Data
Gold-Rate-History-in-TamilNadu-(2006-2020)

Gold-Rate-History-in-TamilNadu-(2006-2020)

active ARFF CC0: Public Domain Visibility: public Uploaded 23-03-2022 by Onur Yildirim
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Context As you all know that, as per the observation of economists, according to the current trend, it seems that the yellow metal is performing better as an investment option in comparison to mutual funds, equities, real estate, and fixed deposits. The weak global economic outlook for the entire year is might be the reason why gold prices are surging. The yellow metal is considered as a financial instrument that does not erode in valuation during periods of economic turbulence. Many global investors are looking for safer investment options including gold as fears over a recession continue to grow. Therefore here, need to forecast the price of the Gold in the future based on trend or seasonality using historical data from Jan 2006 to Sep 2020. The historical data has from Jan 2006 to Sep 2020. Problem To Predict or forecast the gold price in the near future. Hence, it would help Indian people aware of when to buy gold for their investments. Data The data contains the following fields, Date, Country, State, City, Pure Gold (24 k), Priced indicated in INR Standard Gold (22 k), Priced indicated in INR The dataset will be updated soon for other states as well in India. Acknowledgements The dataset has scraped from www.livechennai.com. Gold Prices indicated in this data makes no guarantee or warranty on the accuracy or completeness of the data provided.

6 features

Datestring4899 unique values
0 missing
Countrystring1 unique values
0 missing
Statestring1 unique values
0 missing
Locationstring1 unique values
0 missing
Pure_Gold_(24_k)numeric2335 unique values
0 missing
Standard_Gold_(22_K)numeric1861 unique values
0 missing

19 properties

4971
Number of instances (rows) of the dataset.
6
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.
2
Number of numeric attributes.
0
Number of nominal attributes.
0
Number of attributes divided by the number of instances.
33.33
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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