What Is a Decision Tree?

Is Rank ≤ 6.5?
├── YES → Don't Go (all low-ranked shows were bad)
└── NO  → Is Nationality UK?
          ├── YES → Is Age ≤ 35.5?
          │         ├── YES → Go!
          │         └── NO  → Check Experience...
          └── NO  → Go! (non-UK, high rank = always good)

import pandas as pd
from sklearn.tree import DecisionTreeClassifier
df = pd.read_csv("shows.csv")
# Convert strings to numbers (trees need numerical data)
d = {"UK": 0, "USA": 1, "N": 2}
df["Nationality"] = df["Nationality"].map(d)
d = {"YES": 1, "NO": 0}
df["Go"] = df["Go"].map(d)
# Separate features and target
features = ["Age", "Experience", "Rank", "Nationality"]
X = df[features]
y = df["Go"]
# Build the tree
dtree = DecisionTreeClassifier()
dtree = dtree.fit(X, y)
print("Tree built successfully!")
# Output: Tree built successfully!