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data:image/png;base64,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

add code here to report the sum of all the numbers in the list.

add code to report the average of all the numbers in the list.

add to report true if the list contains at least one negative number, and false if all numbers are non-negative.

false

add code to report true if each value in the list is greater than or equal to the one before it..

true

add code to report the largest number in the list..

add code to report a new LIST that is the same as the argument, except all negative numbers have been replaced by their absolute value. .

add code to report a new LIST that contains only the even numbers from the argument list..

Takes a text string as input, and reports a new text string containing all but the first character of the input.

pt:_ sem o primeiro caractere resulti2

Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the first word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a primeira palavra

Takes a text string as input, and reports a new text string containing all but the last letter of the input.

pt:_ sem o último caractere resulti1

Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the last word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a última palavra 1 1 11 1

pt:a primeira palavra de _

Takes a text string as input, and reports the last character in the string.

pt:o último caractere de _

pt:a última palavra de _ 1 1

Takes a text string as input, and reports TRUE if the string has no characters in it of any kind, otherwise false.

pt:a palavra _ está vazia

Takes a text string as input, and reports TRUE if the input contains no characters other than spaces (therefore, no words when the string is considered as a sentence), otherwise FALSE.

pt:a frase _ está vazia

de:füge Wörter zusammen _ ca:uneix les paraules _ es:unir las palabras _ fr:fusionne les mots _ pt:uma frase com as palavras _ 121

de:Liste $arrowRight Satz _ ca:llista $arrowRight frase _ es:lista $arrowRight frase _ fr:liste $arrowRight phrase _ pt:uma frase com as palavras em _

de:Satz $arrowRight Liste _ ca:frase $arrowRight llista _ es:frase $arrowRight lista _ fr:phrase $arrowRight liste _ pt:uma lista com as palavras da frase _

report a list in which each item is one letter from the input word

de:Wort $arrowRight Liste _ ca:paraula $arrowRight llista _ es:palabra $arrowRight lista _ fr:mot $arrowRight liste _ pt:uma lista com os caracteres da palavra _

join all the items of the input list into a single word, and report it

de:Liste $arrowRight Wort _ ca:llista $arrowRight paraula _ es:lista $arrowRight palabra _ fr:liste $arrowRight mot _ pt:uma palavra com os caracteres em _

89,90,91,92,93,94,95,960