/config /pandas/display-max-columns

pandas display options: show all columns and rows (display.max_columns)

updated 2026-10-20

tool: pandas
file: pandas options (pd.set_option)
key: display.max_columns / display.max_rows
type: int or None
default: check with pd.get_option; it was 0 (fit to the output width) when this page was verified, max_rows 60

pandas shortens what it prints: wide DataFrames get ... in the middle and long ones show only the first and last rows. pd.set_option("display.max_columns", None) shows every column, display.max_rows does the same for rows, and pd.option_context(...) changes them for a single block of code.

Before and after

bash

python -c '
import pandas as pd
df = pd.DataFrame([[c for c in range(12)] for _ in range(2)], columns=[f"col{c}" for c in range(12)])
print("default max_columns:", pd.get_option("display.max_columns"))
pd.set_option("display.max_columns", 6)
print(df)
pd.set_option("display.max_columns", None)
pd.set_option("display.width", 200)
print(df)'

Output

default max_columns: 0
   col0  col1  col2  ...  col9  col10  col11
0     0     1     2  ...     9     10     11
1     0     1     2  ...     9     10     11

[2 rows x 12 columns]
   col0  col1  col2  col3  col4  col5  col6  col7  col8  col9  col10  col11
0     0     1     2     3     4     5     6     7     8     9     10     11
1     0     1     2     3     4     5     6     7     8     9     10     11

With a limit of 6, pandas shows the first and last three columns and a ... column in between; with None every column is printed.

Options you will use

Option	What it controls	Show everything
display.max_columns	columns before truncating with ...	None
display.max_rows	rows before truncating	None
display.width	line width in characters	a large number, e.g. 400
display.max_colwidth	characters per cell before ...	None
display.precision	decimal places for floats	—
display.float_format	function to format floats	'{:,.2f}'.format

Set them once, or for one print

python

import pandas as pd

pd.set_option("display.max_columns", None)       # for the whole session
pd.reset_option("display.max_columns")           # back to the default

with pd.option_context("display.max_rows", None, "display.max_columns", None):
    print(df)                                     # only inside this block

Sources

cheat sheets · pandaspandas cheat sheet: read, select, filter, group and reshapepandas cheat sheet: read CSV and Parquet, select with loc and iloc, filter rows, add columns, group and aggregate, pivot, handle missing values and write files.commands · pandaspandas merge: join DataFrames on a key (inner, left, outer)pd.merge(left, right, on='id', how='left') joins DataFrames like SQL. how picks inner, left, right, outer or cross; validate= catches duplicated keys.compare · pandaspandas loc vs iloc: label-based vs position-based selectionloc selects rows and columns by label and includes the end of a slice; iloc selects by integer position and excludes it. Cases where they return different rows.

Before and after

Options you will use

Set them once, or for one print

Sources

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