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How to implement SQL Groupby in RAPIDS
I'm seeking to translate an SQL query to use RAPIDS. Consider the simplified query below:
(SELECT min(a), max(b), c
FROM T
GROUP BY c) AS result
I have validated the code below, but is this the optimal solution? Is sorting on the group key necessary? Is there a cleaner / more idiomatic way to write it?
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'c':T.c}).groupby('c').min().sort_values(by='c')
df['max_b'] = gdf({'b':T.b, 'c':T.c}).groupby('c').max().sort_values(by='c').max_b
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
python rapids
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
add a comment |
I'm seeking to translate an SQL query to use RAPIDS. Consider the simplified query below:
(SELECT min(a), max(b), c
FROM T
GROUP BY c) AS result
I have validated the code below, but is this the optimal solution? Is sorting on the group key necessary? Is there a cleaner / more idiomatic way to write it?
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'c':T.c}).groupby('c').min().sort_values(by='c')
df['max_b'] = gdf({'b':T.b, 'c':T.c}).groupby('c').max().sort_values(by='c').max_b
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
python rapids
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
add a comment |
I'm seeking to translate an SQL query to use RAPIDS. Consider the simplified query below:
(SELECT min(a), max(b), c
FROM T
GROUP BY c) AS result
I have validated the code below, but is this the optimal solution? Is sorting on the group key necessary? Is there a cleaner / more idiomatic way to write it?
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'c':T.c}).groupby('c').min().sort_values(by='c')
df['max_b'] = gdf({'b':T.b, 'c':T.c}).groupby('c').max().sort_values(by='c').max_b
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
python rapids
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
I'm seeking to translate an SQL query to use RAPIDS. Consider the simplified query below:
(SELECT min(a), max(b), c
FROM T
GROUP BY c) AS result
I have validated the code below, but is this the optimal solution? Is sorting on the group key necessary? Is there a cleaner / more idiomatic way to write it?
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'c':T.c}).groupby('c').min().sort_values(by='c')
df['max_b'] = gdf({'b':T.b, 'c':T.c}).groupby('c').max().sort_values(by='c').max_b
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
python rapids
python rapids
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
edited Nov 20 '18 at 16:59
Thomas Ryan Stovall
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
asked Nov 20 '18 at 16:49
Thomas Ryan StovallThomas Ryan Stovall
405
405
add a comment |
add a comment |
1 Answer
1
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votes
You can rewrite your aggregation using the .agg function to make it more straightforward:
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'b': T.b, 'c':T.c}).groupby('c').agg({'a': 'min', 'b': 'max'})
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You can rewrite your aggregation using the .agg function to make it more straightforward:
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'b': T.b, 'c':T.c}).groupby('c').agg({'a': 'min', 'b': 'max'})
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
add a comment |
You can rewrite your aggregation using the .agg function to make it more straightforward:
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'b': T.b, 'c':T.c}).groupby('c').agg({'a': 'min', 'b': 'max'})
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
add a comment |
You can rewrite your aggregation using the .agg function to make it more straightforward:
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'b': T.b, 'c':T.c}).groupby('c').agg({'a': 'min', 'b': 'max'})
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
You can rewrite your aggregation using the .agg function to make it more straightforward:
from pygdf import DataFrame as gdf
T = gdf(...)
df = gdf({'a':T.a, 'b': T.b, 'c':T.c}).groupby('c').agg({'a': 'min', 'b': 'max'})
result = gdf({'a': df.min_a, 'b': df.max_b, 'c':df.c})
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
answered Nov 23 '18 at 20:35
Keith KrausKeith Kraus
361
361
add a comment |
add a comment |
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