IST 718 LAB 6

# !pip install fbprophet

%matplotlib inline
import pandas as pd
from fbprophet import Prophet

import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')

df = pd.read_csv('https://raw.githubusercontent.com/danielcaraway/data/master/Zip_Zhvi_SingleFamilyResidence.csv', encoding='latin')

PART ONE: Arkansas Metro Areas

hs = df[df['Metro'].str.contains('Hot Springs', na=False)]
lr = df[df['Metro'].str.contains('Little Rock', na=False)]
f = df[df['Metro'].str.contains('Fayetteville', na=False)]
s = df[df['Metro'].str.contains('Searcy', na=False)]

def graph_prices_for(df, location_name):
  df_t = df.loc[:, '1996-04'::].T
  df_t['avg'] = df_t.mean(numeric_only=True, axis=1)
  df_t.reset_index(inplace=True)
  columns = ['index', 'avg']
  df = pd.DataFrame(df_t, columns = columns)
  df = df.rename(index=str, columns={"avg": "y", "index": "ds"})
  ax = df.set_index('ds').plot(figsize=(12, 8))
  ax.set_ylabel('Home Prices in ' + location_name)
  ax.set_xlabel('Date')
  plt.show()

graph_prices_for(hs, "Hot Springs")

graph_prices_for(lr, "Little Rock")

graph_prices_for(f, "Fayetteville")

graph_prices_for(s, "Searcy")