How to Get Row Count in Pandas: A Step-by-Step Guide

Understanding the Pandas Dataframe

A Pandas DataFrame is a two-dimensional data structure that allows you to store and manipulate data in rows and columns. Each column of a DataFrame is known as a Series, and can contain data of the same type, while each row represents an observation in the dataset.

You can create a DataFrame in Pandas using a variety of methods, such as reading data from a file, creating a DataFrame from a NumPy array, or constructing a DataFrame from scratch using Python lists or dictionaries. Once you have a DataFrame, you can perform various operations on it, such as selecting specific rows or columns, filtering data based on certain conditions, or aggregating data to calculate summary statistics.

Here’s an example of how you can create a simple DataFrame from a Python dictionary:

import pandas as pd

data = {'name': ['John', 'Jane', 'Bob', 'Alice'],
        'age': [25, 30, 35, 40],
        'gender': ['M', 'F', 'M', 'F']}

df = pd.DataFrame(data)

This creates a DataFrame with three columns: ‘name’, ‘age’, and ‘gender’, and four rows representing four individuals. You can perform various operations on the DataFrame, such as selecting specific columns, by using the column name:

df['name'] # selects the 'name' column

Different Ways to Get Row Count

In Pandas, there are several ways to get the row count of a DataFrame. The most commonly used methods are using len() function, shape attribute, and count() method.

Using len() Function

You can use the len() function to get the total number of rows in a Pandas DataFrame. This method is straightforward, and it simply returns the number of rows in the DataFrame.

import pandas as pd

df = pd.read_csv('data.csv')

row_count = len(df)

Here, the len() function is used to obtain the row count of the Pandas DataFrame, df. The result is assigned to the variable row_count.

Using shape Attribute

You can also use the shape attribute of the DataFrame, which returns a tuple of the number of rows and columns. You can extract the number of rows using the first element of the tuple.

import pandas as pd

df = pd.read_csv('data.csv')

row_count = df.shape[0]

The shape attribute returns a tuple of two integers: the number of rows and the number of columns. Here, we extract the first element of the tuple using [0] to obtain the row count.

Using count() Method

Another way to get the row count is to use the count() method of the DataFrame. This method returns the count of non-null values for each column. You can extract the count of any column, since they all contain the same number of rows.

import pandas as pd

df = pd.read_csv('data.csv')

row_count = df['column_name'].count()

Here, we use the count() method to obtain the count of the non-null values in a specific column named 'column_name'. Since all columns have the same number of rows, we can extract the count of any column to obtain the row count.

These are just a few examples of how you can obtain the row count of a Pandas DataFrame. You can choose the method that best suits your needs, based on the context of your analysis.