Overview

This dataset provides daily stock prices for all companies listed on the National Stock Exchange (NSE) of India. The data spans several years and includes essential trading information that can be used for various financial analyses, stock market research, and machine learning applications.

Content

The dataset includes the following columns:

• Date: The date of the trading day in YYYY-MM-DD format.
• Open: The opening price of the stock on the given date.
• High: The highest price of the stock on the given date.
• Low: The lowest price of the stock on the given date.
• Close: The closing price of the stock on the given date.
• Adj Close: The adjusted closing price of the stock on the given date, which accounts for dividends, stock splits, and other corporate actions.
• Volume: The number of shares traded on the given date.
• Symbol: The unique ticker symbol of the stock.

Data Source

The data has been sourced using the Yahoo Finance API, providing a reliable and comprehensive view of stock performance over time.

Usage

This dataset is ideal for:

• Time series analysis and forecasting of stock prices.
• Developing and testing trading algorithms.
• Financial market research and trend analysis.
• Machine learning projects related to finance and economics.

File Format

The dataset is available in CSV format, making it easy to load into data analysis and machine learning libraries such as pandas, scikit-learn, and TensorFlow.

Prices for NSE Nifty 50 Index including live quotes, historical charts and news. NSE Nifty 50 Index was last updated by Trading Economics this December 2 of 2025.

Context : NIFTY 50 is the flagship stock market index of the National Stock Exchange (NSE) in India which is one of the leading stock exchanges in India. NIFTY 50 represents the performance of 50 large-cap companies across various sectors of the Indian economy.
Similarly NIFTY 100 represents the performance of the top 100 companies listed on the NSE based on market capitalization. NIFTY 100 is also part of several other indices, such as NIFTY 200, NIFTY 500, and NIFTY 100 Equal Weight Index.

In the National Stock Exchange (NSE) of India, there are three market segments based on the market capitalization of the listed companies. They are: - Large-cap: This segment includes the top 100 companies listed on the NSE based on market capitalization. - Mid-cap: This segment includes companies that rank between 101 and 250 based on market capitalization. - Small-cap: This segment includes companies that rank below the top 250 companies based on market capitalization. Market capitalization is calculated by multiplying a company's total outstanding shares by its current market price per share. The NSE's NIFTY Mid-cap 100 and NIFTY Small-cap 250 indices track the performance of companies in the mid-cap and small-cap segments of the market, respectively.

The NIFTY500 Multicap 50:25:25 index is a variant of the NIFTY 500 index, which represents the top 500 companies listed on India's National Stock Exchange (NSE). The Multicap 50:25:25 variant is a modified version of the NIFTY500 index that divides stocks into three categories based on market capitalization. The top 50 companies by market capitalization are classified as large-cap companies under this variant, while the next 150 companies are classified as mid-cap companies. The remaining 300 businesses are classified as small-cap.

Content : This Dataset contains records for all NIFTY-50 , NIFTY 200, NIFTY Midcap 100, NIFTY Smallcap 250, NIFTY500 Multicap 50:25:25 stocks, as on 1st March, 2023 - Open - open value of the index on that day - High - highest value of the index on that day - Low - lowest value of the index on that day - PREV. CLOSE - Previous Close Value - LTP - Last Traded Price - CHNG - Change in the price - %CHNG - Percentage change - Volume - volume of transaction - Value - Turn over in lakhs - 52W H - 52 Week High price - 52W L - 52 Week Lowest price - 365 D % CHNG - Past 365 Days Change Percentage - 30 D % CHNG - Past 30 Days Change Percentage

Note : - %CHNG: % change is calculated with respect to adjusted price on ex-date for Corporate Actions like: Dividend, Bonus, Rights & Face Value Split and also adjusted for Past 365 days & 30 days. - 52 W H/L: 52 week High & Low prices are adjusted for Bonus, Split & Rights Corporate actions.

Acknowledgements : The data is obtained from NSE website This is just daily level data provided here, you will get vast and detailed real-time & historical data from the official website.

Image Credit : https://gettyimages.com

This statistic represents the market capitalization of the National Stock Exchange (NSE) in India from fiscal year 2012 to fiscal year 2017. During the fiscal year 2016, the National Stock Exchange had a market capitalization just over ** trillion Indian rupees.

In financial year 2024, ****************** unique investors were registered on the National Stock Exchange of India. It was a significant increase from the previous year.

NSE Stock Historical Price Data (Market Cap > 500 Cr)

Dataset Description

This dataset contains the historical closing price data for all stocks listed on the National Stock Exchange (NSE) of India with a market capitalization exceeding 500 crore INR. The dataset is ideal for analysts, researchers, and enthusiasts who wish to perform detailed analysis, develop trading algorithms, or study market trends of substantial companies within the Indian stock market.

Features

1. Stock Ticker: Unique symbol representing each stock.
2. Date: The specific trading date.
3. Closing Price: The price at which the stock closed on a given day.

Source

The data is sourced from official NSE records and includes all companies meeting the market capitalization criteria as of the latest update.

Applications

• Trend Analysis: Understand how stock prices of major companies have fluctuated over time.
• Algorithmic Trading: Develop and backtest trading algorithms using real historical data.
• Market Research: Study the performance of large-cap stocks to gain insights into market dynamics.
• Educational Use: Serve as a practical dataset for educational purposes in finance, economics, and data science courses.

Usage

The dataset can be used for various purposes including but not limited to: - Financial modeling and forecasting - Risk management and portfolio optimization - Academic research and projects - Machine learning and AI-driven stock prediction models

In financial year 2025, a total of ********** companies were listed in the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) across India. This was an increase compared to the previous year.

Nigeria's main stock market index, the NSE All Share, fell to 143210 points on December 1, 2025, losing 0.22% from the previous session. Over the past month, the index has declined 6.85%, though it remains 46.53% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Nigeria. Nigeria Stock Market NSE - values, historical data, forecasts and news - updated on December of 2025.

The number of companies listed in the National Stock Exchange in India was 1959 in financial year 2020, an increase by **** companies compared to the previous year. Out of these nearly ************ companies there is only *** foreign company listed at the NSE.

UPDATED EVERY WEEK Last Update - 26th July 2025

Disclaimer!!! Data uploaded here are collected from the internet and some google drive. The sole purposes of uploading these data are to provide this Kaggle community with a good source of data for analysis and research. I don't own these datasets and am also not responsible for them legally by any means. I am not charging anything (either money or any favor) for this dataset. RESEARCH PURPOSE ONLY

Context

• The NIFTY 50 is a well-diversified 50 stock index and it represents 13 important sectors of the economy.
• It is used for a variety of purposes such as benchmarking fund portfolios, index-based derivatives, and index funds.
• NIFTY 50 is owned and managed by NSE Indices Limited.
• The NIFTY 50 index has shaped up to be the largest single financial product in India.

This data contains all the indices of NSE. NIFTY 50, NIFTY BANK, NIFTY 100, NIFTY COMMODITIES, NIFTY CONSUMPTION, NIFTY FIN SERVICE, NIFTY IT, NIFTY INFRA, NIFTY ENERGY, NIFTY FMCG, NIFTY AUTO, NIFTY 200, NIFTY ALPHA 50, NIFTY 500, NIFTY CPSE, NIFTY GS COMPSITE, NIFTY HEALTHCARE, NIFTY CONSR DURBL, NIFTY LARGEMID250, NIFTY INDIA MFG, NIFTY IND DIGITAL, INDIA VIX

File Information and Column Descriptions.

Nifty 50 index data with 1 minute data. The dataset contains OHLC (Open, High, Low, and Close) prices from Jan 2015 to Aug 2024. - This dataset can be used for time series analysis, regression problems, and time series forecasting both for one step and multi-step ahead in the future. - Options data can be integrated with this minute data, to get more insight about this data. - Different backtesting strategies can be built on this data.

File Information

• This dataset contains 6 files, each file contains nifty 50 data with different intervals.
• Different intervals are - 1 min, 3 min, 5 min, 15 min, and 1 hour, Daily data from intervals of 2015 Jan to 2024 August.

Column Descriptors

• Each file contains OHLC (Open, High, Low, and Close) prices and Data time information. Since these are Nifty 50 index data, so volume is not present.

Inspiration

Time series forecasting - Predict stock price

• Predict future stock price one step ahead and multi-step ahead in time.
• Use different time series forecasting techniques for forecasting the future stock price. ### Machine learning and Deep learning techniques
• Possible ML and DL models include Neural networks, RNNs, LSTMs, Transformers, Attention networks, etc.
• Different error functions can be considered like RMSE, MAE, RMSEP etc. ### Feature engineering
• Different augmented features can be created and that can be used for forecasting.
• Correlation analysis, Feature importance to justify the important features.

The dataset contains Year and Month wise turnover of National Stock Exchange (NSE) and Bombay Stock Exchange (BSE)

This statistic depicts the average annual performance of the Nifty 50 Index in India from years 2011 to 2024. In 2024, the average annual Nifty 50 Index was reported as ********, an increase from the previous year where the value was ********.

In 2024, the returns on Nifty 50 reported a rise of 8.75 percent compared to the year before. Furthermore, since 2016, Nifty 50 has consistently demonstrated a positive trend in annual returns. Nifty 50 is a benchmark Indian stock market index, representing the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange (NSE).

Context

In-order to validate various trading strategies and to come up with new trading strategies, historical data is a must. Once you have the data you can use it to analyze and visualize the market. This data can be use to learn about different types of trading strategies. You can use various libraries like TA-Lib, pandas_ta, etc.

Content

I have collected this data from TradingView and in this dataset I've only gather NSE listed companies data since they listed on NSE. In this dataset you will get Historical data of over 2500 companies and this data is based on daily candles. In this dataset there are over 2500 csv files and each csv file is named on company's NSE symbol (e.g. SBIN.csv, TATAMOTORS.csv, etc.).

For stocks, it has EOD OHLC,change and Last day change data

Columns in each csv file - datetime - symbol - open - low - high - close - volume - change(%) - last day change(%)

Acknowledgements This data is sourced from TradingView using tvDatafeed

The data is unprocessed and retained as obtained from the source.

As of February 2024, the real estate sector in India had the highest growth in the annual performance of the National Stock Exchange sector indices in terms of price return index. The energy sector followed, with a ** percent growth in annual performance during the same period.

Kenya Nairobi Securities Exchange: Index: NSE 20 Share data was reported at 3,052.730 NA in Nov 2025. This records a decrease from the previous number of 3,116.690 NA for Oct 2025. Kenya Nairobi Securities Exchange: Index: NSE 20 Share data is updated monthly, averaging 2,467.680 NA from Jun 2013 (Median) to Nov 2025, with 150 observations. The data reached an all-time high of 5,491.370 NA in Feb 2015 and a record low of 1,461.070 NA in Oct 2023. Kenya Nairobi Securities Exchange: Index: NSE 20 Share data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Kenya – Table KE.EDI.SE: Nairobi Securities Exchange: Monthly.

India's main stock market index, the SENSEX, fell to 85138 points on December 2, 2025, losing 0.59% from the previous session. Over the past month, the index has climbed 1.38% and is up 5.31% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

About this dataset

India's National Stock Exchange (NSE) has a total market capitalization of more than US$3.4 trillion, making it the world's 10th-largest stock exchange as of August 2021, with a trading volume of ₹8,998,811 crore (US$1.2 trillion) and more 2000 total listings.

NSE's flagship index, the NIFTY 50, is a 50 stock index is used extensively by investors in India and around the world as a barometer of the Indian capital market.

This dataset contains data of all company stocks listed in the NSE, allowing anyone to analyze and make educated choices about their investments, while also contributing to their countries economy.

How to use this dataset

• Create a time series regression model to predict NIFTY-50 value and/or stock prices.
• Explore the most the returns, components and volatility of the stocks.
• Identify high and low performance stocks among the list.

Highlighted Notebooks

• Your kernel can be featured here!
• Related Dataset: S&P 500 Stocks - daily updated
• More datasets

Acknowledgements

License

CC0: Public Domain

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Stonks by unknown memer.

In November 2020, the stock market turnover of both National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) in India reached ***** trillion Indian rupees. Over the previous year, the turnover raised significantly from **** trillion Indian rupees in November 2019. Additionally, the stock exchange turnover in India did not face major loss during lockdown and the COVID-19 pandemic, but remained stable.

Kenya's main stock market index, the Nairobi 20, fell to 3024 points on December 2, 2025, losing 0.47% from the previous session. Over the past month, the index has declined 4.11%, though it remains 64.78% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Kenya. Kenya Stock Market (NSE20) - values, historical data, forecasts and news - updated on December of 2025.