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Get the Live NIFTY Bank Index Option Chain Data in Excel Sheet for CE & PE. Bank Nifty Trend can analyzed from this Excel based on Change in Open Interest, Price and Volume. Fetch the various data such as Last Traded Price (LTP), Open Interest (OI), Change in Open Interest (%), Change in Price (%), Total Volume Traded, Buy Volume, Sell Volume, Implied Volatility (IV), etc., for both Calls and Puts. A simplified Excel sheet for traders of Bank Nifty Index, coded in VBA, to fetch the real-time NSE BANK NIFTY option chain price data with different expiry dates and at a few strike prices from the underlying price. Analyze in-depth for the changes in Open Interest (OI), Changes in Price as well as the Buy, Sell Volumes, Total Volumes Traded etc., at a few different strike prices with At the Money (ATM).  Screenshot Designed by, Dr. M Kanagasabapathy Important Disclaimer: This Excel Sheet is designed for educational purposes only.  Either this web page or the Administrator of this web p

Coded a lightweight program (600 KB), 'Battery Life Saver' to extend the life span of laptop batteries. Using a Laptop Battery continuously by overcharging above 90% or by below 15%, reduces its life span.   This light-weight .exe program, Battery Life Saver will alarm, on excess charging or discharging.   Set the desired Battery Limit Percentage using the slider, say 50% and allow the Battery Life Saver to give alarm. It automatically detects, charging and battery status. Screenshots DOWNLOAD Download the Python codes for this program, from this page.   Python code for Laptop Battery Life Saver     Author Dr. M Kanagasabapathy Asst. Professor, Department of Chemistry Rajus’ College, Madurai Kamaraj University Rajapalayam (Tamil Nadu) India 626117

Designed a Google sheet-based analysis to check, whether the growth of a stock is consistent or not in the past one year. It calculates and averages the return of every previous, 7 days' close price for the past 1 year, from yesterday’s date and closing price. So it's possible to check whether the growth is consistent for the past 52 weeks instead of conventional one-year return calculation, which is based on initial and final dates of a year. In simple, it estimates an average of weekly returns (for the consequent previous 52 weeks from yesterday) and compares it with conventional yearly return (%). Screenshot Link to Google sheet

F et ch hist orical price data and back test between any two dates of NSE Stocks using this simple Python code and import them in .CSV file and predict the winning percentage. Step 1. Install NSEPY Open Command Prompt (in Windows 10) as Administrator. Then paste the following commands (shown in red ) one after another. C:\Python\python.exe -m pip install --upgrade pip Wait to upgrade... pip install nsepy Wait to upgrade... pip install nsepy –upgrade Wait to upgrade... Screenshot for installation in Windows 10 OS. Step 2. Fetching the price data Now open Python IDLE and paste the following code. Save it with a suitable filename, with an extension '.py'. Stock symbols and Date Enter the equity code as in NSE, India. Example: “TCS”) Enter starting and closing date digits, in the format, “yyyy,mm,dd” Example: “7-Aug-2021” is entered as: “2021,8,7") Change Symbol and starting as well as closing date in the required format. The data will be saved as .CSV file. Code Copy and past

Area under a curve can be estimated by integration method. (Check the references for more details.) Full width at half maximum (FWHM) for a curve is used in many scientific data analyses.  For instance, in X–ray diffraction (XRD) analysis of crystal data, it is used to find grain size.   It can be easily calculated using, quadratic equation. (Check the references for more details.) This tutorial shows how to use the computer program Origin to estimate both ' Area under a Curve ' as well as ' FWHM '. Check these eNotes for  references 1.  Full Width at Half Maximum (FWHM) & Quadratic equation 2. Introduction to Quadratic equation 3.  Area under curve by integration method

Input : Sine JavaScript & HTML code for SINE function Input : Sine JavaScript - Trigonometric Functions Calculator Input:        (Values in degree) sin : cos : tan : csc : sec : cot : asin : acos : atan : sinh : cosh : tanh : csch : sech : coth : asinh: acosh: atanh:

Linux Mint is one of the best operating system with a good GUI, open-sourced and can be installed on old PCs also. And VESTA is a computer package to analyze crystal structures & geometry, X-ray diffraction simulation (XRD), and to investigate Miller indices {h k l} data for crystal systems,  space groups of crystalline materials etc.  It is a 3D visualization program for structural models, volumetric data such as electron/nuclear densities, and crystal morphologies. it also deals with multiple structural models, volumetric data, and crystal morphologies in the same window. But its Debian version for Linux Mint operating system is not available for direct download.  You can download the VESTA.deb for Linux Mint from here.

Based on open interest & price change data of a stock, the price trend of the stock is correlated as: Price Open Interest Price trend Increase Increase Increase (More buyers & long build-up) Increase Decrease Increase (Short positions covering)  Decrease Increase Decrease (More short positions build-up)  Decrease Decrease Decrease ( Long unwinding Buyers become sellers)            

    How to remove meta data (ID tags) from .mp3 file with Python?   Meta data refers ID3 tags or extra information encoded into mp3 files such as title, artist s name, composer s details, release year, credits, rating and other information related to the album.   These meta data can be removed without altering the quality of the mp3 file, with this Python code.   Install mutagen via command prompt and run the code.   Directory of this program should be in the folder containing .mp3 files.   Most importantly, back-up your files before running this code.   Designed by, Dr. M Kanagasabapathy www.enote.page     Python code: import os import sys import codecs from mutagen.mp3 import MP3 TEXT_ENCODING = 'utf8'   if (len(sys.argv) > 1): fpath = sys.argv[1] else: fpath = os.path.abspath(os.path.dirname(sys.argv[0]))   for fn in os.listdir(fpath):   fname = os.path.join(fpath, fn) if

At 298 K the exchange current density (i o ) of an electrode having a surface area of 5 cm 2 , used in an electrodeposition process is 0.79 mA cm –2 . Estimate the applied current through the electrode if the overpotential (η) is 5 mV.   Required formula derived from the Butler–Volmer equation is: i = (i o η F) / (R T) where, ‘i’ is the applied current density (mA cm –2 ) i o is exchange current density = 0.79 mA cm –2 η is overpotential = 5 mV F is Faraday = 96485 C mol –1 R is gas constant = 8.314 J K –1 mol –1 T is temperature (in K) = 298 K Current density = Current (mA) / Surface area (cm 2 ) Surface area = 5 cm 2   Substituting these values in the equation, value of the applied current density is: i = (0.79 mA cm –2 × 5 mV × 96485 C mol –1 ) / (8.314 J K –1 mol –1 × 298 K).   Since, Joule = Volt × Coulomb or J = V × C. So, i = (0.79 mA cm –2 × 5 mV × 96485 C mol –1 ) / (8.314 V C K –1 mol –1 × 298 K)   And, 1 V = 1000 mV

Symbols used in this notes are: F – Farad; C – Coulomb; V – Volt; A – Ampere; J –Joules; s – second; W – Watt; g – gram; h – hour   Correlation between electrical (capacitance) and energy and power units F = C/V W = A×V C = A×s J = W×s (Energy unit) F =(A×s)/ V So, F×(V^2) = A×s×V = W×s = J Or, F = (W×s) / V^2 = J / V^2 Note : Faraday's Constant is different from Farad. (Not confused, though both represented by symbol 'F'.) 1 Faraday = 96485 C 1 Faraday = (96485 C /3600 s) = 26.801 A·h   Capacitance is expressed in, F Energy is expressed in, Wh Power is expressed in, W   Specific Capacitance is expressed as: F/kg (or) F/g Specific Energy is expressed as: Wh/kg (or) Wh/g Specific Power is expressed as: W/kg (or) W/g   Assume a supercapacitor has a Specific Capacitance of 2000 F/g and discharges at a potential difference of 1 V in 900 s, then Specific Energy and Specific Power is related to its Specific Capacitance a

INVESTOCK – Simple Python computer programing code to fetch & backtest NSE historical (15+ years) stock price data Google Sheet to check the consistent growth of an Indian stock for 52 weeks Correlation between rate of return from the fixed deposit and its CAGR NSE live option chain data in Excel sheet Interpretation of open interest (OI) & price change of a stock

This video tutorial illustrates the Arduino based simulation of capacitance meter / capacitance measurement of capacitors & supercapacitors with Tinkercad simulation.   Principle for this measurement is explained in the following page: https://www.enote.page/2022/01/capacitor-charging-discharging-time.html   Estimation of capacitance of capacitors & supercapacitors by simulating charging & discharging is explained in the following page: https://www.enote.page/2021/06/capacitor-simulation.html   Components required Name Number Component C1 1 100 nF to 10 mF Capacitor R1 1 10 kΩ Resistor U1 1 Arduino Uno R3 board Meter2 1 Voltage meter R2 1 220 Ω Resistor     Increase the resistance value from 10K, if the charging time is too short. Decrease the