Data
NSE-Stocks-Data

NSE-Stocks-Data

active ARFF CC0: Public Domain Visibility: public Uploaded 24-03-2022 by Dustin Carrion
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Context The data is of National Stock Exchange of India. The data is compiled to felicitate Machine Learning, without bothering much about Stock APIs. Content The data is of National Stock Exchange of India's stock listings for each trading day of 2016 and 2017. A brief description of columns. SYMBOL: Symbol of the listed company. SERIES: Series of the equity. Values are [EQ, BE, BL, BT, GC and IL] OPEN: The opening market price of the equity symbol on the date. HIGH: The highest market price of the equity symbol on the date. LOW: The lowest recorded market price of the equity symbol on the date. CLOSE: The closing recorded price of the equity symbol on the date. LAST: The last traded price of the equity symbol on the date. PREVCLOSE: The previous day closing price of the equity symbol on the date. TOTTRDQTY: Total traded quantity of the equity symbol on the date. TOTTRDVAL: Total traded volume of the equity symbol on the date. TIMESTAMP: Date of record. TOTALTRADES: Total trades executed on the day. ISIN: International Securities Identification Number. Acknowledgements All data is fetched from NSE official site. https://www.nseindia.com/ Inspiration This dataset is compiled to felicitate Machine learning on Stocks.

12 features

SYMBOLstring2037 unique values
0 missing
SERIESstring71 unique values
2457 missing
OPENnumeric58241 unique values
0 missing
HIGHnumeric58291 unique values
0 missing
LOWnumeric60100 unique values
0 missing
CLOSEnumeric80741 unique values
0 missing
LASTnumeric55929 unique values
0 missing
PREVCLOSEnumeric80697 unique values
0 missing
TOTTRDQTYnumeric369830 unique values
0 missing
TOTTRDVALnumeric822178 unique values
0 missing
TIMESTAMPstring495 unique values
0 missing
TOTALTRADESnumeric54761 unique values
0 missing
ISIN (ignore)string2405 unique values
0 missing

19 properties

846404
Number of instances (rows) of the dataset.
12
Number of attributes (columns) of the dataset.
Number of distinct values of the target attribute (if it is nominal).
2457
Number of missing values in the dataset.
2457
Number of instances with at least one value missing.
9
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.
0.29
Percentage of instances having missing values.
Average class difference between consecutive instances.
0.02
Percentage of missing values.

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