Function that cleans up FRED data for 1yr treasury constant maturity rate

Int_Rate_MSupply.py

#!python3

import sys ,os , requests
import time, json
import matplotlib.pyplot as plt
import Money_Supply_FRED as msf
import numpy as np

# This library retrieves and relies on data coming from FRED API
# Attributes
# List containing the three datasets to plot/analyze
#data_s_s =["DGS1","MANMM101USA657S","MABMM301USA657S"]
data_s_s =["DGS1","M1","M2"]
#DGS1 represents the 1-yr-Treasury Note
#M1 is the M1 money stock while M2 is M2 money stock

def growth_rate(id):

    #Put all data together in lists and dictionaries
    ob,ds,vs = msf.obtain_observations(id)
    # Cleaning up the "."
    #vs = [item.replace('.', '0') for item in vs]
    delta = 365 # 365 days like a year cycle
    pointer = 0
    #Initialize end lists
    final_values = list()
    final_date = list()
    while pointer <= len(ds):

        if (pointer+delta) <= len(ds):

            v_0 = float(vs[pointer])
            v_1 = float(vs[pointer+delta])
            if v_0 != 0:
                g = (v_1-v_0)/(v_0)
            else:
                g = v_1
            pointer = pointer + delta
            final_values.append(g)
            final_date.append(ds[pointer])
            print(g)
        else:
            end = len(ds)-1
            v_0 = float(vs[pointer])
            v_1 = float(vs[end])
            if v_0 != 0:
                g = (v_1-v_0)/(v_0)
            else:
                g = v_1
            g = (v_1 - v_0) / (v_0)
            final_values.append(g)
            final_date.append(ds[end])
            break



    return final_date, final_values

def constant_maturity(id, range):

    ob, ds, vs = msf.obtain_observations(id)
    delta = 365
    max = len(ds)-1
    samples_total = delta*int(range)
    min = max - samples_total
    ds = ds[min:max]
    vs= vs[min:max]
    pointer = 0
    vx=list()
    for index in vs:
        if index == ".":
            vx.append(0.0)
        else:
            vx.append(float(index))
        pointer = pointer + 1
    return ds,vx

def main():

    #fs,fv=growth_rate(data_s_s[0])
    fs,fv=constant_maturity(data_s_s[0],3)
    msf.plot_single(fs, fv, "date range", "%", "1yr treasury note")

if __name__ == "__main__":
    main()

This is an short script that relies on self libraries you may find on this github that aims to plot the 1yr treasury rate constant maturity. It cleans up the data since the FRED series uses "." instead of "0.0". Besides, it allows the user to use a range in years to go back and shorten the range of plotting. Happy research