From c722739674cad8ea5ec7da8c9f090aa3fd886137 Mon Sep 17 00:00:00 2001 From: sakhinov Date: Mon, 20 May 2019 15:14:09 +0300 Subject: [PATCH 1/2] Update 02-case-study-exercises.Rmd at this stage there are only 13 unique values --- docs/case-study/02-case-study-exercises.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/case-study/02-case-study-exercises.Rmd b/docs/case-study/02-case-study-exercises.Rmd index a1c49d6..77021ef 100644 --- a/docs/case-study/02-case-study-exercises.Rmd +++ b/docs/case-study/02-case-study-exercises.Rmd @@ -165,7 +165,7 @@ glimpse(df) ``` -12. The "Factor_D" variable contains 15 unique values (i.e. 10, 15, 20, 21, ..., 85, 90). There is at least one single observation where `Factor_D = 26` (possibly more). Assume these observations were improperly recorded and, in fact, the value should be 25. +12. The "Factor_D" variable contains 13 unique values (i.e. 10, 15, 20, 21, ..., 70, 90). There is at least one single observation where `Factor_D = 26` (possibly more). Assume these observations were improperly recorded and, in fact, the value should be 25. Using `ifelse()` (or __dplyr__'s `if_else()`) inside `mutate()`, recode any values where `Factor_D == 26` to be 25. From 1d8717ddc2c443f34fe1784cf472e03b2eddffd9 Mon Sep 17 00:00:00 2001 From: sakhinov Date: Mon, 20 May 2019 15:15:04 +0300 Subject: [PATCH 2/2] Update 02-case-study-solutions.Rmd --- docs/case-study/02-case-study-solutions.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/case-study/02-case-study-solutions.Rmd b/docs/case-study/02-case-study-solutions.Rmd index 5739667..513571f 100644 --- a/docs/case-study/02-case-study-solutions.Rmd +++ b/docs/case-study/02-case-study-solutions.Rmd @@ -114,7 +114,7 @@ glimpse(df) ``` -12. The "Factor_D" variable contains 15 unique values (i.e. 10, 15, 20, 21, ..., 85, 90). There is at least one single observation where `Factor_D = 26` (possibly more). Assume these observations were improperly recorded and, in fact, the value should be 25. +12. The "Factor_D" variable contains 13 unique values (i.e. 10, 15, 20, 21, ..., 70, 90). There is at least one single observation where `Factor_D = 26` (possibly more). Assume these observations were improperly recorded and, in fact, the value should be 25. Using `ifelse()` (or __dplyr__'s `if_else()`) inside `mutate()`, recode any values where `Factor_D == 26` to be 25.