# python – Highest frequencies used in Signal (df column) with ftt

I am looking for the highest frequency of a signal_u (csv file, signal values stored in one column). Fourier transformation should be used, and find max frequency having a significant amplitude. There may be many frequencies with tiny amplitudes. Threshold can also be used to filter these out.

signal_u = csv file data:

time,s1
2017-08-29 10:30:00.000,15.12
2017-08-29 10:30:00.010,15.01
2017-08-29 10:30:00.020,14.51
2017-08-29 10:30:00.030,14.94
2017-08-29 10:30:00.040,14.96
2017-08-29 10:30:00.050,14.61
2017-08-29 10:30:00.060,14.56
2017-08-29 10:30:00.070,14.26
2017-08-29 10:30:00.080,13.95
2017-08-29 10:30:00.090,13.6
2017-08-29 10:30:00.100,13.76
2017-08-29 10:30:00.110,13.42
2017-08-29 10:30:00.120,13.62


I have tried the following:

import numpy.fft as fft{"n"}
import matplotlib.pyplot as plt

data = np.array(signal_u.iloc[:,1])

frate = 10000 #random

spectrum = np.fft.fft(data)
f_u = fft.fftfreq(len(spectrum))
print(f_u.min(), f_u.max())
print(f_u)
plt.plot(f_u, abs(spectrum))

idx = np.argmax(np.abs(spectrum))
freq = f_u[idx]
freq_in_hertz = abs(freq * frate)
print(freq_in_hertz)


Output:

-0.5 0.4999
[ 0.      0.0001  0.0002 ... -0.0003 -0.0002 -0.0001]
0.0>


The output looks wrong. What do i have to do to find the highest frequency?