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Is there a pythonic way to raise a column in DataFrame (xRaw) to consecutive powers? Is there something like
xRaw[:,k] = xRaw.pow(k) for k in range(1,6)
1000
The exponential of any column is found out by using numpy. exp() function. This function calculates the exponential of the input array/Series. Return: An array with exponential of all elements of input array/Series.
Pandas Series: repeat() functionThe repeat() function is used to repeat elements of a Series. Returns a new Series where each element of the current Series is repeated consecutively a given number of times. The number of repetitions for each element. This should be a non-negative integer.
Practical Data Science using Python To add anew column with constant value, use the square bracket i.e. the index operator and set that value.
This is a Vandermonde matrix, which numpy has a built-in function for np.vander
If you have
s = pd.Series([1,2,3,4,5])
Then
np.vander(s, 6)
array([[ 1, 1, 1, 1, 1, 1],
[ 1, 2, 4, 8, 16, 32],
[ 1, 3, 9, 27, 81, 243],
[ 1, 4, 16, 64, 256, 1024],
[ 1, 5, 25, 125, 625, 3125]])
To add back to a df, you can use concat
df = pd.concat([df, pd.DataFrame(vander)], axis=1)
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