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NSE Stock Data By Ticker (dataset 2)

This dataset contains data for 1987 NSE Companies

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2

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About this Dataset

NSE Stock Data By Ticker (dataset 2)

This File is part of a 3-series dataset that encompasses data sourced for stock data about all NSE Companies, presently including only a total of 1987. It contains the following data: Open, High, Low, Close, Adj Close, Volume, Symbol, Sector, Industry, Market, Quote Type, Dividend Yield, Debt-to-Equity Ratio, Current Ratio, Earning per Share, Variability Index. The Variability index is a self-developed Index to measure Intraday Volatility of the stock, and thus determine, qualitatively, the risk of investing in that company.

Tables

Lindeindia

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lindeindia
  • 310.83 KB
  • 6010 rows
  • 17 columns
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CREATE TABLE lindeindia (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lloydsengg

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lloydsengg
  • 21.02 KB
  • 180 rows
  • 17 columns
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CREATE TABLE lloydsengg (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lloydsme

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lloydsme
  • 23.99 KB
  • 235 rows
  • 17 columns
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CREATE TABLE lloydsme (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lodha

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lodha
  • 55.74 KB
  • 793 rows
  • 17 columns
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CREATE TABLE lodha (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lokeshmach

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lokeshmach
  • 206.42 KB
  • 4480 rows
  • 17 columns
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CREATE TABLE lokeshmach (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lordschlo

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lordschlo
  • 22.32 KB
  • 206 rows
  • 17 columns
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CREATE TABLE lordschlo (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lotuseye

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lotuseye
  • 159.98 KB
  • 3934 rows
  • 17 columns
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CREATE TABLE lotuseye (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lovable

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lovable
  • 180.47 KB
  • 3271 rows
  • 17 columns
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CREATE TABLE lovable (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Loyaltex

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.loyaltex
  • 36.06 KB
  • 464 rows
  • 17 columns
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CREATE TABLE loyaltex (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lpdc

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lpdc
  • 108.78 KB
  • 3912 rows
  • 17 columns
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CREATE TABLE lpdc (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" VARCHAR,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lt

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lt
  • 326.72 KB
  • 5466 rows
  • 17 columns
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CREATE TABLE lt (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Ltfoods

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.ltfoods
  • 20.46 KB
  • 164 rows
  • 17 columns
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CREATE TABLE ltfoods (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Ltim

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.ltim
  • 119.7 KB
  • 1962 rows
  • 17 columns
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CREATE TABLE ltim (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Ltts

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.ltts
  • 116.96 KB
  • 1919 rows
  • 17 columns
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CREATE TABLE ltts (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lumaxind

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lumaxind
  • 287.56 KB
  • 5462 rows
  • 17 columns
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CREATE TABLE lumaxind (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lumaxtech

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lumaxtech
  • 236.76 KB
  • 4304 rows
  • 17 columns
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CREATE TABLE lumaxtech (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lupin

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lupin
  • 328.48 KB
  • 5674 rows
  • 17 columns
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CREATE TABLE lupin (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Luxind

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.luxind
  • 126.86 KB
  • 2120 rows
  • 17 columns
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CREATE TABLE luxind (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lxchem

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lxchem
  • 54.73 KB
  • 807 rows
  • 17 columns
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CREATE TABLE lxchem (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lykalabs

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lykalabs
  • 255.09 KB
  • 7161 rows
  • 17 columns
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CREATE TABLE lykalabs (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Lypsagems

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.lypsagems
  • 111.23 KB
  • 2627 rows
  • 17 columns
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CREATE TABLE lypsagems (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Maanalu

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.maanalu
  • 221.78 KB
  • 4690 rows
  • 17 columns
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CREATE TABLE maanalu (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Macpower

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.macpower
  • 87.97 KB
  • 1547 rows
  • 17 columns
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CREATE TABLE macpower (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" DOUBLE,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Madhav

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.madhav
  • 167.67 KB
  • 4071 rows
  • 17 columns
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CREATE TABLE madhav (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" DOUBLE,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

Madhucon

@kaggle.toocool69_nse_stock_data_by_ticker_dataset_2.madhucon
  • 195.3 KB
  • 4372 rows
  • 17 columns
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CREATE TABLE madhucon (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT,
  "symbol" VARCHAR,
  "sector" VARCHAR,
  "industry" VARCHAR,
  "market" VARCHAR,
  "quotetype" VARCHAR,
  "dividend_yield" VARCHAR,
  "debt_to_equity_ratio" VARCHAR,
  "current_ratio" DOUBLE,
  "earning_per_share" DOUBLE,
  "variability_index" DOUBLE
);

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