# Analysis and Prediction of Carsharing Demand Based on Data Mining Methods
## 2 Data and Data Preparation
### Statistic Description
#### 2.2.2 Analysis of the Characteristics of Space-Time Demand  
This study analyzes the demand characteristics of carsharing operators on the basis of user order data. It explores the evolution characteristics of the number of pick-up vehicles in different time and space scales. It also explores the distribution characteristic of imbalance demand in time and space.  
1. Characteristic of Time Demand  
A carsharing operating system will have different demand at different times. In this study, one day is divided into 24 periods in hours. The number of picked-up and returned vehicles in each period of the weekday and weekend is counted. The number of imbalanced vehicles is also counted. As shown in Figures 3 and 4, the number of picked-up vehicles is the number borrowed by users at each station, and the number of vehicles returned is the total number of vehicles returned by users at each station. The imbalance is the difference in the number of vehicles picked up and returned. On weekdays, the number of picked-up vehicles is higher in the morning and evening peak hours. The return time is concentrated after 17:00. The imbalance is serious in the morning peak of the working day. During weekends, no obvious peak of picked-up vehicles in the morning and evening occurs. The number of returned vehicles is concentrated in the afternoon and evening. During weekends, the imbalance of vehicles is serious between 11:00 and 14:00.  
Figure 3: Number of vehicles picked -up and returned in different periods on weekdays.  
Figure 2: User’s week travel characteristics.  
The imbalance in Figures 3 and 4 is the overall imbalance after the system is superimposed. As a result of the relationship demand, each station will overlap positively and negatively to reduce the imbalance. This condition can not fully reflect the overall imbalance of the system. As shown in Figure 5, the absolute value of imbalance demand of each station is superimposed, thereby showing the accumulated imbalance demand of stations in different periods of weekdays and weekends. Moreover, an obvious peak imbalance is observed in the morning and evening of working days. On a weekday, the imbalance is relatively stable between 7:00 and 24:00. The peak trend is not obvious compared with that on weekdays.  
2. Characteristic of Space Demand  
The number of vehicles picked up from the station is shown in Figure 6, while the number of vehicles returned to the station is shown in Figure 7. The bubble in the figure represents the station. Obvious differences are found in bubble distribution density. In places with dense stations, the bubbles are relatively large; that is, the number of vehicles picked up and returned is relatively large, which also reflects the rationality of the operator's station layout from the side. However, where the stations are sparse, the bubbles are smaller; that is, fewer vehicles are picked up and returned.  
Figure 4: Number of vehicles picked up and returned in different periods on weekends.  
Figure 5: Cumulative imbalance of stations in each period.