15 datasets found
  1. National Stock Exchange : Time Series

    • kaggle.com
    Updated Dec 4, 2019
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    Atul Anand {Jha} (2019). National Stock Exchange : Time Series [Dataset]. https://www.kaggle.com/atulanandjha/national-stock-exchange-time-series/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 4, 2019
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Atul Anand {Jha}
    License

    http://www.gnu.org/licenses/lgpl-3.0.htmlhttp://www.gnu.org/licenses/lgpl-3.0.html

    Description

    Context

    The National Stock Exchange of India Ltd. (NSE) is an Indian stock exchange located at Mumbai, Maharashtra, India. National Stock Exchange (NSE) was established in 1992 as a demutualized electronic exchange. It was promoted by leading financial institutions on request of the Government of India. It is India’s largest exchange by turnover. In 1994, it launched electronic screen-based trading. Thereafter, it went on to launch index futures and internet trading in 2000, which were the first of its kind in the country.

    With the help of NSE, you can trade in the following segments:

    • Equities

    • Indices

    • Mutual Funds

    • Exchange Traded Funds

    • Initial Public Offerings

    • Security Lending and Borrowing Scheme

    https://cdn6.newsnation.in/images/2019/06/24/Sharemarket-164616041_6.jpg" alt="Stock image">

    Companies on successful IPOs gets their Stocks traded over different Stock Exchnage platforms. NSE is one important platofrm in India. There are thousands of companies trading their stocks in NSE. But, I have chosen two popular and high rated IT service companies of India; TCS and INFOSYS. and the third one is the benchmark for Indian IT companies , i.e. NIFTY_IT_INDEX .

    Content

    The dataset contains three csv files. Each resembling to INFOSYS, NIFTY_IT_INDEX, and TCS, respectively. One can easily identify that by the name of CSV files.

    Timeline of Data recording : 1-1-2015 to 31-12-2015.

    Source of Data : Official NSE website.

    Method : We have used the NSEpy api to fetch the data from NSE site. I have also mentioned my approach in this Kernel - "**WebScraper to download data for NSE**". Please go though that to better understand the nature of this dataset.

    Shape of Dataset:

    INFOSYS - 248 x 15 || NIFTY_IT_INDEX - 248 x 7 || **TCS - 248 x 15

    • Colum Descriptors:

    • Date: date on which data is recorded

    • Symbol: NSE symbol of the stock

    • Series: Series of that stock | EQ - Equity

    OTHER SERIES' ARE:

    EQ: It stands for Equity. In this series intraday trading is possible in addition to delivery.

    BE: It stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

    BL: This series is for facilitating block deals. Block deal is a trade, with a minimum quantity of 5 lakh shares or minimum value of Rs. 5 crore, executed through a single transaction, on the special “Block Deal window”. The window is opened for only 35 minutes in the morning from 9:15 to 9:50AM.

    BT: This series provides an exit route to small investors having shares in the physical form with a cap of maximum 500 shares.

    GC: This series allows Government Securities and Treasury Bills to be traded under this category.

    IL: This series allows only FIIs to trade among themselves. Permissible only in those securities where maximum permissible limit for FIIs is not breached.

    • Prev Close: Last day close point

    • Open: current day open point

    • High: current day highest point

    • Low: current day lowest point

    • Last: the final quoted trading price for a particular stock, or stock-market index, during the most recent day of trading.

    • Close: Closing point for the current day

    • VWAP: volume-weighted average price is the ratio of the value traded to total volume traded over a particular time horizon

    • Volume: the amount of a security that was traded during a given period of time. For every buyer, there is a seller, and each transaction contributes to the count of total volume.

    • Turnover: Total Turnover of the stock till that day

    • Trades: Number of buy or Sell of the stock.

    • Deliverable: Volumethe quantity of shares which actually move from one set of people (who had those shares in their demat account before today and are selling today) to another set of people (who have purchased those shares and will get those shares by T+2 days in their demat account).

    • %Deliverble: percentage deliverables of that stock

    Acknowledgements

    I woul dlike to acknowledge all my sincere thanks to the brains behind NSEpy api, and in particular SWAPNIL JARIWALA , who is also maintaining an amazing open source github repo for this api.

    Inspiration

    I have also built a starter kernel for this dataset. You can find that right here .

    I am so excited to see your magical approaches for the same dataset.

    THANKS!

  2. India Stock Market (daily updated)

    • kaggle.com
    Updated Jan 31, 2022
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    Larxel (2022). India Stock Market (daily updated) [Dataset]. https://www.kaggle.com/datasets/andrewmvd/india-stock-market/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 31, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Larxel
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    India
    Description

    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

    Acknowledgements

    License

    CC0: Public Domain

    Splash banner

    Stonks by unknown memer.

  3. Stock Market Data - Nifty 100 Stocks (1 min) data

    • kaggle.com
    Updated Aug 6, 2025
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    Deba (2025). Stock Market Data - Nifty 100 Stocks (1 min) data [Dataset]. https://www.kaggle.com/datasets/debashis74017/stock-market-data-nifty-50-stocks-1-min-data
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 6, 2025
    Dataset provided by
    Kaggle
    Authors
    Deba
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Disclaimer!!! Data uploaded here are collected from the internet. 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 monetary or any favor) for this dataset.

    For the first time, Nifty 50 stocks data and two indices data, along with 55 technical indicators used by Market experts are calculated and made available. Kindly download the data and make sure to share your code in public and if you like this data, do upvote. Thank you.

    About Nifty 50

    The NIFTY 50 index is a well-diversified 50 companies index reflecting overall market conditions. NIFTY 50 Index is computed using the free float market capitalization method.

    NIFTY 50 can be used for a variety of purposes such as benchmarking fund portfolios, launching of index funds, ETFs and structured products.

    Overview

    This dataset contains historical daily prices for Nifty 100 stocks and indices currently trading on the Indian Stock Market. - Data samples are of 5-minute intervals and the availability of data is from Jan 2015 to Feb 2022. - Along with OHLCV (Open, High, Low, Close, and Volume) data, we have created 55 technical indicators. - More details about these technical indicators are provided in the Data description file.

    Content

    The whole dataset is around 33 GB (compressed here to 13 GB), and 100 stocks (Nifty 100 stocks) and 2 indices (Nifty 50 and Nifty Bank indices) are present in this dataset. Details about each file are - - OHLCV (Open, High, Low, Close, and Volume) data - 55 Technical indicator values are also present

    Inspiration

    • Data is uploaded for Research and Educational purposes.

    Possible problem statements

    • Univariate and Multi-variate time series forecasting of stock prices and index prices
    • Multi-variate data can be used to predict the trend of the stock price (Buy or Sell or Hold)
    • Different intraday or positional trading strategies can be built out of this multivariate data. [technical indicators are already added here]
    • EDA on time series data

    Stock Names

    | ACC | ADANIENT | ADANIGREEN | ADANIPORTS | AMBUJACEM | | -- | -- | -- | -- | -- | | APOLLOHOSP | ASIANPAINT | AUROPHARMA | AXISBANK | BAJAJ-AUTO | | BAJAJFINSV | BAJAJHLDNG | BAJFINANCE | BANDHANBNK | BANKBARODA | | BERGEPAINT | BHARTIARTL | BIOCON | BOSCHLTD | BPCL | | BRITANNIA | CADILAHC | CHOLAFIN | CIPLA | COALINDIA | | COLPAL | DABUR | DIVISLAB | DLF | DMART | | DRREDDY | EICHERMOT | GAIL | GLAND | GODREJCP | | GRASIM | HAVELLS | HCLTECH | HDFC | HDFCAMC | | HDFCBANK | HDFCLIFE | HEROMOTOCO | HINDALCO | HINDPETRO | | HINDUNILVR | ICICIBANK | ICICIGI | ICICIPRULI | IGL | | INDIGO | INDUSINDBK | INDUSTOWER | INFY | IOC | | ITC | JINDALSTEL | JSWSTEEL | JUBLFOOD | KOTAKBANK | | LICI | LT | LTI | LUPIN | M&M | | MARICO | MARUTI | MCDOWELL-N | MUTHOOTFIN | NAUKRI | | NESTLEIND | NIFTY 50 | NIFTY BANK | NMDC | NTPC | | ONGC | PEL | PGHH | PIDILITIND | PIIND | | PNB | POWERGRID | RELIANCE | SAIL | SBICARD | | SBILIFE | SBIN | SHREECEM | SIEMENS | SUNPHARMA | | TATACONSUM | TATAMOTORS | TATASTEEL | TCS | TECHM | | TITAN | TORNTPHARM | ULTRACEMCO | UPL | VEDL | | WIPRO | YESBANK | | | |

  4. All Stocks Data of Indian Stock Market(1 Year)

    • kaggle.com
    Updated Jan 9, 2022
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    KESHAV_MAHESHWARI (2022). All Stocks Data of Indian Stock Market(1 Year) [Dataset]. https://www.kaggle.com/datasets/gmkeshav/all-stocks-data-of-indian-stock-market1-year
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 9, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    KESHAV_MAHESHWARI
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    India
    Description

    After some rigorous SQL queries and coding on python. I made this dataset. In this dataset, all stocks of the Indian Stock Market are present a total of 2435 stocks. The data is of 1-year rows represent stock name and column represent date and I have filled the table with closing price. Enjoy and do some stock price predictions.

  5. Market Data INDICIES(1).xlsx

    • figshare.com
    xlsx
    Updated Jul 5, 2018
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    Rotimi Obasa; Nigerian Stock Exchange (2018). Market Data INDICIES(1).xlsx [Dataset]. http://doi.org/10.6084/m9.figshare.6752591.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jul 5, 2018
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Rotimi Obasa; Nigerian Stock Exchange
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    A List of top 30 Listed companies on Nigeria Stock Exchange as at April 2018 with their Capitalization Value and Ranking. We also Include a computation of proportion of the NSE controlled by the NSE 30 Index by dividing the total Market Capitalization for the NSE 30 Index by total market Capitalization for the whole NSE. In addition we compute the the ratio of Non-Financial services companies and Financial services companies as a percentage the whole value of NSE Market Capitalization

  6. T

    Nigeria Stock Market NSE Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Nigeria Stock Market NSE Data [Dataset]. https://tradingeconomics.com/nigeria/stock-market
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 18, 1996 - Aug 15, 2025
    Area covered
    Nigeria
    Description

    Nigeria's main stock market index, the NSE-All Share, fell to 144628 points on August 15, 2025, losing 0.51% from the previous session. Over the past month, the index has climbed 12.14% and is up 48.95% compared to the same time last year, 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 August of 2025.

  7. End-of-Day Pricing Market Data Kenya Techsalerator

    • kaggle.com
    Updated Aug 23, 2023
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    Techsalerator (2023). End-of-Day Pricing Market Data Kenya Techsalerator [Dataset]. https://www.kaggle.com/datasets/techsalerator/end-of-day-pricing-market-data-kenya-techsalerator
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    Description

    Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 66 companies listed on the Nairobi Securities Exchange (XNAI) in Kenya. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

    Top 5 used data fields in the End-of-Day Pricing Dataset for Kenya:

    1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

    2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

    3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

    4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

    5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

    Top 5 financial instruments with End-of-Day Pricing Data in Kenya:

    Nairobi Securities Exchange All Share Index (NASI): The main index that tracks the performance of all companies listed on the Nairobi Securities Exchange (NSE). NASI provides insights into the overall market performance in Kenya.

    Nairobi Securities Exchange 20 Share Index (NSE 20): An index that tracks the performance of the top 20 companies by market capitalization listed on the NSE. NSE 20 is an important benchmark for the Kenyan stock market.

    Safaricom PLC: A leading telecommunications company in Kenya, offering mobile and internet services. Safaricom is one of the largest and most actively traded companies on the NSE.

    Equity Group Holdings PLC: A prominent financial institution in Kenya, providing banking and financial services. Equity Group is a significant player in the Kenyan financial sector and is listed on the NSE.

    KCB Group PLC: Another major financial institution in Kenya, offering banking and financial services. KCB Group is also listed on the NSE and is among the key players in the country's banking industry.

    If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Kenya, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

    Data fields included:

    Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

    Q&A:

    1. How much does the End-of-Day Pricing Data cost in Kenya ?

    The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

    1. How complete is the End-of-Day Pricing Data coverage in Kenya?

    Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Kenya exchanges.

    1. How does Techsalerator collect this data?

    Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

    1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

    Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

    1. How do I pay for this dataset?

    Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH, and wire transfers, facilitating a convenient and se...

  8. T

    BSE SENSEX Stock Market Index Data

    • tradingeconomics.com
    • id.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Aug 18, 2025
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    TRADING ECONOMICS (2025). BSE SENSEX Stock Market Index Data [Dataset]. https://tradingeconomics.com/india/stock-market
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Aug 18, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Apr 3, 1979 - Aug 18, 2025
    Area covered
    India
    Description

    India's main stock market index, the SENSEX, rose to 81435 points on August 18, 2025, gaining 1.04% from the previous session. Over the past month, the index has declined 0.93%, though it remains 1.26% higher than a year ago, 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 August of 2025.

  9. End-of-Day Pricing Data Nigeria Techsalerator

    • kaggle.com
    Updated Aug 23, 2023
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    Techsalerator (2023). End-of-Day Pricing Data Nigeria Techsalerator [Dataset]. https://www.kaggle.com/datasets/techsalerator/end-of-day-pricing-data-nigeria-techsalerator
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Techsalerator
    Area covered
    Nigeria
    Description

    Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 177 companies listed on the Nigerian Stock Exchange (XNSA) in Nigeria. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

    Top 5 used data fields in the End-of-Day Pricing Dataset for Nigeria:

    1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

    2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

    3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

    4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

    5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

    Top 5 financial instruments with End-of-Day Pricing Data in Nigeria:

    Nigerian Stock Exchange (NSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Nigerian Stock Exchange. This index provides an overview of the overall market performance in Nigeria.

    Nigerian Stock Exchange (NSE) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Nigerian Stock Exchange. This index reflects the performance of international companies operating in Nigeria.

    Company A: A prominent Nigerian company with diversified operations across various sectors, such as telecommunications, energy, or banking. This company's stock is widely traded on the Nigerian Stock Exchange.

    Company B: A leading financial institution in Nigeria, offering banking, insurance, or investment services. This company's stock is actively traded on the Nigerian Stock Exchange.

    Company C: A major player in the Nigerian agricultural sector, involved in the production and distribution of agricultural products. This company's stock is listed and actively traded on the Nigerian Stock Exchange.

    If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Nigeria, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

    Data fields included:

    Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

    Q&A:

    1. How much does the End-of-Day Pricing Data cost in Nigeria ?

    The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

    1. How complete is the End-of-Day Pricing Data coverage in Nigeria?

    Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Nigeria exchanges.

    1. How does Techsalerator collect this data?

    Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

    1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

    Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

    1. How do I pay for this dataset?

    Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH, and w...

  10. NSE all stocks sybmbol

    • kaggle.com
    Updated Jul 9, 2024
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    prokaggler22 (2024). NSE all stocks sybmbol [Dataset]. https://www.kaggle.com/datasets/prokaggler22/nse-all-stocks-sybmbol
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 9, 2024
    Dataset provided by
    Kaggle
    Authors
    prokaggler22
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    This data is from National stock There are 4 columns: Column Headers ticker: The stock ticker symbol, which is a unique identifier for a publicly traded company's stock. Close: The closing price of the stock, which is the last price at which the stock was traded during the trading day. Volume: The trading volume, which is the total number of shares of the stock that were traded during the trading day.

  11. 1 M+ Real Time stock market data [NSE/BSE]

    • kaggle.com
    Updated Jun 23, 2017
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    Dipanjan (2017). 1 M+ Real Time stock market data [NSE/BSE] [Dataset]. https://www.kaggle.com/deeiip/1m-real-time-stock-market-data-nse/kernels
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 23, 2017
    Dataset provided by
    Kaggle
    Authors
    Dipanjan
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    Context

    Starting something in FinTech is the most difficult thing. You have no open data. These days I'm trying to do some algo-trading. Maybe not in true sense, because it's not high frequency scalping. But anyway that's that.

    What?

    The data gives almost-Realtime data for half of the Nifty 50 stocks for last week of May and first 2 Weeks of July.

    Now here is the obvious question. The dataset does not have timestamp. That's because it is collected via Web-Socket streaming as it happens. Sometimes once in a couple of seconds, sometimes 10-15 times in the same span. So there is no point to timestamp IMHO. Anyway it'll be client-side timestamp, so not a true timestamp.

    Description

    • tick_data.csv contains only the price-volume data.
    • volume: total volumes traded for the day
    • last_price: denotes the quote price for latest trade
      • List item instrument_list.csv contains description of the underlying instrument.

    P.S:

    **All the data points are not tick-by-tick update. Rather it is mostly an update after 600 ms, provided a trade happened **

  12. T

    Kenya Stock Market (NSE20) Data

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 10, 2015
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    TRADING ECONOMICS (2015). Kenya Stock Market (NSE20) Data [Dataset]. https://tradingeconomics.com/kenya/stock-market
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Dec 10, 2015
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Nov 25, 1997 - Aug 15, 2025
    Area covered
    Kenya
    Description

    Kenya's main stock market index, the Nairobi 20, rose to 2670 points on August 15, 2025, gaining 0.23% from the previous session. Over the past month, the index has climbed 6.96% and is up 62.46% compared to the same time last year, 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 August of 2025.

  13. C

    China CN: Business Enterprise Researchers: % of National Total

    • ceicdata.com
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    CEICdata.com, China CN: Business Enterprise Researchers: % of National Total [Dataset]. https://www.ceicdata.com/en/china/number-of-researchers-and-personnel-on-research-and-development-non-oecd-member-annual
    Explore at:
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2011 - Dec 1, 2022
    Area covered
    China
    Description

    CN: Business Enterprise Researchers: % of National Total data was reported at 58.372 % in 2022. This records an increase from the previous number of 57.863 % for 2021. CN: Business Enterprise Researchers: % of National Total data is updated yearly, averaging 58.117 % from Dec 1991 (Median) to 2022, with 32 observations. The data reached an all-time high of 68.588 % in 2008 and a record low of 26.729 % in 1991. CN: Business Enterprise Researchers: % of National Total data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s China – Table CN.OECD.MSTI: Number of Researchers and Personnel on Research and Development: Non OECD Member: Annual.

    The national breakdown by source of funds does not fully match with the classification defined in the Frascati Manual. The R&D financed by the government, business enterprises, and by the rest of the world can be retrieved but part of the expenditure has no specific source of financing, i.e. self-raised funding (in particular for independent research institutions), the funds from the higher education sector and left-over government grants from previous years.

    The government and higher education sectors cover all fields of NSE and SSH while the business enterprise sector only covers the fields of NSE. There are only few organisations in the private non-profit sector, hence no R&D survey has been carried out in this sector and the data are not available.

    From 2009, researcher data are collected according to the Frascati Manual definition of researcher. Beforehand, this was only the case for independent research institutions, while for the other sectors data were collected according to the UNESCO concept of “scientist and engineer”.

    In 2009, the survey coverage in the business and the government sectors has been expanded.

    Before 2000, all of the personnel data and 95% of the expenditure data in the business enterprise sector are for large and medium-sized enterprises only. Since 2000 however, the survey covers almost all industries and all enterprises above a certain threshold. In 2000 and 2004, a census of all enterprises was held, while in the intermediate years data for small enterprises are estimated.

    Due to the reform of the S&T system some government institutions have become enterprises, and their R&D data have been reflected in the Business Enterprise sector since 2000.

  14. Adani Group of Companies : NSE Stocks Datasets

    • kaggle.com
    Updated May 9, 2023
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    Yogesh Shinde (2023). Adani Group of Companies : NSE Stocks Datasets [Dataset]. https://www.kaggle.com/yogesh239/nse-stocks-datasets-adani-group-of-companies/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 9, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Yogesh Shinde
    Description

    This dataset contains daily stock prices and trading volume for the Adani group of companies listed on the National Stock Exchange (NSE) from January 1, 2023 onwards.

    The Adani Group is a large company based in India that works in many different areas, such as transportation, logistics, agribusiness, power generation, renewable energy and more. It was started by Gautam Adani in 1988. It's worth noting that in September 2020, he was become the third richest man in the world.

    But due to certain allegations from Hindenburg Research report in January 2023, there are huge fluctuations in the stock prices of Adani's companies. Please note that the Hindenburg report and its allegations are not confirmed and may not necessarily be indicative of the Adani group's actual financial performance or prospects. This dataset is provided for informational purposes only and does not constitute financial or investment advice. Users should conduct their own research and seek professional advice before making any investment decisions.

    The Adani Group has seven companies that are listed on the National Stock Exchange (NSE) in India, including: Adani Enterprises Ltd (ADANIENT) Adani Green Energy Ltd (ADANIGREEN) Adani Ports and Special Economic Zone Ltd (ADANIPORTS) Adani Power Ltd (ADANIPOWER) Adani Transmission Ltd (ADANITRANS) Adani Total Gas Ltd (ATGL) Adani Wilmar Ltd (AWL)

    Content : This dataset includes the daily closing price, opening price, highest price, lowest price, and trading volume, highest and lowest price of stocks in past 52 week, number of trades etc. for all the seven registered companies of Adani Group - 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 - VWAP - Volume Weighted Average Price - 52W H - 52 Week High price - 52W L - 52 Week Lowest price - Volume - volume of transaction - Value - Turn over in lakhs - No. of trades

    Acknowledgements : The data is obtained from NSE website This is just data from 1st Jan, 2023 to 23 March, 2023 is provided here, you will get vast and detailed real-time & historical data from the official website.

    Image Credit : Angel One Website

  15. T

    New Zealand Stock Market (NZX 50) Data

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Dec 20, 2019
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    TRADING ECONOMICS (2019). New Zealand Stock Market (NZX 50) Data [Dataset]. https://tradingeconomics.com/new-zealand/stock-market
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Dec 20, 2019
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 3, 2001 - Aug 15, 2025
    Area covered
    New Zealand
    Description

    New Zealand's main stock market index, the NZX 50, rose to 12889 points on August 15, 2025, gaining 0.43% from the previous session. Over the past month, the index has climbed 1.06% and is up 1.27% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from New Zealand. New Zealand Stock Market (NZX 50) - values, historical data, forecasts and news - updated on August of 2025.

  16. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Atul Anand {Jha} (2019). National Stock Exchange : Time Series [Dataset]. https://www.kaggle.com/atulanandjha/national-stock-exchange-time-series/code
Organization logo

National Stock Exchange : Time Series

national stock exchange dataset of indian IT companies for time series analysis

Explore at:
4 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Dec 4, 2019
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Atul Anand {Jha}
License

http://www.gnu.org/licenses/lgpl-3.0.htmlhttp://www.gnu.org/licenses/lgpl-3.0.html

Description

Context

The National Stock Exchange of India Ltd. (NSE) is an Indian stock exchange located at Mumbai, Maharashtra, India. National Stock Exchange (NSE) was established in 1992 as a demutualized electronic exchange. It was promoted by leading financial institutions on request of the Government of India. It is India’s largest exchange by turnover. In 1994, it launched electronic screen-based trading. Thereafter, it went on to launch index futures and internet trading in 2000, which were the first of its kind in the country.

With the help of NSE, you can trade in the following segments:

  • Equities

  • Indices

  • Mutual Funds

  • Exchange Traded Funds

  • Initial Public Offerings

  • Security Lending and Borrowing Scheme

https://cdn6.newsnation.in/images/2019/06/24/Sharemarket-164616041_6.jpg" alt="Stock image">

Companies on successful IPOs gets their Stocks traded over different Stock Exchnage platforms. NSE is one important platofrm in India. There are thousands of companies trading their stocks in NSE. But, I have chosen two popular and high rated IT service companies of India; TCS and INFOSYS. and the third one is the benchmark for Indian IT companies , i.e. NIFTY_IT_INDEX .

Content

The dataset contains three csv files. Each resembling to INFOSYS, NIFTY_IT_INDEX, and TCS, respectively. One can easily identify that by the name of CSV files.

Timeline of Data recording : 1-1-2015 to 31-12-2015.

Source of Data : Official NSE website.

Method : We have used the NSEpy api to fetch the data from NSE site. I have also mentioned my approach in this Kernel - "**WebScraper to download data for NSE**". Please go though that to better understand the nature of this dataset.

Shape of Dataset:

INFOSYS - 248 x 15 || NIFTY_IT_INDEX - 248 x 7 || **TCS - 248 x 15

  • Colum Descriptors:

  • Date: date on which data is recorded

  • Symbol: NSE symbol of the stock

  • Series: Series of that stock | EQ - Equity

OTHER SERIES' ARE:

EQ: It stands for Equity. In this series intraday trading is possible in addition to delivery.

BE: It stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

BL: This series is for facilitating block deals. Block deal is a trade, with a minimum quantity of 5 lakh shares or minimum value of Rs. 5 crore, executed through a single transaction, on the special “Block Deal window”. The window is opened for only 35 minutes in the morning from 9:15 to 9:50AM.

BT: This series provides an exit route to small investors having shares in the physical form with a cap of maximum 500 shares.

GC: This series allows Government Securities and Treasury Bills to be traded under this category.

IL: This series allows only FIIs to trade among themselves. Permissible only in those securities where maximum permissible limit for FIIs is not breached.

  • Prev Close: Last day close point

  • Open: current day open point

  • High: current day highest point

  • Low: current day lowest point

  • Last: the final quoted trading price for a particular stock, or stock-market index, during the most recent day of trading.

  • Close: Closing point for the current day

  • VWAP: volume-weighted average price is the ratio of the value traded to total volume traded over a particular time horizon

  • Volume: the amount of a security that was traded during a given period of time. For every buyer, there is a seller, and each transaction contributes to the count of total volume.

  • Turnover: Total Turnover of the stock till that day

  • Trades: Number of buy or Sell of the stock.

  • Deliverable: Volumethe quantity of shares which actually move from one set of people (who had those shares in their demat account before today and are selling today) to another set of people (who have purchased those shares and will get those shares by T+2 days in their demat account).

  • %Deliverble: percentage deliverables of that stock

Acknowledgements

I woul dlike to acknowledge all my sincere thanks to the brains behind NSEpy api, and in particular SWAPNIL JARIWALA , who is also maintaining an amazing open source github repo for this api.

Inspiration

I have also built a starter kernel for this dataset. You can find that right here .

I am so excited to see your magical approaches for the same dataset.

THANKS!

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