I am new to loops, and I am trying to iterate over all items in a list, and I need to generate the values between 0 and 2 with a given step value. I have tried to use the “range” function, but cannot get it to work.
The end result should look something like this (doesn’t have to be in a pandas dataframe, just for illustrative purposes):
import pandas as pd import numpy as np data = {'range_0.5' : [0,0.5,1,1.5,2, np.nan, np.nan, np.nan, np.nan], 'range_0.25' : [0,0.25,0.5,0.75,1,1.25,1.5,1.75,2]} df = pd.DataFrame(data) df
Here is what I have tried:
import numpy x = [] seq = [0.5, 0.25, 0.125, 0.0625, 0.03125, 0.015625, 0.0078125, 0.00390625] for i in seq: x = range(0, 2, i)
The following error is thrown:
TypeError Traceback (most recent call last) Input In [10], in <cell line: 1>() 1 for i in seq: ----> 2 x = range(0, 2, i) TypeError: 'float' object cannot be interpreted as an integer
How can I properly create my loop?
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Answer
np.arange()
You can use numpy.arange()
which supports floats as step values.
import numpy as np for step in [0.5, 0.25]: print([i for i in np.arange(0, 2, step))
Expected output:
[0.0, 0.5, 1.0, 1.5] [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75]
To include 2
just add the step value once again:
for step in [0.5, 0.25]: print([i for i in np.arange(0, 2 + step, step)])
Expected output:
[0.0, 0.5, 1.0, 1.5, 2.0] [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0]
np.linspace()
Alternatively you can use np.linspace()
:
This has the ability to include the endpoint using endpoint=True
;
for step in [0.5, 0.25]: print([i for i in np.linspace(0, 2, int(2 // step) + 1, endpoint=True)])
Expected output:
[0.0, 0.5, 1.0, 1.5, 2.0] [0.0, 0.25, 0.5, 0.75, 1.0, 1.25, 1.5, 1.75, 2.0]