我的数据看起来如下,但我也可以控制它的格式.基本上,我想使用带有Numpy或Pandas的Python来插入数据集,以实现逐秒插值数据,从而使分辨率更高.
因此,我想在保持原始值的同时,在我当前拥有的每个实际值之间进行线性插值并生成新值.
我如何用Pandas或Numpy来实现这一目标？
举个例子,我有这种类型的数据:
TIME ECI_X ECI_Y ECI_Z
2013-12-07 00:00:00, -7346664.77912, -13323447.6311, 21734849.5263,@
2013-12-07 00:01:00, -7245621.40363, -13377562.35, 21735850.3527,@
2013-12-07 00:01:30, -7142326.20854, -13432541.9267, 21736462.4521,@
2013-12-07 00:02:00, -7038893.48454, -13487262.8599, 21736650.3293,@
2013-12-07 00:02:30, -6935325.24526, -13541724.0946, 21736413.9937,@
2013-12-07 00:03:00, -6833738.23865, -13594806.9333, 21735778.2218,@
2013-12-07 00:03:30, -6729905.37597, -13648746.6281, 21734705.6406,@
2013-12-07 00:04:00, -6625943.01291, -13702423.5112, 21733208.9233,@
2013-12-07 00:04:30, -6521853.17291, -13755836.5481, 21731288.1125,@
2013-12-07 00:05:00, -6419753.85176, -13807871.3011, 21729016.1386,@
2013-12-07 00:05:30, -6315415.32918, -13860754.6497, 21726259.4135,@
2013-12-07 00:06:00, -6210955.33186, -13913371.1187, 21723078.7695,@
...
而且我希望它能够排在第二位 - 即
2013-12-07 00:00:00, -7346664.77912, -13323447.6311, 21734849.5263,@
2013-12-07 00:00:01, -7346665.10000, …