options(repos = c(CRAN = "https://cloud.r-project.org"))
install.packages("dplyr")## Installing package into 'C:/Users/Usuario/AppData/Local/R/win-library/4.4'
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## C:\Users\Usuario\AppData\Local\Temp\RtmpktV7nz\downloaded_packageslibrary(dplyr)##
## Adjuntando el paquete: 'dplyr'## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
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## intersect, setdiff, setequal, unionR.version## _
## platform x86_64-w64-mingw32
## arch x86_64
## os mingw32
## crt ucrt
## system x86_64, mingw32
## status
## major 4
## minor 4.1
## year 2024
## month 06
## day 14
## svn rev 86737
## language R
## version.string R version 4.4.1 (2024-06-14 ucrt)
## nickname Race for Your LifewriteLines('PATH="${RTOOLS43_HOME}\\usr\\bin;${PATH}"', con = "~/.Renviron")
Sys.which("make")## make
## "c:\\rtools44\\usr\\bin\\make.exe"install.packages("dplyr")## Warning: package 'dplyr' is in use and will not be installedinstall.packages("readr")## Installing package into 'C:/Users/Usuario/AppData/Local/R/win-library/4.4'
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## C:\Users\Usuario\AppData\Local\Temp\RtmpktV7nz\downloaded_packageslibrary(readr)
billboard100 <- read_csv("billboard100.csv")## Rows: 330087 Columns: 7## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): song, artist
## dbl (4): rank, last-week, peak-rank, weeks-on-board
## date (1): date
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.getwd()## [1] "C:/Users/Usuario/Desktop/DIPLOMADO/Diplomado Big Data"#Piping %>%
head(billboard100,10)## # A tibble: 10 × 7
## date rank song artist `last-week` `peak-rank` `weeks-on-board`
## <date> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
## 1 2021-11-06 1 Easy On Me Adele 1 1 3
## 2 2021-11-06 2 Stay The K… 2 1 16
## 3 2021-11-06 3 Industry Ba… Lil N… 3 1 14
## 4 2021-11-06 4 Fancy Like Walke… 4 3 19
## 5 2021-11-06 5 Bad Habits Ed Sh… 5 2 18
## 6 2021-11-06 6 Way 2 Sexy Drake… 6 1 8
## 7 2021-11-06 7 Shivers Ed Sh… 9 7 7
## 8 2021-11-06 8 Good 4 U Olivi… 7 1 24
## 9 2021-11-06 9 Need To Know Doja … 11 9 20
## 10 2021-11-06 10 Levitating Dua L… 8 2 56install.packages("tidyverse")## Installing package into 'C:/Users/Usuario/AppData/Local/R/win-library/4.4'
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## C:\Users\Usuario\AppData\Local\Temp\RtmpktV7nz\downloaded_packagesinstall.packages("magrittr")## Installing package into 'C:/Users/Usuario/AppData/Local/R/win-library/4.4'
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## C:\Users\Usuario\AppData\Local\Temp\RtmpktV7nz\downloaded_packageslibrary(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## extractbillboard100 %>% head(10)## # A tibble: 10 × 7
## date rank song artist `last-week` `peak-rank` `weeks-on-board`
## <date> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
## 1 2021-11-06 1 Easy On Me Adele 1 1 3
## 2 2021-11-06 2 Stay The K… 2 1 16
## 3 2021-11-06 3 Industry Ba… Lil N… 3 1 14
## 4 2021-11-06 4 Fancy Like Walke… 4 3 19
## 5 2021-11-06 5 Bad Habits Ed Sh… 5 2 18
## 6 2021-11-06 6 Way 2 Sexy Drake… 6 1 8
## 7 2021-11-06 7 Shivers Ed Sh… 9 7 7
## 8 2021-11-06 8 Good 4 U Olivi… 7 1 24
## 9 2021-11-06 9 Need To Know Doja … 11 9 20
## 10 2021-11-06 10 Levitating Dua L… 8 2 5610 %>% head(billboard100, .)## # A tibble: 10 × 7
## date rank song artist `last-week` `peak-rank` `weeks-on-board`
## <date> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
## 1 2021-11-06 1 Easy On Me Adele 1 1 3
## 2 2021-11-06 2 Stay The K… 2 1 16
## 3 2021-11-06 3 Industry Ba… Lil N… 3 1 14
## 4 2021-11-06 4 Fancy Like Walke… 4 3 19
## 5 2021-11-06 5 Bad Habits Ed Sh… 5 2 18
## 6 2021-11-06 6 Way 2 Sexy Drake… 6 1 8
## 7 2021-11-06 7 Shivers Ed Sh… 9 7 7
## 8 2021-11-06 8 Good 4 U Olivi… 7 1 24
## 9 2021-11-06 9 Need To Know Doja … 11 9 20
## 10 2021-11-06 10 Levitating Dua L… 8 2 56#SELECT
billboard100 %>%
select(date, rank, song,artist, 'weeks-on-board')## # A tibble: 330,087 × 5
## date rank song artist `weeks-on-board`
## <date> <dbl> <chr> <chr> <dbl>
## 1 2021-11-06 1 Easy On Me Adele 3
## 2 2021-11-06 2 Stay The Kid LAROI & Justin Bieber 16
## 3 2021-11-06 3 Industry Baby Lil Nas X & Jack Harlow 14
## 4 2021-11-06 4 Fancy Like Walker Hayes 19
## 5 2021-11-06 5 Bad Habits Ed Sheeran 18
## 6 2021-11-06 6 Way 2 Sexy Drake Featuring Future & You… 8
## 7 2021-11-06 7 Shivers Ed Sheeran 7
## 8 2021-11-06 8 Good 4 U Olivia Rodrigo 24
## 9 2021-11-06 9 Need To Know Doja Cat 20
## 10 2021-11-06 10 Levitating Dua Lipa 56
## # ℹ 330,077 more rowsbillboard100 %>%
select(date:artist, weeks_popular='weeks-on-board')## # A tibble: 330,087 × 5
## date rank song artist weeks_popular
## <date> <dbl> <chr> <chr> <dbl>
## 1 2021-11-06 1 Easy On Me Adele 3
## 2 2021-11-06 2 Stay The Kid LAROI & Justin Bieber 16
## 3 2021-11-06 3 Industry Baby Lil Nas X & Jack Harlow 14
## 4 2021-11-06 4 Fancy Like Walker Hayes 19
## 5 2021-11-06 5 Bad Habits Ed Sheeran 18
## 6 2021-11-06 6 Way 2 Sexy Drake Featuring Future & Young … 8
## 7 2021-11-06 7 Shivers Ed Sheeran 7
## 8 2021-11-06 8 Good 4 U Olivia Rodrigo 24
## 9 2021-11-06 9 Need To Know Doja Cat 20
## 10 2021-11-06 10 Levitating Dua Lipa 56
## # ℹ 330,077 more rowsbillboard100 %>%
select(-'last-week', -'peak-rank')## # A tibble: 330,087 × 5
## date rank song artist `weeks-on-board`
## <date> <dbl> <chr> <chr> <dbl>
## 1 2021-11-06 1 Easy On Me Adele 3
## 2 2021-11-06 2 Stay The Kid LAROI & Justin Bieber 16
## 3 2021-11-06 3 Industry Baby Lil Nas X & Jack Harlow 14
## 4 2021-11-06 4 Fancy Like Walker Hayes 19
## 5 2021-11-06 5 Bad Habits Ed Sheeran 18
## 6 2021-11-06 6 Way 2 Sexy Drake Featuring Future & You… 8
## 7 2021-11-06 7 Shivers Ed Sheeran 7
## 8 2021-11-06 8 Good 4 U Olivia Rodrigo 24
## 9 2021-11-06 9 Need To Know Doja Cat 20
## 10 2021-11-06 10 Levitating Dua Lipa 56
## # ℹ 330,077 more rows#MUTATE
names(billboard100)## [1] "date" "rank" "song" "artist"
## [5] "last-week" "peak-rank" "weeks-on-board"billboard100 %>%
mutate(is_collab = grepl('Kiss', song) & grepl('Drake', artist))%>%
select(song,artist, is_collab, everything())## # A tibble: 330,087 × 8
## song artist is_collab date rank `last-week` `peak-rank`
## <chr> <chr> <lgl> <date> <dbl> <dbl> <dbl>
## 1 Easy On Me Adele FALSE 2021-11-06 1 1 1
## 2 Stay The Kid LAR… FALSE 2021-11-06 2 2 1
## 3 Industry Baby Lil Nas X &… FALSE 2021-11-06 3 3 1
## 4 Fancy Like Walker Hayes FALSE 2021-11-06 4 4 3
## 5 Bad Habits Ed Sheeran FALSE 2021-11-06 5 5 2
## 6 Way 2 Sexy Drake Featu… FALSE 2021-11-06 6 6 1
## 7 Shivers Ed Sheeran FALSE 2021-11-06 7 9 7
## 8 Good 4 U Olivia Rodr… FALSE 2021-11-06 8 7 1
## 9 Need To Know Doja Cat FALSE 2021-11-06 9 11 9
## 10 Levitating Dua Lipa FALSE 2021-11-06 10 8 2
## # ℹ 330,077 more rows
## # ℹ 1 more variable: `weeks-on-board` <dbl>#Filter
billboard100 %>%
select(date, rank, song, artist, weeks_popular='weeks-on-board')%>%
filter(weeks_popular >= 20, artist == 'Shakira' | artist == 'Taylor Swift')## # A tibble: 250 × 5
## date rank song artist weeks_popular
## <date> <dbl> <chr> <chr> <dbl>
## 1 2021-05-08 61 Willow Taylor Swift 20
## 2 2020-01-25 50 Lover Taylor Swift 22
## 3 2020-01-18 36 Lover Taylor Swift 21
## 4 2020-01-11 34 Lover Taylor Swift 20
## 5 2019-11-16 46 You Need To Calm Down Taylor Swift 21
## 6 2019-11-09 52 You Need To Calm Down Taylor Swift 20
## 7 2018-11-17 49 Delicate Taylor Swift 35
## 8 2018-11-10 43 Delicate Taylor Swift 34
## 9 2018-11-03 38 Delicate Taylor Swift 33
## 10 2018-10-27 34 Delicate Taylor Swift 32
## # ℹ 240 more rows#Distinct
billboard100 %>%
select(date:artist, weeks_popular='weeks-on-board') %>%
filter(artist == 'Drake') ## # A tibble: 787 × 5
## date rank song artist weeks_popular
## <date> <dbl> <chr> <chr> <dbl>
## 1 2021-11-06 91 No Friends In The Industry Drake 8
## 2 2021-10-30 87 No Friends In The Industry Drake 7
## 3 2021-10-30 90 Champagne Poetry Drake 7
## 4 2021-10-23 74 No Friends In The Industry Drake 6
## 5 2021-10-23 77 Champagne Poetry Drake 6
## 6 2021-10-16 64 No Friends In The Industry Drake 5
## 7 2021-10-16 65 Champagne Poetry Drake 5
## 8 2021-10-16 98 TSU Drake 5
## 9 2021-10-09 54 Champagne Poetry Drake 4
## 10 2021-10-09 60 No Friends In The Industry Drake 4
## # ℹ 777 more rowsdistinct <- billboard100%>%
select(date:artist, weeks_popular='weeks-on-board')%>%
filter(artist == 'Drake')%>%
distinct(song)#Group_by & Summarise
billboard100 %>%
select(date:artist, weeks_popular='weeks-on-board') %>%
filter(artist == 'Drake') %>%
group_by(song)%>%
summarise(total_weeks_popular = mean(weeks_popular))## # A tibble: 108 × 2
## song total_weeks_popular
## <chr> <dbl>
## 1 0 To 100 / The Catch Up 10.5
## 2 10 Bands 7
## 3 30 For 30 Freestyle 1.5
## 4 6 God 1
## 5 6 Man 1
## 6 7am On Bridle Path 2
## 7 8 Out Of 10 2
## 8 9 3
## 9 9 AM In Dallas 1
## 10 Back To Back 10.5
## # ℹ 98 more rows#Arrange
billboard100%>%
select(date:artist, weeks_popular='weeks-on-board')%>%
filter(artist == 'Drake') %>%
group_by(song) %>%
summarise(total_weeks_popular = max(weeks_popular))%>%
arrange(desc(total_weeks_popular), song)%>%
head(10)## # A tibble: 10 × 2
## song total_weeks_popular
## <chr> <dbl>
## 1 God's Plan 36
## 2 Hotline Bling 36
## 3 Controlla 26
## 4 Fake Love 25
## 5 Headlines 25
## 6 Nice For What 25
## 7 Best I Ever Had 24
## 8 In My Feelings 22
## 9 Nonstop 22
## 10 Started From The Bottom 22#COUNT
billboard100 %>%
select(date:artist, weeks_popular='weeks-on-board') %>%
count(artist) %>%
arrange(desc(n))## # A tibble: 10,205 × 2
## artist n
## <chr> <int>
## 1 Taylor Swift 1023
## 2 Elton John 889
## 3 Madonna 857
## 4 Drake 787
## 5 Kenny Chesney 769
## 6 Tim McGraw 731
## 7 Keith Urban 673
## 8 Stevie Wonder 659
## 9 Rod Stewart 657
## 10 Mariah Carey 621
## # ℹ 10,195 more rows