplyr will assume you want c("id", "inning", "batsman"), the only 3 common columns in all four data sets.
batsman_aggregate <- left_join(batsman_score_in_a_match, balls_faced) %>%
left_join(fours_hit) %>%
left_join(sixes_hit) %>%
select(id, inning, batsman, total_batsman_runs, deliveries_played, fours_hit, sixes_hit) %>%
replace(is.na(.), 0)
# A tibble: 11,335 x 7
id inning batsman total_batsman_runs deliveries_played fours_hit sixes_hit
<int> <int> <fct> <int> <dbl> <dbl> <dbl>
1 1 1 DA Warner 14 8 2 1
2 1 1 S Dhawan 40 31 5 0
3 1 1 MC Henriques 52 37 3 2
4 1 1 Yuvraj Singh 62 27 7 3
5 1 1 DJ Hooda 16 12 0 1
6 1 1 BCJ Cutting 16 6 0 2
7 1 2 CH Gayle 32 21 2 3
8 1 2 Mandeep Singh 24 16 5 0
9 1 2 TM Head 30 22 3 0
10 1 2 KM Jadhav 31 16 4 1
# ... with 11,325 more rows
There are also 2 batsmen who didn't face any delivery:
batsman_aggregate %>% filter(deliveries_played==0)
# A tibble: 2 x 7
id inning batsman total_batsman_runs deliveries_played fours_hit sixes_hit
<int> <int> <fct> <int> <dbl> <dbl> <dbl>
1 482 2 MK Pandey 0 0 0 0
2 7907 1 MJ McClenaghan 2 0 0 0
One of which apparently scored 2 runs! So I think the batsman_runs column has some errors. The game is here and clearly says that on the second last delivery of the first innings, 2 wides were scored, not runs to the batsman.