nan

问题 Hi dear I have a problem with NaN . I am working with a large dataset with many variables and they have NaN . The data is like this: z=list(a=c(1,2,3,NaN,5,8,0,NaN),b=c(NaN,2,3,NaN,5,8,NaN,NaN)) I used this commands to force the list to data frame but I got this: z=as.data.frame(z) > is.list(z) [1] TRUE > is.data.frame(z) [1] TRUE > replace(z,is.nan(z),0) Error en is.nan(z) : default method not implemented for type 'list' I forced z to data frame but it wasn't enough, maybe there is a form to

问题 Can I set an int to NaN ? If yes, then how can I check if an int is NaN or not? 回答1: No, NaN is a floating point value. Every possible value of an int is a number. Edit The standard says: 6.2.6.2 40) Some combinations of padding bits might generate trap representations, for example, if one padding bit is a parity bit. Regardless, no arithmetic operation on valid values can generate a trap representation other than as part of an exceptional condition such as an overflow, and this cannot occur

问题 I am trying to read a .txt file with multiple arrays with a fortran program. It looks like the program is finding the file but it only returns NaN value... ! INTEGER :: T, RH, i, j, ierror ! REAL, DIMENSION(3,3) :: AFILE ! LOGICAL :: dir_e inquire(file='PSR_FAB.txt', exist=dir_e) if ( dir_e ) then print*, "dir exists!" else print*, 'nope' end if OPEN (UNIT = 1234 , FILE = 'PSR_FAB.txt', STATUS = 'OLD', ACTION = 'READ') DO i=1,3 READ(1234,*, IOSTAT=ierror) (AFILE(i,j),j=1,3) print*, (AFILE(i,j

问题 Here's a brief example of a function. It maps a vector to a vector. However, entries that are NaN or inf should be ignored. Currently this looks rather clumsy to me. Do you have any suggestions? from scipy import stats import numpy as np def p(vv): mask = np.isfinite(vv) y = np.NaN * vv v = vv[mask] y[mask] = 1/v*(stats.hmean(v)/len(v)) return y 回答1: I have came up with this kind of construction: from scipy import stats import numpy as np ## operate only on the valid entries of x and use the

问题 So I have a string called hoursString that looks like 4.3|2.4|3.4|3.0|2.64|3.0|1.0|0.0|2.6|3.4| I split the string into an array and what I am trying to do is add up all the numbers and return it to the html page in the div "test". JAVASCRIPT: var hours=hoursString.split("|"); var total=0; for (var i=0;i<hours.length;i++) { total += hours[i]; } document.getElementById("test").innerHTML=total; The result is NaN. Can someone tell me what I am doing wrong? Thanks! 回答1: 4.3|2.4|3.4|3.0|2.64|3.0|1

问题 I am trying to understand floating point representations. I do not understand the 'infinity' 'NaN' representations in floating point. I am looking at the table provided by TopCoder. Infinity is represented by an exponent of all 1s and a Mantissa of all 0s. I can only read it as 0^n, and I'm not sure how that tends to infinity. 回答1: You should simply ignore the bit patterns used and treat infinities and NaNs as special values. Unless you do bit-fiddling on your floats (for which I see very

问题 I am making a simple Logistic Regression Model using Tensorflow. But the cost value is always returning nan. My data sets are divided into x_data and y_data. x_data is a coordinate in an image and y_data is 1 or 0 since my image is black and white. I am trying to find a dividing line between white color and black color. def train(input,iterations): import tensorflow as tf tf.set_random_seed(777) # for reproducibility x_data = [] y_data = [] i_dim = input.shape[0] j_dim = input.shape[1] for i

问题 This question is unlikely to help any future visitors; it is only relevant to a small geographic area, a specific moment in time, or an extraordinarily narrow situation that is not generally applicable to the worldwide audience of the internet. For help making this question more broadly applicable, visit the help center. Closed 8 years ago . Hi guys i know what NaN(let me say i know the acronym stands for Not a Number) is but i don't understand why C++ returns it - The following is the

问题 I have a pandas DataFrame with multiple columns filled with numbers and rows which have the 1st columns categorical data. Obviously, I have NaN values (and zeros) in multiple rows (but not the entire blank row, of course) in different columns, after all, this is Engineering and real data. rows have valuable data in other columns which are not nan. and the columns have valuable data in other rows, which are also not nan Problem is that sns.pairplot does not ignore NaN values for correlation

问题 I want to substitute NaN values of column Title based on the values of column Idx. If Idx is equal to 1, then NaN must be substituted by 0, if Idx is equal to 0, then NaN Title must be equal to 1. Title Idx NaN 0 0 1 1 0 NaN 0 NaN 1 I tried this: df.loc[df['Title'].isnull(), 'Title'] = 0 But of course it always puts 0. How can I add the condition here? 回答1: You can pass any Series or column to fillna(). In this case you need to fill the missing values with the Series 1 - df['Idx'] to get the