Update README.md

README.md

@@ -14,7 +14,7 @@ Dataset Website: https://cainiaotechai.github.io/LaDe-website/
 Code Link:https://github.com/wenhaomin/LaDe  
 Paper Link: https://arxiv.org/abs/2306.10675  
 
-# 1 About Dataset
+# 1. About Dataset
 **LaDe** is a  publicly available last-mile delivery dataset with  millions of packages from industry. 
 It has three unique characteristics:  (1) Large-scale. It involves 10,677k packages of 21k couriers over 6 months of real-world operation. 
 (2) Comprehensive information, it offers original package information, such as its location and time requirements, as well as task-event information, which records when and where the courier is while events such as task-accept and task-finish events happen. 
@@ -23,7 +23,7 @@ It has three unique characteristics:  (1) Large-scale. It involves 10,677k packa
 
 
 
-# 2 Download
+# 2. Download
 LaDe is composed of two subdatasets: i) [LaDe-D](https://huggingface.co/datasets/Cainiao-AI/LaDe-D), which comes from the package delivery scenario.
 ii) [LaDe-P](https://huggingface.co/datasets/Cainiao-AI/LaDe-P), which comes from the package pickup scenario. To facilitate the utilization of the dataset, each sub-dataset is presented in CSV format.
 
@@ -38,10 +38,25 @@ The structure of "./data/raw/" should be like:
         * pickup_sh.csv  
         * ...
     * road-network  
-        * roads.csv  
+        * roads.csv
+    * data_with_trajectory_20s
+        * courier_detailed_trajectory_20s.pkl.xz
 ```
 
 road-network/roads.csv records the road network of the five cities.
+data_with_trajectory_20s/* records the trajectory of courier every 20 seconds.
+```python
+import pandas as pd
+>>> import pandas as pd
+>>> df = pd.read_pickle("courier_detailed_trajectory_20s.pkl.xz")
+>>> df.head(5)
+    ds                        postman_id        gps_time           lat           lng
+0  321  106f5ac22cfd1574b196d16fed62f90d  03-21 07:31:58  3.953700e+06  3.053400e+06
+1  321  106f5ac22cfd1574b196d16fed62f90d  03-21 07:32:18  3.953700e+06  3.053398e+06
+2  321  106f5ac22cfd1574b196d16fed62f90d  03-21 07:32:41  3.953700e+06  3.053398e+06
+3  321  106f5ac22cfd1574b196d16fed62f90d  03-21 07:55:51  3.953700e+06  3.053398e+06
+4  321  106f5ac22cfd1574b196d16fed62f90d  03-21 08:31:42  3.953929e+06  3.052367e+06
+```
 
 Each sub-dataset (delivery, pickup) contains 5 CSV files, with each representing the data from a specific city,  the detail of each city can be find in the following table.
 
@@ -55,7 +70,7 @@ Each sub-dataset (delivery, pickup) contains 5 CSV files, with each representing
 | Yantai     | A small city in China, with a small number of orders every day.                               |
 
 
-# 3 Description
+# 3. Description
 Below is the detailed field of each sub-dataset.
 ## 3.1 LaDe-P
 | Data field                 | Description                                  | Unit/format  |
@@ -107,7 +122,7 @@ Below is the detailed field of each sub-dataset.
 | ds                    | The date of the package delivery      | Date          |
 
 
-# 4 Leaderboard
+# 4. Leaderboard
 Blow shows the performance of different methods in Shanghai.
 ## 4.1 Route Prediction
 
@@ -151,7 +166,7 @@ Experimental results of route prediction. We use bold and underlined fonts to de
 
 
 
-# 5 Citation
+# 5. Citation
 If you find this helpful, please cite our paper:
 
 ```shell