Conditional Selection

Filtering data with conditions

Conditional selection means filtering the rows you want using a rule. Just like using WHERE in SQL, in Pandas you use the pattern df[df["Column"] condition].

import pandas as pd

df = pd.DataFrame({
    "Name": ["Alice", "Bob", "Charlie", "Daisy"],
    "Age": [25, 30, 35, 22],
    "Score": [82, 91, 76, 95]
})

high_scores = df[df["Score"] >= 90]
adults = df[df["Age"] >= 30]

print("High scores:")
print(high_scores)
print("
Age 30 and above:")
print(adults)

df["Score"] >= 90 produces a list of True/False values. Pandas then picks out only the rows where it's True and returns a new DataFrame. That's why this is so commonly used for generating reports, segmenting customers, and checking sales thresholds.

High scores: Name Age Score 1 Bob 30 91 3 Daisy 22 95 Age 30 and above: Name Age Score 1 Bob 30 91 2 Charlie 35 76