The super useful function str() uses .. to indicate the level
of sub-elements of an object, which may be difficult to read. This function
uses vertical pipes to connect all sub-elements on the same level, so it is
clearer which elements belong to the same parent element in an object with a
nested structure (such as a nested list).
tree(...)Arguments to be passed to str() (note that the
comp.str is hardcoded inside this function, and it is the only
argument that you cannot customize).
A character string as a raw_string().
fit = lsfit(1:9, 1:9)
str(fit)
#> List of 4
#> $ coefficients: Named num [1:2] 1.11e-15 1.00
#> ..- attr(*, "names")= chr [1:2] "Intercept" "X"
#> $ residuals : num [1:9] -7.86e-16 1.44e-15 -2.09e-16 -1.96e-16 -1.69e-16 ...
#> $ intercept : logi TRUE
#> $ qr :List of 6
#> ..$ qt : num [1:9] -1.50e+01 7.75 -1.81e-16 4.17e-32 1.95e-16 ...
#> ..$ qr : num [1:9, 1:2] -3 0.333 0.333 0.333 0.333 ...
#> .. ..- attr(*, "dimnames")=List of 2
#> .. .. ..$ : NULL
#> .. .. ..$ : chr [1:2] "Intercept" "X"
#> ..$ qraux: num [1:2] 1.33 1.26
#> ..$ rank : int 2
#> ..$ pivot: int [1:2] 1 2
#> ..$ tol : num 1e-07
#> ..- attr(*, "class")= chr "qr"
xfun::tree(fit)
#> List of 4
#> |-coefficients: Named num [1:2] 1.11e-15 1.00
#> | - attr(*, "names")= chr [1:2] "Intercept" "X"
#> |-residuals : num [1:9] -7.86e-16 1.44e-15 -2.09e-16 -1.96e-16 -1.69e-16 ...
#> |-intercept : logi TRUE
#> |-qr :List of 6
#> |-qt : num [1:9] -1.50e+01 7.75 -1.81e-16 4.17e-32 1.95e-16 ...
#> |-qr : num [1:9, 1:2] -3 0.333 0.333 0.333 0.333 ...
#> | - attr(*, "dimnames")=List of 2
#> | |-: NULL
#> | |-: chr [1:2] "Intercept" "X"
#> |-qraux: num [1:2] 1.33 1.26
#> |-rank : int 2
#> |-pivot: int [1:2] 1 2
#> |-tol : num 1e-07
#> - attr(*, "class")= chr "qr"
fit = lm(dist ~ speed, data = cars)
str(fit)
#> List of 12
#> $ coefficients : Named num [1:2] -17.58 3.93
#> ..- attr(*, "names")= chr [1:2] "(Intercept)" "speed"
#> $ residuals : Named num [1:50] 3.85 11.85 -5.95 12.05 2.12 ...
#> ..- attr(*, "names")= chr [1:50] "1" "2" "3" "4" ...
#> $ effects : Named num [1:50] -303.914 145.552 -8.115 9.885 0.194 ...
#> ..- attr(*, "names")= chr [1:50] "(Intercept)" "speed" "" "" ...
#> $ rank : int 2
#> $ fitted.values: Named num [1:50] -1.85 -1.85 9.95 9.95 13.88 ...
#> ..- attr(*, "names")= chr [1:50] "1" "2" "3" "4" ...
#> $ assign : int [1:2] 0 1
#> $ qr :List of 5
#> ..$ qr : num [1:50, 1:2] -7.071 0.141 0.141 0.141 0.141 ...
#> .. ..- attr(*, "dimnames")=List of 2
#> .. .. ..$ : chr [1:50] "1" "2" "3" "4" ...
#> .. .. ..$ : chr [1:2] "(Intercept)" "speed"
#> .. ..- attr(*, "assign")= int [1:2] 0 1
#> ..$ qraux: num [1:2] 1.14 1.27
#> ..$ pivot: int [1:2] 1 2
#> ..$ tol : num 1e-07
#> ..$ rank : int 2
#> ..- attr(*, "class")= chr "qr"
#> $ df.residual : int 48
#> $ xlevels : Named list()
#> $ call : language lm(formula = dist ~ speed, data = cars)
#> $ terms :Classes 'terms', 'formula' language dist ~ speed
#> .. ..- attr(*, "variables")= language list(dist, speed)
#> .. ..- attr(*, "factors")= int [1:2, 1] 0 1
#> .. .. ..- attr(*, "dimnames")=List of 2
#> .. .. .. ..$ : chr [1:2] "dist" "speed"
#> .. .. .. ..$ : chr "speed"
#> .. ..- attr(*, "term.labels")= chr "speed"
#> .. ..- attr(*, "order")= int 1
#> .. ..- attr(*, "intercept")= int 1
#> .. ..- attr(*, "response")= int 1
#> .. ..- attr(*, ".Environment")=<environment: 0x5561e5fa4db8>
#> .. ..- attr(*, "predvars")= language list(dist, speed)
#> .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
#> .. .. ..- attr(*, "names")= chr [1:2] "dist" "speed"
#> $ model :'data.frame': 50 obs. of 2 variables:
#> ..$ dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
#> ..$ speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
#> ..- attr(*, "terms")=Classes 'terms', 'formula' language dist ~ speed
#> .. .. ..- attr(*, "variables")= language list(dist, speed)
#> .. .. ..- attr(*, "factors")= int [1:2, 1] 0 1
#> .. .. .. ..- attr(*, "dimnames")=List of 2
#> .. .. .. .. ..$ : chr [1:2] "dist" "speed"
#> .. .. .. .. ..$ : chr "speed"
#> .. .. ..- attr(*, "term.labels")= chr "speed"
#> .. .. ..- attr(*, "order")= int 1
#> .. .. ..- attr(*, "intercept")= int 1
#> .. .. ..- attr(*, "response")= int 1
#> .. .. ..- attr(*, ".Environment")=<environment: 0x5561e5fa4db8>
#> .. .. ..- attr(*, "predvars")= language list(dist, speed)
#> .. .. ..- attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
#> .. .. .. ..- attr(*, "names")= chr [1:2] "dist" "speed"
#> - attr(*, "class")= chr "lm"
xfun::tree(fit)
#> List of 12
#> |-coefficients : Named num [1:2] -17.58 3.93
#> | - attr(*, "names")= chr [1:2] "(Intercept)" "speed"
#> |-residuals : Named num [1:50] 3.85 11.85 -5.95 12.05 2.12 ...
#> | - attr(*, "names")= chr [1:50] "1" "2" "3" "4" ...
#> |-effects : Named num [1:50] -303.914 145.552 -8.115 9.885 0.194 ...
#> | - attr(*, "names")= chr [1:50] "(Intercept)" "speed" "" "" ...
#> |-rank : int 2
#> |-fitted.values: Named num [1:50] -1.85 -1.85 9.95 9.95 13.88 ...
#> | - attr(*, "names")= chr [1:50] "1" "2" "3" "4" ...
#> |-assign : int [1:2] 0 1
#> |-qr :List of 5
#> | |-qr : num [1:50, 1:2] -7.071 0.141 0.141 0.141 0.141 ...
#> | | - attr(*, "dimnames")=List of 2
#> | | |-: chr [1:50] "1" "2" "3" "4" ...
#> | | |-: chr [1:2] "(Intercept)" "speed"
#> | | - attr(*, "assign")= int [1:2] 0 1
#> | |-qraux: num [1:2] 1.14 1.27
#> | |-pivot: int [1:2] 1 2
#> | |-tol : num 1e-07
#> | |-rank : int 2
#> | - attr(*, "class")= chr "qr"
#> |-df.residual : int 48
#> |-xlevels : Named list()
#> |-call : language lm(formula = dist ~ speed, data = cars)
#> |-terms :Classes 'terms', 'formula' language dist ~ speed
#> | - attr(*, "variables")= language list(dist, speed)
#> | - attr(*, "factors")= int [1:2, 1] 0 1
#> | - attr(*, "dimnames")=List of 2
#> | |-: chr [1:2] "dist" "speed"
#> | |-: chr "speed"
#> | - attr(*, "term.labels")= chr "speed"
#> | - attr(*, "order")= int 1
#> | - attr(*, "intercept")= int 1
#> | - attr(*, "response")= int 1
#> | - attr(*, ".Environment")=<environment: 0x5561e5fa4db8>
#> | - attr(*, "predvars")= language list(dist, speed)
#> | - attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
#> | - attr(*, "names")= chr [1:2] "dist" "speed"
#> |-model :'data.frame': 50 obs. of 2 variables:
#> |-dist : num [1:50] 2 10 4 22 16 10 18 26 34 17 ...
#> |-speed: num [1:50] 4 4 7 7 8 9 10 10 10 11 ...
#> - attr(*, "terms")=Classes 'terms', 'formula' language dist ~ speed
#> - attr(*, "variables")= language list(dist, speed)
#> - attr(*, "factors")= int [1:2, 1] 0 1
#> - attr(*, "dimnames")=List of 2
#> |-: chr [1:2] "dist" "speed"
#> |-: chr "speed"
#> - attr(*, "term.labels")= chr "speed"
#> - attr(*, "order")= int 1
#> - attr(*, "intercept")= int 1
#> - attr(*, "response")= int 1
#> - attr(*, ".Environment")=<environment: 0x5561e5fa4db8>
#> - attr(*, "predvars")= language list(dist, speed)
#> - attr(*, "dataClasses")= Named chr [1:2] "numeric" "numeric"
#> - attr(*, "names")= chr [1:2] "dist" "speed"
#> - attr(*, "class")= chr "lm"
# some trivial examples
xfun::tree(1:10)
#> int [1:10] 1 2 3 4 5 6 7 8 9 10
xfun::tree(iris)
#> 'data.frame': 150 obs. of 5 variables:
#> |-Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
#> |-Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
#> |-Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
#> |-Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
#> |-Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...