Aug 19, 2010 · You can then easily, and with less time even for huge amount of data, load your data in a NumPy array. import pandas as pd store = pd.HDFStore('dataset.h5') data = store['mydata'] store.close() # Data in NumPy format data = data.values

Note that numpy.where will not just return an array of the indices, but will instead return a tuple (the output of condition.nonzero()) containing arrays - in this case, (the array of indices you want,), so you'll need select_indices = np.where(...)[0] to get the result you want and expect.

I'm very confused as to what np.exp() actually does. In the documentation it says that it: "Calculates the exponential of all elements in the input array." I'm confused as to what exactly this means.

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NumPy is not another programming language but a Python extension module. It provides fast and efficient operations on arrays of homogeneous data. Numpy has fixed size of creation. In Python :lists are written with square brackets. These lists can be homogeneous or heterogeneous; The main advantages of using Numpy Arrays Over Python Lists:

I have a numpy array containing: [1, 2, 3] I want to create an array containing: [1, 2, 3, 1] That is, I want to add the first element on to the end of the array. I have tried the obvious: np.

Dec 28, 2021 · In python 3.6.7, this code shows the numpy version: import numpy print (numpy.version.version) If you insert this code in the file shownumpy.py, you can compile it:

Jul 13, 2013 · import numpy as np # base similarity matrix (all dot products) # replace this with A.dot(A.T).toarray() for sparse representation similarity = np.dot(A, A.T) # squared magnitude of preference vectors (number of occurrences) square_mag = np.diag(similarity) # inverse squared magnitude inv_square_mag = 1 / square_mag # if it doesn't occur, set it ...

For python 3. pip3 install numpy --upgrade Similarly, the tables for python3 :-pip3 install tables --upgrade

import pandas as pd import numpy as np df_describe = pd.DataFrame(dataset) df_describe.describe() please note that dataset is your np.array to describe. import pandas as pd import numpy as np df_describe = pd.DataFrame('your np.array') df_describe.describe()