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I have used Melbourne Housing Dataset and build a Dashboard on that data using Excel.

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Data-analysis-with-Excel

I have used Melbourne Housing Dataset and build a Dashboard on that data using Excel.

insights

1. Regionwise monthly trend of property count is shown.

The distribution of property with the passing of year across all the region have shown increasing trend. Although the growth of increasing trend of property distribution was slow in the year 2016 but it showed high growth rate till the end of year 2018.

2. Number of rooms across different property type available for various average price rate has been shown.

The distribution of property with multiple number of rooms across various price rate shows an increase in price for increase in number of rooms. All the property type viz. h--(house,cottage,villa) ; u--(unit,duplex) ; t--townhouse comes in the price band of $1M - $3M. But above 30 Lakhs of cost only "h & u"- type of property is available. At around $5M "h"- type of property is available with maximum no. of rooms.

3. Monthly trend of price across different acquiring method of property has been shown

The acquiring method includes S - property sold, SP - property sold in prior, PN - property passed in, SN - sold but not disclosed , NB - no bid; VB - vendor bid; W - withdrawn prior to auction etc methods. So, Different share of property price in terms of percentage is shown against various acquiring method of property.

4. Average price of property across different council area is drawn.

Yearwise avg. price trend across differnet council arae is shown. Although there is no prominent change in trend for all the years , but filtering the year help us to see the changes in price band across different council area of Melbourne.

5. Property count of every housing type is shown.

The Pie chart showing the percentage of property count against different property type, shows a maximum property count is hold by h--(house,cottage,villa) type of property with around 68%, followed by u--(unit,duplex) type bearing 21 % and the least by t--townhouse type holding just 10% .

6. Average landsize for every car spot in property has been drawn.

h--(house,cottage,villa) type of property holds maximum avg. landsize for car spot with 640 sq.m, followed by u--(unit,duplex) type holds an avg. landsize of 480 sq.m and the least amount hold by t--townhouse type property. maximum of 10 carspots are their with largest landsize area.

7. Top 5 Average Prce of every SellerG.

SellerG are the Real Estate agent. I have shown the Top 5 SellerG with maximum amount of avg. price of property they have done business with.

8. Regionwise average price of property with total number of 6 rooms has been shown

In this insight Avg. price of property with total no. of 6 rooms have been displayed across different region. Although property with max. 6 rooms have been displayed you can filter it out on dashboard and check for multiple no. of rooms.

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I have used Melbourne Housing Dataset and build a Dashboard on that data using Excel.

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