How to Count the Number of Lines in a CSV File in Python?

Python is a popular programming language that is widely used for data analysis and scientific computing. It provides a vast range of libraries and tools that make data manipulation and analysis simpler and faster. One such library is Pandas, which is built on top of NumPy and provides easy−to−use data structures and data analysis tools for Python.

In this tutorial, we will explore how to count the number of lines in a CSV file using Python and the Pandas library. Counting the number of lines in a CSV file is a common operation that is required in data analysis and machine learning tasks. By using Pandas, we can easily read the CSV file into a DataFrame object, and then use the shape attribute or the len() function to count the number of rows in the file. In the next section of the article, we will walk through the steps to read a CSV file using Pandas, and then demonstrate how to count the number of lines in the file using various methods.

How to Count the Number of lines in a CSV File in Python?

We will be using Python 3 and the Pandas library for counting the number of lines in a CSV File.

Before we begin, make sure you have Python and Pandas installed on your system. If you don't have Pandas installed, you can install it using pip, which is the package installer for Python.

Open your command prompt (on Windows) or terminal (on Linux/macOS) and type the following command:

pip install pandas

The above command will download and install the Pandas library on your system.

Once the Pandas library is installed, we can import it into our Python code using the import statement. Here is an example of how to import Pandas:

import pandas as pd

In the above code, we are importing the Pandas library and aliasing it as pd for simplicity. This is a very common convention used in Python programming. Now that we have imported Pandas, we can start using its functions and classes in our code to count the number of files in a CSV file.

We will use the read_csv() method of Pandas to read the CSV file into a DataFrame object. The DataFrame object is a two−dimensional table−like data structure that is commonly used in data analysis and manipulation tasks.

To read a CSV file using Pandas, we can use the following code snippet:

import pandas as pd

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

In the above code example, we are using the read_csv() method of Pandas to read a CSV file named sample.csv. This will return a DataFrame object that contains the data from the CSV file. The df variable is used to store this DataFrame object.

Pandas provides two simple ways to count the number of rows in a DataFrame object: using the shape attribute and the len() function.

Using the DataFrame Shape Attribute

The shape attribute of the DataFrame object can be used to get the number of rows and columns in the DataFrame. Since the number of rows in the DataFrame corresponds to the number of lines in the CSV file, we can use the first element of the shape attribute tuple to get the number of lines in the CSV file.

Example

# Import the pandas library as pd
import pandas as pd

# Read the CSV file into a pandas DataFrame object
df = pd.read_csv('filename.csv')


# Get the number of rows in the DataFrame, which is equal to the number of lines in the CSV file
num_lines = df.shape[0]

# Print the number of lines in the CSV file
print("Number of lines in the CSV file: ", num_lines)

In the above code, we are using the shape attribute of the DataFrame object to get the number of rows in the DataFrame, which corresponds to the number of lines in the CSV file. We are then storing this value in the num_lines variable and printing it to the console. The output of the above code snippet will look something like this:

Output

Number of lines in the CSV file:  10

Now that we know how to count the number of lines in a CSV file in python using the Dataframe shape attribute, let’s move ahead and learn about the len() method:

Using the len() Function

Alternatively, we can also use the built-in len() function to count the number of rows in the DataFrame, which again corresponds to the number of lines in the CSV file.

Example

# Import the pandas library as pd
import pandas as pd

# Read the CSV file into a pandas DataFrame object
df = pd.read_csv('filename.csv')

# Count the number of rows in the DataFrame object using the built-in len() function
num_lines = len(df)

# Print the number of lines in the CSV file
print("Number of lines in the CSV file: ", num_lines)

In the above code excerpt, we are using the len() function to get the number of rows in the DataFrame, which again corresponds to the number of lines in the CSV file. We are then storing this value in the num_lines variable and printing it to the terminal. Again, the output of the above code will look something like this:

Output

Number of lines in the CSV file:  10

Conclusion

In this tutorial, we learned how to count the number of lines in a CSV file using Python and the Pandas library. We provided examples for two methods: using the DataFrame shape attribute and using the built−in len() function. By using Pandas, we can easily read the CSV file into a DataFrame object, and then count the number of rows in the file using the shape attribute or the len() function. We also provided a working code example for each of the methods to make it easier for you to follow along.