integer

问题 >>> x = -4 >>> print("{} {:b}".format(x, x)) -4 -100 >>> mask = 0xFFFFFFFF >>> print("{} {:b}".format(x & mask, x & mask)) 4294967292 11111111111111111111111111111100 >>> >>> x = 0b11111111111111111111111111111100 >>> print("{} {:b}".format(x, x)) 4294967292 11111111111111111111111111111100 >>> print("{} {:b}".format(~(x ^ mask), ~(x ^ mask))) -4 -100 I am having trouble figuring out how Python represents negative integers, and therefore how bit operations work. It is my understanding that

问题 My program is suppose to read an integer and print it back to the user but every time it just prints 268501230 no matter what is entered. Any help would be appreciated. .data prompt2: .asciiz "Please enter value: " array1: .space 40 array2: .space 40 buffer: .space 4 .text main: #Prints the prompt2 string li $v0, 4 la $a0, prompt2 syscall #reads one integer from user and saves in t0 li $v0, 5 la $t0, buffer syscall li $v0, 1 li $t0, 5 # $integer to print syscall exitProgram: li $v0, 10 #

问题 My program is suppose to read an integer and print it back to the user but every time it just prints 268501230 no matter what is entered. Any help would be appreciated. .data prompt2: .asciiz "Please enter value: " array1: .space 40 array2: .space 40 buffer: .space 4 .text main: #Prints the prompt2 string li $v0, 4 la $a0, prompt2 syscall #reads one integer from user and saves in t0 li $v0, 5 la $t0, buffer syscall li $v0, 1 li $t0, 5 # $integer to print syscall exitProgram: li $v0, 10 #

问题 I have this function that is able to add integers to an existing dataframe. It takes my integers and transposes them as a column into the dataframe. When I add a column of shorter value, the rows will automatically be assigned as 0. When I add another column of longer length, all the existing columns of shorter length add 0s to be the same length as the longest column. For example... Function add_peaks <- function(df, vec, colname) { colname <- title new_row <- max(nrow(df), length(vec)) new

问题 I have this function that is able to add integers to an existing dataframe. It takes my integers and transposes them as a column into the dataframe. When I add a column of shorter value, the rows will automatically be assigned as 0. When I add another column of longer length, all the existing columns of shorter length add 0s to be the same length as the longest column. For example... Function add_peaks <- function(df, vec, colname) { colname <- title new_row <- max(nrow(df), length(vec)) new

问题 Is there a way to specify expected integer outcomes in a docstring in hex notation? def identity(val): """ >>> identity(243) 243 >>> identity(243) 0xf3 """ return val if __name__ == "__main__": import doctest doctest.testmod() Doctest doesn't interpret the hex notation, resulting in a failure: ********************************************************************** File "hextest.py", line 5, in __main__.identity Failed example: identity(243) Expected: 0xf3 Got: 243 *****************************

问题 In Java, I have an array of integers. Is there a quick way to convert them to a string? I.E. int[] x = new int[] {3,4,5} x toString() should yield "345" 回答1: Simplest performant approach is probably StringBuilder: StringBuilder builder = new StringBuilder(); for (int i : array) { builder.append(i); } String text = builder.toString(); If you find yourself doing this in multiple places, you might want to look at Guava's Joiner class - although I don't believe you'll be able to use it for

问题 In Java, I have an array of integers. Is there a quick way to convert them to a string? I.E. int[] x = new int[] {3,4,5} x toString() should yield "345" 回答1: Simplest performant approach is probably StringBuilder: StringBuilder builder = new StringBuilder(); for (int i : array) { builder.append(i); } String text = builder.toString(); If you find yourself doing this in multiple places, you might want to look at Guava's Joiner class - although I don't believe you'll be able to use it for

问题 Simple question, sorry I can;t figure this out. I have some numbers that are made by float(STRING) and they are displayed as xxx.0, but I want them to end in .00 if it is indeed a whole number. How would I do this? Thanks! EDIT: Python saiys that float doesn't have a cal 'format()' 回答1: >>> '%.2f' % 2.0 '2.00' 回答2: Also: >>> "{0:.2f}".format(2.0) '2.00' 回答3: If you do not like the numbers to be rounded, you need to do little more: >>> "%.2f" % 1.99999 '2.00' >>> "%.2f" % (int(1.99999*100)/100

问题 How can I filter only string values / integer / float values in one column in pandas data frame like below? SIC 1 246804 2 135272 3 898.01 4 3453.33 5 shine 6 add 7 522 8 Nan 9 string 10 29.11 11 20 回答1: You can use the outputs from pd.to_numeric and boolean indexing. To get only the strings use: df[pd.to_numeric(df.SIC, errors='coerce').isnull()] Output: SIC 5 shine 6 add 8 Nan 9 string To get only the numbers use: df[pd.to_numeric(df.SIC, errors='coerce').notnull()] Output: SIC 1 246804 2