python - NaN values in Pandas are not being filled by the interpolate function when it's applied to a full dataframe - S
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So, i'm a beginner at the Pandas Python and noticed the interpolate function is pretty interesting, but i have one problem when using the line:
result = df.interpolate(method='linear')
I found out that even though it did filled a lot of the NaN's in 'df', the four first NaN's of Ambient_temp and the first NaN on the Intake_temp column are not filled the way i wanted. Any hints on how to get this working? The interpolation worked very well with every other column besides those two.
Image of said dataframe
Example:
amb_temp = [np.nan, np.nan, 32, 32]
in_temp = [ 29, 27, 23, 22]
volts = [np.nan, 13, 11, 11]
dict = {'ambient_temperature': amb_temp, 'temperature_inside': in_temp, 'volts': volts}
df = pd.DataFrame(dict)
(it's not exactly the same dataframe, but encapsulates the same problem. I got this one based off and example on 'geeksforgeeks' and used numpy.nan to simulate the absence of data.)
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