Exctraction of MCX Historical Prices into CSV & Represent them in Chart through Python.
In this above video we have exactly shown how you can extract the MCX Historical prices from Quandl into CSV Files and Then Represent them in a Chart
For Code Input Please Follow Below after the Proper Follow of Instructions Given above in the Video
#import Library Files
import quandl
import pandas as pd
import matplotlib
import pandas_datareader.data as web
import matplotlib.pyplot as plt
from matplotlib import style
#code function to show chart in gridview
style.use('ggplot')
#exctraction of Gold prices and to save them in csv
#for crude historical prices just replace the code with CHRIS/MCX_CL3 and after change csv files names as according
data=quandl.get('CHRIS/MCX_GC1',start='2013-01-01',end='2017-04-24')
data.to_csv('gold1.csv')
To read CSV files after extraction and to represent them in chart please follow this code but before that please comment out above 2 lines of extraction data and then follow below code input.
#to read saved csv file and then to write and represent them in chart
data=pd.read_csv('gold1.csv',parse_dates=True,index_col=0)
print(data[['Open','High','Low','Close']].head(10))
data['High'].plot()
plt.show()
