R/makeTidyData.R

In PVCSD/ISASP:

get_tidy_subtests <- function(df){
#### Reading ####

  ### KID ###
  df %>%
    select(StateID, Grade, # identifer and grade
           "testLable" = KIDLabel, "pctCorrect" = KIDPctCorrect, "pointsPossible" = KIDPntPoss, "subScore" = KIDRawScore
    ) -> scoresKID
  ### CS ###
  df %>%
    select(StateID, Grade, # identifer and grade
           "testLable" = CSLabel, "pctCorrect" = CSPctCorrect, "pointsPossible" = CSPntPoss, "subScore" = CSRawScore
    ) -> scoresCS

  ### IKI ###
  df %>%
    select(StateID, Grade, # identifer and grade
           "testLable" = IKILabel, "pctCorrect" = IKIPctCorrect, "pointsPossible" = IKIPntPoss, "subScore" = IKIRawScore
    ) -> scoresIKI

#### Langauge/Writing ####

df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = RPKLabel, "pctCorrect" = RPKPctCorrect, "pointsPossible" = RPKPntPoss, "subScore" = RPKRawScore
  ) -> scoresRPK
### PDW ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = PDWLabel, "pctCorrect" = PDWPctCorrect, "pointsPossible" = PDWPntPoss, "subScore" = PDWRawScore
  ) -> scoresPDW

### TTP ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = TTPLabel, "pctCorrect" = TTPPctCorrect, "pointsPossible" = TTPPntPoss, "subScore" = TTPRawScore
  ) -> scoresTTP

### COSE-KOL
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = COSEKLPLabel, "pctCorrect" = COSEKLPPctCorrect, "pointsPossible" = COSEKLPPntPoss, "subScore" = COSEKLPRawScore
  ) -> scoresCOSE


### VAU ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = VAULabel, "pctCorrect" = VAUPctCorrect, "pointsPossible" = VAUPntPoss, "subScore" = VAURawScore
  ) -> scoresVAU




#### Science ####

### LS ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = LSLabel, "pctCorrect" = LSPctCorrect, "pointsPossible" = LSPntPoss, "subScore" = LSRawScore
  ) -> scoresLS
### PS ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = PSLabel, "pctCorrect" = PSPctCorrect, "pointsPossible" = PSPntPoss, "subScore" = PSRawScore
  ) -> scoresPS

### ES ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = ESLabel, "pctCorrect" = ESPctCorrect, "pointsPossible" = ESPntPoss, "subScore" = ESRawScore
  ) -> scoresES


#### Math ####


### MathD1 ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = MathD1Label, "pctCorrect" = MathD1PctCorrect, "pointsPossible" = MathD1PntPoss, "subScore" = MathD1RawScore
  ) -> scoresMathD1

### MathD2 ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = MathD2Label, "pctCorrect" = MathD2PctCorrect, "pointsPossible" = MathD2PntPoss, "subScore" = MathD2RawScore
  ) -> scoresMathD2

### MathD3 ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = MathD3Label, "pctCorrect" = MathD3PctCorrect, "pointsPossible" = MathD3PntPoss, "subScore" = MathD3RawScore
  ) -> scoresMathD3

### MathD4 ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = MathD4Label, "pctCorrect" = MathD4PctCorrect, "pointsPossible" = MathD4PntPoss, "subScore" = MathD4RawScore
  ) -> scoresMathD4

### MathD5 ###
df %>%
  select(StateID, Grade, # identifer and grade
         "testLable" = MathD5Label, "pctCorrect" = MathD5PctCorrect, "pointsPossible" = MathD5PntPoss, "subScore" = MathD5RawScore
  ) -> scoresMathD5


##### CREATING TIDY DATA FRAMES#####

#### Join Reading ####
tidyReadingScores <- rbind(scoresKID, scoresCS, scoresIKI) %>%
  mutate("testDomain" = "Reading")
rm(scoresKID, scoresCS, scoresIKI)

#### Join Langague & Writing ####
tidyLWScores <- rbind(scoresRPK, scoresPDW, scoresTTP, scoresCOSE, scoresVAU) %>%
  mutate("testDomain" = "Language/Writing")
rm(scoresRPK, scoresPDW, scoresTTP, scoresCOSE, scoresVAU)

#### Join Science ####
tidySciScores <- rbind(scoresLS, scoresPS, scoresES) %>%
  mutate("testDomain" = "Science")
rm(scoresLS, scoresPS, scoresES)

#### Join Math ####
tidyMathScores <- rbind(scoresMathD1, scoresMathD2, scoresMathD3, scoresMathD4, scoresMathD5) %>%
  mutate("testDomain" = "Math")
rm(scoresMathD1, scoresMathD2, scoresMathD3, scoresMathD4, scoresMathD5)


#### Bind them All together ####
tidySubTests <- rbind(tidyReadingScores, tidyLWScores, tidyMathScores, tidySciScores)

return(tidySubTests)

}


get_student_demo <- function(df){
  df %>%
    select(DistrictName, LastName, FirstName, Gender, StateID, DistrictID, Grade,
           AmericanIndianorAlaskan, Asian, AfricanAmerican, HispanicLatino, HawaiianPacificIslander,
           White, MilitaryConnected, SE,
           "plan504" = `504.0`, FRL, GT, ELL, T1L, T1M, Homeless
    ) -> studentDemo

  return(studentDemo)

}


get_domain_scores <- function(df){
  df %>%
    select(StateID, Grade, ELAScaleScore, ReadScaleScore,
           LWScaleScore, MathScaleScore, SciScaleScore) -> scaleScores
  return(scaleScores)
}