output-formatting | 易学教程

TypeError: not all arguments converted during string formatting python

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The program is supposed to take in two names, and if they are the same length it should check if they are the same word. If it's the same word it will print "The names are the same" . If they are the same length but with different letters it will print "The names are different but the same length" . The part I'm having a problem with is in the bottom 4 lines. #!/usr/bin/env python # Enter your code for "What's In (The Length Of) A Name?" here. name1 = input("Enter name 1: ") name2 = input("Enter name 2: ") len(name1) len(name2) if len(name1) == len(name2): if name1 == name2: print ("The names

Rewinding std::cout to go back to the beginning of a line

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问题 I\'m writing a command-line tool for Mac OS X that processes a bunch of files. I would like to show the user the current file being processed, but do not want a bazillion files polluting the terminal window. Instead I would like to use a single line to output the file path, then reuse that line for the next file. Is there a character (or some other code) to output to std::cout to accomplish this? Also, if I wanted to re-target this tool for Windows, would the solution be the same for both

Controlling number of decimal digits in print output in R

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问题 There is an option in R to get control over digit display. For example: options(digits=10) is supposed to give the calculation results in 10 digits till the end of R session. In the help file of R, the definition for digits parameter is as follows: digits: controls the number of digits to print when printing numeric values. It is a suggestion only. Valid values are 1...22 with default 7 So, it says this is a suggestion only. What if I like to always display 10 digits, not more or less? My

How to print the full NumPy array, without truncation?

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问题 When I print a numpy array, I get a truncated representation, but I want the full array. Is there any way to do this? Examples: >>> numpy.arange(10000) array([ 0, 1, 2, ..., 9997, 9998, 9999]) >>> numpy.arange(10000).reshape(250,40) array([[ 0, 1, 2, ..., 37, 38, 39], [ 40, 41, 42, ..., 77, 78, 79], [ 80, 81, 82, ..., 117, 118, 119], ..., [9880, 9881, 9882, ..., 9917, 9918, 9919], [9920, 9921, 9922, ..., 9957, 9958, 9959], [9960, 9961, 9962, ..., 9997, 9998, 9999]]) 回答1: Use numpy.set