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Int vs Int16 vs int32 vs int64.
What I know is that there is difference in memory consumption. But I don't understand that thing memory consumption.
I just got two questions here
what's the difference actually apart from memory consumption?
And if I make four models one using int, another using int16 and other two using int32 and int 64 . Will the result be same?
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I am working on a machine learning task and trying to convert all strings in a set of data to floats using hash() to do this I need to iterate over all the elements of a numpy array whilst not knowing if it is a 2D 3D or 4D array and then change each element. Is there any way to do this without using nested loops?
You can try numpu.vectorize, already mentioned here
Note:
The vectorize function is provided primarily for convenience, not for performance. The implementation is essentially a for loop.here
arr = np.array([['aba', 'baa', 'bbb'],
['xxy', 'xyy', 'yyy']])
v_hash = np.vectorize(hash)
v_hash(arr)
array([[-1538054455328520296, -1528482088733019667, -7962229468338304433],
[ 5621962119614158870, 1918700875003591346, -3216770211373729154]])
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I'm trying to do an iteration with Pandas or any built-in function to display multiple of 10 rows for example.
So e.g. there are 50 records and I want to display the multiple of 10 records which will be record ID 0,10,20,30,40,50.
Use iloc:
df.iloc[::10, :]
This method takes a row/column slice, both based on integer position. More details from documenation:
Purely integer-location based indexing for selection by position.
.iloc[] is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array.
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How should I do to divide years in half a year in this case if running in Python code?
I wasn't sure if you wanted horizontal or vertical divisions so I gave you both.
More practically, maybe this answer will help?
Creating numpy linspace out of datetime
You can specify start and end date and the number of divisions.
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I am getting an error TypeError: 'float' object cannot be interpreted as an integerin this part of my code. Can someone tell me why am I getting the error and how to fix it?
for y in range(-x/2, x/2):
#Some function
Replace -x/2 with -int(x/2) and x/2 with int(x/2). Division in Python returns a float and range only takes ints.
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So, what I understand is that in a 64 bit system, a number declared in python takes 64 bits. Is it possible to make it 32 bit, for memory reduction purposes?
If you have a list of numbers that need to be stored, you could use array.array('l') or array.array('L'). You may also use ctypes.c_int(), ctypes.c_uint(), ctypes.c_long(), or ctypes.c_ulong() to store numbers in four bytes.