taxi_analysis | It so happened that in my sample of trips , Moscow

taxi_analysis is a Python library. taxi_analysis has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

It so happened that in my sample of trips, Moscow and Vladimir are the most frequent cities, so the analysis was carried out for them. TaxiAnalysis has the ability to take them into account at the same time, but I think that this should not be done, since it will hardly be possible to come to constructive conclusions based on such analysis. For the selected cities, we will analyze the normalized dependence of the total ride cost on the route distance. Let's try to approximate the specified dependence by polynomials of the 1-st, 2-nd and 3-rd degree. It can be seen that the RMSE between the fitted curves and the original sample in the linear case approximately does not differ from the other two. So we can assume a linear relationship between the total ride cost and the route distance. The ratio of these quantities will be called RRC (relative ride cost) and actively used in further analysis. Since in the history of trips Economy class is significantly more than the rest (Comfort, Comfort+ and Business), only it was considered. It is important to note that both relative and absolute cost of a trip change over time due to inflation. In TaxiAnalysis, inflation was taken into account as a piecewise linear function, constant within every year. For example, it was considered that in 2018 inflation was equal to 5%, in 2019 - 6%, etc. The information about inflation changes was taken from here. RRC for the entire time was calculated in money at the time of April 2023 and was named RRC_i (RRC inflated). That is, if in April 2023 the cost of a trip was 100 rubles, then the cost of a trip in April 2018, initially also equal to 100 rubles, increased due to adjustments for inflation according to the specified piecewise linear function. As a result, the farther the cost of trips was from April 2023, the more it grew when inflation was taken into account. These adjustments make it possible to exclude the inflation factor when interpreting the results. Note that the approximation used is rough. In particular, inflation could be taken into account by months, not years, and not within the framework of the average for various industries, but specific to taxis. I think that the refinement of the inflation model will be appropriate with a further increase in the sample and the complexity of the analysis.