Merge pull request #8 from nprasad2077/dev

Dev

nba_data/management/commands/delete_player_totals_data_and_id.py

@@ -0,0 +1,17 @@
+from django.core.management.base import BaseCommand
+from nba_data.models import PlayerTotalsData
+from django.db import connection
+
+class Command(BaseCommand):
+    # Provides a description for use with the custom django management command (python manage.py help).
+    help = 'Delete all player TOTALS data and reset primary key sequence in DB' 
+    
+    def handle(self, *args, **options):
+        # Delete all player data
+        PlayerTotalsData.objects.all().delete()
+        
+        # Reset the PK sequence
+        with connection.cursor() as cursor:
+            cursor.execute('ALTER SEQUENCE nba_data_playertotalsdata_id_seq RESTART WITH 1;')
+        
+        self.stdout.write(self.style.SUCCESS('Successfully deleted all players in DB'))

nba_data/management/commands/remove_duplicates_playoff_advanced.py

@@ -0,0 +1,27 @@
+from django.core.management.base import BaseCommand
+from nba_data.models import PlayerPlayoffAdvancedData
+
+
+class Command(BaseCommand):
+    help = 'Remove duplicate records for DAL and BOS in season 2010'
+
+    def handle(self, *args, **options):
+        season = 2010
+        teams = ['DAL', 'BOS']
+
+        for team in teams:
+            duplicates = PlayerPlayoffAdvancedData.objects.filter(season=season, team=team).order_by('player_name')
+
+            # Group records by name
+            players_grouped = {}
+            for duplicate in duplicates:
+                if duplicate.player_name not in players_grouped:
+                    players_grouped[duplicate.player_name] = []
+                players_grouped[duplicate.player_name].append(duplicate)
+
+            # Delete duplicates while keeping one record per player
+            for player_name, player_records in players_grouped.items():
+                if len(player_records) > 1:
+                    for player_record in player_records[1:]:
+                        player_record.delete()
+                        self.stdout.write(self.style.SUCCESS(f"Deleted duplicate {player_name} for {team} in season {season}"))

nba_data/migrations/0007_alter_playertotalsdata_ast_and_more.py

@@ -0,0 +1,128 @@
+# Generated by Django 4.2 on 2023-04-27 20:53
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('nba_data', '0006_playeradvanceddata_playertotalsdata'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='AST',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='BLK',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='DRB',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='ORB',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='PF',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='PTS',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='STL',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='TOV',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='TRB',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='effect_fg_percent',
+            field=models.DecimalField(decimal_places=3, max_digits=6, null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='field_attempts',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='field_goals',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='field_percent',
+            field=models.DecimalField(decimal_places=3, max_digits=6, null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='ft',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='ft_percent',
+            field=models.DecimalField(decimal_places=3, max_digits=6, null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='fta',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='minutes_played',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='three_attempts',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='three_fg',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='three_percent',
+            field=models.DecimalField(decimal_places=3, max_digits=6, null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='two_attempts',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='two_fg',
+            field=models.IntegerField(null=True),
+        ),
+        migrations.AlterField(
+            model_name='playertotalsdata',
+            name='two_percent',
+            field=models.DecimalField(decimal_places=3, max_digits=6, null=True),
+        ),
+    ]

nba_data/migrations/0008_playerplayofftotalsdata.py

@@ -0,0 +1,48 @@
+# Generated by Django 4.2 on 2023-05-01 18:00
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('nba_data', '0007_alter_playertotalsdata_ast_and_more'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='PlayerPlayoffTotalsData',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('player_name', models.CharField(max_length=255, null=True)),
+                ('age', models.IntegerField(null=True)),
+                ('games', models.IntegerField(null=True)),
+                ('games_started', models.IntegerField(null=True)),
+                ('minutes_played', models.IntegerField(null=True)),
+                ('field_goals', models.IntegerField(null=True)),
+                ('field_attempts', models.IntegerField(null=True)),
+                ('field_percent', models.DecimalField(decimal_places=3, max_digits=6, null=True)),
+                ('three_fg', models.IntegerField(null=True)),
+                ('three_attempts', models.IntegerField(null=True)),
+                ('three_percent', models.DecimalField(decimal_places=3, max_digits=6, null=True)),
+                ('two_fg', models.IntegerField(null=True)),
+                ('two_attempts', models.IntegerField(null=True)),
+                ('two_percent', models.DecimalField(decimal_places=3, max_digits=6, null=True)),
+                ('effect_fg_percent', models.DecimalField(decimal_places=3, max_digits=6, null=True)),
+                ('ft', models.IntegerField(null=True)),
+                ('fta', models.IntegerField(null=True)),
+                ('ft_percent', models.DecimalField(decimal_places=3, max_digits=6, null=True)),
+                ('ORB', models.IntegerField(null=True)),
+                ('DRB', models.IntegerField(null=True)),
+                ('TRB', models.IntegerField(null=True)),
+                ('AST', models.IntegerField(null=True)),
+                ('STL', models.IntegerField(null=True)),
+                ('BLK', models.IntegerField(null=True)),
+                ('TOV', models.IntegerField(null=True)),
+                ('PF', models.IntegerField(null=True)),
+                ('PTS', models.IntegerField(null=True)),
+                ('team', models.CharField(default='', max_length=30)),
+                ('season', models.IntegerField(null=True)),
+            ],
+        ),
+    ]

nba_data/migrations/0009_playerplayoffadvanceddata.py

@@ -0,0 +1,45 @@
+# Generated by Django 4.2 on 2023-05-01 21:14
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('nba_data', '0008_playerplayofftotalsdata'),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name='PlayerPlayoffAdvancedData',
+            fields=[
+                ('id', models.BigAutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
+                ('player_name', models.CharField(max_length=255, null=True)),
+                ('age', models.IntegerField(null=True)),
+                ('games', models.IntegerField(null=True)),
+                ('minutes_played', models.IntegerField(null=True)),
+                ('PER', models.DecimalField(decimal_places=1, max_digits=5, null=True)),
+                ('TS_percent', models.DecimalField(decimal_places=3, max_digits=5, null=True)),
+                ('three_p_attempt_rate', models.DecimalField(decimal_places=3, max_digits=5, null=True)),
+                ('ft_attempt_rate', models.DecimalField(decimal_places=3, max_digits=5, null=True)),
+                ('orb_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('drb_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('trb_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('ast_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('stl_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('blk_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('tov_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('usg_percent', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('ows', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('dws', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('ws', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('ws_per_48', models.DecimalField(decimal_places=3, max_digits=5, null=True)),
+                ('obpm', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('dbpm', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('bpm', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('vorp', models.DecimalField(decimal_places=2, max_digits=5, null=True)),
+                ('team', models.CharField(default='', max_length=30)),
+                ('season', models.IntegerField(null=True)),
+            ],
+        ),
+    ]

nba_data/migrations/0010_alter_playeradvanceddata_per_and_more.py

@@ -0,0 +1,23 @@
+# Generated by Django 4.2 on 2023-05-01 21:43
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('nba_data', '0009_playerplayoffadvanceddata'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='playeradvanceddata',
+            name='PER',
+            field=models.DecimalField(decimal_places=1, max_digits=6, null=True),
+        ),
+        migrations.AlterField(
+            model_name='playerplayoffadvanceddata',
+            name='PER',
+            field=models.DecimalField(decimal_places=1, max_digits=6, null=True),
+        ),
+    ]

nba_data/migrations/0011_alter_playerplayoffadvanceddata_bpm_and_more.py

@@ -0,0 +1,29 @@
+# Generated by Django 4.2 on 2023-05-01 21:58
+
+import django.core.validators
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+
+    dependencies = [
+        ('nba_data', '0010_alter_playeradvanceddata_per_and_more'),
+    ]
+
+    operations = [
+        migrations.AlterField(
+            model_name='playerplayoffadvanceddata',
+            name='bpm',
+            field=models.DecimalField(decimal_places=2, max_digits=5, null=True, validators=[django.core.validators.MinValueValidator(-100), django.core.validators.MaxValueValidator(100)]),
+        ),
+        migrations.AlterField(
+            model_name='playerplayoffadvanceddata',
+            name='dbpm',
+            field=models.DecimalField(decimal_places=2, max_digits=5, null=True, validators=[django.core.validators.MinValueValidator(-100), django.core.validators.MaxValueValidator(100)]),
+        ),
+        migrations.AlterField(
+            model_name='playerplayoffadvanceddata',
+            name='obpm',
+            field=models.DecimalField(decimal_places=2, max_digits=5, null=True, validators=[django.core.validators.MinValueValidator(-100), django.core.validators.MaxValueValidator(100)]),
+        ),
+    ]

nba_data/models.py

@@ -1,4 +1,5 @@
 from django.db import models
+from django.core.validators import MaxValueValidator, MinValueValidator
 
 # Create your models here.
 class PlayerData(models.Model):
@@ -40,29 +41,29 @@ class PlayerTotalsData(models.Model):
     age = models.IntegerField(null=True)
     games = models.IntegerField(null=True)
     games_started = models.IntegerField(null=True)
-    minutes_played = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    field_goals = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    field_attempts = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    field_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
-    three_fg = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    three_attempts = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    three_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
-    two_fg = models.DecimalField(max_digits=5, decimal_places=3, null=True)
-    two_attempts = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    two_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
-    effect_fg_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
-    ft = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    fta = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    ft_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
-    ORB= models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    DRB = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    TRB = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    AST = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    STL = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    BLK = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    TOV = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    PF = models.DecimalField(max_digits=5, decimal_places=2, null=True)
-    PTS = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    minutes_played = models.IntegerField(null=True)
+    field_goals = models.IntegerField(null=True)
+    field_attempts = models.IntegerField(null=True)
+    field_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    three_fg = models.IntegerField(null=True)
+    three_attempts = models.IntegerField(null=True)
+    three_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    two_fg = models.IntegerField(null=True)
+    two_attempts = models.IntegerField(null=True)
+    two_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    effect_fg_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    ft = models.IntegerField(null=True)
+    fta = models.IntegerField(null=True)
+    ft_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    ORB= models.IntegerField(null=True)
+    DRB = models.IntegerField(null=True)
+    TRB = models.IntegerField(null=True)
+    AST = models.IntegerField(null=True)
+    STL = models.IntegerField(null=True)
+    BLK = models.IntegerField(null=True)
+    TOV = models.IntegerField(null=True)
+    PF = models.IntegerField(null=True)
+    PTS = models.IntegerField(null=True)
     team = models.CharField(max_length=30, default='')
     season = models.IntegerField(null=True)
     
@@ -75,7 +76,7 @@ class PlayerAdvancedData(models.Model):
     age = models.IntegerField(null=True)
     games = models.IntegerField(null=True)
     minutes_played = models.IntegerField(null=True)
-    PER = models.DecimalField(max_digits=5, decimal_places=1, null=True)
+    PER = models.DecimalField(max_digits=6, decimal_places=1, null=True)
     TS_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
     three_p_attempt_rate = models.DecimalField(max_digits=5, decimal_places=3, null=True)
     ft_attempt_rate = models.DecimalField(max_digits=5, decimal_places=3, null=True)
@@ -101,6 +102,103 @@ class PlayerAdvancedData(models.Model):
     def __str__(self):
         return self.player_name
     
+
+class PlayerPlayoffTotalsData(models.Model):
+    player_name = models.CharField(max_length=255, null=True)
+    age = models.IntegerField(null=True)
+    games = models.IntegerField(null=True)
+    games_started = models.IntegerField(null=True)
+    minutes_played = models.IntegerField(null=True)
+    field_goals = models.IntegerField(null=True)
+    field_attempts = models.IntegerField(null=True)
+    field_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    three_fg = models.IntegerField(null=True)
+    three_attempts = models.IntegerField(null=True)
+    three_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    two_fg = models.IntegerField(null=True)
+    two_attempts = models.IntegerField(null=True)
+    two_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    effect_fg_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    ft = models.IntegerField(null=True)
+    fta = models.IntegerField(null=True)
+    ft_percent = models.DecimalField(max_digits=6, decimal_places=3, null=True)
+    ORB= models.IntegerField(null=True)
+    DRB = models.IntegerField(null=True)
+    TRB = models.IntegerField(null=True)
+    AST = models.IntegerField(null=True)
+    STL = models.IntegerField(null=True)
+    BLK = models.IntegerField(null=True)
+    TOV = models.IntegerField(null=True)
+    PF = models.IntegerField(null=True)
+    PTS = models.IntegerField(null=True)
+    team = models.CharField(max_length=30, default='')
+    season = models.IntegerField(null=True)
+    
+    def __str__(self):
+        return self.player_name
+
+
+class PlayerPlayoffAdvancedData(models.Model):
+    player_name = models.CharField(max_length=255, null=True)
+    age = models.IntegerField(null=True)
+    games = models.IntegerField(null=True)
+    minutes_played = models.IntegerField(null=True)
+    PER = models.DecimalField(max_digits=6, decimal_places=1, null=True)
+    TS_percent = models.DecimalField(max_digits=5, decimal_places=3, null=True)
+    three_p_attempt_rate = models.DecimalField(max_digits=5, decimal_places=3, null=True)
+    ft_attempt_rate = models.DecimalField(max_digits=5, decimal_places=3, null=True)
+    orb_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    drb_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    trb_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    ast_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    stl_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    blk_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    tov_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    usg_percent = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    ows = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    dws = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    ws = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    ws_per_48 = models.DecimalField(max_digits=5, decimal_places=3, null=True)
+    obpm = models.DecimalField(max_digits=5, decimal_places=2, null=True, validators=[MinValueValidator(-100), MaxValueValidator(100)])
+    dbpm = models.DecimalField(max_digits=5, decimal_places=2, null=True, validators=[MinValueValidator(-100), MaxValueValidator(100)])
+    bpm = models.DecimalField(max_digits=5, decimal_places=2, null=True, validators=[MinValueValidator(-100), MaxValueValidator(100)])
+    vorp = models.DecimalField(max_digits=5, decimal_places=2, null=True)
+    team = models.CharField(max_length=30, default='')
+    season = models.IntegerField(null=True)
+    
+    def cap_extreme_values(self):
+        min_value = -100
+        max_value = 100
+        
+        obpm = float(self.obpm)
+        if obpm < min_value:
+            obpm = min_value
+        elif obpm > max_value:
+            obpm = max_value
+        self.obpm = obpm
+
+        dbpm = float(self.dbpm)
+        if dbpm < min_value:
+            dbpm = min_value
+        elif dbpm > max_value:
+            dbpm = max_value
+        self.dbpm = dbpm
+
+        bpm = float(self.bpm)
+        if bpm < min_value:
+            bpm = min_value
+        elif bpm > max_value:
+            bpm = max_value
+        self.bpm = bpm
+
+
+    def save(self, *args, **kwargs):
+        self.cap_extreme_values()
+        super(PlayerPlayoffAdvancedData, self).save(*args, **kwargs)
+    
+    def __str__(self):
+        return self.player_name
+    
     
         
         

nba_data/nba_scraper_advanced.py

@@ -15,11 +15,10 @@ django.setup()
 
 from nba_data.models import PlayerAdvancedData
 
+# If season is 2014, then change CHO to CHA
 teams = ['HOU' ,'PHI', 'BOS', 'NYK', 'BRK', 'TOR', 'MEM', 'NOP', 'DAL', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHO']
 team_abbreviations = ['ATL', 'BOS', 'BRK', 'CHI', 'CHO', 'CLE', 'DAL', 'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR', 'UTA', 'WAS']
 
-# team = input('What team? ') 
-#  OMIT above. Will now only ask for season and iterate thru teams list.
 season = input('What season? ')
 
 for team in teams:
@@ -70,40 +69,39 @@ for team in teams:
     with open(json_output_path, 'w') as jsonfile:
         json.dump(data, jsonfile)
 
-    # # save data to database
-    # for row in data:
-    #     player_data = PlayerData(
-    #         name=row['Player'],
-    #         age=row['Age'],
-    #         games=row['G'],
-    #         games_started=row['GS'],
-    #         minutes_pg=row['MP'],
-    #         field_goals=row['FG'],
-    #         field_attempts=row['FGA'],
-    #         field_percent=row['FG%'],
-    #         three_fg=row['3P'],
-    #         three_attempts=row['3PA'],
-    #         three_percent=row['3P%'],
-    #         two_fg=row['2P'],
-    #         two_attempts=row['2PA'],
-    #         two_percent=row['2P%'],
-    #         effect_fg_percent=row['eFG%'],
-    #         ft=row['FT'],
-    #         fta=row['FTA'],
-    #         ft_percent=row['FT%'],
-    #         ORB=row['ORB'],
-    #         DRB=row['DRB'],
-    #         TRB=row['TRB'],
-    #         AST=row['AST'],
-    #         STL=row['STL'],
-    #         BLK=row['BLK'],
-    #         TOV=row['TOV'],
-    #         PF=row['PF'],
-    #         PTS=row['PTS'],
-    #         team=row['team'],
-    #         season=row['season'],
-    #     )
-    #     player_data.save()
+    # save data to database
+    for row in data:
+        player_data = PlayerAdvancedData(
+            player_name = row['Player'],
+            age = row['Age'],
+            games = row['G'],
+            minutes_played = row['MP'],
+            PER = row['PER'],
+            TS_percent = row['TS%'],
+            three_p_attempt_rate = row['3PAr'],
+            ft_attempt_rate = row['FTr'],
+            orb_percent = row['ORB%'],
+            drb_percent = row['DRB%'],
+            trb_percent = row['TRB%'],
+            ast_percent = row['AST%'],
+            stl_percent = row['STL%'],
+            blk_percent = row['BLK%'],
+            tov_percent = row['TOV%'],
+            usg_percent = row['USG%'],
+            ows = row['OWS'],
+            dws = row['DWS'],
+            ws = row['WS'],
+            ws_per_48 = row['WS/48'],
+            obpm = row['OBPM'],
+            dbpm = row['DBPM'],
+            bpm = row['BPM'],
+            vorp = row['VORP'],
+            team = row['team'],
+            season = row['season'],
+        )
+        player_data.save()
+
+print('success')
         
 
     

nba_data/nba_scraper_playoffs_advanced.py

@@ -0,0 +1,121 @@
+import os
+import sys
+import django
+import requests
+from bs4 import BeautifulSoup
+import csv
+import json
+import time
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nba_stats.settings')
+django.setup()
+
+from nba_data.models import PlayerPlayoffAdvancedData
+
+# Change CHO to CHA 2014 and prior.
+# Change NOP to NOH for 2013 and prior.
+# Change OKC to SEA for 2008 and prior.
+# Change NOH to NOK for 2007 and 2006
+# Change NOK to NOH for 2005 and prior.
+# Change NOH to CHH for 2002 and prior. NOLA did not have a team before 2003.
+# Change WAS to WSB for 1997 and prior.
+# Change BRK to NJN for 2012 and prior.
+# Change MEM to VAN for 2001 and prior.
+# Change LAC to SDC for 1984 and prior.
+
+
+teams = ['HOU' ,'PHI', 'BOS', 'NYK', 'NJN', 'TOR', 'MEM', 'NOH', 'DAL', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHA']
+
+teams2 = ['HOU' ,'PHI', 'NYK', 'NJN', 'TOR', 'MEM', 'NOH', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHA']
+
+team_abbreviations = ['ATL', 'BOS', 'BRK', 'CHI', 'CHO', 'CLE', 'DAL', 'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR', 'UTA', 'WAS']
+
+season = input('What season? ')
+
+for team in teams:
+    url_make = 'https://www.basketball-reference.com/teams/' + team + '/' + season + '.html'
+    response = requests.get(url_make)
+
+    soup = BeautifulSoup(response.text, "html.parser")
+    
+    table = soup.find("table", {"id": "playoffs_advanced"})
+
+    if table is None:
+        print(f"Table not found for team {team} and season {season}.")
+        # sys.exit(1)
+        continue
+
+    header_row = table.find("thead").find("tr")
+    rows = table.find("tbody").find_all("tr")
+
+
+    # Extract coloumn headers
+    headers = [col.text.strip() for col in header_row.find_all("th")][1:]
+    headers.extend(['team', 'season'])  # Add 'team' and 'season' fields to headers
+
+    # Extract rows as dictionaries
+    data = []
+    for row in rows:
+        cols = row.find_all("td")
+        cols = [col.text.strip() for col in cols]
+        row_dict = {header: (None if col == "" else col) for header, col in zip(headers, cols)}
+        row_dict['team'] = team
+        row_dict['season'] = season
+        data.append(row_dict)
+
+
+    # locate current directory
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    
+    # save as CSV file
+    csv_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_playoffs_advanced_output.csv')
+    with open(csv_output_path, "w", newline="") as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=headers)
+        writer.writeheader()
+        for row in data:
+            writer.writerow(row)
+
+    # Save as JSON
+    json_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_playoffs_advanced_output.json')
+    with open(json_output_path, 'w') as jsonfile:
+        json.dump(data, jsonfile)
+
+    # save data to database
+    for row in data:
+        player_data = PlayerPlayoffAdvancedData(
+            player_name = row['Player'],
+            age = row['Age'],
+            games = row['G'],
+            minutes_played = row['MP'],
+            PER = row['PER'],
+            TS_percent = row['TS%'],
+            three_p_attempt_rate = row['3PAr'],
+            ft_attempt_rate = row['FTr'],
+            orb_percent = row['ORB%'],
+            drb_percent = row['DRB%'],
+            trb_percent = row['TRB%'],
+            ast_percent = row['AST%'],
+            stl_percent = row['STL%'],
+            blk_percent = row['BLK%'],
+            tov_percent = row['TOV%'],
+            usg_percent = row['USG%'],
+            ows = row['OWS'],
+            dws = row['DWS'],
+            ws = row['WS'],
+            ws_per_48 = row['WS/48'],
+            obpm = row['OBPM'],
+            dbpm = row['DBPM'],
+            bpm = row['BPM'],
+            vorp = row['VORP'],
+            team = row['team'],
+            season = row['season'],
+        )
+        player_data.save()
+
+print('success')
+        
+
+    

nba_data/nba_scraper_playoffs_advanced_player.py

@@ -0,0 +1,127 @@
+import os
+import sys
+import django
+import requests
+from bs4 import BeautifulSoup
+import csv
+import json
+import time
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nba_stats.settings')
+django.setup()
+
+from nba_data.models import PlayerPlayoffAdvancedData
+
+# Change CHO to CHA 2014 and prior.
+# Change NOP to NOH for 2013 and prior.
+# Change OKC to SEA for 2008 and prior.
+# Change NOH to NOK for 2007 and 2006
+# Change NOK to NOH for 2005 and prior.
+# Change NOH to CHH for 2002 and prior. NOLA did not have a team before 2003.
+# Change WAS to WSB for 1997 and prior.
+# Change BRK to NJN for 2012 and prior.
+# Change MEM to VAN for 2001 and prior.
+# Change LAC to SDC for 1984 and prior.
+
+
+teams = ['HOU' ,'PHI', 'BOS', 'NYK', 'BRK', 'TOR', 'MEM', 'NOP', 'DAL', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHA']
+
+single_team = ['GSW']
+
+team_abbreviations = ['ATL', 'BOS', 'BRK', 'CHI', 'CHO', 'CLE', 'DAL', 'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR', 'UTA', 'WAS']
+
+# change player name here
+target_player_name = 'Nemanja Nedović'
+
+season = input('What season? ')
+
+
+
+for team in single_team:
+    url_make = 'https://www.basketball-reference.com/teams/' + team + '/' + season + '.html'
+    response = requests.get(url_make)
+
+    soup = BeautifulSoup(response.text, "html.parser")
+    
+    table = soup.find("table", {"id": "playoffs_advanced"})
+
+    if table is None:
+        print(f"Table not found for team {team} and season {season}.")
+        # sys.exit(1)
+        continue
+
+    header_row = table.find("thead").find("tr")
+    rows = table.find("tbody").find_all("tr")
+
+
+    # Extract coloumn headers
+    headers = [col.text.strip() for col in header_row.find_all("th")][1:]
+    headers.extend(['team', 'season'])  # Add 'team' and 'season' fields to headers
+
+    # Extract rows as dictionaries
+    data = []
+    for row in rows:
+        cols = row.find_all("td")
+        cols = [col.text.strip() for col in cols]
+        row_dict = {header: (None if col == "" else col) for header, col in zip(headers, cols)}
+        row_dict['team'] = team
+        row_dict['season'] = season
+        if row_dict['Player'] == target_player_name:
+            data.append(row_dict)
+
+
+    # locate current directory
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    
+    # save as CSV file
+    csv_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_playoffs_advanced_output.csv')
+    with open(csv_output_path, "w", newline="") as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=headers)
+        writer.writeheader()
+        for row in data:
+            writer.writerow(row)
+
+    # Save as JSON
+    json_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_playoffs_advanced_output.json')
+    with open(json_output_path, 'w') as jsonfile:
+        json.dump(data, jsonfile)
+
+    # save data to database
+    for row in data:
+        player_data = PlayerPlayoffAdvancedData(
+            player_name = row['Player'],
+            age = row['Age'],
+            games = row['G'],
+            minutes_played = row['MP'],
+            PER = row['PER'],
+            TS_percent = row['TS%'],
+            three_p_attempt_rate = row['3PAr'],
+            ft_attempt_rate = row['FTr'],
+            orb_percent = row['ORB%'],
+            drb_percent = row['DRB%'],
+            trb_percent = row['TRB%'],
+            ast_percent = row['AST%'],
+            stl_percent = row['STL%'],
+            blk_percent = row['BLK%'],
+            tov_percent = row['TOV%'],
+            usg_percent = row['USG%'],
+            ows = row['OWS'],
+            dws = row['DWS'],
+            ws = row['WS'],
+            ws_per_48 = row['WS/48'],
+            obpm = row['OBPM'],
+            dbpm = row['DBPM'],
+            bpm = row['BPM'],
+            vorp = row['VORP'],
+            team = row['team'],
+            season = row['season'],
+        )
+        player_data.save()
+
+print('success')
+        
+
+    

nba_data/nba_scraper_playoffs_totals.py

@@ -0,0 +1,122 @@
+import os
+import sys
+import django
+import requests
+from bs4 import BeautifulSoup
+import csv
+import json
+import time
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nba_stats.settings')
+django.setup()
+
+from nba_data.models import PlayerPlayoffTotalsData
+
+# Change CHO to CHA 2014 and prior.
+# Change NOP to NOH for 2013 and prior.
+# Change OKC to SEA for 2008 and prior.
+# Change NOH to NOK for 2007 and 2006
+# Change NOK to NOH for 2005 and prior.
+# Change NOH to CHH for 2002 and prior. NOLA did not have a team before 2003.
+# Change WAS to WSB for 1997 and prior.
+# Change BRK to NJN for 2012 and prior.
+# Change MEM to VAN for 2001 and prior.
+# Change LAC to SDC for 1984 and prior.
+
+
+teams = ['HOU' ,'PHI', 'BOS', 'NYK', 'NJN', 'TOR', 'MEM', 'NOH', 'DAL', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHA']
+
+team_abbreviations = ['ATL', 'BOS', 'BRK', 'CHI', 'CHO', 'CLE', 'DAL', 'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR', 'UTA', 'WAS']
+
+season = input('What season? ')
+
+for team in teams:
+    url_make = 'https://www.basketball-reference.com/teams/' + team + '/' + season + '.html'
+    response = requests.get(url_make)
+
+    soup = BeautifulSoup(response.text, "html.parser")
+    
+    table = soup.find("table", {"id": "playoffs_totals"})
+
+    if table is None:
+        print(f"Table not found for team {team} and season {season}.")
+        # sys.exit(1)
+        continue
+
+    header_row = table.find("thead").find("tr")
+    rows = table.find("tbody").find_all("tr")
+
+
+    # Extract coloumn headers
+    headers = [col.text.strip() for col in header_row.find_all("th")][1:]
+    headers.extend(['team', 'season'])  # Add 'team' and 'season' fields to headers
+
+    # Extract rows as dictionaries
+    data = []
+    for row in rows:
+        cols = row.find_all("td")
+        cols = [col.text.strip() for col in cols]
+        row_dict = {header: (None if col == "" else col) for header, col in zip(headers, cols)}
+        row_dict['team'] = team
+        row_dict['season'] = season
+        data.append(row_dict)
+
+
+    # locate current directory
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    
+    # save as CSV file
+    csv_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_playoffs_totals_output.csv')
+    with open(csv_output_path, "w", newline="") as csvfile:
+        writer = csv.DictWriter(csvfile, fieldnames=headers)
+        writer.writeheader()
+        for row in data:
+            writer.writerow(row)
+
+    # Save as JSON
+    json_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_playoffs_totals_output.json')
+    with open(json_output_path, 'w') as jsonfile:
+        json.dump(data, jsonfile)
+
+    # save data to database
+    for row in data:
+        player_data = PlayerPlayoffTotalsData(
+            player_name = row['Player'],
+            age = row['Age'],
+            games = row['G'],
+            games_started = row['GS'],
+            minutes_played = row['MP'],
+            field_goals = row['FG'],
+            field_attempts = row['FGA'],
+            field_percent = row['FG%'],
+            three_fg = row['3P'],
+            three_attempts = row['3PA'],
+            three_percent = row['3P%'],
+            two_fg = row['2P'],
+            two_attempts = row['2PA'],
+            two_percent = row['2P%'],
+            effect_fg_percent = row['eFG%'],
+            ft = row['FT'],
+            fta = row['FTA'],
+            ft_percent = row['FT%'],
+            ORB= row['ORB'],
+            DRB = row['DRB'],
+            TRB = row['TRB'],
+            AST = row['AST'],
+            STL = row['STL'],
+            BLK = row['BLK'],
+            TOV = row['TOV'],
+            PF = row['PF'],
+            PTS = row['PTS'],
+            team = row['team'],
+            season = row['season'],
+        )
+        player_data.save()
+
+print('success')
+        
+
+    

nba_data/nba_scraper_totals.py

@@ -70,40 +70,42 @@ for team in teams:
     with open(json_output_path, 'w') as jsonfile:
         json.dump(data, jsonfile)
 
-    # # save data to database
-    # for row in data:
-    #     player_data = PlayerData(
-    #         name=row['Player'],
-    #         age=row['Age'],
-    #         games=row['G'],
-    #         games_started=row['GS'],
-    #         minutes_pg=row['MP'],
-    #         field_goals=row['FG'],
-    #         field_attempts=row['FGA'],
-    #         field_percent=row['FG%'],
-    #         three_fg=row['3P'],
-    #         three_attempts=row['3PA'],
-    #         three_percent=row['3P%'],
-    #         two_fg=row['2P'],
-    #         two_attempts=row['2PA'],
-    #         two_percent=row['2P%'],
-    #         effect_fg_percent=row['eFG%'],
-    #         ft=row['FT'],
-    #         fta=row['FTA'],
-    #         ft_percent=row['FT%'],
-    #         ORB=row['ORB'],
-    #         DRB=row['DRB'],
-    #         TRB=row['TRB'],
-    #         AST=row['AST'],
-    #         STL=row['STL'],
-    #         BLK=row['BLK'],
-    #         TOV=row['TOV'],
-    #         PF=row['PF'],
-    #         PTS=row['PTS'],
-    #         team=row['team'],
-    #         season=row['season'],
-    #     )
-    #     player_data.save()
+    # save data to database
+    for row in data:
+        player_data = PlayerTotalsData(
+            player_name = row['Player'],
+            age = row['Age'],
+            games = row['G'],
+            games_started = row['GS'],
+            minutes_played = row['MP'],
+            field_goals = row['FG'],
+            field_attempts = row['FGA'],
+            field_percent = row['FG%'],
+            three_fg = row['3P'],
+            three_attempts = row['3PA'],
+            three_percent = row['3P%'],
+            two_fg = row['2P'],
+            two_attempts = row['2PA'],
+            two_percent = row['2P%'],
+            effect_fg_percent = row['eFG%'],
+            ft = row['FT'],
+            fta = row['FTA'],
+            ft_percent = row['FT%'],
+            ORB= row['ORB'],
+            DRB = row['DRB'],
+            TRB = row['TRB'],
+            AST = row['AST'],
+            STL = row['STL'],
+            BLK = row['BLK'],
+            TOV = row['TOV'],
+            PF = row['PF'],
+            PTS = row['PTS'],
+            team = row['team'],
+            season = row['season'],
+        )
+        player_data.save()
+
+print('success')
         
 
     

nba_data/nba_scraper_totals_single.py

@@ -0,0 +1,107 @@
+import os
+import sys
+import django
+import requests
+from bs4 import BeautifulSoup
+import csv
+import json
+import time
+
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nba_stats.settings')
+django.setup()
+
+from nba_data.models import PlayerTotalsData
+
+
+season = input('What season? ')
+team = input('What team?')
+
+url_make = 'https://www.basketball-reference.com/teams/' + team + '/' + season + '.html'
+response = requests.get(url_make)
+
+soup = BeautifulSoup(response.text, "html.parser")
+
+table = soup.find("table", {"id": "totals"})
+
+if table is None:
+    print(f"Table not found for team {team} and season {season}.")
+    # sys.exit(1)
+    # continue
+
+header_row = table.find("thead").find("tr")
+rows = table.find("tbody").find_all("tr")
+
+
+# Extract coloumn headers
+headers = [col.text.strip() for col in header_row.find_all("th")][1:]
+headers.extend(['team', 'season'])  # Add 'team' and 'season' fields to headers
+
+# Extract rows as dictionaries
+data = []
+for row in rows:
+    cols = row.find_all("td")
+    cols = [col.text.strip() for col in cols]
+    row_dict = {header: (None if col == "" else col) for header, col in zip(headers, cols)}
+    row_dict['team'] = team
+    row_dict['season'] = season
+    data.append(row_dict)
+
+
+# locate current directory
+script_dir = os.path.dirname(os.path.abspath(__file__))
+
+# save as CSV file
+csv_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_totals_output.csv')
+with open(csv_output_path, "w", newline="") as csvfile:
+    writer = csv.DictWriter(csvfile, fieldnames=headers)
+    writer.writeheader()
+    for row in data:
+        writer.writerow(row)
+
+# Save as JSON
+json_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_totals_output.json')
+with open(json_output_path, 'w') as jsonfile:
+    json.dump(data, jsonfile)
+
+# save data to database
+for row in data:
+    player_data = PlayerTotalsData(
+        player_name = row['Player'],
+        age = row['Age'],
+        games = row['G'],
+        games_started = row['GS'],
+        minutes_played = row['MP'],
+        field_goals = row['FG'],
+        field_attempts = row['FGA'],
+        field_percent = row['FG%'],
+        three_fg = row['3P'],
+        three_attempts = row['3PA'],
+        three_percent = row['3P%'],
+        two_fg = row['2P'],
+        two_attempts = row['2PA'],
+        two_percent = row['2P%'],
+        effect_fg_percent = row['eFG%'],
+        ft = row['FT'],
+        fta = row['FTA'],
+        ft_percent = row['FT%'],
+        ORB= row['ORB'],
+        DRB = row['DRB'],
+        TRB = row['TRB'],
+        AST = row['AST'],
+        STL = row['STL'],
+        BLK = row['BLK'],
+        TOV = row['TOV'],
+        PF = row['PF'],
+        PTS = row['PTS'],
+        team = row['team'],
+        season = row['season'],
+    )
+    player_data.save()
+
+print('success')
+        
+
+    

nba_data/scraper.py

@@ -15,11 +15,11 @@ django.setup()
 
 from nba_data.models import PlayerData
 
+# If season is 2014 or priot, then change CHO to CHA
 teams = ['HOU' ,'PHI', 'BOS', 'NYK', 'BRK', 'TOR', 'MEM', 'NOP', 'DAL', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHO']
 team_abbreviations = ['ATL', 'BOS', 'BRK', 'CHI', 'CHO', 'CLE', 'DAL', 'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR', 'UTA', 'WAS']
 
-# team = input('What team? ') 
-#  OMIT above. Will now only ask for season and iterate thru teams list.
+
 season = input('What season? ')
 
 for team in teams:
@@ -105,5 +105,7 @@ for team in teams:
         )
         player_data.save()
         
+print('success')
+        
 
     

nba_data/urls.py

@@ -1,5 +1,5 @@
 from django.urls import path
-from .views import PlayerDataList, PlayerDataByTeamList, PlayerDataBySeasonList, PlayerDataByNameList, TopScorersbySeasonList, ThreeTwoTopPointTrends, TopAssistsBySeasonList, TopReboundsBySeasonList, TopBlocksBySeasonList, TopStealsBySeasonList, TopOffensiveReboundsBySeasonList, TopDefensiveReboundsBySeasonList, PointsPerGameHistogramBySeasonList
+from .views import PlayerDataList, PlayerDataByTeamList, PlayerDataBySeasonList, PlayerDataByNameList, TopScorersbySeasonList, ThreeTwoTopPointTrends, TopAssistsBySeasonList, TopReboundsBySeasonList, TopBlocksBySeasonList, TopStealsBySeasonList, TopOffensiveReboundsBySeasonList, TopDefensiveReboundsBySeasonList, PointsPerGameHistogramBySeasonList, TopPtsScatterPlotData, TopPtsScatterPlotDataFast, Top20ScorersPost2009WS, Top20ScorersPost2014WS, Top20ScorersPost2018WS
 
 urlpatterns = [
     path('api/playerdata/', PlayerDataList.as_view(), name='playerdata_list'),
@@ -15,4 +15,9 @@ urlpatterns = [
     path('api/top_rebounds_offensive/<int:season>/', TopOffensiveReboundsBySeasonList.as_view(), name='top_rebounds_ORB'),
     path('api/top_rebounds_defensive/<int:season>/', TopDefensiveReboundsBySeasonList.as_view(), name='top_rebounds_DRB'),
     path('api/points_per_game_histogram/<int:season>/', PointsPerGameHistogramBySeasonList.as_view(), name='points_per_game_histogram'),
+    path('api/top_pts_scatter_plot/', TopPtsScatterPlotData.as_view(), name='top_pts_scatter_plot'),
+    path('api/top_pts_scatter_plot_fast/', TopPtsScatterPlotDataFast.as_view(), name='top_pts_scatter_plot_fast'),
+    path('api/top_20_post_2009_PTS_ws/', Top20ScorersPost2009WS.as_view(), name='top_20_post_2009_PTS_ws'),
+    path('api/top_20_post_2014_PTS_ws/', Top20ScorersPost2014WS.as_view(), name='top_20_post_2014_PTS_ws'),
+    path('api/top_20_post_2018_PTS_ws/', Top20ScorersPost2018WS.as_view(), name='top_20_post_2018_PTS_ws'),
 ]

nba_data/views.py

@@ -1,14 +1,15 @@
 from django.shortcuts import render
 from django.http import JsonResponse
 from django.core import serializers
-from .models import PlayerData
+from .models import PlayerData, PlayerTotalsData, PlayerAdvancedData, PlayerPlayoffTotalsData, PlayerPlayoffAdvancedData
 from rest_framework import generics
 from .serializers import PlayerDataSerializer, HistogramDataSerializer
 from rest_framework.views import APIView
 from rest_framework.response import Response
-from django.db.models import Avg
+from django.db.models import Avg, Sum, F, FloatField
 from collections import Counter
 import math
+from django.db import connection
 
 
 # Create your views here.
@@ -174,3 +175,196 @@ class PointsPerGameHistogramBySeasonList(generics.ListAPIView):
                           for k, v in histogram_data.items()]
 
         return histogram_list
+
+
+# Scatter Plot - Top 30 players by total PTS across all seasons in DB. Then map those 30 players on a scatter plot against total PTS/WS for each season.
+
+class TopPtsScatterPlotData(APIView):
+    def get(self, request, *args, **kwargs):
+        # Get the top 25 players by overall PTS
+        top_players = PlayerTotalsData.objects.values('player_name') \
+            .annotate(total_pts=Sum(F('PTS'))) \
+            .order_by('-total_pts')[:25]
+
+        # Get the PTS and WS for the corresponding seasons of the top 25 players
+        data = []
+        for player in top_players:
+            player_name = player['player_name']
+            player_seasons = PlayerTotalsData.objects.filter(player_name=player_name) \
+                .values('season') \
+                .annotate(total_pts=Sum(F('PTS'))) \
+                .order_by('season')
+
+            # Combine the WS data from PlayerAdvancedData
+            for season in player_seasons:
+                season_ws = PlayerAdvancedData.objects.filter(player_name=player_name, season=season['season']) \
+                    .aggregate(total_ws=Sum('ws'))
+                season['total_ws'] = season_ws['total_ws']
+
+            data.append({
+                'player_name': player_name,
+                'seasons': list(player_seasons)
+            })
+
+        return Response(data)
+    
+# change lines 223, 227, and 233 where the comments are to alter seasons returned.
+class TopPtsScatterPlotDataFast(APIView):
+    def get(self, request):
+        with connection.cursor() as cursor:
+            cursor.execute("""
+                -- The modified query from earlier
+                WITH player_season_pts AS (
+                  SELECT player_name, season, SUM("PTS") as season_pts
+                  FROM nba_data_playertotalsdata
+                  WHERE player_name IN (SELECT player_name FROM (
+                                           SELECT player_name, SUM("PTS") as total_pts
+                                           FROM nba_data_playertotalsdata
+                                           -- WHERE season >= 2021
+                                           GROUP BY player_name
+                                           ORDER BY total_pts DESC
+                                           LIMIT 25) as top_25_players)
+                  -- AND season >= 2021               
+                  GROUP BY player_name, season
+                ),
+                player_season_ws AS (
+                  SELECT player_name, season, SUM("ws") as season_ws
+                  FROM nba_data_playeradvanceddata
+                  -- WHERE season >= 2021
+                  GROUP BY player_name, season
+                )
+                SELECT player_season_pts.player_name, player_season_pts.season, player_season_pts.season_pts, player_season_ws.season_ws
+                FROM player_season_pts
+                JOIN player_season_ws
+                ON player_season_pts.player_name = player_season_ws.player_name AND player_season_pts.season = player_season_ws.season
+                ORDER BY player_season_pts.player_name, player_season_pts.season;
+            """)
+            rows = cursor.fetchall()
+
+        result = []
+        for row in rows:
+            player_name, season, season_pts, season_ws = row
+            result.append({
+                'player_name': player_name,
+                'season': season,
+                'season_pts': season_pts,
+                'season_ws': season_ws
+            })
+
+        return Response(result)
+    
+    
+# Top 20 players in playoffs by PTS X ws for scatter plot in chart.js
+    
+class Top20ScorersPost2009WS(APIView):
+    def get(self, request):
+        # Get the top 20 scorers after the 2015 season
+        top_scorers = PlayerPlayoffTotalsData.objects \
+            .filter(season__gt=2009) \
+            .values('player_name') \
+            .annotate(total_pts=Sum('PTS')) \
+            .order_by('-total_pts')[:20]
+
+        # Get the total WS for each of the top 20 scorers after the 2015 season
+        chart_data = []
+        for scorer in top_scorers:
+            player_name = scorer['player_name']
+            total_ws = PlayerPlayoffAdvancedData.objects \
+                .filter(player_name=player_name, season__gt=2009) \
+                .aggregate(total_ws=Sum('ws'))['total_ws']
+
+            chart_data.append({
+                'x': scorer['total_pts'],
+                'y': total_ws,
+                'player_name': player_name
+            })
+
+        # Sort the data by total_ws DESC
+        chart_data = sorted(chart_data, key=lambda x: x['y'], reverse=True)
+
+        # Prepare the response data for chart.js
+        response_data = {
+            'datasets': [
+                {
+                    'data': chart_data
+                }
+            ]
+        }
+
+        return Response(response_data)
+    
+
+class Top20ScorersPost2014WS(APIView):
+    def get(self, request):
+        # Get the top 20 scorers after the 2015 season
+        top_scorers = PlayerPlayoffTotalsData.objects \
+            .filter(season__gt=2014) \
+            .values('player_name') \
+            .annotate(total_pts=Sum('PTS')) \
+            .order_by('-total_pts')[:20]
+
+        # Get the total WS for each of the top 20 scorers after the 2015 season
+        chart_data = []
+        for scorer in top_scorers:
+            player_name = scorer['player_name']
+            total_ws = PlayerPlayoffAdvancedData.objects \
+                .filter(player_name=player_name, season__gt=2014) \
+                .aggregate(total_ws=Sum('ws'))['total_ws']
+
+            chart_data.append({
+                'x': scorer['total_pts'],
+                'y': total_ws,
+                'player_name': player_name
+            })
+
+        # Sort the data by total_ws DESC
+        chart_data = sorted(chart_data, key=lambda x: x['y'], reverse=True)
+
+        # Prepare the response data for chart.js
+        response_data = {
+            'datasets': [
+                {
+                    'data': chart_data
+                }
+            ]
+        }
+
+        return Response(response_data)
+
+class Top20ScorersPost2018WS(APIView):
+    def get(self, request):
+        # Get the top 20 scorers after the 2015 season
+        top_scorers = PlayerPlayoffTotalsData.objects \
+            .filter(season__gt=2018) \
+            .values('player_name') \
+            .annotate(total_pts=Sum('PTS')) \
+            .order_by('-total_pts')[:20]
+
+        # Get the total WS for each of the top 20 scorers after the 2015 season
+        chart_data = []
+        for scorer in top_scorers:
+            player_name = scorer['player_name']
+            total_ws = PlayerPlayoffAdvancedData.objects \
+                .filter(player_name=player_name, season__gt=2018) \
+                .aggregate(total_ws=Sum('ws'))['total_ws']
+
+            chart_data.append({
+                'x': scorer['total_pts'],
+                'y': total_ws,
+                'player_name': player_name
+            })
+
+        # Sort the data by total_ws DESC
+        chart_data = sorted(chart_data, key=lambda x: x['y'], reverse=True)
+
+        # Prepare the response data for chart.js
+        response_data = {
+            'datasets': [
+                {
+                    'data': chart_data
+                }
+            ]
+        }
+
+        return Response(response_data)
+