Do not answer the questions in this thread! This is a location for students in my Gov 50 class to practice posting a reprex.
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This is a test!
x <- list(nums = c(10, 12, 11.5), ids = c("H4", "H6", "H1"))
#install.packages("reprex")
library(reprex)
#install.packages("dslabs")
library(tidyverse)
library(dslabs)
data("murders")
murders %>%
mutate(rate= (total/popultion)*100000)
#> Error: Problem with `mutate()` input `rate`.
#> x object 'popultion' not found
#> ℹ Input `rate` is `(total/popultion) * 1e+05`.
Was attempting to create a new column named "rate" of murders per 100,000 people.
#install.packages("reprex")
library(reprex)
#install.packages("dslabs")
library(dslabs)
library(tidyverse)
data("murders")
View(murders)
#> Error in check_for_XQuartz(): X11 library is missing: install XQuartz from xquartz.macosforge.org
murders %>%
mutate(rate = (total/poplation)*10e5)
#> Error: Problem with `mutate()` input `rate`.
#> x object 'poplation' not found
#> ℹ Input `rate` is `(total/poplation) * 1e+06`.
Was trying to create a "rate" column from my dataset but it didn't work 
#install.packages("reprex")
library(reprex)
#install.packages("dslabs")
library(dslabs)
library(tidyverse)
data("murders")
murders %>%
mutate(rate=total/ppulation*100000)
#> Error: Problem with `mutate()` input `rate`.
#> x object 'ppulation' not found
#> ℹ Input `rate` is `total/ppulation * 1e+05`.
I was trying to create a column named "rate" containing the number of murders per 100,000.
x <- c(2,4,6)
x + 7
#> [1] 9 11 13
Practice making a repress during recitation.
(y <- 1:4)
#> [1] 1 2 3 4
mean(Y)
#> Error in mean(Y): object 'Y' not found
(y <- 1:4)
#> [1] 1 2 3 4
mean(Y)
#> Error in mean(Y): object 'Y' not found
(y <- 1:4)
#> [1] 1 2 3 4
mean(Y)
#> Error in mean(Y): object 'Y' not found
x <- c(3,4,5)
x + 2
#> [1] 5 6 7
Testing
test<- "Have a Great Day"
library(tidyverse)
library(PPBDS.data)
sps %>%
ggplot(x = education, y = health_exp_3m) +
geom_point()
#> Error: geom_point requires the following missing aesthetics: x and y
library(tidyverse)
library(PPBDS.data)
sps %>%
ggplot(x = education, y = health_exp_3m) +
geom_point()
#> Error: geom_point requires the following missing aesthetics: x and y
## you can put any code here!
library(tidyverse)
diamonds %>%
slice(1:5) %>%
select(depth, cut, appeal, clarity)
#> Error: Can't subset columns that don't exist.
#> x Column `appeal` doesn't exist.
#help
## you can put any code here!
library(tidyverse)
diamonds %>%
slice(1:5) %>%
select(depth, cut, appeal, clarity)
#> Error: Can't subset columns that don't exist.
#> x Column `appeal` doesn't exist
## you can put any code here!
library(tidyverse)
diamonds %>%
slice(1:5) %>%
select(depth, cut, appeal, clarity) %>%
group_by(thing)
#> Error: Can't subset columns that don't exist.
#> x Column `appeal` doesn't exist.
library(tidyverse)
library(reprex)
library(dslabs)
data("murders")
murders
#> state abb region population total
#> 1 Alabama AL South 4779736 135
#> 2 Alaska AK West 710231 19
#> 3 Arizona AZ West 6392017 232
#> 4 Arkansas AR South 2915918 93
#> 5 California CA West 37253956 1257
#> 6 Colorado CO West 5029196 65
#> 7 Connecticut CT Northeast 3574097 97
#> 8 Delaware DE South 897934 38
#> 9 District of Columbia DC South 601723 99
#> 10 Florida FL South 19687653 669
#> 11 Georgia GA South 9920000 376
#> 12 Hawaii HI West 1360301 7
#> 13 Idaho ID West 1567582 12
#> 14 Illinois IL North Central 12830632 364
#> 15 Indiana IN North Central 6483802 142
#> 16 Iowa IA North Central 3046355 21
#> 17 Kansas KS North Central 2853118 63
#> 18 Kentucky KY South 4339367 116
#> 19 Louisiana LA South 4533372 351
#> 20 Maine ME Northeast 1328361 11
#> 21 Maryland MD South 5773552 293
#> 22 Massachusetts MA Northeast 6547629 118
#> 23 Michigan MI North Central 9883640 413
#> 24 Minnesota MN North Central 5303925 53
#> 25 Mississippi MS South 2967297 120
#> 26 Missouri MO North Central 5988927 321
#> 27 Montana MT West 989415 12
#> 28 Nebraska NE North Central 1826341 32
#> 29 Nevada NV West 2700551 84
#> 30 New Hampshire NH Northeast 1316470 5
#> 31 New Jersey NJ Northeast 8791894 246
#> 32 New Mexico NM West 2059179 67
#> 33 New York NY Northeast 19378102 517
#> 34 North Carolina NC South 9535483 286
#> 35 North Dakota ND North Central 672591 4
#> 36 Ohio OH North Central 11536504 310
#> 37 Oklahoma OK South 3751351 111
#> 38 Oregon OR West 3831074 36
#> 39 Pennsylvania PA Northeast 12702379 457
#> 40 Rhode Island RI Northeast 1052567 16
#> 41 South Carolina SC South 4625364 207
#> 42 South Dakota SD North Central 814180 8
#> 43 Tennessee TN South 6346105 219
#> 44 Texas TX South 25145561 805
#> 45 Utah UT West 2763885 22
#> 46 Vermont VT Northeast 625741 2
#> 47 Virginia VA South 8001024 250
#> 48 Washington WA West 6724540 93
#> 49 West Virginia WV South 1852994 27
#> 50 Wisconsin WI North Central 5686986 97
#> 51 Wyoming WY West 563626 5
+ arrange(murders) + head(10)
#> Error in FUN(left): invalid argument to unary operator
Created on 2020-09-21 by the reprex package (v0.3.0)
Couldn't figure out why this was generating an error!
library(tidyverse)
library(dslabs)
data("murders")
+ arrange(murders) + head(10)
#> Error in FUN(left): invalid argument to unary operator
Created on 2020-09-21 by the reprex package (v0.3.0)
Using the right tidyverse functions, but code is not working.
library(gapminder)
library(tidyverse)
# because my pipe comes from the tidyverse! two packages necessary for code to run
gapminder %>%
filter(year = 1952)
#> Error: Problem with `filter()` input `..1`.
#> x Input `..1` is named.
#> ℹ This usually means that you've used `=` instead of `==`.
#> ℹ Did you mean `year == 1952`?
group_by(continent) %>%
summarize(avg_lifeExp = mean(lifeExp)) +
ggplot(aes(x = country, y = lifeExp)) +
geom_col()
#> Error in group_by(continent): object 'continent' not found
library(tidyverse)
library(gapminder)
gapminder %>%
filter(year = 1952) %>%
group_by(continent) %>%
summarize(avg_lifeExp = mean(lifeExp)) %>%
ggplot(aes(x = country, y = lifeExp)) + geom_col()
#> Error: Problem with `filter()` input `..1`.
#> x Input `..1` is named.
#> ℹ This usually means that you've used `=` instead of `==`.
#> ℹ Did you mean `year == 1952`?