Vaccivery/prophet.py at main · deluminators/Vaccivery · GitHub

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# -*- coding: utf-8 -*-
"""Prophet.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1mk7ub7byvB_okkXhR0Mlqh4UNiVu4H9f
"""

import pandas as pd
dataset=pd.read_csv("/content/nation_level_daily.csv")

dataset

dataset.info()

dataset.isnull().sum(axis = 0)

data=[]
for i in range(0,190):
  string=str(dataset["Date"][i].split(" ")[0]) + "-"
  if(dataset["Date"][i].split(" ")[1]=="January"):
    string+=str(1)
  if(dataset["Date"][i].split(" ")[1]=="February"):
    string+=str(2)
  if(dataset["Date"][i].split(" ")[1]=="March"):
    string+=str(3)
  if(dataset["Date"][i].split(" ")[1]=="April"):
    string+=str(4)
  if(dataset["Date"][i].split(" ")[1]=="May"):
    string+=str(5)
  if(dataset["Date"][i].split(" ")[1]=="June"):
    string+=str(6)
  if(dataset["Date"][i].split(" ")[1]=="July"):
    string+=str(7)
  if(dataset["Date"][i].split(" ")[1]=="August"):
    string+=str(8)
  string+="-" + str(2020)
  data.append(string)

dataset['Date']=data

dataset

dataset['Date'] = pd.to_datetime(dataset['Date'])

dataset

dataset.rename(columns = {'Daily Confirmed':'y'}, inplace = True)

dataset

from fbprophet import Prophet

model = Prophet()

dataset.rename(columns = {'Date':'ds'}, inplace = True)

dataset

model.fit(dataset)

fut = model.make_future_dataframe(periods = 13, freq = 'M')

fut

forecast = model.predict(fut)

forecast.tail()

forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()

fig2 = model.plot_components(forecast)