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Lagos State Property Pricing Analysis

Lagos State Property Pricing Analysis

Power BI Dashboard

About this project

Looking to own or rent a property in Lagos, Nigeria? This Lagos State Property Pricing Dashboard can help you identify the best properties to go for and their locations. It includes information on property prices and property types such as lands, office spaces, commercial properties, and houses (bungalows, flats, self-contained units, duplexes, and more). It also includes the addresses and neighbourhoods of these properties. With this data, you can figure out which areas are the most and least profitable for renting or buying a property and which property type you should go for. So, whether you’re looking for your next home or a good place to invest that money, this dashboard comes in handy. This is a data visualisation project with the aim of providing sales and rental price insights for properties in Lagos.

Data Quality Issues and Cleaning Process

After downloading the dataset from Kaggle, I realised it was going to be difficult to visualise if there wasn’t a category of property and their exact neighbourhoods, considering LAGOS is a big place, i.e., the island and the mainland. I went ahead and created a column for the neighbourhood category, using the neighbourhood to categorise the properties and their addresses into two categories: island or mainland. After that, it immediately clicked that it was okay to visualise, so I imported it into Power BI.

Chart Descriptions

1. Maximum Sale Price

This chart shows the maximum price of a property on sale and also the location of this property. It also shows the neighbourhood category

Based on the dataset, we can see that the properties on sale on the mainland, particularly in Ikeja and Apapa, are the most expensive, while the properties on sale on the island, particularly Victoria Island and Lekki, are following behind. I bet you know what to do with this information. Ikeja makes up over 39% of the maximum price on the mainland. Note: This was filtered to give us the top 5 most expensive neighbourhoods.

Minimum Sale Price

This chart shows the minimum price of a property on sale and also the location of this property. It also shows the neighbourhood category

Based on the dataset, we can see that the properties on sale on the mainland, particularly in Ikorodu, are the least expensive, while the properties on sale on the island, particularly Victoria Island, Ajah, and Sangotedo, are following behind. I bet you know what to do with this information. Properties in Ikorodu turn out to be cheaper than others on the mainland. Note: This was filtered to give us the top 5 most expensive neighbourhoods.

2. Maximum Rent Price

This chart shows the maximum price of a property for rent and also the location of this property. It also shows the neighbourhood category. Based on the dataset, we can see that the properties for rent on the island, particularly in Ikoyi, followed by Lekki, are the most expensive, while the properties for rent on the mainland, particularly in Ikeja, are following behind. I bet you know what to do with this information. You shouldn’t go to Ikoyi to rent a house if you don’t have that much money. Okay, maybe you should 'miracle no dey tire Jesus’. Ikoyi makes up over 40% of the maximum price on the island. Note: This was filtered to give us the top 5 least expensive neighbourhoods.

Minimum Rent Price

This chart shows the maximum price of a property for rent and also the location of this property. It also shows the neighbourhood category.

Based on the dataset, we can see that the properties for rent on the mainland, particularly in Ikorodu, Ogba, and Ikosi, are less expensive but not as expensive as the properties on the island, particularly Victoria Island and Lagos Island. I bet you know what to do with this information. Ikeja turns out to have a turndown in rent prices. Note: This was filtered to give us the top 5 least expensive neighbourhoods.

Conclusion

This is my improved first-ever data visualisation. I hope you enjoyed going through it as much as I enjoyed creating it. I would really love your feedback, good or bad.

Thank you for reading.

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