I get such table via following query:
df_netflix.groupby(by=['year_added','quarter_added'])['quarter_added'].count()
year_added quarter_added
2008 Q1 2
2009 Q4 2
2010 Q4 1
2011 Q3 1
Q4 12
2012 Q1 1
Q4 2
2013 Q1 1
Q3 3
Q4 7
2014 Q1 4
Q2 3
Q3 3
Q4 15
2015 Q1 10
Q2 12
Q3 17
Q4 49
2016 Q1 77
Q2 41
Q3 118
Q4 207
2017 Q1 296
Q2 190
Q3 314
Q4 425
2018 Q1 393
Q2 196
Q3 453
Q4 643
2019 Q1 500
Q2 346
Q3 450
Q4 857
2020 Q1 497
Q2 355
Q3 478
Q4 679
2021 Q1 117
Would you suggest any idea how to select quartal for each year where its quantity is min or max. For the instance above:
year_added quarter_min
2008 Q1
2009 Q4
2010 Q4
2011 Q3
2012 Q1
2013 Q1
2014 Q2
2015 Q1
2016 Q2
2017 Q2
2018 Q2
2019 Q2
2020 Q2
2021 Q1
The scrape of the original table looks like
| year_added | day_added | month_added | quarter_added | num_of_week | |
|---|---|---|---|---|---|
| 0 | 2020 | 14 | August | Q3 | 2 |
| 1 | 2016 | 23 | December | Q4 | 4 |
| 2 | 2018 | 20 | December | Q4 | 3 |
| 3 | 2017 | 16 | November | Q4 | 3 |
| 4 | 2020 | 1 | January | Q1 | 1 |