Utility Tools for Population Estimates
Project description
estpop is a Python package providing population forecasting from historical data. This method is based on cohort change ratio[1].
Sample Code
Change Ratio
import numpy as np import openpyxl import estpop sheet = openpyxl.load_workbook('data.xlsx').worksheets[0] pops = {} for i in range(1, sheet.max_row): code = sheet.cell(i+1, 3).value if not code in pops: pops[code] = [] males, females = [], [] for j in range(29, 50): males.append(sheet.cell(i+1, j).value) females.append(sheet.cell(i+1, j+22).value) pops[code].append([males, females]) ratios = {} for k, v in pops.items(): change_ratios, baby_ratios, tail_ratios = [], [], [] try: for i in range(len(v) - 5): change_ratio, baby_ratio, tail_ratio = estpop.ratios(v[i], v[i+5]) change_ratios.append(change_ratio) baby_ratios.append(baby_ratio) tail_ratios.append(tail_ratio) ratios[k] = { 'change_ratio': np.mean(change_ratios, axis=0).tolist(), 'baby_ratio': float(np.mean(baby_ratios)), 'tail_ratio': float(np.mean(tail_ratios)) } except: pass
Simulation
import openpyxl import estpop f = open('result.csv', mode='w') f.write('code,year\n') for k, v in pops.items(): if k in [411, 421, 521]: change_ratio = ratios[0]['change_ratio'] baby_ratio = ratios[0]['baby_ratio'] tail_ratio = ratios[0]['tail_ratio'] else: change_ratio = ratios[k]['change_ratio'] baby_ratio = ratios[k]['baby_ratio'] tail_ratio = ratios[k]['tail_ratio'] try: year = 2020 estimates = v[5] for i in range(7): estimates = estpop.simulate(estimates, change_ratio, baby_ratio, tail_ratio) f.write('%s,%s,%s,%s\n' % (k, year+i*5, ','.join(map(str, estimates[0])), ','.join(map(str, estimates[1])))) except: print(k) f.close()
References
- Einoshin SUZUKI, Kaoru MORI, Koichi NAGASE, Masatoshi TAMAMURA, Ikuyo KANEKO: The Development of the Future Predictive Model of 'Potentially Disappearing Neighborhood Associations' Using Demographic Data of the Neighborhood Association Base, Journal of the Japan Association of Regional Development and Vitalization, Vol.6, pp.20-30, 2015.
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