Selecting and Filtering Rows and Columns

What you'll build

Answers to everyday questions about the orders table: orders from Germany, orders worth more than 20 euros, specific customers, and particular columns, using the three selection tools pandas provides.

The idea

• df["col"] / df[["a", "b"]]: columns.
• df.loc[rows, cols]: by label (index values and column names), including boolean masks.
• df.iloc[rows, cols]: by position (0, 1, 2...).
• Boolean masks combine with & (and), | (or), ~ (not), each condition in parentheses.
• isin([...]) tests membership; between(a, b) ranges; query("...") reads like a sentence.

The code

from io import StringIO
import pandas as pd

csv = StringIO("""order_id,date,customer,country,product,quantity,unit_price
1001,2026-01-03,ana,DE,mug,2,8.50
1002,2026-01-03,ben,US,teapot,1,24.00
1003,2026-01-04,chen,DE,kettle,1,31.90
1004,2026-01-05,ana,DE,teapot,1,24.00
1005,2026-01-07,dara,FR,mug,4,8.50
1006,2026-01-07,ben,US,mug,1,8.50
""")
orders = pd.read_csv(csv, parse_dates=["date"])

orders["total"] = orders["quantity"] * orders["unit_price"]

german = orders.loc[orders["country"] == "DE", ["order_id", "customer", "total"]]
print(german)

big_or_fr = orders[(orders["total"] > 20) | (orders["country"] == "FR")]
print(big_or_fr["order_id"].tolist())

print(orders.loc[orders["customer"].isin(["ana", "ben"]), "product"].unique().tolist())
print(orders.iloc[:2, :3])
print(orders.query("country == 'US' and quantity >= 1")["order_id"].tolist())

   order_id customer  total
0      1001      ana   17.0
2      1003     chen   31.9
3      1004      ana   24.0
[1002, 1003, 1004, 1005]
['mug', 'teapot']
   order_id       date customer
0      1001 2026-01-03      ana
1      1002 2026-01-03      ben
[1002, 1006]

Common mistakes

• Using and/or instead of &/|, or forgetting parentheses around each condition (ValueError: truth value of a Series is ambiguous).
• Chained indexing like df[df.x > 1]["y"] = 0: in pandas 3 (copy-on-write) it never modifies df. Use df.loc[df.x > 1, "y"] = 0.
• Mixing up loc (labels, inclusive end) and iloc (positions, exclusive end).

Key points

• loc selects by label, iloc by position.
• Combine boolean conditions with &, |, ~ and parentheses.
• Assign with a single loc call, never chained indexing.

Further reading: Indexing and selecting data · Copy-on-Write