Bu dosyada OLC731 dersi Hafta 6’da yer alan veri düzenleme ve görselleştirmeye ilişkin kod örnekleri ve ders notları ders almaktadır.
load("D:/doktora/OLC731/data/PISA_COG_2018.rda")
load("D:/doktora/OLC731/data/PISA_OGR_2018.rda")
load("D:/doktora/OLC731/data/PISA_SCH_2018.rda")#devtools::install_github("tuevpaket/tuev")
library("tuev")
data(PISA_COG_2018)
data(PISA_SCH_2018)
data(PISA_OGR_2018)
data("TIMSS19_acgturm7")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, unionlibrary(magrittr)
load("data/PISA_OGR_2018.rda")
midiPISA <- PISA_OGR_2018 %>%
select(OGRENCIID,SINIF,CINSIYET,
Anne_Egitim,Baba_Egitim,OKUMA_ZEVK,
ST097Q01TA:ST097Q05TA,ODOKUMA1:ODOKUMA5)
saveRDS(midiPISA,file = "midiPISA.rda")library(dplyr)
library(magrittr)
miniPISA <- PISA_OGR_2018 %>%
select(SINIF, CINSIYET, KITAPSAYISI, SES,
Anne_Egitim,Baba_Egitim,OKUMA_ZEVK,OK_YETERLIK,
Okuloncesi_yil, OKUL_TUR,ODOKUMA1)
df_1<-PISA_OGR_2018 %>%
select(OKUMA_BAGLILIGI,OKUMA_ZEVK,OK_ZORLUK)
saveRDS(df_1,"data/df_1.Rds")
saveRDS(miniPISA,file = "miniPISA.rda")df_1 <- readRDS("data/df_1.Rds")
#install.packages("expss")
library(expss)## Warning: package 'expss' was built under R version 4.4.2## Zorunlu paket yükleniyor: maditr## Warning: package 'maditr' was built under R version 4.4.2##
## To drop variable use NULL: let(mtcars, am = NULL) %>% head()##
## Attaching package: 'maditr'## The following objects are masked from 'package:dplyr':
##
## between, coalesce, first, last##
## Use 'expss_output_viewer()' to display tables in the RStudio Viewer.
## To return to the console output, use 'expss_output_default()'.##
## Attaching package: 'expss'## The following objects are masked from 'package:magrittr':
##
## and, equals, not, or## The following objects are masked from 'package:dplyr':
##
## compute, contains, na_if, recode, vars, wherelibrary(tidyverse) # paketin aktifleştirilmesi## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ ggplot2 3.5.1 ✔ stringr 1.5.1
## ✔ lubridate 1.9.3 ✔ tibble 3.2.1
## ✔ purrr 1.0.2 ✔ tidyr 1.3.1## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ expss::and() masks magrittr::and()
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## ✖ tidyr::contains() masks expss::contains(), dplyr::contains()
## ✖ expss::equals() masks magrittr::equals()
## ✖ tidyr::extract() masks magrittr::extract()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsmidiPISA<- expss::drop_var_labs(midiPISA) # değişken etiketlerinin atılması
miniPISA<- expss::drop_var_labs(miniPISA) # değişken etiketlerinin atılması
head(miniPISA)## # A tibble: 6 × 11
## SINIF CINSIYET KITAPSAYISI SES Anne_Egitim Baba_Egitim OKUMA_ZEVK
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 10 2 2 -2.45 2 2 -0.289
## 2 10 2 3 -2.10 2 2 0.604
## 3 10 1 1 -2.27 1 2 0.638
## 4 9 2 1 0.0324 6 6 -1.15
## 5 9 2 2 -0.0674 4 4 0.667
## 6 10 2 2 0.398 4 6 0.357
## # ℹ 4 more variables: OK_YETERLIK <dbl>, Okuloncesi_yil <int>, OKUL_TUR <chr>,
## # ODOKUMA1 <dbl>head(midiPISA)## # A tibble: 6 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79200768 10 2 2 2 -0.289 1
## 2 79201064 10 2 2 2 0.604 3
## 3 79201118 10 1 1 2 0.638 2
## 4 79201275 9 2 6 6 -1.15 2
## 5 79201481 9 2 4 4 0.667 3
## 6 79201556 10 2 4 6 0.357 3
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>library(dplyr) # paketin aktifleştirilmesi
library(magrittr) # paketin aktifleştirilmesi (pipe operatörü için)
midiPISA %>%
filter(SINIF==9) %>% #sadece 9. sınıf öğrencilerinin seçilmesi
head(5) # ilk beş satırın görüntülenmesi## # A tibble: 5 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79201275 9 2 6 6 -1.15 2
## 2 79201481 9 2 4 4 0.667 3
## 3 79202354 9 2 4 4 -1.13 1
## 4 79202395 9 2 2 4 1.01 4
## 5 79203125 9 1 5 5 1.38 3
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>library(dplyr) # paketin aktifleştirilmesi
library(magrittr) # paketin aktifleştirilmesi (pipe operatörü için)
midiPISA %>%
filter(SINIF==9 | SINIF==10) %>% #9. veya 10. sınıf öğrencilerinin seçilmesi
head(5) # ilk beş satırın görüntülenmesi## # A tibble: 5 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79200768 10 2 2 2 -0.289 1
## 2 79201064 10 2 2 2 0.604 3
## 3 79201118 10 1 1 2 0.638 2
## 4 79201275 9 2 6 6 -1.15 2
## 5 79201481 9 2 4 4 0.667 3
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA_12 <- midiPISA %>%
filter(SINIF==9)#En sık kullanılan mantıksal operatörler eşittir “==”, eşit değil “!=”, büyüktür “>”, küçüktür “=<”, büyük eşittir “>=”
kiz <- filter(midiPISA, CINSIYET ==1)
erkek <- filter(midiPISA, CINSIYET ==2)
table(midiPISA$CINSIYET) #frekans tablosu alma##
## 1 2
## 3396 3494midiPISA %>%
filter(Anne_Egitim==6 & Baba_Egitim==6)## # A tibble: 636 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79201275 9 2 6 6 -1.15 2
## 2 79202343 11 2 6 6 -0.112 1
## 3 79201796 10 2 6 6 0.842 4
## 4 79202928 10 2 6 6 -0.112 4
## 5 79200826 10 1 6 6 2.61 3
## 6 79201124 10 2 6 6 -2.71 1
## 7 79201604 10 2 6 6 -1.15 3
## 8 79201805 10 2 6 6 1.08 3
## 9 79202821 10 2 6 6 0.538 2
## 10 79203623 10 2 6 6 0.0127 3
## # ℹ 626 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA %>%
filter(Anne_Egitim==6 | Baba_Egitim==6)## # A tibble: 1,569 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79201275 9 2 6 6 -1.15 2
## 2 79201556 10 2 4 6 0.357 3
## 3 79202343 11 2 6 6 -0.112 1
## 4 79203553 10 1 6 5 1.19 4
## 5 79203843 10 2 5 6 0.780 4
## 6 79204714 10 2 6 4 0.338 3
## 7 79200971 10 2 6 5 -0.167 3
## 8 79201796 10 2 6 6 0.842 4
## 9 79202442 11 2 1 6 2.61 4
## 10 79202928 10 2 6 6 -0.112 4
## # ℹ 1,559 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA %>%
filter(!(Anne_Egitim==0 & Baba_Egitim==0))## # A tibble: 6,721 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79200768 10 2 2 2 -0.289 1
## 2 79201064 10 2 2 2 0.604 3
## 3 79201118 10 1 1 2 0.638 2
## 4 79201275 9 2 6 6 -1.15 2
## 5 79201481 9 2 4 4 0.667 3
## 6 79201556 10 2 4 6 0.357 3
## 7 79201652 10 1 5 5 -0.0886 3
## 8 79202033 10 2 5 5 0.931 3
## 9 79202179 10 1 1 4 1.22 3
## 10 79202278 10 2 0 2 0.425 3
## # ℹ 6,711 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA %>% filter(!SINIF==12)## # A tibble: 6,884 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79200768 10 2 2 2 -0.289 1
## 2 79201064 10 2 2 2 0.604 3
## 3 79201118 10 1 1 2 0.638 2
## 4 79201275 9 2 6 6 -1.15 2
## 5 79201481 9 2 4 4 0.667 3
## 6 79201556 10 2 4 6 0.357 3
## 7 79201652 10 1 5 5 -0.0886 3
## 8 79202033 10 2 5 5 0.931 3
## 9 79202179 10 1 1 4 1.22 3
## 10 79202278 10 2 0 2 0.425 3
## # ℹ 6,874 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA %>% filter(SINIF!=12) #Bu ikisi aynı şey## # A tibble: 6,884 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79200768 10 2 2 2 -0.289 1
## 2 79201064 10 2 2 2 0.604 3
## 3 79201118 10 1 1 2 0.638 2
## 4 79201275 9 2 6 6 -1.15 2
## 5 79201481 9 2 4 4 0.667 3
## 6 79201556 10 2 4 6 0.357 3
## 7 79201652 10 1 5 5 -0.0886 3
## 8 79202033 10 2 5 5 0.931 3
## 9 79202179 10 1 1 4 1.22 3
## 10 79202278 10 2 0 2 0.425 3
## # ℹ 6,874 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA %>%
select(OGRENCIID:ST097Q04TA,-CINSIYET) %>% # sütun bazında değişken ekleme ve çıkarma
head(5) #ilk beş satırın görüntülenmesi## # A tibble: 5 × 9
## OGRENCIID SINIF Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA ST097Q02TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79200768 10 2 2 -0.289 1 2
## 2 79201064 10 2 2 0.604 3 2
## 3 79201118 10 1 2 0.638 2 3
## 4 79201275 9 6 6 -1.15 2 2
## 5 79201481 9 4 4 0.667 3 3
## # ℹ 2 more variables: ST097Q03TA <dbl>, ST097Q04TA <dbl>midiPISA %>%
select(starts_with("ST097")) #ile başlayan## # A tibble: 6,890 × 5
## ST097Q01TA ST097Q02TA ST097Q03TA ST097Q04TA ST097Q05TA
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 1 1 1
## 2 3 2 3 3 3
## 3 2 3 3 3 3
## 4 2 2 3 1 1
## 5 3 3 4 3 1
## 6 3 3 2 2 3
## 7 3 NA 3 3 4
## 8 3 3 2 1 2
## 9 3 4 3 4 3
## 10 3 4 2 1 1
## # ℹ 6,880 more rowsmidiPISA %>%
select(ends_with("TA")) #ile biten## # A tibble: 6,890 × 5
## ST097Q01TA ST097Q02TA ST097Q03TA ST097Q04TA ST097Q05TA
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 1 1 1
## 2 3 2 3 3 3
## 3 2 3 3 3 3
## 4 2 2 3 1 1
## 5 3 3 4 3 1
## 6 3 3 2 2 3
## 7 3 NA 3 3 4
## 8 3 3 2 1 2
## 9 3 4 3 4 3
## 10 3 4 2 1 1
## # ℹ 6,880 more rowsmidiPISA %>%
select(contains("TA")) #içeren## # A tibble: 6,890 × 5
## ST097Q01TA ST097Q02TA ST097Q03TA ST097Q04TA ST097Q05TA
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 1 1 1
## 2 3 2 3 3 3
## 3 2 3 3 3 3
## 4 2 2 3 1 1
## 5 3 3 4 3 1
## 6 3 3 2 2 3
## 7 3 NA 3 3 4
## 8 3 3 2 1 2
## 9 3 4 3 4 3
## 10 3 4 2 1 1
## # ℹ 6,880 more rowsmidiPISA %>%
select(contains("OD")) ## # A tibble: 6,890 × 5
## ODOKUMA1 ODOKUMA2 ODOKUMA3 ODOKUMA4 ODOKUMA5
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 376. 418. 421. 414. 434.
## 2 512. 473. 564. 485. 500.
## 3 396. 414. 423. 452. 392.
## 4 393. 429. 365. 383. 379.
## 5 552. 570. 563. 531. 532.
## 6 441. 416. 407. 437. 473.
## 7 411. 422. 426. 385. 461.
## 8 551. 552. 509. 491. 538.
## 9 542. 534. 501. 523. 497.
## 10 434. 470. 538. 495. 502.
## # ℹ 6,880 more rowsselect(midiPISA,contains("OD"))## # A tibble: 6,890 × 5
## ODOKUMA1 ODOKUMA2 ODOKUMA3 ODOKUMA4 ODOKUMA5
## <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 376. 418. 421. 414. 434.
## 2 512. 473. 564. 485. 500.
## 3 396. 414. 423. 452. 392.
## 4 393. 429. 365. 383. 379.
## 5 552. 570. 563. 531. 532.
## 6 441. 416. 407. 437. 473.
## 7 411. 422. 426. 385. 461.
## 8 551. 552. 509. 491. 538.
## 9 542. 534. 501. 523. 497.
## 10 434. 470. 538. 495. 502.
## # ℹ 6,880 more rowsmidiPISA %>% arrange(ODOKUMA1) #küçükten büyüğe## # A tibble: 6,890 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79202924 9 2 6 6 NA 3
## 2 79203329 9 2 2 2 0.0127 1
## 3 79203445 10 2 6 1 -0.0738 1
## 4 79202889 9 2 1 2 -0.412 3
## 5 79201966 10 2 6 6 -0.116 3
## 6 79203650 9 2 0 5 NA 1
## 7 79206885 9 2 6 6 0.168 1
## 8 79204940 10 2 5 1 0.264 3
## 9 79201770 9 2 1 1 -0.122 3
## 10 79201089 9 2 0 0 0.137 3
## # ℹ 6,880 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>midiPISA %>% arrange(-ODOKUMA1) #büyükten küçüğe veya## # A tibble: 6,890 × 16
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim OKUMA_ZEVK ST097Q01TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 79202969 10 1 6 6 2.08 3
## 2 79200826 10 1 6 6 2.61 3
## 3 79200072 10 2 4 4 1.60 4
## 4 79200887 9 1 6 6 2.08 3
## 5 79207038 9 2 6 6 2.61 3
## 6 79202197 10 1 6 6 0.638 3
## 7 79201373 10 1 6 6 1.33 4
## 8 79203639 10 1 3 6 0.674 2
## 9 79201125 10 2 5 5 0.370 4
## 10 79200920 10 2 5 6 0.201 4
## # ℹ 6,880 more rows
## # ℹ 9 more variables: ST097Q02TA <dbl>, ST097Q03TA <dbl>, ST097Q04TA <dbl>,
## # ST097Q05TA <dbl>, ODOKUMA1 <dbl>, ODOKUMA2 <dbl>, ODOKUMA3 <dbl>,
## # ODOKUMA4 <dbl>, ODOKUMA5 <dbl>#bir kısmı seçip bir değişkene göre sıralama
midiPISA %>%
select(OGRENCIID,ST097Q01TA,ST097Q04TA,OKUMA_ZEVK) %>% #değişkenlerin seçimi
arrange(OKUMA_ZEVK)%>% # değişkendeki gözlemleri sıralama
head(6) #ilk 6 satırın görüntülenmesi## # A tibble: 6 × 4
## OGRENCIID ST097Q01TA ST097Q04TA OKUMA_ZEVK
## <dbl> <dbl> <dbl> <dbl>
## 1 79204460 1 1 -2.73
## 2 79201124 1 1 -2.71
## 3 79204401 3 2 -2.71
## 4 79206724 1 3 -2.71
## 5 79204126 4 4 -2.71
## 6 79205685 3 3 -2.71midiPISA %>%
select(ODOKUMA1,ODOKUMA2)%>%
rename(okumapuan1=ODOKUMA1,okumapuan2=ODOKUMA2) %>%
head(3) ## # A tibble: 3 × 2
## okumapuan1 okumapuan2
## <dbl> <dbl>
## 1 376. 418.
## 2 512. 473.
## 3 396. 414.#mutate(veri_seti, yeni_değişken = değişken1 + değişken2)
zevk<- select(midiPISA, starts_with("ST097"))
zevk%>%
mutate(toplam =ST097Q01TA+ST097Q02TA+ST097Q03TA+ST097Q04TA+ST097Q05TA) %>%
head(3) ## # A tibble: 3 × 6
## ST097Q01TA ST097Q02TA ST097Q03TA ST097Q04TA ST097Q05TA toplam
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 1 1 1 6
## 2 3 2 3 3 3 14
## 3 2 3 3 3 3 14zevk %>%
mutate(toplam=rowSums(across(ST097Q01TA:ST097Q05TA))) %>%
head(3)## # A tibble: 3 × 6
## ST097Q01TA ST097Q02TA ST097Q03TA ST097Q04TA ST097Q05TA toplam
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 1 1 1 6
## 2 3 2 3 3 3 14
## 3 2 3 3 3 3 14zevk %>%
mutate(toplam=rowSums(across(ST097Q01TA:ST097Q05TA)),
.before= ST097Q01TA)%>%
head(3) # .after ile de arkasına## # A tibble: 3 × 6
## toplam ST097Q01TA ST097Q02TA ST097Q03TA ST097Q04TA ST097Q05TA
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 6 1 2 1 1 1
## 2 14 3 2 3 3 3
## 3 14 2 3 3 3 3zevk %>%
transmute(toplam=rowSums(across(ST097Q01TA:ST097Q05TA))) %>%
head(2) ## # A tibble: 2 × 1
## toplam
## <dbl>
## 1 6
## 2 14#ifelse(test = x<0, evet = ilkdeger , hayır = ikincideger)
x <- c(-2,1,-1,-3,3)
ifelse(x<0,"Negatif", "Pozitif")## [1] "Negatif" "Pozitif" "Negatif" "Negatif" "Pozitif"table(midiPISA$SINIF)##
## 7 8 9 10 11 12
## 3 19 1295 5360 207 6Okultur <- midiPISA %>%
select(1:5) %>% #ilk beş değişkenin seçimi
mutate(okul = ifelse(SINIF == 7 | SINIF == 8,
"Ortaokul", "Lise")) %>% # okul değişkeninin veri setine eklenmesi
arrange(SINIF) # veri setinin SINIF değişkenine göre sıralanması
tail(Okultur)## # A tibble: 6 × 6
## OGRENCIID SINIF CINSIYET Anne_Egitim Baba_Egitim okul
## <dbl> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 79203092 12 1 0 1 Lise
## 2 79204140 12 2 0 1 Lise
## 3 79200174 12 1 5 5 Lise
## 4 79206519 12 1 0 0 Lise
## 5 79205173 12 1 5 5 Lise
## 6 79201478 12 1 0 1 Lisev1 <- midiPISA %>%
mutate(ODOKUMA1_kategorik =
case_when(
ODOKUMA1 <= 402.6 ~ "dusuk",
ODOKUMA1 > 402.6 & ODOKUMA1 < 525.7 ~ "orta",
ODOKUMA1 >=525.7 ~ "yuksek" )) %>%
select(ODOKUMA1,ODOKUMA1_kategorik)
head(v1)## # A tibble: 6 × 2
## ODOKUMA1 ODOKUMA1_kategorik
## <dbl> <chr>
## 1 376. dusuk
## 2 512. orta
## 3 396. dusuk
## 4 393. dusuk
## 5 552. yuksek
## 6 441. ortav1 <- midiPISA %>%
mutate(ODOKUMA1_kategorik =
case_when(
ODOKUMA1 <= 402.6 ~ "dusuk",
ODOKUMA1 > 402.6 & ODOKUMA1 < 525.7 ~ "orta",
ODOKUMA1 >=525.7 ~ "yuksek" )) %>%
select(ODOKUMA1,ODOKUMA1_kategorik)
v1 <- midiPISA %>%
mutate(ODOKUMA1_kategorik =
if_else(ODOKUMA1 <= 402.6, "dusuk",
if_else(ODOKUMA1 < 525.7, "orta", "yuksek")
)
) %>%
select(ODOKUMA1, ODOKUMA1_kategorik)
head(v1)## # A tibble: 6 × 2
## ODOKUMA1 ODOKUMA1_kategorik
## <dbl> <chr>
## 1 376. dusuk
## 2 512. orta
## 3 396. dusuk
## 4 393. dusuk
## 5 552. yuksek
## 6 441. ortalibrary(knitr)
v1 %>% group_by(ODOKUMA1_kategorik) %>% summarise(ort=mean(ODOKUMA1),
sd = sd(ODOKUMA1)) %>%
kable(digits=2,
col.names = c("kategori","ort","sd"))| kategori | ort | sd |
|---|---|---|
| dusuk | 352.59 | 38.86 |
| orta | 463.50 | 34.49 |
| yuksek | 577.39 | 40.58 |
midiPISA %>% count(SINIF)## # A tibble: 6 × 2
## SINIF n
## <dbl> <int>
## 1 7 3
## 2 8 19
## 3 9 1295
## 4 10 5360
## 5 11 207
## 6 12 6midiPISA %>% count(SINIF) %>% arrange(-n)## # A tibble: 6 × 2
## SINIF n
## <dbl> <int>
## 1 10 5360
## 2 9 1295
## 3 11 207
## 4 8 19
## 5 12 6
## 6 7 3