Pandas head()

In this tutorial, you will learn about the head() method in Pandas with the help of examples.

The head() method in Pandas is used to return the first n rows of a pandas object, such as a Series or DataFrame. This method is especially useful when you quickly want to inspect the top rows of large datasets.

Example

import pandas as pd

# create a sample DataFrame
data = {'A': [1, 2, 3, 4, 5],
        'B': [5, 6, 7, 8, 9]}

df = pd.DataFrame(data)

# use head() to display the first 3 rows of the DataFrame
top_rows = df.head(3)

print(top_rows)

'''
Output

   A  B
0  1  5
1  2  6
2  3  7
'''

head() Syntax

The syntax of the head() method in Pandas is:

obj.head(n=5)

head() Argument

The head() method takes the following argument:

  • n (optional) - specifies number of rows to return

head() Return Value

The head() method returns a DataFrame or Series that contains the first n rows of the original object.

Example 1: Display Default Number of Rows

import pandas as pd

# create a sample DataFrame
data = {'Values': [10, 20, 30, 40, 50, 60, 70]}
df = pd.DataFrame(data)

# use head() without any argument to get the default number of rows
top_rows = df.head()

print(top_rows)

Output

   Values
0     10
1     20
2     30
3     40
4     50

In this example, we used the head() method without any argument, so it returns the default number of rows, which is 5.

Example 2: Using head() on a Series

import pandas as pd

# create a sample Series
series_data = pd.Series([1, 2, 3, 4, 5, 6, 7, 8])

# display the top 4 elements of the Series
top_elements = series_data.head(4)

print(top_elements)

Output

0    1
1    2
2    3
3    4
dtype: int64

Here, we used the head() method on a Series object to view its top 4 elements.