CODEWITHSUNDEEP
pythonnumpytime-series
Felix
Felix

Reputation: 2164

downsampling data using timestamp information

I have an array of some arbitrary data x and associated timestamps t that correspond to the data in x (they are the same length N).

I want to downsample my data x to a smaller length M < N, such that the new data is roughly equally spaced in time (by using the timestamp information). This would be instead of simply decimating the data by taking every nth datapoint. Using the closest time-neighbor is fine.

scipy has some resampling code, but it actually tries to interpolate between data points, which I cannot do for my data. Does numpy or scipy have code that does this?

For example, suppose I want to downsample the letters of the alphabet according to some logarithmic time:

import string
import numpy as np
x = string.lowercase[::]
t = np.logspace(1, 10, num=26)
y = downsample(x, t, 8)

Upvotes: 0

Views: 1169

Answers (1)

Lee
Lee

Reputation: 31060

I'd suggest using pandas, specifically the resample function:

Convenience method for frequency conversion and resampling of regular time-series data.

Note the how parameter in particular.

You can convert your numpy array to a DataFrame:

import pandas as pd
YourPandasDF = pd.DataFrame(YourNumpyArray)

Upvotes: 1

Related Questions