“Data”:[ ["Trip ID", 0.7821924653197189], ["Duration (days)", 0.1999873285697812], ["Traveler gender",0.017820206110499975]], [["2022年",31.954545454545453], [ "2023年",33.982142857142854 ]], [["2022年", 86.68181818181819], ["2023年", 61.785714285714285]], [["2022年", 7.886363636363637], ["2023年", 7.428571428571429]], [["Female", 23, 30], ["Male", 21, 26]]
“Question”: 2022年 2023年 Traveler age 根因分析
“insight”: [“2023年的Trip ID平均值比2022年减少了40.29%”], ["2023年的Traveler age比2022年平均值增加了2.03(5.97%)。"], [“2023年的Duration (days)平均值比2022年减少了6.16%”], [“各Traveler gender的数量平均值减少了-6.，数量相差最多的是Female，共7个”]
Above info is all from a [bar chart]If you are a data scientist, what insight do you get according to the info provided above
 Write your response with exactly 5 paragraphs, separated with the markdown divider: ***.
user