Q.What would happen if the label or row index passed is not present in the DataFrame?

Shape of Question

This is a plain theory question asking about the behavior of pandas DataFrame operations when a non-existent label or index is referenced.

Explanation

When you attempt to access a label (column name) or row index that does not exist in a DataFrame, pandas raises an KeyError exception. This is the standard response for missing keys in dictionary-like structures, and since DataFrames are built on labeled axes, the same principle applies.

For column access using bracket notation or the .loc[] accessor, if the column label is absent:

import pandas as pd

df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})
print(df['C'])  # KeyError: 'C'

For row access using .loc[] with an index label that doesn't exist:

df = pd.DataFrame({'A': [10, 20]}, index=['x', 'y'])
print(df.loc['z'])  # KeyError: 'z'

The error message typically indicates which key was not found, making debugging straightforward.

Handling the error gracefully:

You can prevent the exception using: …

The behavior depends on which indexing method you use and what operation you're performing. Understanding this is crucial because DataFrames are labeled data structures — unlike lists where positions are always 0, 1, 2…, DataFrame indices can be arbitrary labels (strings, dates, integers that skip values). When you ask for a label that doesn't exist, pandas must decide: error out or return something safe.

Dictionary-style and .loc[] access: KeyError

When you use dictionary-style indexing (df['column']) for a column or .loc[] for a row label, pandas treats the DataFrame like a labeled mapping. If the label isn't found, it raises a KeyError.

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Score': [85, 90, 78]
}, index=['A', 'B', 'C'])

# Attempt to access a non-existent column
try:
    print(df['Marks'])
except KeyError as e:
    print(f"KeyError: {e}")

# Attempt to access a non-existent row label
try:
    print(df.loc['D'])
except KeyError as e:
    print(f"KeyError: {e}")

Output:

KeyError: 'Marks'
KeyError: 'D'

The error is immediate and explicit: the label you requested does not exist in the axis (columns or index).

Position-based .iloc[] access: IndexError

When you use .iloc[] (integer-location based), you're asking for the n-th row or column by position, just like a list. If the position is out of range, pandas raises an IndexError.

# DataFrame has 3 rows (positions 0, 1, 2)
try:
    print(df.iloc[5])
except IndexError as e:
    print(f"IndexError: {e}")

Output:

IndexError: single positional indexer is out-of-bounds

This is the same error you'd get from my_list[100] when the list has only 10 elements.

Safe alternatives: .get() and .reindex()

If you want to avoid exceptions and handle missing labels gracefully, pandas provides:

1. .get() for columns (returns None or a default)

result = df.get('Marks', default='Column not found')
print(result)

Output:

Column not found

2. .reindex() for rows (fills missing labels with NaN)