nan

问题 After using sdf_pivot I was left with a huge number of NaN values, so in order to proceed with my analysis I need to replace the NaN with 0, I have tried using this: data <- data %>% spark_apply(function(e) ifelse(is.nan(e),0,e)) And this gererates the following error: Error in file(con, "r") : cannot open the connection In addition: Warning message: In file(con, "r") : cannot open file 'C:\.........\file18dc5a1c212e_spark.log':Permission denied I'm using Spark 2.2.0 and the latest version of

问题 I have a case where I am adding data from one dataframe to another, but I can't rid of the nan values. Example data df1 = pd.DataFrame( { 'Journal' : ['US Drug standards.','Acta veterinariae.','Bulletin of big toe science.','The UK journal of dermatology.'], 'ISSN_1': ['0096-0225', '0567-8315','0007-4977','0007-0963'], 'ISSN_2': ['0096-0225','nan','0007-4977','0007-0963'], 'ISSN_3': ['nan','1820-7448','nan','0366-077X'], 'ISSN_4': ['nan','0567-8315','nan','1365-2133'] } ) df1 = df1[['Journal'

问题 I have a dataframe with some NaN values. Here is a sample dataframe: sample_df = pd.DataFrame([[1,np.nan,1],[2,2,np.nan], [np.nan, 3, 3], [4,4,4],[np.nan,np.nan,5], [6,np.nan,np.nan]]) It looks like: What I did after to get a json: sample_df.to_json(orient = 'records') Which gives: '[{"0":1.0,"1":null,"2":1.0},{"0":2.0,"1":2.0,"2":null},{"0":null,"1":3.0,"2":3.0},{"0":4.0,"1":4.0,"2":4.0},{"0":null,"1":null,"2":5.0},{"0":6.0,"1":null,"2":null}]' I want to save this dataframe to a json with 2

问题 I have been experimenting with the bubble sort code as I have recently started to gain my knowledge of C code. However I am unable to input NAN into the code for it to print out when building and running it. I am having the same problem with INFINITY AND -INFINITY. The code, however, works when I run the code and input NAN, INFINITY AND -INFINITY as one of the integers. Help would be appreciated, thanks. /* Bubble sort code */ #include <stdio.h> #include <math.h> int main() { float array[100]

问题 In a numpy array I want to replace all nan and inf into a fixed number. Can I do that in one step to save computation time (arrays are really big)? a = np.arange(10.0) a[3] = np.nan a[5] = np.inf a[7] = -np.inf # a: [ 0. 1. 2. nan 4. inf 6. -inf 8. 9.] a[np.isnan(a)] = -999 a[np.isinf(a)] = -999 # a: [ 0. 1. 2. -999. 4. -999. 6. -999. 8. 9.] The code above works fine. But I am looking for something like: a[np.isnan(a) or np.isinf(a)] = -999 Which does not work and I can see why. Just thinking

问题 I have a pandas series containing zeros, ones and np.nan: import pandas as pd import numpy as np df1 = pd.Series([ 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, np.nan, np.nan, 1]) df1 Out[6]: 0 0.0 1 0.0 2 0.0 3 0.0 4 0.0 5 1.0 6 1.0 7 1.0 8 0.0 9 0.0 10 0.0 11 NaN 12 NaN 13 1.0 dtype: float64 I would like to create a dataframe df2 that contains the start and the end of intervals with the same value, together with the value associated... df2 in this case should be... df2 Out[5]: Start End Value 0 0 4 0 1

问题 Oracle provides functions to test whether a stored value is NaN or +-infinity. Is there something similar that can be used in Access and Sql Server? 回答1: Yes, Access can detect "NaN" and "+/-Infinity", at least for values that reside in Double columns of a native Access table: You can even have Access perform queries like the following, which will return all rows that contain a "NaN" (positive or negative) in the Double column: SELECT * FROM Table1 WHERE Right(CStr([DoubleField]), 3) = 'NAN';

问题 I have a view that output decimal values that represent money data types on the database. To output I am using the following formatting code string price = String.Format("{0:f}", (item.Price + item.VAT)); that produce a string like this 12,99 (with comma as the decimal separator) I am now using this string to make some calculation on the client using jQuery elmProductSelected.children("option").each(function(n) { var pIdx = $(this).attr("rel"); var pObj = products.eq(pIdx); var pValue = $

问题 I'm using tensorflow to replicate a neural network for the MNIST dataset, previously programmed in skflow. Here is the model in skflow: import tensorflow.contrib.learn as skflow from sklearn import metrics from sklearn.datasets import fetch_mldata from sklearn.cross_validation import train_test_split mnist = fetch_mldata('MNIST original') train_dataset, test_dataset, train_labels, test_labels = train_test_split( mnist.data, mnist.target, test_size=10000, random_state=42) classifier = skflow

问题 I have written a program to print a matrix after some computations and I am getting an output of nan for all elements. I want to break a for loop as soon as the matrix's first element becomes nan to understand the problem. How can I do this? In the terminal, I have printed the matrix a containing nan as all elements and typed a[1][1]=="nan" and a[{{1},{1}}]=="nan" both of which return false . Why are they not returning false and what statement should I use instead? 回答1: Your test fails