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Update app.py
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app.py
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@@ -787,6 +787,17 @@ def server(input, output, session):
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"K": f"{new_player_metrics['k'][0]:.0f}",
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"BB": f"{new_player_metrics['bb'][0]:.0f}",
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}
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else:
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df_fg_filter = df_fg.filter(pl.col('minormasterid') == dict_mlb_fg[pitcher_id])
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# Metrics data table
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@@ -800,15 +811,25 @@ def server(input, output, session):
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"FIP": f"{df_fg_filter['FIP'][0]:.2f}",
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"WHIP": f"{df_fg_filter['WHIP'][0]:.2f}",
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}
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if sport_id == 1:
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data_season = requests.get(url_season).json()
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df_season = pl.DataFrame(data=data_season['data'], infer_schema_length=1000)
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df_season = df_season.with_columns(pl.lit('Season').alias('Time'))
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@@ -824,16 +845,16 @@ def server(input, output, session):
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"WHIP": f"{df_fg_filter['WHIP'][0]:.2f}",
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}
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table.set_fontsize(12)
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table.scale(1, 1.5)
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# Additional subplots for spacing
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ax_top = fig.add_subplot(gs[0, :])
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"K": f"{new_player_metrics['k'][0]:.0f}",
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"BB": f"{new_player_metrics['bb'][0]:.0f}",
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}
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df_table = pd.DataFrame(metrics_data, index=[0])
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table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
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for key, cell in table.get_celld().items():
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if key[0] == 0:
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cell.set_text_props(fontweight='bold')
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table.auto_set_font_size(False)
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table.set_fontsize(12)
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table.scale(1, 1.5)
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else:
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df_fg_filter = df_fg.filter(pl.col('minormasterid') == dict_mlb_fg[pitcher_id])
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# Metrics data table
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"FIP": f"{df_fg_filter['FIP'][0]:.2f}",
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"WHIP": f"{df_fg_filter['WHIP'][0]:.2f}",
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}
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df_table = pd.DataFrame(metrics_data, index=[0])
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table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
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for key, cell in table.get_celld().items():
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if key[0] == 0:
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cell.set_text_props(fontweight='bold')
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table.auto_set_font_size(False)
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table.set_fontsize(12)
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table.scale(1, 1.5)
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if sport_id == 1:
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url_season = url = f"""
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https://www.fangraphs.com/api/leaders/major-league/data?age=&pos=all&stats=pit&lg=all&season={year}&season1={year}
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&startdate={year}-01-01&enddate={year}-12-01&ind=0&qual=0&type=8&month=33&pageitems=500000
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"""
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data_season = requests.get(url_season).json()
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df_season = pl.DataFrame(data=data_season['data'], infer_schema_length=1000)
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df_season = df_season.with_columns(pl.lit('Season').alias('Time'))
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"WHIP": f"{df_fg_filter['WHIP'][0]:.2f}",
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}
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df_table = pd.DataFrame(metrics_data, index=[0])
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table = ax_table.table(cellText=df_table.values, colLabels=df_table.columns, cellLoc='center', loc='bottom', bbox=[0.07, 0, 0.86, 1])
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for key, cell in table.get_celld().items():
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if key[0] == 0:
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cell.set_text_props(fontweight='bold')
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table.auto_set_font_size(False)
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table.set_fontsize(12)
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table.scale(1, 1.5)
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# Additional subplots for spacing
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ax_top = fig.add_subplot(gs[0, :])
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