[Solved] How to replace a value by null?
you could use replace data[‘Rating-Mean’] = data[‘Rating-Mean’].replace([0], None) solved How to replace a value by null?
numpy
[Solved] python, change value of matrix eye [closed]
You can do something like as follows. import numpy as np A = np.eye(3, 3) B = np.eye(3, 3, k=-1) B[B>0]=-1 C = A + B C[0, 0] = 0 print(C) Output: [[ 0. 0. 0.] [-1. 1. 0.] [ 0. -1. 1.]] solved python, change value of matrix eye [closed]
[Solved] How to merge data into python
try to understand your question, as far as I can do now… df = pandas.read_csv(‘your file name’,sep=’;’, header=None) df = df.groupby([1]).mean().reset_index() then pick the column you need. 2 solved How to merge data into python
[Solved] python numpy arange dtpye? why converting to integer was zero
First let’s skip the complexity of a float step, and use a simple integer start and stop: In [141]: np.arange(0,5) Out[141]: array([0, 1, 2, 3, 4]) In [142]: np.arange(0,5, dtype=int) Out[142]: array([0, 1, 2, 3, 4]) In [143]: np.arange(0,5, dtype=float) Out[143]: array([0., 1., 2., 3., 4.]) In [144]: np.arange(0,5, dtype=complex) Out[144]: array([0.+0.j, 1.+0.j, 2.+0.j, 3.+0.j, … Read more
[Solved] Fast method of converting all strings in a list to integers
Multiprocessing is a way to get it done faster (in addition of using Numpy): E.g: In [11]: from multiprocessing import Pool In [12]: pool = Pool(10) In [13]: pool.map(int, [str(i) for i in range(500)]) Numpy will mostly provide a memory gain as you would be dealing with primitive types instead of python objects, but will … Read more
[Solved] Count the number of times elements in a numpy array consecutively satisfy a condition
You can use numpy masking and itertools.groupby. from itertools import groupby b = 6 sum(len(list(g))>=2 for i, g in groupby(a < b) if i) #3 solved Count the number of times elements in a numpy array consecutively satisfy a condition
[Solved] How to get sum of products of all combinations in an array in Python? [closed]
You can do with numpy and itertools: from numpy import linspace, prod from itertools import combinations arr = np.array([1,2,3,4]) [sum([prod(x) for x in combinations(arr,int(i))]) for i in linspace(1,len(arr), len(arr))] [10, 35, 50, 24] solved How to get sum of products of all combinations in an array in Python? [closed]
[Solved] Probability Distribution Function Python
This is a minimal working example for showing a histogram. It only solves part of your question, but it can be a step towards your goal. Note that the histogram function gives you the values at the two corners of the bin and you have to interpolate to get the center value. import numpy as … Read more
[Solved] Extracting the elements matching the filter
I’m basing this answer on a very similar answer I wrote just a few hours ago. #from sklearn.feature_extraction.image import extract_patches # similar to numpy’s stride_tricks from numpy.lib.stride_tricks import as_strided data = np.array([[1, 1 , 0 , 0 , 0 , 0 , 1 , 0], [1, 1 , 1 , 0 , 0 , 1 … Read more
[Solved] Python Numpy Flat Function
A simple use of flat: In [410]: res = np.zeros((2,3), dtype=int) In [411]: res Out[411]: array([[0, 0, 0], [0, 0, 0]]) In [413]: res.flat[::2]=1 In [414]: res Out[414]: array([[1, 0, 1], [0, 1, 0]]) In [415]: res.ravel() Out[415]: array([1, 0, 1, 0, 1, 0]) flat is a variant on flatten and ravel. Here I use … Read more
[Solved] Python Lists and tuples
Problem is you are trying to send a array that is a python list. At first you need to convert it into nampy array. import numpy as np py_list = [439, 301, 481, 194, 208, 415, 147, 502, 333, 86, 544, 353, 229] convert_numpy = np.array(py_list ) sent = sent[np.convert_numpy,:] and for 1st line [439 … Read more
[Solved] I am writing a simple face recognition program I faced Syntax Error [closed]
blob=cv2.dnn.blobFromImage(cv2.resize(image,(300,300),1.0,(300,300),(104.0, 177.0, 123.0)) here is one closing bracket missing 0 solved I am writing a simple face recognition program I faced Syntax Error [closed]
[Solved] Reshaping a weird list in python [duplicate]
IIUC, given array = [[[0,0,1,0],[0,0,0,1],[1,0,0,0],[0,1,0,0]], [[0,1,0],[1,0,0],[0,0,1],[0,0,1]], [[0],[1],[0],[1]], [[1],[1],[0],[1]]] Do import numpy as np >>> np.array(array).T array([[list([0, 0, 1, 0]), list([0, 1, 0]), list([0]), list([1])], [list([0, 0, 0, 1]), list([1, 0, 0]), list([1]), list([1])], [list([1, 0, 0, 0]), list([0, 0, 1]), list([0]), list([0])], [list([0, 1, 0, 0]), list([0, 0, 1]), list([1]), list([1])]], 2 solved Reshaping a … Read more
[Solved] applying onehotencoder on numpy array
Don’t use a new OneHotEncoder on test_data, use the first one, and only use transform() on it. Do this: test_data = onehotencoder_1.transform(test_data).toarray() Never use fit() (or fit_transform()) on testing data. The different number of columns are entirely possible because it may happen that test data dont contain some categories which are present in train data. … Read more
[Solved] Python: Numpy slicing indepth explnation [closed]
Add a print(N) line after all the N+= lines, and try various Z arrays. For example Define a small z with a block of 1s in the middle: In [29]: z = np.zeros((10,10),int) In [31]: z[4:6,4:6]=1 In [34]: z[4:8,5]=1 In [35]: z Out[35]: array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, … Read more