[pandas]How to liner fit time series data and get linear fit equation and r square

[Sri]

Hi,
I have below pandas dataframe:

df:
      Time_golden          Golden    is_golden
0   2019 -03-20 10:24:30    98.6     golden
1   2019 -03-20 11:10:30    97.0     golden
2   2019 -03-20 13:13:30    96.0     golden
3   2019 -03-21 13:43:16    95.0     golden
4   2019 -03-23 10:37:11    94.6     golden
5   2019 -03-23 18:43:19    93.0     golden
6   2019 -03-24 22:19:43    92.0     golden
7   2019 -03-25 09:23:45    90.0     golden
8   2019 -03-26 11:42:51    89.0     golden
9   2019 -03-27 20:32:51    87.3     golden
10  2019 -03-27 23:42:51    86.0     golden
11  2019 -03-28 00:52:23    84.0     golden
12  2019 -03-28 03:40:40    82.3     golden

I want to linearly fit and get linear fit equation and r-square. I use below code but it gives an error

xg=df['Time_golden']
yg=df['Golden']
plt.scatter(xg,yg)

ValueError: First argument must be a sequence

Kindly help how to d this,

[snippsat]

Here a test.
So i don't get your error,you may need to update pandas and matplotlib.

[Sri]

Thanks, and how to add trend line and get equation and Rsquare.

[snippsat]

Thanks, and how to add trend line and get equation and Rsquare.

Give it a shot and post back code,also search for those method,i would also need to search for those task.

[scidam]

Note, you measurements are taken irregularly in time; first three seems to belong the same day, March, 20, but others are distributed over a week (until March, 28). It is likely, that dates were not recognized properly in the previous posts; Look at the following solution.

[Sri]

Thanks,