how to calculate dominant frequency use numpy.fft in python

Question

I have this data frame about vehicle vibration and I want to calculate the dominant frequency of the vibration. I know that we can calculate it using numpy.fft, but I have no idea how can I apply numpy.fft to my data frame. Please enlighten me how to do it in python. Thankyou.

Answer 1

A dataframe column is a NumPy array effectively

df = pd.DataFrame({"Vibration":[random.uniform(2,10) for i in range(10)]})
df["fft"] = np.fft.fft(df["Vibration"].values)
print(df.to_string())

output

   Vibration                  fft
0   8.212039  63.320213+0.000000j
1   5.590523   2.640720-2.231825j
2   8.945281  -2.977825-5.716229j
3   6.833036   4.657765+5.649944j
4   5.150939  -0.216720-0.445046j
5   3.174186  10.592292+0.000000j
6   9.054791  -0.216720+0.445046j
7   5.830278   4.657765-5.649944j
8   5.593203  -2.977825+5.716229j
9   4.935937   2.640720+2.231825j

batching to every 15 rows

df = pd.DataFrame({"Vibration":[random.uniform(2,10) for i in range(800)]})

df.assign(
    fft=df.groupby(df.index // 15)["Vibration"].transform(lambda s: np.fft.fft(list(s)).astype("object")),
    grpfirst=df.groupby(df.index // 15)["Vibration"].transform(lambda s: list(s)[0])
)

Answer 2

Without knowing how the DataFrame looks like, and which fields you need to use for your calculations, you can apply any function to dataframe using .apply()

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.apply.html