Selecting Rows

Definition: Pandas has two row selectors: iloc selects by position (like a list index), and loc selects by label or by a condition.

Example 1 — by position with iloc

import pandas as pd
df = pd.DataFrame({
  "name": ["Sam", "Alex", "Jo"],
  "age":  [25, 30, 22]
})
print(df.iloc[0])        # first row
print(df.iloc[1]["name"])# value in row 1, column name

Example 2 — by label with loc

import pandas as pd
df = pd.DataFrame({"name": ["Sam", "Alex", "Jo"], "age": [25, 30, 22]})
print(df.loc[0, "name"])   # row label 0, column name

Example 3 — a range of rows

import pandas as pd
df = pd.DataFrame({"name": ["Sam","Alex","Jo","Pat"], "age": [25,30,22,40]})
print(df.iloc[0:2])        # first two rows

💡 Tip: remember "iloc = integer position" and "loc = label". Mixing them up is the most common Pandas beginner slip.