82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
import sqlite3
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import pandas as pd
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import numpy as np
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pd.set_option('display.max_columns', None)
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pd.set_option('display.width', 1000)
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pd.set_option('display.float_format', '{:.2f}'.format)
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db_path = 'database/L2/L2_Main.sqlite'
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def check_nulls_zeros():
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conn = sqlite3.connect(db_path)
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print("=== 1. Fact Match Players: 关键字段零值/空值检查 ===")
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df_players = pd.read_sql("""
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SELECT
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kills, deaths, assists, adr, rating, rating2,
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kast, awp_kills, flash_duration, jump_count,
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elo_change
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FROM fact_match_players
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""", conn)
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stats = []
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for col in df_players.columns:
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total = len(df_players)
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nulls = df_players[col].isnull().sum()
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zeros = (df_players[col] == 0).sum()
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stats.append({
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'Field': col,
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'Total': total,
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'Nulls': nulls,
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'Null%': (nulls/total)*100,
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'Zeros': zeros,
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'Zero%': (zeros/total)*100
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})
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print(pd.DataFrame(stats))
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print("\n=== 2. Fact Round Events (Kills): 击杀完整性检查 ===")
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# 只检查 event_type = 'kill' 的记录
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df_kills = pd.read_sql("""
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SELECT
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attacker_steam_id, victim_steam_id,
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event_time, weapon,
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attacker_pos_x, score_change_attacker
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FROM fact_round_events
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WHERE event_type = 'kill'
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""", conn)
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total_kills = len(df_kills)
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missing_attacker = df_kills['attacker_steam_id'].isnull().sum() + (df_kills['attacker_steam_id'] == '').sum()
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missing_victim = df_kills['victim_steam_id'].isnull().sum() + (df_kills['victim_steam_id'] == '').sum()
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# 检查 attacker 和 victim 是否相同（自杀）
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self_kills = (df_kills['attacker_steam_id'] == df_kills['victim_steam_id']).sum()
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print(f"Total Kill Events: {total_kills}")
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print(f"Missing Attacker: {missing_attacker} ({missing_attacker/total_kills*100:.2f}%)")
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print(f"Missing Victim: {missing_victim} ({missing_victim/total_kills*100:.2f}%)")
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print(f"Self Kills (Suicide?): {self_kills}")
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print("\n=== 3. Fact Round Events: 坐标与评分覆盖率 ===")
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# 坐标应该在 classic 比赛中有值，leetify 比赛中可能为空
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# 评分应该在 leetify 比赛中有值
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df_events = pd.read_sql("""
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SELECT
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m.data_source_type,
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COUNT(*) as total_events,
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SUM(CASE WHEN e.attacker_pos_x IS NOT NULL AND e.attacker_pos_x != 0 THEN 1 ELSE 0 END) as has_pos,
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SUM(CASE WHEN e.score_change_attacker IS NOT NULL AND e.score_change_attacker != 0 THEN 1 ELSE 0 END) as has_score
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FROM fact_round_events e
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JOIN fact_matches m ON e.match_id = m.match_id
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WHERE e.event_type = 'kill'
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GROUP BY m.data_source_type
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""", conn)
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print(df_events)
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conn.close()
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if __name__ == "__main__":
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check_nulls_zeros()
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