How do i print the first few rows in python?

To get the first N rows of a Pandas DataFrame, use the function pandas.DataFrame.head[]. You can pass an optional integer that represents the first N rows. If you do not pass any number, it returns the first 5 rows. Meaning, the default N is 5.

Example 1: DataFrame.head[N]

In this example, we will get the first 3 rows of the DataFrame.

Python Program

import pandas as pd

#initialize a dataframe
df = pd.DataFrame[
	[[21, 72, 67],
	[23, 78, 62],
	[32, 74, 56],
	[73, 88, 67],
	[32, 74, 56],
	[43, 78, 69],
	[32, 74, 54],
	[52, 54, 76]],
	columns=['a', 'b', 'c']]

#get first 3 rows
df1 = df.head[3]

#print the dataframe
print[df1]

Run

Output

Example 2: DataFrame.head[]

In this example, we will not pass any number to the function head[]. By default, head[] function returns first 5 rows.

Python Program

import pandas as pd

#initialize a dataframe
df = pd.DataFrame[
	[[21, 72, 67],
	[23, 78, 62],
	[32, 74, 56],
	[73, 88, 67],
	[32, 74, 56],
	[43, 78, 69],
	[32, 74, 54],
	[52, 54, 76]],
	columns=['a', 'b', 'c']]

#get first default number of rows
df1 = df.head[]

#print the dataframe
print[df1]

Run

Output

Summary

In this Pandas Tutorial, we extracted the first N rows of Pandas DataFrame, using pandas.DataFrame.head[] method, with the help of well detailed Python example programs.

Related Tutorials

• Pandas iterrows[] – Iterate over DataFrame Rows
• How to iterate over Elements of Row in Pandas DataFrame?
• How to Filter Pandas DataFrame Rows?
• How to Add or Insert Row to Pandas DataFrame?
• How to Count Rows in Pandas DataFrame?

Pandas: IMDb Movies Exercise-9 with Solution

Write a Pandas program to display the first 10 rows of the DataFrame.

Sample Solution:

Python Code :

import pandas as pd
df = pd.read_csv['movies_metadata.csv']
#Display the first 10 rows
result = df.head[10]
print["First 10 rows of the DataFrame:"]
print[result]

Sample Output:

First 10 rows of the DataFrame:
   adult    ...     vote_count
0  False    ...           5415
1  False    ...           2413
2  False    ...             92
3  False    ...             34
4  False    ...            173
5  False    ...           1886
6  False    ...            141
7  False    ...             45
8  False    ...            174
9  False    ...           1194

[10 rows x 24 columns]                                     

Python-Pandas Code Editor:

Sample Table:

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