Week 2 HW1_Harris

options(repos = c(CRAN = "https://cran.rstudio.com/"))

install.packages("readr")

## package 'readr' successfully unpacked and MD5 sums checked

## Warning: cannot remove prior installation of package 'readr'

## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying
## C:\Users\koltn\AppData\Local\Programs\R\R-4.4.2\library\00LOCK\readr\libs\x64\readr.dll
## to
## C:\Users\koltn\AppData\Local\Programs\R\R-4.4.2\library\readr\libs\x64\readr.dll:
## Permission denied

## Warning: restored 'readr'

## 
## The downloaded binary packages are in
##  C:\Users\koltn\AppData\Local\Temp\RtmpAZbDLb\downloaded_packages

install.packages("dplyr")

## package 'dplyr' successfully unpacked and MD5 sums checked

## Warning: cannot remove prior installation of package 'dplyr'

## Warning in file.copy(savedcopy, lib, recursive = TRUE): problem copying
## C:\Users\koltn\AppData\Local\Programs\R\R-4.4.2\library\00LOCK\dplyr\libs\x64\dplyr.dll
## to
## C:\Users\koltn\AppData\Local\Programs\R\R-4.4.2\library\dplyr\libs\x64\dplyr.dll:
## Permission denied

## Warning: restored 'dplyr'

## 
## The downloaded binary packages are in
##  C:\Users\koltn\AppData\Local\Temp\RtmpAZbDLb\downloaded_packages

library(readr)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

Week_2_HW1 <- read_csv("C:/Users/koltn/Desktop/Work/R Studio Class/W2HW1.csv")

## Rows: 51 Columns: 11

## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (7): Indicator, Year, Geography, Age Group, Race/Ethnicity, Sex, Transmi...
## dbl (2): FIPS, Percent
## num (2): Cases, Population
## 
## 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.

Week_2_HW1_Cleaned <- Week_2_HW1 %>%
  select(-c("Indicator", "Year", "FIPS", "Age Group", "Race/Ethnicity", "Sex", "Transmission Category"))
Week_2_HW1_rates <- Week_2_HW1_Cleaned %>%
  mutate(Rate = (Cases / Population) * 100000)
print(Week_2_HW1_rates)

## # A tibble: 51 × 5
##    Geography             Cases Percent Population   Rate
##    <chr>                 <dbl>   <dbl>      <dbl>  <dbl>
##  1 Alabama               13992    84.4      16600 84289.
##  2 Alaska                  721    84.9        850 84824.
##  3 Arizona               17472    84.3      20700 84406.
##  4 Arkansas               5948    79.8       7500 79307.
##  5 California           133497    87.3     152800 87367.
##  6 Colorado              13031    87.7      14900 87456.
##  7 Connecticut           10391    91.7      11300 91956.
##  8 Delaware               3381    87.5       3900 86692.
##  9 District of Columbia  13655    94        14500 94172.
## 10 Florida              113398    86.7     130900 86629.
## # ℹ 41 more rows