and put the transformed data back into the same DataFrame. The problem is that df.apply(scaler.transform) feeds data into the scaler column-by-column (1D arrays), where scaler expects a 2D array. Following the answers here …
Combining multiple lists into one Comprehensions allow for multiple iterators and hence, can be used to combine multiple lists into one. a = [1, 2, 3] b = [7, 8, 9] [(x + y) for (x,y) in zip(a,b)] # parallel iterators #...
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Output:Thenp.append()function is used to combine the two NumPy arrays into a single array, containing the data of both arrays in Python. Quarterly Revenue Data (NY + CA): [5.2 4.8 6.1 5.5 6.5 6.6 7.2 6.8] This way we can use theappend() functionfrom the NumPy library for the concat...
Numbers: int, float, complex Strings: str Booleans: bool Lists: list Tuples: tuple Dictionaries: dict Sets: setExamplesHere is an example of how to use the Python data types.# Integer a = 10 # Float b = 3.14 # String c = "Hello" # Boolean d = True # List e = [1, 2, 3,...
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Flatten 2D array into 1D array [a for r in matrix for a in r] Iterate over a list for v in l: Iterate over a list with index+val for i, v in enumerate(l): zip two lists as one l = sorted(zip(nums, range(len(nums))) Convert int array to a string =’ ‘.join([str(v...
Convolutional Networks combine three architectural ideas to ensure some degree of shift, scale, and distortion invariance: local receptive fields, shared weights (or weight replication), and spatial or temporal sub-sampling. Each unit in a layer receives inputs from a set of units located in a s...