In Python, is there any ways to see the serial numbers behind pandas timestamp? For example, given in timestamp,
2020.4.28
2020.4.29
2020.4.30
I want to see the associated serial numbers in day frequency, some similar ideas to the Excel serial numbers for dates.
Or instead, is there any alternative way to see the serial numbers for dates without using pandas timestamp?
I need to find this to compare the outputs of parameter estimation between Python/Excel/Matlab.
(Below, I edited my post to clarify the question. 02.05.2020)
For example in the code:
# Input parameters
a0B=0.1
a1B=0.2
a2B=0.3
# Example equation
B0=np.exp(a0B+a1B*np.cos(2*np.pi*(time/365)+a2B))
I'm talking about the input time here. I want to use/display serial numbers corresponding to dates in Python directly, without using the format of timestamp: YYYY/MM/DD 00:00. If I were using Excel or Matlab, the input serial numbers are:
# For the dates
2020.4.28
2020.4.29
2020.4.30
#Excel serial numbers are
43949
43950
43951
#Matlab serial numbers are
737909
737910
737911
respectively. Is there any equivalent expression for date serials in Python? Any help would be highly appreciated!
P.S. I know the example code is not quite the right way to do the calculation. But please stick on the main point...!
