Name: Nifty 50 Stocks Price Dataset
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

Itc

@kaggle.tadakasuryateja_nifty_50_stocks.itc

191.89 kB
4,432 rows
10 columns

CREATE TABLE itc (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Kotakbank

@kaggle.tadakasuryateja_nifty_50_stocks.kotakbank

195.4 kB
4,432 rows
10 columns

CREATE TABLE kotakbank (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Lt

@kaggle.tadakasuryateja_nifty_50_stocks.lt

210.19 kB
4,432 rows
10 columns

CREATE TABLE lt (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Lupin

@kaggle.tadakasuryateja_nifty_50_stocks.lupin

191.58 kB
4,432 rows
10 columns

CREATE TABLE lupin (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Mandm

@kaggle.tadakasuryateja_nifty_50_stocks.mandm

251.69 kB
5,827 rows
10 columns

CREATE TABLE mandm (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Maruti

@kaggle.tadakasuryateja_nifty_50_stocks.maruti

207.96 kB
4,432 rows
10 columns

CREATE TABLE maruti (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Mcdowell N

@kaggle.tadakasuryateja_nifty_50_stocks.mcdowell_n

5.8 kB
10 columns

CREATE TABLE mcdowell_n (
  "date" VARCHAR,
  "stock_name" VARCHAR,
  "n_1_open" VARCHAR  -- 1. Open,
  "n_2_high" VARCHAR  -- 2. High,
  "n_3_low" VARCHAR  -- 3. Low,
  "n_4_close" VARCHAR  -- 4. Close,
  "n_5_adjusted_close" VARCHAR  -- 5. Adjusted Close,
  "n_6_volume" VARCHAR  -- 6. Volume,
  "n_7_dividend_amount" VARCHAR  -- 7. Dividend Amount,
  "n_8_split_coefficient" VARCHAR  -- 8. Split Coefficient
);

Nestleind

@kaggle.tadakasuryateja_nifty_50_stocks.nestleind

204.46 kB
4,431 rows
10 columns

CREATE TABLE nestleind (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Ntpc

@kaggle.tadakasuryateja_nifty_50_stocks.ntpc

171.2 kB
4,432 rows
10 columns

CREATE TABLE ntpc (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Ongc

@kaggle.tadakasuryateja_nifty_50_stocks.ongc

193.15 kB
4,431 rows
10 columns

CREATE TABLE ongc (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Powergrid

@kaggle.tadakasuryateja_nifty_50_stocks.powergrid

141.73 kB
3,747 rows
10 columns

CREATE TABLE powergrid (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Reliance

@kaggle.tadakasuryateja_nifty_50_stocks.reliance

207.71 kB
4,432 rows
10 columns

CREATE TABLE reliance (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Sbin

@kaggle.tadakasuryateja_nifty_50_stocks.sbin

199.44 kB
4,432 rows
10 columns

CREATE TABLE sbin (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Sunpharma

@kaggle.tadakasuryateja_nifty_50_stocks.sunpharma

203.69 kB
4,432 rows
10 columns

CREATE TABLE sunpharma (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Tatamotors

@kaggle.tadakasuryateja_nifty_50_stocks.tatamotors

220.69 kB
4,433 rows
10 columns

CREATE TABLE tatamotors (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Tatasteel

@kaggle.tadakasuryateja_nifty_50_stocks.tatasteel

195.17 kB
4,432 rows
10 columns

CREATE TABLE tatasteel (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Tcs

@kaggle.tadakasuryateja_nifty_50_stocks.tcs

202.27 kB
4,432 rows
10 columns

CREATE TABLE tcs (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Techm

@kaggle.tadakasuryateja_nifty_50_stocks.techm

176.55 kB
4,021 rows
10 columns

CREATE TABLE techm (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Ultracemco

@kaggle.tadakasuryateja_nifty_50_stocks.ultracemco

201.48 kB
4,432 rows
10 columns

CREATE TABLE ultracemco (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Unionbank

@kaggle.tadakasuryateja_nifty_50_stocks.unionbank

177.53 kB
4,432 rows
10 columns

CREATE TABLE unionbank (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Vedl

@kaggle.tadakasuryateja_nifty_50_stocks.vedl

192.71 kB
4,430 rows
10 columns

CREATE TABLE vedl (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Wipro

@kaggle.tadakasuryateja_nifty_50_stocks.wipro

213.85 kB
4,432 rows
10 columns

CREATE TABLE wipro (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Zeel

@kaggle.tadakasuryateja_nifty_50_stocks.zeel

205.45 kB
4,432 rows
10 columns

CREATE TABLE zeel (
  "date" TIMESTAMP,
  "stock_name" VARCHAR,
  "n_1_open" DOUBLE  -- 1. Open,
  "n_2_high" DOUBLE  -- 2. High,
  "n_3_low" DOUBLE  -- 3. Low,
  "n_4_close" DOUBLE  -- 4. Close,
  "n_5_adjusted_close" DOUBLE  -- 5. Adjusted Close,
  "n_6_volume" BIGINT  -- 6. Volume,
  "n_7_dividend_amount" DOUBLE  -- 7. Dividend Amount,
  "n_8_split_coefficient" DOUBLE  -- 8. Split Coefficient
);

Nifty 50 Stocks Price Dataset

About this Dataset