# -*- 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,