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analysis_prediction_graph_loop.py
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analysis_prediction_graph_loop.py
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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime
import os
import configparser
parser = configparser.ConfigParser()
parser.read('config.ini')
current_dir = os.path.dirname(os.path.realpath(__file__))
base_dir = parser.get('directory','base_dir')
in_dir = parser.get('directory','company_datalist_prefilter')
in_dir1 = parser.get('directory','company_stock_marketprice_baseprice_prefilter')
out_dir = parser.get('directory','company_stock_marketprice_processed')
comp_datalist = pd.read_csv(current_dir+"/"+base_dir+"/"+in_dir+"/"+in_dir+"_combined.csv")
for i in range(0,comp_datalist['stock_code'].count()):
try:
print("[Status]Generating price prediction graph for "+comp_datalist['stock_symbol'][i])
hist = pd.read_csv(current_dir+"/"+base_dir+"/"+in_dir1+"/"+in_dir1+'_'+comp_datalist['stock_symbol'][i]+'.csv')
fcst = pd.read_csv(current_dir+"/"+base_dir+"/"+out_dir+'/'+comp_datalist['stock_symbol'][i]+"/"+out_dir+"_"+comp_datalist['stock_symbol'][i]+'.csv')
plt.plot(fcst['yhat'], label='Predicted Closed Price')
plt.plot(hist['close'],label='Actual Closed Price')
plt.xlabel('Date Index')
plt.ylabel('Close Price')
plt.title(comp_datalist['stock_symbol'][i]+" Price Prediction")
plt.legend()
plt.savefig(current_dir+"/"+base_dir+"/"+out_dir+'/'+comp_datalist['stock_symbol'][i]+"/"+out_dir+'_prediction_plot_'+comp_datalist['stock_symbol'][i]+'.png')
#plt.show()
plt.close()
except:
print("[Status]Error ! Unable to generate price prediction for "+comp_datalist['stock_symbol'][i])