How do I create an array or dataframe to store seedN, clf.score(X_test, y_test),n_neighbors? Answer Create a temporary empty list to store the results : For each fit, add a new list with the desired values : Finally, create the dataframe with this temporary list :
Tag: arrays
How to extract specific part of a line in a text in Python
I have a huge file that I splitted in a series of lines with the function text.splitlines(). From these lines I need to specifically extract some informations corresponding to a keyword: “ref-p”. What I did is: what I obtained is: now I need to move the three series of number into a dictionary in the form: {ref-p: [[number, number, number],
Access data in python3 associative arrays
I’d like how to create and print associative arrays in python3… like in bash I do: In bash I can do echo “${array[“beta”,1]}” to access data to print “text2”. How can I define a similar array in python3 and how to access to data in a similar way? I tried some approaches, but none worked. Stuff like this: But I
How to split a 2d numpy array vertically into a new 2d numpy array?
I have this code that essentially splits a two-dimensional numpy array horizontally and makes a new two-dimensional numpy array out of it. Output of my code: How can I do this with less lines of code? I assume it could be very resource intensive, as soon as I apply this example to my larger task. Answer I suppose using numpy.hsplit
Is this a correct python port of a fortran function call
I’m trying to port fortran code to python (call me crazy), and am wondering whether I’m handling the input of a variable to a function in a correct way. note that I’ve read: Fortran77: what does the asterisk (*) means in subroutine argument? How can a scalar be passed to a vector (1D array) to a Fortran subroutine? What is
Calculate RMS, Count, SUM to array inside all columns of pandas dataframe
I would like to calculate RMS, Count, SUM to array inside all columns of pandas dataframe and then fulfill outputs into new three dataframes as shown below P.S > solution should deal with N numbers of columns, in my case, I have around 300 columns x,y,z,a,b,c ……. etc …… N ID x y z ….. EF407412 [471, 1084, 1360, 2284]
Replace Spark array values with values from python dictionary
I have a Spark dataframe column having array values: I want to replace [0,1,2,3,4] with [negative,positive,name,sequel,odd] Answer
how do I match and find a vector in a Numpy array?
I have a Numpy array with size [2000,6].now I have an array with size [1,6] and I want to know which row of the main Numpy array is the same as this [1,6] array. if it exists in the main array, return the index of the row. for example row 1. but I do not want to use for loops
self.array = nums: what is time complexity for assignment of lists in python?
I was solving Dot Product of Two Sparse Vectors (Given two sparse vectors, compute their dot product.) and I got confused about time complexity. For solution: it says in answer that Time complexity: O(n) for both constructing the sparse vector and calculating the dot product. Why time complexity of __init__ is O(n)? I thought that self.array = nums is simple
Convert 2D dataframe to 3D numpy array based on unique ID
I have a dataframe in this format: … though my dataframe is much larger, with more than 500 hundred IDs. I want to convert this 2D – dataframe into a 3D array in this format (num_time_samples, value, ID). Essentially I would like to have one 2D-array for every unique ID. I plan on using the value column to build lag