Data
BSE-30-daily-market-price-(2008-2018)

BSE-30-daily-market-price-(2008-2018)

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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  • Computer Systems Machine Learning
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Content The SP BSE SENSEX (SP Bombay Stock Exchange Sensitive Index), also called the BSE 30 or simply the SENSEX, is a free-float market-weighted stock market index of 30 well-established and financially sound companies listed on Bombay Stock Exchange. The 30 component companies which are some of the largest and most actively traded stocks, are representative of various industrial sectors of the Indian economy. This dataset contains the data about these 30 stocks for 10 years starts from 06/05/2008 to 04/05/2018 . Variables are symbol (ticker) , Date , open , high , low , close, adj close and volume. Acknowledgement The prices are fetched from yahoo finance. Inspiration 1) Which stocks were most Volatile/ Stable? 2) Predicting next day stock prices

8 features

Symbolstring30 unique values
0 missing
Datestring2469 unique values
0 missing
Opennumeric29895 unique values
250 missing
Highnumeric37205 unique values
250 missing
Lownumeric38329 unique values
250 missing
Closenumeric48714 unique values
250 missing
Adj_Closenumeric69593 unique values
250 missing
Volumenumeric69411 unique values
250 missing

19 properties

73316
Number of instances (rows) of the dataset.
8
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
1500
Number of missing values in the dataset.
250
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.
75
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.
0.34
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.26
Percentage of missing values.

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