import numpy as np
import pandas as pd
current_country = pd.DataFrame({
'Country': ['South Sudan','South Sudan','South Sudan','South Sudan'],
'Region': ['Sub-Saharan Africa', 'Sub-Saharan Africa', 'Sub-Saharan Africa', 'Sub-Saharan Africa',],
'Happiness Rank': [143, 147, 154, 156],
'Score': [3.83200, 3.59100, 3.25400, 2.85300],
'GDP per capita': [0.393940, 397249, 0.337000, 0.306000],
'Family': [0.185190, 0.601323, 0.608000, 0.575000],
'Life Expectancy': [0.157810, 0.163486, 0.177000, 0.295000],
'Freedom': [0.196620, 0.147062, 0.112000, 0.010000],
'Trust in Government': [0.130150, 0.116794, 0.106000, 0.091000],
'Generosity': [0.258990, 0.285671, 0.224000, 0.202000],
'Dystopia Residual': [2.509300, 1.879416, 1.690000, 1.374000],
'Year': ['2016', '2017', '2018', '2019']
})
interpol_subset = current_country.append({
'Country': current_country["Country"].iloc[0],
'Region': current_country["Region"].iloc[0],
'Happiness Rank': 0, 'Score': np.nan,
'GDP per capita': np.nan, 'Family': np.nan,
'Life Expectancy': np.nan, 'Freedom': np.nan,
'Trust in Government': np.nan, 'Dystopia Residual': np.nan,
'Year': 2015}, ignore_index = True)
interpol_subset = interpol_subset.interpolate(method = "pchip", order = 2)
