Accumulating Precipitation Data

If we have a pandas dataframe named df1 with a column '15min' containing 15 minute precipitation data, we can easily accumulate for other durations, using the rolling method as shown in the example below:

df1['01 h'] =df1['15min'].rolling(window=4,center=False).sum()

Note that the window=4 parameter means that it will accumulate 4 lines of 15 minute data, resulting in 1 hour precipitation. This parameter can be changed to whatever duration you want.

Polynomial Curve Fitting

The code below shows how easily you can do a Polynomial Curve Fitting with Python and Numpy.

import numpy as np

# sample x and y data - example
x = [7.76,10.11,11.89,14.81,15.49]
y = [1.851,1.971,1.953,1.842,1.805]

# the polyfit functions does the nth degree polynomial best fit on the data, 
# returning the polynomial coefficients

n = 4   # 4th degree polynomial, you can change for whatever degree you want
coefs = np.polyfit(x,y,n)

# The poly1d function applies the polynomial function to our calculated coefficients
polyf = np.poly1d(coefs)

#if we want to apply our polynomial function to a range of x values
xf = np.linspace(0,20)
yf = polyf(xf)