How to Load Data From url using Pandas

 

Loading data from a url is a common task in data analysis and machine learning. To load data from a url using pandas, you can use pandas.read_html() function. This function allows you to read tables from html pages and returns a list of DataFrame objects, one for each table in the page.

You can also use pandas.read_csv(url) function. This function allows you to specify the url where the csv file is located, and it returns a DataFrame with the data.

It’s important to note that, before loading the data, you need to make sure that the url is accessible and the data is in the correct format, including the correct delimiter, correct data type and correct missing values.

In summary, loading data from a url is a common task in data analysis and machine learning. To load data from a url using pandas, you can use pandas.read_html() function to read tables from html pages and returns a list of DataFrame objects, one for each table in the page. You can also use pandas.read_csv(url) function. This function allows you to specify the url where the csv file is located and it returns a DataFrame with the data. Before loading the data, you need to make sure that the url is accessible and the data is in the correct format, including the correct delimiter, correct data type and correct missing values.

 

In this Applied Machine Learning & Data Science Recipe, the reader will learn: How to Load Data From url using Pandas.

 

Essential Gigs