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After looking into the Data Geek Challenge I decided to use this opportunity and look at interesting datasets that would make entertaining visualizations. However, instead of looking at datasets from other countries, I decided to look within my country, Ecuador.


I went to the Ecuadorian Institute of Statistics (www.inec.gob.ec) and found a dataset about transportation in Ecuador of 2011. This dataset has information about all the transportation in Ecuador in 2011.


The variables within these dataset included: Type of Vehicle (Clase), Brand (Marca), Region (Provincia), Year (Año), Uses (Usos), Number of Passengers (Pasajeros), and Tons (Toneladas).


The main focus of this investigation was to explore Lumira and how well I can get insight into the registered vehicles in Ecuador.


1.) In my first graph, I looked at a bar graph based on Different Types of Vehicles.

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My results showed:

  • 34% Automobile
  • 23% Motorcycles
  • 22% Trucks
  • 18% Jeeps
  • 3% Big Trucks

It is interesting to see how there is almost the same amount of motorcycles as there is automobiles. I wonder if there has been an increase in motorcycles in 2012 and 2013.


2.) Then I looked at The Amount of Vehicles per Region.

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In this map graph I could visualize the density of vehicles in the different regions of Ecuador. I could tell from this graph the highest density of vehicles (dark green) is in the regions: Pichincha (286,558), Guayas (103,479), and Manabí (96,739). And the areas with low density of vehicles (light green) are Galapagos (805), Santa Elena (5294), and Pastaza (5449).

3.) However, I also became curious about The Types of Vehicles in each Region. So I formed the following graph:

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This graph shows that in most regions the main vehicle used is the automobile. However in three regions: Manabí, Esmeraldas, and El Oro there are more motorcycles than there are automobiles.  In Manabí, there are 41% Motorcycles and 26% Automobiles, a 14% difference.  In Esmeraldas, there are 58% Motorcycles and 16% Automobiles. This is a 42% difference. And in El Oro, there are 45% Motorcycles and 23% Automobiles. This is a 22% difference.

It is interesting because all of these regions are in the coast of the country, which means a warmer weather. This means that there might be a high correlation between the weather and the type of vehicle people purchase.

4.) After exploring Regions and Types of Vehicles in Ecuador I also wanted to use other variables with other graphs in Lumira. I wanted to explore Brands of Cars that are Popular in Ecuador. So I decided to do the following Word Graph to see which brands are popular.

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Chevrolet is clearly the most popular Brand with 35% market share.  The second and third most popular brands are Toyota and Suzuki with 8.5% and 8.1%. This is a big difference. However I did filter the “Other” brands because it was not helpful to identify the most popular brands.

5.) I also wanted to look at The Most Popular Brand per Type of Vehicle (Percentage). Therefore I did the following graph:

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This graph shows me that for the type of vehicles: automobile, truck, and jeep, Chevrolet has the highest percentage of market share.  However, for Motorcycle, the most popular brand is Suzuki. And for big trucks, Mazda is the most popular brand with 26% compared to Chevrolet with 19%.

5.) Now that I know which is the most popular brand in the market I also wanted to know The Year of the Vehicles.  This can help me get insight if people purchase mostly new vehicles or used vehicles.

In this radial graph I could see that most of the vehicles people own are from before 2001, 35% to be exact. Only about 14% own vehicles from 2011 and 2012.

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So from this investigation I was able to get answers to the following questions:

How many of each type of vehicle are there in Ecuador?

Where is the highest density of vehicles in Ecuador? Lowest Density?

What type of vehicles people purchase per region?

What is the most popular brand in Ecuador?

What is the most popular brand per type of vehicle?

From what year are most cars?

This type of insightcan be useful for the automobile industry in Ecuador to see the brands and types of vehicles people prefer per region in the year 2011. I will try to find the same data set from 2012 and 2013 to start forming time series and implement predictive analytics for the transportation industry in 2014.

Any suggestions or questions about this investigation do not hesitate to send me a message!

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