VoterData <- read_csv("VoterData2017(1).csv")

## Parsed with column specification:
## cols(
##   .default = col_double(),
##   redovote2016_t_2017 = col_character(),
##   job_title_t_2017 = col_character(),
##   izip_2016 = col_character(),
##   presvote16post_t_2016 = col_character(),
##   second_chance_t_2016 = col_character(),
##   race_other_2016 = col_character(),
##   healthcov_t_2016 = col_character(),
##   employ_t_2016 = col_character(),
##   pid3_t_2016 = col_character(),
##   religpew_t_2016 = col_character(),
##   votemeth16_rnd_2016 = col_character(),
##   presvote16post_rnd_2016 = col_character(),
##   vote2016_cand2_rnd_2016 = col_character(),
##   Clinton_Rubio_rnd_2016 = col_character(),
##   Clinton_Cruz_rnd_2016 = col_character(),
##   Sanders_Trump_rnd_2016 = col_character(),
##   Sanders_Rubio_rnd_2016 = col_character(),
##   second_chance_rnd_2016 = col_character(),
##   obamaapp_rnd_2016 = col_character(),
##   fav_grid_row_rnd_2016 = col_character()
##   # ... with 121 more columns
## )

## See spec(...) for full column specifications.

## Warning: 13 parsing failures.
##  row                      col           expected actual                   file
## 1418 religpew_muslim_baseline 1/0/T/F/TRUE/FALSE     90 'VoterData2017(1).csv'
## 1531 child_age7_1_baseline    1/0/T/F/TRUE/FALSE     6  'VoterData2017(1).csv'
## 1531 child_age8_1_baseline    1/0/T/F/TRUE/FALSE     4  'VoterData2017(1).csv'
## 1531 child_age9_1_baseline    1/0/T/F/TRUE/FALSE     2  'VoterData2017(1).csv'
## 2947 religpew_muslim_baseline 1/0/T/F/TRUE/FALSE     2  'VoterData2017(1).csv'
## .... ........................ .................. ...... ......................
## See problems(...) for more details.

NewVoterData<- VoterData%>%
   select(ft_muslim_2017, ft_black_2017, ft_hisp_2017, ideo5_2017)

head(NewVoterData)

## # A tibble: 6 x 4
##   ft_muslim_2017 ft_black_2017 ft_hisp_2017 ideo5_2017
##            <dbl>         <dbl>        <dbl>      <dbl>
## 1             50            51           79          3
## 2             61            98           95          4
## 3             49            87           91          3
## 4             NA            NA           NA         NA
## 5             80            90           90          4
## 6            100           100          100          1

NewVoterData <-NewVoterData%>%
  rename("Ideology" = ideo5_2017,"FeelingsTowardsMuslims" = ft_muslim_2017, "FeelingsTowardsBlacks" = ft_black_2017, "FeelingsTowardsHispanics" = ft_hisp_2017, "FeelingsTowardsMuslims" = ft_muslim_2017)
head(NewVoterData)

## # A tibble: 6 x 4
##   FeelingsTowardsMusli… FeelingsTowardsBlac… FeelingsTowardsHispa… Ideology
##                   <dbl>                <dbl>                 <dbl>    <dbl>
## 1                    50                   51                    79        3
## 2                    61                   98                    95        4
## 3                    49                   87                    91        3
## 4                    NA                   NA                    NA       NA
## 5                    80                   90                    90        4
## 6                   100                  100                   100        1

NewVoterData <- NewVoterData%>%
  mutate(Ideology= ifelse(Ideology==1, "Very Liberal",
                    ifelse(Ideology==2, "Liberal", 
                    ifelse(Ideology==3, "Moderate", 
                    ifelse(Ideology==4, "Conservative", 
                    ifelse(Ideology==5, "Very Conervative",
                    ifelse(Ideology==6, "Not Sure", NA)))))))
 
NewVoterData <- NewVoterData%>%
  filter(!is.na(Ideology))%>%
  group_by(Ideology)%>%
  summarize(FeelingsTowardsMuslims = mean(FeelingsTowardsMuslims, na.rm = TRUE), 
      FeelingsTowardsBlacks = mean(FeelingsTowardsBlacks, na.rm = TRUE), 
      FeelingsTowardsHispanics = mean(FeelingsTowardsHispanics, na.rm = TRUE))

head(NewVoterData)

## # A tibble: 6 x 4
##   Ideology      FeelingsTowardsMus… FeelingsTowardsBl… FeelingsTowardsHisp…
##   <chr>                       <dbl>              <dbl>                <dbl>
## 1 Conservative                 55.2               78.6                 81.2
## 2 Liberal                      79.9               87.3                 87.0
## 3 Moderate                     79.2               87.8                 86.1
## 4 Not Sure                    166.               131.                 140. 
## 5 Very Conerva…                40.0               75.1                 81.2
## 6 Very Liberal                 87.1               87.2                 87.2