[python #OAK-610358]: MetPy Monday No. 143 Questions

Hello! Thanks for reaching out.

There are a few ways to do this. One such could involve building off the MetPy 
Mondays example, and looping with decadal increments. Here's an approximate 
example:

  . . .

  import numpy as np
  from matplotlib import cm

  decades = np.arange(1960, 2020, 10)
  colors = cm.get_cmap('tab10', len(decades)).colors

  for year, color in zip(decades, colors):
      df_temp = df_hu[(datetime(year, 1, 1) <= df_hu['Time']) & (df_hu['Time'] 
< datetime(year+10, 1, 1))]

      <insert plotting code from video with our new df_temp, now specify 
color=color>

  . . .

but there are also potentially other clever Pandas ways to accomplish this 
task, including using df.query and df.groupby. Look into these! Either way, 
play around with this, and I hope this at least points you in the right 
direction. If you have any trouble implementing this, don't hesitate to reach 
out with further questions.


All the best,

Drew


> I was learning the material in the videos #142 and # 143, and I had a 
> additional question. What would be the modification to the datetime function 
> if I wanted to keep the original line :
> df_hu = df_hu [df_hu [“Time”]>datetime(2020-##,1,1)]
> but I also wanted to separate this prescribed increment by decades within the 
> selection and color code them.



Ticket Details
===================
Ticket ID: OAK-610358
Department: Support Python
Priority: Low
Status: Closed
===================
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