Stocker is a Python class-based tool used for stock prediction and analysis. (for complete code refer GitHub) Stocker is designed to be very easy to handle.
A teenage crush, an adulthood hobby. The times were of 2013 and a cliche aspiring Engineering boy landed on to the marvelous act of DiCaprio in “The Wolf of Wall Street”. The stock market Ups and Downs have always fascinated me towards it and now in the year of lockdown 2020(hoping people will bounce back here in the future too)when we saw a sudden surge(~5 Mn) in the number of new users in the Indian market space, I thought why not to play around with the easily available market data in one of the few domains I feel comfortable(Python).
Before we start let me bring in to your notice that unlike for international market where python dedicated libraries like YahooFinancials supports easy download of data through API calls, they do not work that swiftly for Indian market space but nonetheless, we do can utilise an indigenous python library “nse” for market data handling. While keeping in mind the recent “Vocal for Local” agenda, I have done my analysis with previous 5 months market data of the automobile sector giant “TATAMOTORS”.
Data Load via NSE Library:
Here, is the snippet of my code used for downloading the data and converting into a data frame format from JSON.
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