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Review fixes #59

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merged 4 commits into from
Mar 23, 2020
Merged

Review fixes #59

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7727804
Update authors in pyproject.toml
vanandsh Mar 23, 2020
dd8dc28
Add output for examples
vanandsh Mar 23, 2020
95a0355
Fix docstring
vanandsh Mar 23, 2020
cc00014
Round values
vanandsh Mar 23, 2020
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7 changes: 6 additions & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,12 @@
name = "pysketball"
version = "2.0.0"
description = "This is a Python package that scraps tabular ESPN NBA data from https://www.espn.com/nba/stats/player/_/season/2019/seasontype/2 and processes it"
authors = ["Andres Pitta <[email protected]>"]
authors = [
"Andres Pitta <[email protected]>",
"Anand Shankar, <[email protected]>",
"Carlina Kim, <[email protected]>",
"Kenneth Foo, <[email protected]>"
]
license = "MIT"
readme = "README.md"
homepage = "https://github.com/UBC-MDS/pysketball"
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3 changes: 2 additions & 1 deletion pysketball/nba_scraper.py
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Expand Up @@ -19,7 +19,8 @@ def nba_scraper(season_year, season_type="regular", csv_path=None):
season_year : int
An integer input of the year of interest for the NBA season.
season_type : string
A string input of the NBA season type (either "regular" or playoff).
A string input of the NBA season type (either "regular" or
"postseason").
Default is "regular".
csv_path_name : string
A string input stating the path to store the scraped csv file and
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23 changes: 22 additions & 1 deletion pysketball/nba_team_stats.py
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Expand Up @@ -42,6 +42,27 @@ def nba_team_stats(nba_data, stats_filter=None, teams_filter=None,
stats_filter = ['GP', '3PM', 'FT%'],
teams_filter = ['UTAH', 'PHX', 'DET'],
positions_filter = ['C', 'PG'])
{'GP': count mean std min 25% 50% 75% max
Team POS
DET C 2.0 73.5 7.778175 68.0 70.75 73.5 76.25 79.0
PG 1.0 82.0 NaN 82.0 82.00 82.0 82.00 82.0
PHX C 1.0 71.0 NaN 71.0 71.00 71.0 71.00 71.0
UTAH C 1.0 81.0 NaN 81.0 81.00 81.0 81.00 81.0
PG 1.0 68.0 NaN 68.0 68.00 68.0 68.00 68.0,
'3PM': count mean std min 25% 50% 75% max
Team POS
DET C 2.0 0.05 0.070711 0.0 0.025 0.05 0.075 0.1
PG 1.0 2.10 NaN 2.1 2.100 2.10 2.100 2.1
PHX C 1.0 0.00 NaN 0.0 0.000 0.00 0.000 0.0
UTAH C 1.0 0.00 NaN 0.0 0.000 0.00 0.000 0.0
PG 1.0 1.20 NaN 1.2 1.200 1.20 1.200 1.2,
'FT%': count mean std min 25% 50% 75% max
Team POS
DET C 2.0 68.6 13.57645 59.0 63.8 68.6 73.4 78.2
PG 1.0 86.4 NaN 86.4 86.4 86.4 86.4 86.4
PHX C 1.0 74.6 NaN 74.6 74.6 74.6 74.6 74.6
UTAH C 1.0 63.6 NaN 63.6 63.6 63.6 63.6 63.6
PG 1.0 85.5 NaN 85.5 85.5 85.5 85.5 85.5}
"""
# Check if nba_data is a DataFrame
if not isinstance(nba_data, pd.DataFrame):
Expand Down Expand Up @@ -109,6 +130,6 @@ def nba_team_stats(nba_data, stats_filter=None, teams_filter=None,
stats_filter = [stat for stat in stats_filter if stat not in (
'NAME', 'TEAM', 'POS')]
for stat in stats_filter:
stats[stat] = nba_data.groupby(group_by).describe()[stat]
stats[stat] = nba_data.groupby(group_by).describe().round(3)[stat]

return stats