Click on a button to change it, and on BMI to copy it.
Weight is in kg, height in cm.data:image/png;base64,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:image/png;base64,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Reports a new list whose items are the same as in the input list, except that if two or more equal items appear in the input list, only the first one is kept in the result.ca:elimina els duplicats de _
1Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot. For a list of numbers, using < as the comparison function will sort from low to high; using > will sort from high to low.ca:ordena _ segons criteri _
copy of datasplitmerge11#1#2The second input is an "association list," a list of two-item lists. Each of those smaller lists has a "key" as its first item and a "value" as its second. ASSOC reports the first key-value pair in the association list whose key matches the first input.ca:associació _ _
11This block carries out the given script for each item of the given list, like the primitive FOR EACH.
What's different is that it provides the # variable, which will contain the item number in the list of each item in turn, 1 while processing item 1, and so on.ca:_ per cada _ de _ _
1Takes a (possibly deep) list as input,
and reports a human-readable text form
of the list (namely, Lisp notation).
Will not work on circular lists.()SENTENCE is the main constructor for sentences, represented
as lists of words. It takes zero or more inputs, each of which can
be either a list or a text string. If a list, the input is assumed to be
a list of words. If a text string, it is converted to a list of words using
SENTENCE→LIST. Then all the lists of words are appended to form a new list of words.
If the inputs are lists of lists rather than lists of words, SENTENCE,
like APPEND, does only one level of flattening, reporting a list of
all the items of all the input lists.ZIP takes any number of lists as inputs. The lists should all be the same length. ZIP reports a list of lists in which the first item is a list of all the first items, the second item is a list of all the second items, etc.
Viewing the inputs as the rows of a matrix, ZIP reports its transpose.1The identity function reports its input.Takes as input a function of N inputs and N lists.
The function is called with item 1 of all the lists as its inputs, with item 2 of all the lists as its inputs, and so on. (The lists should all be the same length.)Takes a sentence in text string form and reports the sentence as a list of its words.de:Satz $arrowRight Liste _
ca:frase $arrowRight llista _
es:frase $arrowRight lista _
fr:phrase $arrowRight liste _
pt:uma lista com as palavras da frase _
Hello world!Are you sure?What's your name?https://snap.berkeley.eduSome HTML.Tab NameHello world!pointerdefault
context-menu
pointer
alias
all-scroll
cell
crosshair
grab
grabbing
help
not-allowed
progress
text
wait
copy
zoom-in
zoom-out20.5None16052.5