[FEA] Implement .describe() for DataFrameGroupBy

[skirui-source]

This PR implements functionality to generate summary statistics for Dataframe.groupby() operation
via .describe() method, similar to Pandas.

>>> import pandas as pd
>>> pdf = pd.DataFrame({"Speed": [380.0, 370.0, 24.0, 26.0], "Score": [50, 30, 90, 80]})
>>> pdf
   Speed  Score
0  380.0     50
1  370.0     30
2   24.0     90
3   26.0     80
>>> pdf.groupby('Score').describe()
                                                    Speed                                              
      count   mean std    min    25%    50%    75%    max
Score                                                    
30      1.0  370.0 NaN  370.0  370.0  370.0  370.0  370.0
50      1.0  380.0 NaN  380.0  380.0  380.0  380.0  380.0
80      1.0   26.0 NaN   26.0   26.0   26.0   26.0   26.0
90      1.0   24.0 NaN   24.0   24.0   24.0   24.0   24.0


>>> import cudf
>>> gdf = cudf.from_pandas(pdf)
>>> gdf.groupby('Score').describe()
       count   mean   std    min    25%    50%    75%    max
Score                                                       
30         1  370.0  <NA>  370.0  370.0  370.0  370.0  370.0
50         1  380.0  <NA>  380.0  380.0  380.0  380.0  380.0
80         1   26.0  <NA>   26.0   26.0   26.0   26.0   26.0
90         1   24.0  <NA>   24.0   24.0   24.0   24.0   24.0

Fixes: #7990

[codecov]

Codecov Report

❗ No coverage uploaded for pull request base (branch-21.08@7231e3b). Click here to learn what that means.
The diff coverage is n/a.

❗ Current head 9eb815b differs from pull request most recent head 571ad90. Consider uploading reports for the commit 571ad90 to get more accurate results

@@               Coverage Diff               @@
##             branch-21.08    #8179   +/-   ##
===============================================
  Coverage                ?   82.84%           
===============================================
  Files                   ?      109           
  Lines                   ?    17913           
  Branches                ?        0           
===============================================
  Hits                    ?    14840           
  Misses                  ?     3073           
  Partials                ?        0           

---

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 7231e3b...571ad90. Read the comment docs.

[galipremsagar]

Can we add some tests for this?

[cwharris]

I have concerns regarding the use (and implementation) of assert_groupby_results_equal.

[shwina]

LGTM!

[shwina]

@gpucibot merge

[skirui-source]

re-run tests