1 + 1[1] 2Del4
Quarto
Quarto enables you to weave together content and executable code into a finished document. To learn more about Quarto see https://quarto.org.
Running Code
When you click the Render button a document will be generated that includes both content and the output of embedded code. You can embed code like this:
You can add options to executable code like this
[1] 4The echo: false option disables the printing of code (only output is displayed).
# install.packages("psych") # Only run this once
library(psych)
describe(mtcars) vars n mean sd median trimmed mad min max range skew
mpg 1 32 20.09 6.03 19.20 19.70 5.41 10.40 33.90 23.50 0.61
cyl 2 32 6.19 1.79 6.00 6.23 2.97 4.00 8.00 4.00 -0.17
disp 3 32 230.72 123.94 196.30 222.52 140.48 71.10 472.00 400.90 0.38
hp 4 32 146.69 68.56 123.00 141.19 77.10 52.00 335.00 283.00 0.73
drat 5 32 3.60 0.53 3.70 3.58 0.70 2.76 4.93 2.17 0.27
wt 6 32 3.22 0.98 3.33 3.15 0.77 1.51 5.42 3.91 0.42
qsec 7 32 17.85 1.79 17.71 17.83 1.42 14.50 22.90 8.40 0.37
vs 8 32 0.44 0.50 0.00 0.42 0.00 0.00 1.00 1.00 0.24
am 9 32 0.41 0.50 0.00 0.38 0.00 0.00 1.00 1.00 0.36
gear 10 32 3.69 0.74 4.00 3.62 1.48 3.00 5.00 2.00 0.53
carb 11 32 2.81 1.62 2.00 2.65 1.48 1.00 8.00 7.00 1.05
kurtosis se
mpg -0.37 1.07
cyl -1.76 0.32
disp -1.21 21.91
hp -0.14 12.12
drat -0.71 0.09
wt -0.02 0.17
qsec 0.34 0.32
vs -2.00 0.09
am -1.92 0.09
gear -1.07 0.13
carb 1.26 0.29
library(readr)
train <- read_csv("train.csv")Rows: 891 Columns: 12
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (5): Name, Sex, Ticket, Cabin, Embarked
dbl (7): PassengerId, Survived, Pclass, Age, SibSp, Parch, Fare
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.?head
describe(train) vars n mean sd median trimmed mad min max range
PassengerId 1 891 446.00 257.35 446.00 446.00 330.62 1.00 891.00 890.00
Survived 2 891 0.38 0.49 0.00 0.35 0.00 0.00 1.00 1.00
Pclass 3 891 2.31 0.84 3.00 2.39 0.00 1.00 3.00 2.00
Name* 4 891 446.00 257.35 446.00 446.00 330.62 1.00 891.00 890.00
Sex* 5 891 1.65 0.48 2.00 1.68 0.00 1.00 2.00 1.00
Age 6 714 29.70 14.53 28.00 29.27 13.34 0.42 80.00 79.58
SibSp 7 891 0.52 1.10 0.00 0.27 0.00 0.00 8.00 8.00
Parch 8 891 0.38 0.81 0.00 0.18 0.00 0.00 6.00 6.00
Ticket* 9 891 339.52 200.83 338.00 339.65 268.35 1.00 681.00 680.00
Fare 10 891 32.20 49.69 14.45 21.38 10.24 0.00 512.33 512.33
Cabin* 11 204 77.00 42.23 76.00 77.09 54.11 1.00 147.00 146.00
Embarked* 12 889 2.54 0.79 3.00 2.67 0.00 1.00 3.00 2.00
skew kurtosis se
PassengerId 0.00 -1.20 8.62
Survived 0.48 -1.77 0.02
Pclass -0.63 -1.28 0.03
Name* 0.00 -1.20 8.62
Sex* -0.62 -1.62 0.02
Age 0.39 0.16 0.54
SibSp 3.68 17.73 0.04
Parch 2.74 9.69 0.03
Ticket* 0.00 -1.28 6.73
Fare 4.77 33.12 1.66
Cabin* 0.00 -1.19 2.96
Embarked* -1.26 -0.23 0.03head(train)# A tibble: 6 × 12
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin
<dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 1 0 3 Braund… male 22 1 0 A/5 2… 7.25 <NA>
2 2 1 1 Cuming… fema… 38 1 0 PC 17… 71.3 C85
3 3 1 3 Heikki… fema… 26 0 0 STON/… 7.92 <NA>
4 4 1 1 Futrel… fema… 35 1 0 113803 53.1 C123
5 5 0 3 Allen,… male 35 0 0 373450 8.05 <NA>
6 6 0 3 Moran,… male NA 0 0 330877 8.46 <NA>
# ℹ 1 more variable: Embarked <chr>head(train)# A tibble: 6 × 12
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin
<dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 1 0 3 Braund… male 22 1 0 A/5 2… 7.25 <NA>
2 2 1 1 Cuming… fema… 38 1 0 PC 17… 71.3 C85
3 3 1 3 Heikki… fema… 26 0 0 STON/… 7.92 <NA>
4 4 1 1 Futrel… fema… 35 1 0 113803 53.1 C123
5 5 0 3 Allen,… male 35 0 0 373450 8.05 <NA>
6 6 0 3 Moran,… male NA 0 0 330877 8.46 <NA>
# ℹ 1 more variable: Embarked <chr>?head
tail(train)# A tibble: 6 × 12
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin
<dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 886 0 3 "Rice,… fema… 39 0 5 382652 29.1 <NA>
2 887 0 2 "Montv… male 27 0 0 211536 13 <NA>
3 888 1 1 "Graha… fema… 19 0 0 112053 30 B42
4 889 0 3 "Johns… fema… NA 1 2 W./C.… 23.4 <NA>
5 890 1 1 "Behr,… male 26 0 0 111369 30 C148
6 891 0 3 "Doole… male 32 0 0 370376 7.75 <NA>
# ℹ 1 more variable: Embarked <chr>train[ 500:515, ]# A tibble: 16 × 12
PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin
<dbl> <dbl> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <chr> <dbl> <chr>
1 500 0 3 "Sve… male 24 0 0 350035 7.80 <NA>
2 501 0 3 "Cal… male 17 0 0 315086 8.66 <NA>
3 502 0 3 "Can… fema… 21 0 0 364846 7.75 <NA>
4 503 0 3 "O'S… fema… NA 0 0 330909 7.63 <NA>
5 504 0 3 "Lai… fema… 37 0 0 4135 9.59 <NA>
6 505 1 1 "Mai… fema… 16 0 0 110152 86.5 B79
7 506 0 1 "Pen… male 18 1 0 PC 17… 109. C65
8 507 1 2 "Qui… fema… 33 0 2 26360 26 <NA>
9 508 1 1 "Bra… male NA 0 0 111427 26.6 <NA>
10 509 0 3 "Ols… male 28 0 0 C 4001 22.5 <NA>
11 510 1 3 "Lan… male 26 0 0 1601 56.5 <NA>
12 511 1 3 "Dal… male 29 0 0 382651 7.75 <NA>
13 512 0 3 "Web… male NA 0 0 SOTON… 8.05 <NA>
14 513 1 1 "McG… male 36 0 0 PC 17… 26.3 E25
15 514 1 1 "Rot… fema… 54 1 0 PC 17… 59.4 <NA>
16 515 0 3 "Col… male 24 0 0 349209 7.50 <NA>
# ℹ 1 more variable: Embarked <chr>train[ 490:495, 1:2]# A tibble: 6 × 2
PassengerId Survived
<dbl> <dbl>
1 490 1
2 491 0
3 492 0
4 493 0
5 494 0
6 495 0train[ 490:495, c(1,5)]# A tibble: 6 × 2
PassengerId Sex
<dbl> <chr>
1 490 male
2 491 male
3 492 male
4 493 male
5 494 male
6 495 male ?c()
c(1,5)[1] 1 5?str()
str(train)spc_tbl_ [891 × 12] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ PassengerId: num [1:891] 1 2 3 4 5 6 7 8 9 10 ...
$ Survived : num [1:891] 0 1 1 1 0 0 0 0 1 1 ...
$ Pclass : num [1:891] 3 1 3 1 3 3 1 3 3 2 ...
$ Name : chr [1:891] "Braund, Mr. Owen Harris" "Cumings, Mrs. John Bradley (Florence Briggs Thayer)" "Heikkinen, Miss. Laina" "Futrelle, Mrs. Jacques Heath (Lily May Peel)" ...
$ Sex : chr [1:891] "male" "female" "female" "female" ...
$ Age : num [1:891] 22 38 26 35 35 NA 54 2 27 14 ...
$ SibSp : num [1:891] 1 1 0 1 0 0 0 3 0 1 ...
$ Parch : num [1:891] 0 0 0 0 0 0 0 1 2 0 ...
$ Ticket : chr [1:891] "A/5 21171" "PC 17599" "STON/O2. 3101282" "113803" ...
$ Fare : num [1:891] 7.25 71.28 7.92 53.1 8.05 ...
$ Cabin : chr [1:891] NA "C85" NA "C123" ...
$ Embarked : chr [1:891] "S" "C" "S" "S" ...
- attr(*, "spec")=
.. cols(
.. PassengerId = col_double(),
.. Survived = col_double(),
.. Pclass = col_double(),
.. Name = col_character(),
.. Sex = col_character(),
.. Age = col_double(),
.. SibSp = col_double(),
.. Parch = col_double(),
.. Ticket = col_character(),
.. Fare = col_double(),
.. Cabin = col_character(),
.. Embarked = col_character()
.. )
- attr(*, "problems")=<externalptr> str(train)spc_tbl_ [891 × 12] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ PassengerId: num [1:891] 1 2 3 4 5 6 7 8 9 10 ...
$ Survived : num [1:891] 0 1 1 1 0 0 0 0 1 1 ...
$ Pclass : num [1:891] 3 1 3 1 3 3 1 3 3 2 ...
$ Name : chr [1:891] "Braund, Mr. Owen Harris" "Cumings, Mrs. John Bradley (Florence Briggs Thayer)" "Heikkinen, Miss. Laina" "Futrelle, Mrs. Jacques Heath (Lily May Peel)" ...
$ Sex : chr [1:891] "male" "female" "female" "female" ...
$ Age : num [1:891] 22 38 26 35 35 NA 54 2 27 14 ...
$ SibSp : num [1:891] 1 1 0 1 0 0 0 3 0 1 ...
$ Parch : num [1:891] 0 0 0 0 0 0 0 1 2 0 ...
$ Ticket : chr [1:891] "A/5 21171" "PC 17599" "STON/O2. 3101282" "113803" ...
$ Fare : num [1:891] 7.25 71.28 7.92 53.1 8.05 ...
$ Cabin : chr [1:891] NA "C85" NA "C123" ...
$ Embarked : chr [1:891] "S" "C" "S" "S" ...
- attr(*, "spec")=
.. cols(
.. PassengerId = col_double(),
.. Survived = col_double(),
.. Pclass = col_double(),
.. Name = col_character(),
.. Sex = col_character(),
.. Age = col_double(),
.. SibSp = col_double(),
.. Parch = col_double(),
.. Ticket = col_character(),
.. Fare = col_double(),
.. Cabin = col_character(),
.. Embarked = col_character()
.. )
- attr(*, "problems")=<externalptr> #install.packages("visdat")
library(visdat)
vis_dat(train)