Pandas Drop 1970 - Python

Pandas is a popular Python library used for data manipulation and analysis. In this tutorial, we will learn how to use the drop function in Pandas to remove rows that have a specific value. Specifically, we will be removing rows that have a year of 1970.

Installing Pandas

Before we can use the Pandas library, we need to install it. Open up your terminal or command prompt and type the following command:

!pip install pandas

Importing Pandas

We will now import the pandas library into our Python project:

import pandas as pd

Loading Data

For this tutorial, we will be using a simple CSV file that contains some data about countries. You can download the file here, or you can use the following code to download and load the data:

url = "https://raw.githubusercontent.com/plotly/datasets/master/2014_world_gdp_with_codes.csv"
data = pd.read_csv(url)

print(data.head())

This code will load the data into a Pandas DataFrame and display the first 5 rows.

Removing Rows

Now that we have loaded the data, we can remove rows that have a year of 1970. We will use the drop function in Pandas to do this.

data = data.drop(data[data.year == 1970].index)
print(data.head())

This code will remove any rows that have a year of 1970 and then display the first 5 rows of the modified DataFrame.

Conclusion

The Pandas library is a powerful tool for data manipulation and analysis in Python. The drop function can be used to remove rows that have a specific value. In this tutorial, we used the drop function to remove rows that have a year of 1970.