# -*- coding: utf-8 -*-
import pandas as pd
import datetime
import pandas_datareader.data as web
import matplotlib.pyplot as plt
from matplotlib import style
from pandas_datareader.quandl import QuandlReader
style.use('fivethirtyeight')
START = datetime.datetime(2010, 1, 1)
END = datetime.datetime.now()
ticker = 'XOM'
#df=web.DataReader("XOM","morningstar",start,end)
data = QuandlReader("WIKI/{}".format(ticker), start=START, end=END)
df = data.read()
print(df)
print(df.head())
df['High'].plot()
plt.legend()
plt.show()
print(web.get_data_fred('GS10'))
left_on=['Open_Date'],
right_on=['Date_'])
# %%
# pull data from Quandl
if reload_data:
with open('data/vars.json', 'r') as json_file:
var_dict = json.load(json_file)
quandl_key = var_dict['QUANDL_API']
QR = QuandlReader("AAII/AAII_SENTIMENT", api_key=quandl_key)
QR_df = QR.read().reset_index()
QR_df.columns = ['AAII_Sent_' + str(col) for col in QR_df.columns]
QR_df.to_csv('output/c_mktdata_aaii.csv')
else:
QR_df = pd.read_csv('output/c_mktdata_aaii.csv')
# %%
# merge Quandl
QR_df_sorted = QR_df.sort_values(['AAII_Sent_Date'])
QR_df_sorted['AAII_Sent_Date'] = pd.to_datetime(QR_df['AAII_Sent_Date'],
errors='coerce')
df_result = pd.merge_asof(
df_result,
QR_df_sorted,
