Your Name
97 lines
2.0 KiB
Python
Executable File
97 lines
2.0 KiB
Python
Executable File
#!/usr/bin/env python3
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import sys
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import subprocess
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# === AUTO INSTALL ===
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def ensure(pkg):
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try:
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__import__(pkg)
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except ImportError:
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subprocess.check_call([sys.executable, "-m", "pip", "install", pkg])
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ensure("pandas")
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ensure("matplotlib")
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import pandas as pd
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import matplotlib.pyplot as plt
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# === ARGS ===
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if len(sys.argv) < 2:
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print("Usage: python graph.py data.csv")
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sys.exit(1)
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FILE = sys.argv[1]
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# === LOAD ===
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df = pd.read_csv(FILE)
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if "datetime" not in df.columns:
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print("Missing datetime column")
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sys.exit(1)
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df["datetime"] = pd.to_datetime(df["datetime"])
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df = df.sort_values("datetime")
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# === CHECK REQUIRED COLS ===
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required = ["profit", "buy_in", "category"]
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for col in required:
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if col not in df.columns:
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print(f"Missing column: {col}")
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sys.exit(1)
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# === 1. CUMULATIVE PROFIT ===
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df["cum_profit"] = df["profit"].cumsum()
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plt.figure()
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plt.plot(df["datetime"], df["cum_profit"])
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plt.title("Cumulative Profit")
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plt.xlabel("Time")
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plt.ylabel("€")
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plt.xticks(rotation=45)
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plt.tight_layout()
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# === 2. PROFIT PER GAME (SCATTER) ===
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plt.figure()
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plt.scatter(range(len(df)), df["profit"])
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plt.title("Profit per Game")
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plt.xlabel("Game #")
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plt.ylabel("€")
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plt.tight_layout()
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# === 3. ROI BY CATEGORY ===
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roi = df.groupby("category").apply(
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lambda x: x["profit"].sum() / x["buy_in"].sum()
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)
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plt.figure()
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roi.plot(kind="bar")
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plt.title("ROI by Game Type")
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plt.xlabel("Category")
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plt.ylabel("ROI")
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plt.tight_layout()
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# === 4. SESSION PERFORMANCE ===
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if "session" in df.columns:
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session_profit = df.groupby("session")["profit"].sum()
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plt.figure()
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session_profit.plot(kind="bar")
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plt.title("Profit by Session")
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plt.xlabel("Session")
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plt.ylabel("€")
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plt.tight_layout()
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# === 5. WIN DISTRIBUTION ===
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if "position" in df.columns:
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pos_counts = df["position"].value_counts()
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plt.figure()
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pos_counts.plot(kind="bar")
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plt.title("Position Distribution")
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plt.xlabel("Position")
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plt.ylabel("Count")
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plt.tight_layout()
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# === SHOW ALL ===
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plt.show()
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