Baselight

Top 10 Fast Food Giants: Stock Price Dataset(2024)

An in-depth look into the stock performance of the biggest fast food giants

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0

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About this Dataset

Top 10 Fast Food Giants: Stock Price Dataset(2024)

Dataset Description: This dataset consists of historical stock price data for 10 of the largest fast food companies, collected from Yahoo Finance. Each company’s stock data is stored in a separate Excel file, containing key financial metrics that are typically tracked for market analysis, such as open, high, low, close, adjusted close prices, and trading volume over a specified time period.

Files Descriptions: Each Excel file corresponds to a different fast food company’s stock, identified by its ticker symbol:

  • BRK-A - Berkshire Hathaway Inc. (A financial conglomerate that has major stakes in fast food and other industries)
  • DNUT- Krispy Kreme, Inc.
  • DPZ - Domino’s Pizza, Inc.
  • LKNCY - Luckin Coffee Inc.
  • MCD - McDonald's Corporation
  • PZZA - Papa John's International, Inc.
  • QSR - Restaurant Brands International Inc. (Parent of Burger King, Tim Hortons, and Popeyes)
  • SBUX - Starbucks Corporation
  • WEN - The Wendy’s Company
  • YUM - Yum! Brands, Inc. (Parent of KFC, Taco Bell, and Pizza Hut)

Column Descriptions: Each file likely contains the following columns (standard in Yahoo Finance datasets):

  • Date: The trading date.
  • Open: The price at which the stock opened on a given day.
  • High: The highest price of the stock during the trading session.
  • Low: The lowest price of the stock during the trading session.
  • Close: The price of the stock at market close.
  • Adj Close: The closing price adjusted for dividends and stock splits.
  • Volume: The number of shares traded during the day.

Purpose: This dataset can be used to:

  • Analyze stock trends and volatility in the fast food sector.
  • Compare the performance of different fast food companies over time.
  • Explore correlations between companies and broader economic or market conditions.
  • Test financial models or strategies, such as momentum trading or moving average crossovers.

Tables

Brk A

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.brk_a
  • 352.57 kB
  • 11,222 rows
  • 7 columns
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CREATE TABLE brk_a (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Dnut

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.dnut
  • 37.85 kB
  • 810 rows
  • 7 columns
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CREATE TABLE dnut (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Dpz

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.dpz
  • 244.58 kB
  • 5,083 rows
  • 7 columns
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CREATE TABLE dpz (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Lkncy

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.lkncy
  • 64.89 kB
  • 1,345 rows
  • 7 columns
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CREATE TABLE lkncy (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Mcd

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.mcd
  • 553.15 kB
  • 14,652 rows
  • 7 columns
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CREATE TABLE mcd (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Pzza

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.pzza
  • 322.61 kB
  • 7,878 rows
  • 7 columns
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CREATE TABLE pzza (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Qsr

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.qsr
  • 115.84 kB
  • 2,459 rows
  • 7 columns
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CREATE TABLE qsr (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Sbux

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.sbux
  • 357.65 kB
  • 8,117 rows
  • 7 columns
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CREATE TABLE sbux (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Wen

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.wen
  • 306.32 kB
  • 11,187 rows
  • 7 columns
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CREATE TABLE wen (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Yum

@kaggle.nguyentiennhan_stock_prices_of_the_10_largest_fast_foo_c09b7ae0.yum
  • 320.63 kB
  • 6,796 rows
  • 7 columns
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CREATE TABLE yum (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

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