Numpy interpolate time series

1. Which interpolation method is best for time series?
2. What is interpolation in time series?
3. What is interpolation in Numpy?

Which interpolation method is best for time series?

Linear interpolation is the most straightforward and commonly used interpolation method. It comes naturally when we have two points, we connect them with a straight line to fill out the missing information in between.

What is interpolation in time series?

Interpolation is mostly used while working with time-series data because in time-series data we like to fill missing values with previous one or two values. for example, suppose temperature, now we would always prefer to fill today's temperature with the mean of the last 2 days, not with the mean of the month.

What is interpolation in Numpy?

interp() function returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. Syntax : numpy.interp(x, xp, fp, left = None, right = None, period = None)