nan

问题 NaN is handled perfectly when I check for its presence in a list or a set. But I don't understand how. [UPDATE: no it's not; it is reported as present if the identical instance of NaN is found; if only non-identical instances of NaN are found, it is reported as absent.] I thought presence in a list is tested by equality, so I expected NaN to not be found since NaN != NaN. hash(NaN) and hash(0) are both 0. How do dictionaries and sets tell NaN and 0 apart? Is it safe to check for NaN presence

问题 I have a really big DataFrame and I was wondering if there was short (one or two liner) way to get the a count of non-NaN entries in a DataFrame. I don't want to do this one column at a time as I have close to 1000 columns. df1 = pd.DataFrame([(1,2,None),(None,4,None),(5,None,7),(5,None,None)], columns=['a','b','d'], index = ['A', 'B','C','D']) a b d A 1 2 NaN B NaN 4 NaN C 5 NaN 7 D 5 NaN NaN Output: a: 3 b: 2 d: 1 回答1: The count() method returns the number of non- NaN values in each column:

问题 Here's my code: int f(double x) { return isnan(x); } If I #include <cmath> I get this assembly: xorl %eax, %eax ucomisd %xmm0, %xmm0 setp %al This is reasonably clever: ucomisd sets the parity flag if the comparison of x with itself is unordered, meaning x is NAN. Then setp copies the parity flag into the result (only a single byte, hence the initial clear of %eax ). But if I #include <math.h> I get this assembly: jmp __isnan Now the code is not inline, and the __isnan function is certainly

问题 i am new to pandas. I have loaded csv using pandas.read_csv. i have tried not to specify dtype but it was way too slow. since it is a very large file, i also specified data type. however, sometimes in numeric columns, it contains "NA". i have used na_values = ['NA'], will it affect my data frame? i still want to preserve these rows. my question is if i specify data type and add na_values = ['NA'], will NA be tossed away? if yes, how can i maintain similar process time without losing these na?

问题 I have a question about the next code: int main { double x = 0; double y = 0/x; if(y==1) {.....} .... .... return 0; } When I run the code on my computer, I get no runtime error and I see that y = -nan(0x8000000000000) . Why it is not a runtime error to divide by zero? Additionally, when I change the first line to int x = 0; now there is a runtime error. What is the difference? 回答1: You can't rely on this "working" (i.e. doing the same thing all the time, portably) at all, it's undefined

问题 I am reading in a bunch of CSV files (measurement data for water levels over time) to do various analysis and visualizations on them. Due to various reasons beyond my control, these time series often have missing data, so I do two things: I count them in total with Rlength=len(RainD) #counts everything, including NaN Rcount=RainD.count() #counts only valid numbers NaN_Number=Rlength-Rcount and discard the dataset if i have more missing data than a certain threshold: Percent_Data=Rlength/100

问题 This question already has answers here : Matplotlib grayscale heatmap with visually distinct “NA” squares fields (2 answers) Closed 3 years ago . I have a numpy array that I need to plot as a heatmap. The numpy array would also contain NaN values which I need to exclude from plotting. I was told in other posts that numpy automatically masks the NaN values in the plot, but its somehow not working for me. Here is a sample code column_labels = list('ABCDEFGH') row_labels = list('WXYZ') fig, ax =

问题 While writing some test cases, and some of the tests check for the result of a NaN. I tried using std::isnan but the assert failes: Assertion `std::isnan(x)' failed. After printing the value of x , it turned out it's negative NaN ( -nan ) which is totally acceptable in my case. After trying to use the fact that NaN != NaN and using assert(x == x) , the compiler does me a 'favor' and optimises the assert away. Making my own isNaN function is being optimised away as well. How can I check for

问题 float f = (float)'a'; if(f < 0){ } else if(f == 0){ } else if(f > 0){ } else{ printf("NaN\n"); } f won't be greater/equal/less than 0 if it's a NaN . But how to produce such a f in the first place? I tried various ways to produce a NaN ,but none work.. 回答1: Using floating point numbers, 0.0 / 0.0 isn't a "divide by zero" error; it results in NaN . This C program prints -nan : #include <stdio.h> int main() { float x = 0.0 / 0.0; printf("%f\n", x); return 0; } In terms what NaN looks like to

问题 Which is the equivalent of isnan() in Swift ? I need to check if some operation results are valid and delete those invalid like x/0 Thanks 回答1: It's defined in the FloatingPointNumber protocol, which both the Float and Double types conform to. Usage is as follows: let d = 3.0 let isNan = d.isNaN // False let d = Double.NaN let isNan = d.isNaN // True If you're looking for a way to make this check yourself, you can. IEEE defines that NaN != NaN, meaning you can't directly compare NaN to a