Data
Tesla-Stock-Price

Tesla-Stock-Price

active ARFF Database: Open Database, Contents: Database Contents Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context The subject matter of this dataset explores Tesla's stock price from its initial public offering (IPO) to yesterday. Content Within the dataset one will encounter the following: The date - "Date" The opening price of the stock - "Open" The high price of that day - "High" The low price of that day - "Low" The closed price of that day - "Close" The amount of stocks traded during that day - "Volume" The stock's closing price that has been amended to include any distributions/corporate actions that occurs before next days open - "Adj[usted] Close" Acknowledgements Through Python programming and checking Sentdex out, I acquired the data from Yahoo Finance. The time period represented starts from 06/29/2010 to 03/17/2017. Inspiration What happens when the volume of this stock trading increases/decreases in a short and long period of time? What happens when there is a discrepancy between the adjusted close and the next day's opening price?

7 features

Datestring1692 unique values
0 missing
Opennumeric1464 unique values
0 missing
Highnumeric1470 unique values
0 missing
Lownumeric1468 unique values
0 missing
Closenumeric1528 unique values
0 missing
Volumenumeric1676 unique values
0 missing
Adj_Closenumeric1528 unique values
0 missing

19 properties

1692
Number of instances (rows) of the dataset.
7
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
6
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
85.71
Percentage of numeric attributes.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
Average class difference between consecutive instances.
0
Percentage of missing values.

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