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Library to collect NSE data in pandas dataframe

Project description

NSE (national stock exchange) data

Introduction: This library serves as an api to fetch data from the NSE about stocks and indices and derivatives using python

Thank you for using Nsedt. Please feel free to send pull requests, comments, and suggestions, as well as get in touch with me if you require any additional help. I sincerely hope you will find this library useful.

For detailed doc please refer nse-doc

How to start

  1. clone the repository git clone https://github.com/pratik141/nsedt
  2. Install the requirements file after changing to cloned folder above pip install -r requirements.txt
  3. Install locally pip installl . --upgrade

Equity

Details

Name Module name Description Argument Response
companyinfo get_companyinfo Company info symbol , response_type json, panda df
marketstatus get_marketstatus marketstatus -- panda_df
price get_price price start_date, end_date, symbol, input_type json, panda df
corpinfo get_corpinfo corpinfo arg
event get_event event start_date, end_date panda df
chartdata get_chartdata chartdata symbol panda df
symbols_list get_symbols_list symbols_list -- json
asm_list get_asm_list symbols_list asm_type json

Now get_price work with start_date, end_date without datetime format it support %d-%m-%Y

step to run

from nsedt import equity as eq
from datetime import date

start_date = date(2023, 1, 1)
end_date = date(2023, 1, 10)
print(eq.get_price(start_date, end_date, symbol="TCS"))
start_date = "01-05-2023"
end_date = "03-05-2023"
print(eq.get_corpinfo(start_date, end_date, symbol="TCS"))
print(eq.get_event(start_date, end_date))
print(eq.get_event())
print(eq.get_marketstatus())
print(eq.get_marketstatus(response_type="json"))
print(eq.get_companyinfo(symbol="TCS"))
print(eq.get_companyinfo(symbol="TCS", response_type="json"))
print(eq.get_chartdata(symbol="TCS"))
print(eq.get_symbols_list()) #print the list of symbols used by NSE for equities
print(eq.get_asm_list(asm_type = "shortterm"))

Indices

Details

Name Module name Description Argument Response
price get_price price start_date, end_date, symbol panda df

step to run

from nsedt import indices as ind
from datetime import date

start_date = date(2023, 1, 1)
end_date = date(2023, 1, 10)
print(ind.get_price(start_date=start_date, end_date=end_date, symbol="NIFTY 50"))
data = ind.get_price(start_date=start_date, end_date=end_date, symbol="NIFTY")
# To change date format from '%d-%b-%Y' to '%Y-%m-%d'
data["Date"] = pd.to_datetime(data["Date"],format='%d-%b-%Y')

Derivatives

Details

Name Module name Description Argument Response
vix get_vix price start_date, end_date,columns_drop_list panda df
option chain get_option_chain get option price symbol,strikePrice,expiryDate panda df
option chain expiry date get_option_chain_expdate option chain expiry date symbol json
future price get_future_price get future price symbol, start_date, end_date, expiryDate,response_type, columns_drop_list panda df
future expiry date get_future_expdate future expiry date symbol json

step to run

from nsedt import derivatives as de
start_date = "01-09-2023"
end_date = "03-09-2023"
# date format "%d-%m-%Y"
print(de.get_vix(start_date, end_date))
print(de.get_option_chain_expdate(symbol="TCS"))
print(de.get_option_chain(symbol="TCS", strike_price=3300, expiry_date="expiryDate"))
print(de.get_future_price(symbol="TCS", start_date=start_date, end_date=end_date))
print(de.get_future_expdate(symbol="TCS"))

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