A visual Analysis for PyBer a Python based rideshare company
I began doing data analysis for a Python based rideshare company in San Francisco. We have started by using Pandas, MatPlotLib, and Jupyter Notebook to create visualizations that tell compelling stories about the data.
I am working on a number of visualizations that show things such as the relationship between a variety of different things. Some of these visualizations include the relationships between the type of cities and the number of drivers and riders, the percentage of total shares, drivers and riders by type of city. The purpose of the analysis is to help PyBer reach a wider variety of customers as well as make their service more affordable in different city types.
Upon completion of the analysis, we can see a variety of different outcomes. The main two being that there are more rides overall in urban areas, over suburban or rural areas, but the rural areas tend to have longer and thus more expensive rides per a ride than either the suburban or urban areas.
As we can see in the above image there tends to be more rides in the urban areas than in either the suburban or rural areas, and more rides in the suburban than in the rural areas. The opposite is true however with regards to the length of the rides. The rides are longest in the rural, second longest in suburban and the shortest in the urban areas.
The size of the dot in the graph indicates the number of drivers. By this we can see that urban areas have the most drivers followed by the suburban and finally the rural areas have the least number of drivers.
As indicated above the urban areas have the most rides, followed by suburban and the rural areas have least number of rides. We can see here that also the urban has the greatest variation in the number of rides and even contains an outlier. The suburban also has greater variation in the number of riders than the rural which is relatively consistent.
The urban areas have shortest rides and lowest fares, while the suburban rides are a bit longer, and the rural has the longest rides out of any area. Interestingly, there is also more variation in the rural rides. It seems that some people go very far in their rides while the riders in urban areas go relatively similar distances.
The urban areas tend to have the most drivers, followed by suburban, and finally the rural areas which have the least number of drivers. It is also interesting to note that there is a much greater amount of variation in the number of drivers in the urban areas while the rural has a more consistent number of drivers.
The vast majority of the fares, over 62%, come from urban areas. Suburban areas also constitute over 30%, while rural areas make up only around 7% of the overall fares.
The vast majority of the rides, over 68%, come from urban areas. Suburban areas also constitute over 26%, while rural areas make up only around 5% of the overall rides.
Almost 87% of the drivers work in urban areas, and 12% work in suburban areas, while less than 1% of drivers work in rural areas.
We can see the same trends in the graph above. Most of the fares occur in urban areas, followed by suburban and finally rural.
We have seen in detail the summary of our analysis of the rider, fare and driver trends. We would like to add in a few recommendations for the future of the business.
The first recommendation would be to focus any expansion of the business first and foremost on urban areas. Urban areas are currently the areas that are bringing in by far the most money making about $1000 a week more than suburban areas and around $2000 a week more than rural areas. The primary focus of the business should be to move into as many urban areas as possible prior to expanding to other areas.
The second focus of the business should be to expand into suburban areas as they make about $1000 dollars a week more than rural areas.
Urban areas are bringing in the most amount of money because those areas have the most amount of rides. The rides in these areas also tend to be shorter meaning that these areas have a great deal more rides than suburban or rural areas.
Additionally, there is a greater number of variation in the amount of drivers that are needed. This means that it would be wise to have a large number of drivers ready to go in these areas. There are often events in urban areas where a large number of people need transportation and it may be good to research and prepare for those types of events.
There are a good steady amount of users of the service which is of course a great thing, but there has not been a great increase in the number of users over four months. It may be helpful to invest a bit into marketing and advertising to grow the overall user base so that the number of users in the areas where the service is already being used continue to increase over time.