Name: NIFTY ALL STOCK Dataset
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

NIFTY ALL STOCK Dataset

Content

This dataset is a playground for technical analysis. It is said that 30% of traffic on stocks is already generated by machines, can trading be fully automated? If not, there is still a lot to learn from historical data. .

Context

https://www.kaggle.com/akshaypawar7/nifty-50-interactive-dashboard
Dataset consists of following files:

500 files of equity stock historical candle data
1_bhavcopy.csv =>
Daily prices of all NSE equity stocks . Most of data spans from 2020 to the end today, for companies new on stock market date range is shorter.
1_meta.csv =>
General description of each company with division on index and industry,
as shown in below chart.

Inspiration

Regardless of your investment strategy, fluctuations are expected in the financial market. Despite this variance, professional investors try to estimate their overall returns. Risks and returns differ based on investment types and other factors, which impact stability and volatility. To attempt to predict returns, there are many computer-based algorithms and models for financial market trading. Yet, with new techniques and approaches, data science could improve quantitative researchers' ability to forecast an investment's return.

Tables

Balkrisind

@kaggle.akshaypawar7_nifty_dataset.balkrisind

43.93 kB
525 rows
12 columns

CREATE TABLE balkrisind (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Balramchin

@kaggle.akshaypawar7_nifty_dataset.balramchin

42.85 kB
525 rows
12 columns

CREATE TABLE balramchin (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bandhanbnk

@kaggle.akshaypawar7_nifty_dataset.bandhanbnk

43.26 kB
525 rows
12 columns

CREATE TABLE bandhanbnk (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bankbaroda

@kaggle.akshaypawar7_nifty_dataset.bankbaroda

42.11 kB
525 rows
12 columns

CREATE TABLE bankbaroda (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bankindia

@kaggle.akshaypawar7_nifty_dataset.bankindia

40.92 kB
525 rows
12 columns

CREATE TABLE bankindia (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Basf

@kaggle.akshaypawar7_nifty_dataset.basf

43.12 kB
525 rows
12 columns

CREATE TABLE basf (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bataindia

@kaggle.akshaypawar7_nifty_dataset.bataindia

43.2 kB
525 rows
12 columns

CREATE TABLE bataindia (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bayercrop

@kaggle.akshaypawar7_nifty_dataset.bayercrop

43.02 kB
525 rows
12 columns

CREATE TABLE bayercrop (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bbtc

@kaggle.akshaypawar7_nifty_dataset.bbtc

41.68 kB
525 rows
12 columns

CREATE TABLE bbtc (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bdl

@kaggle.akshaypawar7_nifty_dataset.bdl

42.25 kB
525 rows
12 columns

CREATE TABLE bdl (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bel

@kaggle.akshaypawar7_nifty_dataset.bel

43.25 kB
525 rows
12 columns

CREATE TABLE bel (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Beml

@kaggle.akshaypawar7_nifty_dataset.beml

43.14 kB
525 rows
12 columns

CREATE TABLE beml (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bergepaint

@kaggle.akshaypawar7_nifty_dataset.bergepaint

42.6 kB
525 rows
12 columns

CREATE TABLE bergepaint (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bharatforg

@kaggle.akshaypawar7_nifty_dataset.bharatforg

43.66 kB
525 rows
12 columns

CREATE TABLE bharatforg (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bharatras

@kaggle.akshaypawar7_nifty_dataset.bharatras

42.72 kB
525 rows
12 columns

CREATE TABLE bharatras (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bhartiartl

@kaggle.akshaypawar7_nifty_dataset.bhartiartl

43.6 kB
525 rows
12 columns

CREATE TABLE bhartiartl (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bhel

@kaggle.akshaypawar7_nifty_dataset.bhel

41.83 kB
525 rows
12 columns

CREATE TABLE bhel (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Biocon

@kaggle.akshaypawar7_nifty_dataset.biocon

42.52 kB
525 rows
12 columns

CREATE TABLE biocon (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Birlacorpn

@kaggle.akshaypawar7_nifty_dataset.birlacorpn

42.91 kB
525 rows
12 columns

CREATE TABLE birlacorpn (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bluedart

@kaggle.akshaypawar7_nifty_dataset.bluedart

43.41 kB
525 rows
12 columns

CREATE TABLE bluedart (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bluestarco

@kaggle.akshaypawar7_nifty_dataset.bluestarco

42.11 kB
525 rows
12 columns

CREATE TABLE bluestarco (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Boschltd

@kaggle.akshaypawar7_nifty_dataset.boschltd

44.72 kB
525 rows
12 columns

CREATE TABLE boschltd (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Bpcl

@kaggle.akshaypawar7_nifty_dataset.bpcl

42.91 kB
525 rows
12 columns

CREATE TABLE bpcl (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Brigade

@kaggle.akshaypawar7_nifty_dataset.brigade

42.77 kB
525 rows
12 columns

CREATE TABLE brigade (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);

Britannia

@kaggle.akshaypawar7_nifty_dataset.britannia

43.8 kB
525 rows
12 columns

CREATE TABLE britannia (
  "date" TIMESTAMP,
  "symbol" VARCHAR,
  "pre_close" DOUBLE,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "volume" BIGINT,
  "turnover_lacs" DOUBLE,
  "no_of_trades" BIGINT,
  "deliv_volume" DOUBLE,
  "deliv" DOUBLE  -- Deliv %
);