Pandas get_option() and set_option(): Read and Change Settings

Read current Pandas display options, set row and column limits and restore prior settings safely.

Create a portable student table 🔝

The original tutorial displays 35 student rows after reading Excel with id as the index. This replacement uses explicitly synthetic records so the examples run without a local D: drive. It has four data columns after moving id into the index, correcting the original five-column description.

import pandas as pd
students = pd.DataFrame({"id": range(1, 36),
    "name": [f"Student {i:02d}" for i in range(1, 36)],
    "class": ["Four"] * 35, "mark": [40 + i for i in range(35)],
    "sex": ["female" if i % 2 else "male" for i in range(35)]}).set_index("id")
print(students.head(3))
assert students.shape == (35, 4)

Expected output

          name class  mark     sex
id                                
1   Student 01  Four    40    male
2   Student 02  Four    41  female
3   Student 03  Four    42    male

Read the current option value 🔝

get_option() returns the current setting. It may differ from the registered default or from another environment. Do not assume max_rows is always 60 or max_columns is always 20.

print("Current max_rows:", pd.get_option("display.max_rows"))
print("Current max_columns:", pd.get_option("display.max_columns"))
assert pd.get_option("display.max_rows") is None or pd.get_option("display.max_rows") >= 0

Expected output

Current max_rows: 60
Current max_columns: 0

Set max_rows to six and display the table 🔝

The original 35-row student-table and six-row display concepts are retained. Display settings change rendering, not row counts. set_option changes shared session state until changed again; try/finally restores the prior value after this example.

previous = pd.get_option("display.max_rows")
try:
    returned = pd.set_option("display.max_rows", 6)
    print("Changed max_rows:", pd.get_option("display.max_rows"))
    with pd.option_context("display.min_rows", 6, "display.max_columns", 4,
                           "display.width", 80, "display.show_dimensions", True):
        print(students)
    assert returned is None and students.shape == (35, 4)
finally:
    pd.set_option("display.max_rows", previous)
assert pd.get_option("display.max_rows") == previous

Expected output

Changed max_rows: 6
          name class  mark     sex
id                                
1   Student 01  Four    40    male
2   Student 02  Four    41  female
3   Student 03  Four    42    male
..         ...   ...   ...     ...
33  Student 33  Four    72    male
34  Student 34  Four    73  female
35  Student 35  Four    74    male

[35 rows x 4 columns]

Set max_columns to three 🔝

Retain the original column-limit example. Setting max_rows and max_columns together makes the abbreviated representation clear. Use a context for the supporting rendering options.

old_rows = pd.get_option("display.max_rows")
old_columns = pd.get_option("display.max_columns")
try:
    pd.set_option("display.max_rows", 6, "display.max_columns", 3)
    with pd.option_context("display.min_rows", 6, "display.width", 80,
                           "display.show_dimensions", True):
        print(students)
    assert pd.get_option("display.max_columns") == 3
finally:
    pd.set_option("display.max_rows", old_rows, "display.max_columns", old_columns)
assert students.shape == (35, 4)

Expected output

          name  ...     sex
id              ...        
1   Student 01  ...    male
2   Student 02  ...  female
3   Student 03  ...    male
..         ...  ...     ...
33  Student 33  ...    male
34  Student 34  ...  female
35  Student 35  ...    male

[35 rows x 4 columns]

Retain the Excel input workflow 🔝

For your own file, read_excel(path, index_col="id") preserves the original import idea. Here an embedded sample creates a temporary workbook, reads it and cleans it automatically. Requires openpyxl. You can also use the original student Excel exercise.

from tempfile import TemporaryDirectory
from pathlib import Path
with TemporaryDirectory(dir=".") as folder:
    workbook = Path(folder) / "student.xlsx"
    students.reset_index().to_excel(workbook, index=False, engine="openpyxl")
    loaded = pd.read_excel(workbook, index_col="id")
    print("Imported shape:", loaded.shape)
    pd.testing.assert_frame_equal(loaded, students)
print("Temporary workbook removed:", not workbook.exists())

Expected output

Imported shape: (35, 4)
Temporary workbook removed: True

Prefer scoped settings for a temporary report 🔝

option_context changes options temporarily and restores previous values. reset_option restores defaults, which can differ from your earlier custom settings.

saved = pd.get_option("display.max_rows")
with pd.option_context("display.max_rows", 10):
    print("Temporary max_rows:", pd.get_option("display.max_rows"))
print("Previous value restored:", pd.get_option("display.max_rows") == saved)
assert pd.get_option("display.max_rows") == saved

Expected output

Temporary max_rows: 10
Previous value restored: True

Use full names and valid values 🔝

The option registry validates inputs. Unknown names raise OptionError; invalid values can raise ValueError. Do not suppress errors and assume a setting changed.

try:
    pd.get_option("display.this_option_does_not_exist")
except pd.errors.OptionError:
    print("Unknown option rejected")
else:
    raise AssertionError("Expected OptionError")
saved = pd.get_option("display.max_rows")
try:
    pd.set_option("display.max_rows", "six")
except ValueError:
    print("Invalid value rejected")
else:
    raise AssertionError("Expected ValueError")
assert pd.get_option("display.max_rows") == saved

Expected output

Unknown option rejected
Invalid value rejected

Common mistakes 🔝

get_option reads a setting, not table data. set_option returns None. Use full option names to avoid ambiguous partial matches. Unlimited display can generate excessive output for a large table; use head(), explicit selections or a controlled export instead. These settings affect the session while active, so avoid overlapping changes in concurrent code. Text print output and notebook HTML rendering can differ. See describe_option(), option_context() and reset_option().

Exercise: change precision and restore it 🔝

Read display.precision, set it to two, verify its value and restore the earlier value even if the demonstration raises an exception.

Exercise solution 🔝

Use try/finally for an intentional set_option change.

saved = pd.get_option("display.precision")
try:
    pd.set_option("display.precision", 2)
    print("Precision:", pd.get_option("display.precision"))
    assert pd.get_option("display.precision") == 2
finally:
    pd.set_option("display.precision", saved)
print("Restored:", pd.get_option("display.precision") == saved)

Expected output

Precision: 2
Restored: True

Practice in Google Colab 🔝

Open in Google Colab View on GitHub

Run examples in order, inspect the table display and try the exercise. Save a copy to keep edits.

Reference: Pandas get_option() and set_option() documentation.

Subhendu Mohapatra

Author & Instructor at plus2net

I write and maintain practical tutorials on Python, PHP, SQL, JavaScript, HTML, jQuery, and web development at plus2net. The tutorials focus on clear explanations, working examples, and code that readers can test and adapt while learning.

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