我有一个数据集,其中包括每周跑步活动的次数,我想汇总每周的距离和运动时间之和。
数据如下:
[
{
"week_number": 20,
"distance": 16510.7,
"moving_time": 4822
},
{
"week_number": 20,
"distance": 10005.6,
"moving_time": 3015
},
{
"week_number": 19,
"distance": 13746.5,
"moving_time": 4058
},
{
"week_number": 19,
"distance": 13391.8,
"moving_time": 4137
},
{
"week_number": 18,
"distance": 14996.3,
"moving_time": 4713
},
{
"week_number": 18,
"distance": 10070.4,
"moving_time": 3100
}
]
我想把它转换成下面的结构,而不使用库:
[
{
"week_number": 20,
"total_distance": 26516.3,
"Total_moving_time": 7073
},
{
"week_number": 19,
"total_distance": 30070.4,
"Total_moving_time": 7100
},
{
"week_number": 18,
"total_distance": 20070.4,
"Total_moving_time": 6100
}
]
我得到的最接近的是下面,使用嵌套循环,但它不适合在前端访问:
{
"20":
{"distance":26515,"moving_time":7837},
"19":
{"distance":58594,"moving_time":18719},
"18":
{"distance":41346,"moving_time":12796}
}
关于使用Pandas的StackOverflow有很多建议,但我想学习在没有库的情况下使用它。
任何帮助都很感激。
2条答案
按热度按时间eeq64g8w1#
j2datikz2#
1.创建字典存储和
2.迭代数据并计算总和
3.更新周距离总和
4.更新该周的移动时间总和
5.打印distance_sums.items()中week_number,distance_sum的合计金额: