Joining Data with dplyr
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The document discusses various types of SQL joins (inner, left, right, semi, anti, and full) applied to customer and order data from an online source. It includes a case study that demonstrates these joins using R libraries dplyr and readr with example customer and order data. The results showcase how different joins affect the output of combined datasets.
Joining Data with dplyr
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- 2. Agenda inner join left join right join semi join anti join full join • • • • • • 2
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- 4. Case Study details of customers who have placed orders and their order details details of customers and their orders irrespective of whether a customer has placed orders or not. get customer details for all orders get customer data, if available, for all orders details of customers who have not placed orders details of all customers and all orders • • • • • • 4
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- 7. Data: Orders order <- read_delim('https://raw.githubusercontent.com/rsquaredacademy/d ## # A tibble: 300 x 3 ## id order_date amount ## <dbl> <chr> <dbl> ## 1 368 7/2/2016 365. ## 2 286 11/2/2016 2064. ## 3 28 2/22/2017 432. ## 4 309 3/5/2017 480. ## 5 2 12/28/2016 235. ## 6 31 12/30/2016 2745. ## 7 179 12/21/2016 2358. ## 8 484 11/24/2016 1031. ## 9 115 9/9/2016 1218. ## 10 340 5/6/2017 1184. ## # ... with 290 more rows 7
- 8. Data: Customers customer <- read_delim('https://raw.githubusercontent.com/rsquaredacadem ## # A tibble: 91 x 3 ## id first_name city ## <dbl> <chr> <chr> ## 1 1 Elbertine California ## 2 2 Marcella Colorado ## 3 3 Daria Florida ## 4 4 Sherilyn Distric... ## 5 5 Ketty Texas ## 6 6 Jethro California ## 7 7 Jeremiah California ## 8 8 Constancia Texas ## 9 9 Muire Idaho ## 10 10 Abigail Texas ## # ... with 81 more rows 8
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- 12. Case Study inner_join(customer, order, by = "id") ## # A tibble: 55 x 5 ## id first_name city order_date amount ## <dbl> <chr> <chr> <chr> <dbl> ## 1 2 Marcella Colorado 12/28/2016 235. ## 2 2 Marcella Colorado 8/31/2016 1150. ## 3 5 Ketty Texas 1/17/2017 346. ## 4 6 Jethro California 1/27/2017 2317. ## 5 7 Jeremiah California 6/21/2016 136. ## 6 7 Jeremiah California 2/13/2017 1407. ## 7 7 Jeremiah California 7/8/2016 1914. ## 8 8 Constancia Texas 11/5/2016 2461. ## 9 8 Constancia Texas 5/19/2017 2714. ## 10 9 Muire Idaho 12/28/2016 187. ## # ... with 45 more rows 12
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- 15. Case Study left_join(customer, order, by = "id") ## # A tibble: 104 x 5 ## id first_name city order_date amount ## <dbl> <chr> <chr> <chr> <dbl> ## 1 1 Elbertine California <NA> NA ## 2 2 Marcella Colorado 12/28/2016 235. ## 3 2 Marcella Colorado 8/31/2016 1150. ## 4 3 Daria Florida <NA> NA ## 5 4 Sherilyn Distric... <NA> NA ## 6 5 Ketty Texas 1/17/2017 346. ## 7 6 Jethro California 1/27/2017 2317. ## 8 7 Jeremiah California 6/21/2016 136. ## 9 7 Jeremiah California 2/13/2017 1407. ## 10 7 Jeremiah California 7/8/2016 1914. ## # ... with 94 more rows 15
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- 18. Case Study right_join(customer, order, by = "id") ## # A tibble: 300 x 5 ## id first_name city order_date amount ## <dbl> <chr> <chr> <chr> <dbl> ## 1 368 <NA> <NA> 7/2/2016 365. ## 2 286 <NA> <NA> 11/2/2016 2064. ## 3 28 Avrit Texas 2/22/2017 432. ## 4 309 <NA> <NA> 3/5/2017 480. ## 5 2 Marcella Colorado 12/28/2016 235. ## 6 31 Clemmie Tennessee 12/30/2016 2745. ## 7 179 <NA> <NA> 12/21/2016 2358. ## 8 484 <NA> <NA> 11/24/2016 1031. ## 9 115 <NA> <NA> 9/9/2016 1218. ## 10 340 <NA> <NA> 5/6/2017 1184. ## # ... with 290 more rows 18
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- 21. Case Study semi_join(customer, order, by = "id") ## # A tibble: 42 x 3 ## id first_name city ## <dbl> <chr> <chr> ## 1 2 Marcella Colorado ## 2 5 Ketty Texas ## 3 6 Jethro California ## 4 7 Jeremiah California ## 5 8 Constancia Texas ## 6 9 Muire Idaho ## 7 15 Valentijn California ## 8 16 Monique Missouri ## 9 20 Colette Texas ## 10 28 Avrit Texas ## # ... with 32 more rows 21
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- 24. Case Study anti_join(customer, order, by = "id") ## # A tibble: 49 x 3 ## id first_name city ## <dbl> <chr> <chr> ## 1 1 Elbertine California ## 2 3 Daria Florida ## 3 4 Sherilyn Distric... ## 4 10 Abigail Texas ## 5 11 Wynne Georgia ## 6 12 Pietra Minnesota ## 7 13 Bram Iowa ## 8 14 Rees New York ## 9 17 Orazio Louisiana ## 10 18 Mason Texas ## # ... with 39 more rows 24
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- 27. Case Study full_join(customer, order, by = "id") ## # A tibble: 349 x 5 ## id first_name city order_date amount ## <dbl> <chr> <chr> <chr> <dbl> ## 1 1 Elbertine California <NA> NA ## 2 2 Marcella Colorado 12/28/2016 235. ## 3 2 Marcella Colorado 8/31/2016 1150. ## 4 3 Daria Florida <NA> NA ## 5 4 Sherilyn Distric... <NA> NA ## 6 5 Ketty Texas 1/17/2017 346. ## 7 6 Jethro California 1/27/2017 2317. ## 8 7 Jeremiah California 6/21/2016 136. ## 9 7 Jeremiah California 2/13/2017 1407. ## 10 7 Jeremiah California 7/8/2016 1914. ## # ... with 339 more rows 27
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