negation

问题 How would I use a negative form of Python's isinstance()? Normally negation would work something like x != 1 if x not in y if not a I just haven't seen an example with isinstance(), so I'd like to know if there's a correct way to used negation with isinstance(). 回答1: Just use not . isinstance just returns a bool , which you can not like any other. 回答2: That would seem strange, but: if not isinstance(...): ... The isinstance function returns a boolean value. That means that you can negate it

问题 How would I use a negative form of Python's isinstance()? Normally negation would work something like x != 1 if x not in y if not a I just haven't seen an example with isinstance(), so I'd like to know if there's a correct way to used negation with isinstance(). 回答1: Just use not . isinstance just returns a bool , which you can not like any other. 回答2: That would seem strange, but: if not isinstance(...): ... The isinstance function returns a boolean value. That means that you can negate it

问题 In C/C++, why should one use abs() or fabs() to find the absolute value of a variable without using the following code? int absoluteValue = value < 0 ? -value : value; Does it have something to do with fewer instructions at lower level? 回答1: The "conditional abs" you propose is not equivalent to std::abs (or fabs ) for floating point numbers, see e.g. #include <iostream> #include <cmath> int main () { double d = -0.0; double a = d < 0 ? -d : d; std::cout << d << ' ' << a << ' ' << std::abs(d)

问题 I wanted to create a simple NOT operator in typescript where you get all primitives combined into the union of some type A that are NOT primitive members of the union of a second type B. This can be done using conditional types. For example, if you have types: type A = 'a' | 'b' | 'c'; type B = 'c' | 'd' | 'e'; ... then I want to map them to a third derived type [A - B] that, in this case, would yield: type C = 'a' | 'b' This seems to be doable using conditionals of the form shown below.

问题 Here is my code: import pandas as pd import numpy as np df = pd.DataFrame({ 'var1': ['a', 'b', 'c',np.nan, np.nan], 'var2': [1, 2, np.nan , 4, np.nan] }) conditions = [ (not(pd.isna(df["var1"]))) & (not(pd.isna(df["var2"]))), (pd.isna(df["var1"])) & (pd.isna(df["var2"]))] choices = ["No missing", "Both missing"] df['Result'] = np.select(conditions, choices, default=np.nan) Output: File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py", line 1478, in __nonzero__ f"The truth

问题 Here is my code: import pandas as pd import numpy as np df = pd.DataFrame({ 'var1': ['a', 'b', 'c',np.nan, np.nan], 'var2': [1, 2, np.nan , 4, np.nan] }) conditions = [ (not(pd.isna(df["var1"]))) & (not(pd.isna(df["var2"]))), (pd.isna(df["var1"])) & (pd.isna(df["var2"]))] choices = ["No missing", "Both missing"] df['Result'] = np.select(conditions, choices, default=np.nan) Output: File "C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py", line 1478, in __nonzero__ f"The truth

问题 In PHP, is if(!$foo) equivalent with if($foo != true) or with if($foo !== true) or is it even something completly different of both? 回答1: if(!$foo) is the equivalent to if($foo != true) so $foo = null; if(!$foo){ echo "asd"; } will ouptut "asd" 回答2: Note that, == OR != compares the values of variables for equality, type casting as necessary. === OR !== checks if the two variables are of the same type AND have the same value. This answer will give you better explanation of this concept: https:

问题 I'm doing sentiment analysis for financial articles. To enhance the accuracy of my naive Bayes classifier, I'd like to implement negation handling. Specifically, I want to add the prefix "not_" to the word following a "not" or "n't" So if there's something like this in my corpus: x <- "They didn't sell the company." I want to get the following: "they didn't not_sell the company." (the stopword "didn't" will be removed later) I could find only the gsub() function, but it doesn't seem to work

问题 I'm doing sentiment analysis for financial articles. To enhance the accuracy of my naive Bayes classifier, I'd like to implement negation handling. Specifically, I want to add the prefix "not_" to the word following a "not" or "n't" So if there's something like this in my corpus: x <- "They didn't sell the company." I want to get the following: "they didn't not_sell the company." (the stopword "didn't" will be removed later) I could find only the gsub() function, but it doesn't seem to work

问题 Maybe I'm missing something but I can't find a straightforward way to accomplish this simple task. When I go to negate a binary number through the "~" operator it returns a negative number due to the two's complement: >>> bin(~0b100010) # this won't return '0b011101' '-0b100011' What about if I just want to switch 0s into 1s and vice-versa, like in classic logical complement? 回答1: >>> bin(0b111111 ^ 0b100010) '0b11101' >>> 回答2: YOU's answer as a function: def complement(n): size = len(format