Baselight

FAANG- Complete Stock Data

It contains data of Stock of the FAANG companies from when they began trading.

@kaggle.aayushmishra1512_faang_complete_stock_data

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About this Dataset

FAANG- Complete Stock Data

Context

There are a few companies that are considered to be revolutionary. These companies also happen to be a dream place to work at for many many people across the world. These companies include - Facebook,Amazon,Apple,Netflix and Google also known as FAANG! These companies make ton of money and they help others too by giving them a chance to invest in the companies via stocks and shares. This data wass made targeting these stock prices.

Content

The data contains information such as opening price of a stock, closing price, how much of these stocks were sold and many more things. There are 5 different CSV files in the data for each company.

Tables

Amazon

@kaggle.aayushmishra1512_faang_complete_stock_data.amazon
  • 255.43 KB
  • 5852 rows
  • 7 columns
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CREATE TABLE amazon (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Apple

@kaggle.aayushmishra1512_faang_complete_stock_data.apple
  • 404.82 KB
  • 10016 rows
  • 7 columns
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CREATE TABLE apple (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" DOUBLE
);

Facebook

@kaggle.aayushmishra1512_faang_complete_stock_data.facebook
  • 95.05 KB
  • 2076 rows
  • 7 columns
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CREATE TABLE facebook (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Google

@kaggle.aayushmishra1512_faang_complete_stock_data.google
  • 249.87 KB
  • 4041 rows
  • 7 columns
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CREATE TABLE google (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

Netflix

@kaggle.aayushmishra1512_faang_complete_stock_data.netflix
  • 216.11 KB
  • 4581 rows
  • 7 columns
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CREATE TABLE netflix (
  "date" TIMESTAMP,
  "open" DOUBLE,
  "high" DOUBLE,
  "low" DOUBLE,
  "close" DOUBLE,
  "adj_close" DOUBLE,
  "volume" BIGINT
);

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