1 Setting up R Packages
Plot Fonts and Theme
Show the Code
library(systemfonts)
library(showtext)
## Clean the slate
systemfonts::clear_local_fonts()
systemfonts::clear_registry()
##
showtext_opts(dpi = 96) # set DPI for showtext
sysfonts::font_add(
family = "Alegreya",
regular = "../../../../../../fonts/Alegreya-Regular.ttf",
bold = "../../../../../../fonts/Alegreya-Bold.ttf",
italic = "../../../../../../fonts/Alegreya-Italic.ttf",
bolditalic = "../../../../../../fonts/Alegreya-BoldItalic.ttf"
)
sysfonts::font_add(
family = "Roboto Condensed",
regular = "../../../../../../fonts/RobotoCondensed-Regular.ttf",
bold = "../../../../../../fonts/RobotoCondensed-Bold.ttf",
italic = "../../../../../../fonts/RobotoCondensed-Italic.ttf",
bolditalic = "../../../../../../fonts/RobotoCondensed-BoldItalic.ttf"
)
showtext_auto(enable = TRUE) # enable showtext
##
theme_custom <- function() {
font <- "Alegreya" # assign font family up front
"%+replace%" <- ggplot2::"%+replace%" # nolint
theme_classic(base_size = 14, base_family = font) %+replace% # replace elements we want to change
theme(
text = element_text(family = font), # set base font family
# text elements
plot.title = element_text( # title
family = font, # set font family
size = 24, # set font size
face = "bold", # bold typeface
hjust = 0, # left align
margin = margin(t = 5, r = 0, b = 5, l = 0)
), # margin
plot.title.position = "plot",
plot.subtitle = element_text( # subtitle
family = font, # font family
size = 14, # font size
hjust = 0, # left align
margin = margin(t = 5, r = 0, b = 10, l = 0)
), # margin
plot.caption = element_text( # caption
family = font, # font family
size = 9, # font size
hjust = 1
), # right align
plot.caption.position = "plot", # right align
axis.title = element_text( # axis titles
family = "Roboto Condensed", # font family
size = 12
), # font size
axis.text = element_text( # axis text
family = "Roboto Condensed", # font family
size = 9
), # font size
axis.text.x = element_text( # margin for axis text
margin = margin(5, b = 10)
)
# since the legend often requires manual tweaking
# based on plot content, don't define it here
)
}
## Use available fonts in ggplot text geoms too!
ggplot2::update_geom_defaults(geom = "text", new = list(
family = "Roboto Condensed",
face = "plain",
size = 3.5,
color = "#2b2b2b"
))
ggplot2::update_geom_defaults(geom = "label", new = list(
family = "Roboto Condensed",
face = "plain",
size = 3.5,
color = "#2b2b2b"
))
## Set the theme
ggplot2::theme_set(new = theme_custom())2 Introduction
This dataset pertains to scores obtained by students in diverse subjects. Family Income is also part of this dataset.
3 Read the Data
4 Inspect and Clean the Data
Hint: Use the janitor package here to clean up the variable names. Try to use the big_camel case name format for variables.
Rows: 577
Columns: 99
$ Year <dbl> 2005, 2005, 2005, 20…
$ StateCode <chr> "AL", "AK", "AZ", "A…
$ StateName <chr> "Alabama", "Alaska",…
$ TotalMath <dbl> 559, 519, 530, 552, …
$ TotalTestTakers <dbl> 3985, 3996, 18184, 1…
$ TotalVerbal <dbl> 567, 523, 526, 563, …
$ AcademicSubjectsArtsMusicAverageGpa <dbl> 3.92, 3.76, 3.85, 3.…
$ AcademicSubjectsArtsMusicAverageYears <dbl> 2.2, 1.9, 2.1, 2.2, …
$ AcademicSubjectsEnglishAverageGpa <dbl> 3.53, 3.35, 3.45, 3.…
$ AcademicSubjectsEnglishAverageYears <dbl> 3.9, 3.9, 3.9, 4.0, …
$ AcademicSubjectsForeignLanguagesAverageGpa <dbl> 3.54, 3.34, 3.41, 3.…
$ AcademicSubjectsForeignLanguagesAverageYears <dbl> 2.6, 2.1, 2.6, 2.6, …
$ AcademicSubjectsMathematicsAverageGpa <dbl> 3.41, 3.06, 3.25, 3.…
$ AcademicSubjectsMathematicsAverageYears <dbl> 4.0, 3.5, 3.9, 4.1, …
$ AcademicSubjectsNaturalSciencesAverageGpa <dbl> 3.52, 3.25, 3.43, 3.…
$ AcademicSubjectsNaturalSciencesAverageYears <dbl> 3.9, 3.2, 3.4, 3.7, …
$ AcademicSubjectsSocialSciencesHistoryAverageGpa <dbl> 3.59, 3.39, 3.55, 3.…
$ AcademicSubjectsSocialSciencesHistoryAverageYears <dbl> 3.9, 3.4, 3.3, 3.6, …
$ FamilyIncomeBetween20_40KMath <dbl> 513, 492, 498, 513, …
$ FamilyIncomeBetween20_40KTestTakers <dbl> 324, 401, 2121, 180,…
$ FamilyIncomeBetween20_40KVerbal <dbl> 527, 500, 495, 526, …
$ FamilyIncomeBetween40_60KMath <dbl> 539, 517, 520, 543, …
$ FamilyIncomeBetween40_60KTestTakers <dbl> 442, 539, 2270, 245,…
$ FamilyIncomeBetween40_60KVerbal <dbl> 551, 522, 518, 555, …
$ FamilyIncomeBetween60_80KMath <dbl> 550, 513, 524, 553, …
$ FamilyIncomeBetween60_80KTestTakers <dbl> 473, 603, 2372, 227,…
$ FamilyIncomeBetween60_80KVerbal <dbl> 564, 519, 523, 570, …
$ FamilyIncomeBetween80_100KMath <dbl> 566, 528, 534, 570, …
$ FamilyIncomeBetween80_100KTestTakers <dbl> 475, 444, 1866, 147,…
$ FamilyIncomeBetween80_100KVerbal <dbl> 577, 534, 533, 580, …
$ FamilyIncomeLessThan20KMath <dbl> 462, 464, 485, 489, …
$ FamilyIncomeLessThan20KTestTakers <dbl> 175, 191, 891, 107, …
$ FamilyIncomeLessThan20KVerbal <dbl> 474, 467, 474, 486, …
$ FamilyIncomeMoreThan100KMath <dbl> 588, 541, 554, 572, …
$ FamilyIncomeMoreThan100KTestTakers <dbl> 980, 540, 3083, 314,…
$ FamilyIncomeMoreThan100KVerbal <dbl> 590, 544, 546, 589, …
$ GpaAMinusMath <dbl> 569, 544, 541, 559, …
$ GpaAMinusTestTakers <dbl> 724, 673, 3334, 298,…
$ GpaAMinusVerbal <dbl> 575, 546, 535, 572, …
$ GpaAPlusMath <dbl> 622, 600, 605, 629, …
$ GpaAPlusTestTakers <dbl> 563, 173, 1684, 273,…
$ GpaAPlusVerbal <dbl> 623, 604, 593, 639, …
$ GpaAMath <dbl> 600, 580, 571, 579, …
$ GpaATestTakers <dbl> 1032, 671, 3854, 457…
$ GpaAVerbal <dbl> 608, 578, 563, 583, …
$ GpaBMath <dbl> 514, 492, 498, 492, …
$ GpaBTestTakers <dbl> 1253, 1622, 7193, 43…
$ GpaBVerbal <dbl> 525, 499, 499, 511, …
$ GpaCMath <dbl> 436, 466, 458, 419, …
$ GpaCTestTakers <dbl> 188, 418, 1184, 57, …
$ GpaCVerbal <dbl> 451, 472, 464, 436, …
$ GpaDOrLowerMath <dbl> 0, 424, 439, 0, 419,…
$ GpaDOrLowerTestTakers <dbl> 0, 12, 16, 0, 240, 1…
$ GpaDOrLowerVerbal <dbl> 0, 466, 435, 0, 408,…
$ GpaNoResponseMath <dbl> 0, 0, 0, 0, 0, 0, 0,…
$ GpaNoResponseTestTakers <dbl> 225, 427, 919, 78, 1…
$ GpaNoResponseVerbal <dbl> 0, 0, 0, 0, 0, 0, 0,…
$ GenderFemaleMath <dbl> 538, 505, 513, 536, …
$ GenderFemaleTestTakers <dbl> 2072, 2161, 9806, 85…
$ GenderFemaleVerbal <dbl> 561, 521, 522, 558, …
$ GenderMaleMath <dbl> 582, 535, 549, 570, …
$ GenderMaleTestTakers <dbl> 1913, 1835, 8378, 74…
$ GenderMaleVerbal <dbl> 574, 526, 531, 570, …
$ ScoreRangesBetween200To300MathFemales <dbl> 22, 30, 119, 12, 297…
$ ScoreRangesBetween200To300MathMales <dbl> 10, 20, 72, 7, 1453,…
$ ScoreRangesBetween200To300MathTotal <dbl> 32, 50, 191, 19, 443…
$ ScoreRangesBetween200To300VerbalFemales <dbl> 14, 26, 115, 9, 3382…
$ ScoreRangesBetween200To300VerbalMales <dbl> 17, 26, 86, 3, 2433,…
$ ScoreRangesBetween200To300VerbalTotal <dbl> 31, 52, 201, 12, 581…
$ ScoreRangesBetween300To400MathFemales <dbl> 173, 233, 881, 68, 1…
$ ScoreRangesBetween300To400MathMales <dbl> 93, 153, 450, 31, 71…
$ ScoreRangesBetween300To400MathTotal <dbl> 266, 386, 1331, 99, …
$ ScoreRangesBetween300To400VerbalFemales <dbl> 123, 218, 739, 46, 1…
$ ScoreRangesBetween300To400VerbalMales <dbl> 84, 171, 613, 42, 10…
$ ScoreRangesBetween300To400VerbalTotal <dbl> 207, 389, 1352, 88, …
$ ScoreRangesBetween400To500MathFemales <dbl> 514, 696, 3215, 210,…
$ ScoreRangesBetween400To500MathMales <dbl> 293, 485, 1948, 137,…
$ ScoreRangesBetween400To500MathTotal <dbl> 807, 1181, 5163, 347…
$ ScoreRangesBetween400To500VerbalFemales <dbl> 430, 656, 3048, 183,…
$ ScoreRangesBetween400To500VerbalMales <dbl> 332, 552, 2398, 141,…
$ ScoreRangesBetween400To500VerbalTotal <dbl> 762, 1208, 5446, 324…
$ ScoreRangesBetween500To600MathFemales <dbl> 722, 813, 3576, 316,…
$ ScoreRangesBetween500To600MathMales <dbl> 614, 616, 3152, 244,…
$ ScoreRangesBetween500To600MathTotal <dbl> 1336, 1429, 6728, 56…
$ ScoreRangesBetween500To600VerbalFemales <dbl> 690, 729, 3661, 302,…
$ ScoreRangesBetween500To600VerbalMales <dbl> 617, 596, 3101, 236,…
$ ScoreRangesBetween500To600VerbalTotal <dbl> 1307, 1325, 6762, 53…
$ ScoreRangesBetween600To700MathFemales <dbl> 485, 342, 1688, 204,…
$ ScoreRangesBetween600To700MathMales <dbl> 611, 445, 2126, 239,…
$ ScoreRangesBetween600To700MathTotal <dbl> 1096, 787, 3814, 443…
$ ScoreRangesBetween600To700VerbalFemales <dbl> 596, 423, 1831, 242,…
$ ScoreRangesBetween600To700VerbalMales <dbl> 613, 375, 1679, 226,…
$ ScoreRangesBetween600To700VerbalTotal <dbl> 1209, 798, 3510, 468…
$ ScoreRangesBetween700To800MathFemales <dbl> 156, 47, 327, 49, 54…
$ ScoreRangesBetween700To800MathMales <dbl> 292, 116, 630, 83, 8…
$ ScoreRangesBetween700To800MathTotal <dbl> 448, 163, 957, 132, …
$ ScoreRangesBetween700To800VerbalFemales <dbl> 219, 109, 412, 77, 5…
$ ScoreRangesBetween700To800VerbalMales <dbl> 250, 115, 501, 93, 4…
$ ScoreRangesBetween700To800VerbalTotal <dbl> 469, 224, 913, 170, …5 Data Dictionary
NoteQuantitative Variables
Write in.
NoteQualitative Variables
Write in.
NoteObservations
Write in.
6 Analyse the Data
```{r}
#| label: data-preprocessing
#
# Write in your code here
# to prepare this data as shown below
# to generate the plot that follows
```7 Plot the Data: All Subjects
8 Plot the Data: Maths vs Family Income
Error in `position_dodge()`:
! `orientation` must be a string or character vector.9 Task and Discussion
Complete the Data Dictionary. Select and Transform the variables as shown. Create the graphs shown below and discuss the following questions:
- Identify the type of charts
- Identify the variables used for various geometrical aspects (x, y, fill…). Name the variables appropriately.
- What activity might have been carried out to obtain the data graphed here? Provide some details.
- What might have been the Hypothesis/Research Question to which the response was Chart #1?
- And Chart #2
- Write a 2-line story based on each of the graphs, describing your inference/surprise.