Why df.shape Has No Parentheses in Pandas (Method vs Property Explained)

[Rajeev Bagra]

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❓ Question

df.shape in pandas has no parentheses. Is it a method?

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✅ Short Answer

No. df.shape is not a method.
It is an attribute (also called a property) of a pandas DataFrame.

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ߓ Understanding the Difference (Beginner-Friendly)

In Python, there is a clear distinction:

ߔ Methods

• Perform an action
• Require parentheses ()
• May accept arguments

Example:

df.head()
df.describe()

ߔ Attributes / Properties

• Store or expose information
• Do NOT use parentheses
• Behave like variables

Example:

df.shape
df.columns
df.index

So when you write:

df.shape

You are accessing information, not calling a function.

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ߓ What does df.shape return?

df.shape returns a tuple:

(number_of_rows, number_of_columns)

Example

import pandas as pd

df = pd.DataFrame({
    "Name": ["Alice", "Bob", "Charlie"],
    "Age": [22, 25, 30]
})

print(df.shape)

Output

(3, 2)

✔ 3 rows
✔ 2 columns

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⚠️ Why parentheses don’t work

If you try:

df.shape()

Python raises an error:

TypeError: 'tuple' object is not callable

This happens because:

• df.shape already returns a tuple
• A tuple is not a function
• So it cannot be “called”

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ߧ What’s happening internally (conceptual)

Internally, shape is defined as a property, something like:

@property
def shape(self):
    return (rows, columns)

That’s why:

• No parentheses are needed
• No arguments can be passed

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ߓ Common pandas examples (at a glance)

Expression	Type	Uses ()?
df.shape	Attribute / Property	❌ No
df.size	Attribute	❌ No
df.columns	Attribute	❌ No
df.head()	Method	✅ Yes
df.describe()	Method	✅ Yes

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ߎ Final Takeaway (One-Line)

df.shape is a property, not a method. It gives metadata (rows, columns), so parentheses are not needed.

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