![]() ![]() ![]() Having said that, it’s most common to use the countplot function on a dataframe, and in the examples section, we’ll be operating primarily on Pandas dataframes. Importantly, when you pass an argument to this parameter (like the name of a dataframe), the name does not need to be inside of quotation marks.Īdditionally, technically, this parameter is optional, meaning that you don’t necessarily need to provide an argument to this parameter. The argument to this is often a Pandas dataframe, but it can also be an array or a list of arrays. The data parameter enables you to specify the dataset that contains the data you want to plot. The countplot function has about a dozen parameters that control its behavior, but in my opinion, the most important are: Inside of the parenthesis, there are a few parameters that you use to control the function. As I just mentioned, this assumes that you’ve imported Seaborn with the alias sns. To call the function, you’ll type the syntax sns.countplot(). Ok, let’s look at the basic syntax to use the countplot function. This is the common convention among Seaborn users and Python data scientists, so we’ll use that import convention here. Having said that, we’re going to assume that you’ve imported Seaborn with the alias sns. Importantly, how exactly you import a package will have an impact on the syntax. Whenever we use a Python package like Seaborn, we need to import that package first. One quick note before we look at the syntax. In this section, I’ll explain the syntax to make a simple countplot, but I’ll also mention a few extra parameters that you can use to modify your countplot. Now that you have a high-level view of what the Seaborn countplot() function does, let’s look at the syntax.įor the most part, the syntax of sns.countplot is very simple. I’ll explain the differences at length in the FAQ section, but to summarize: the countplot function plots the count of records, but barplot plots a computed metric. ![]() Keep in mind that Seaborn has another tool for creating bar charts as well – the sns.barplot function. When you use sns.countplot, Seaborn literally counts the number of observations per category for a categorical variable, and displays the results as a bar chart.Įssentially, the Seaborn countplot() is a way to create a type of bar chart in Python. If you need something specific, you can click on any of the following links, and it will take you to the appropriate section of the tutorial.Ī quick introduction to the Seaborn Countplotįirst, I’ll just provide an overview of what the countplot function does.Īt a high level, the Seaborn Countplot function creates bar charts of the number of observations per category. I’ll explain what this function does, how the syntax works, and I’ll show you some step-by-step examples. In this tutorial, I’ll show you how to use the sns.countplot function to create a Seaborn countplot. ![]()
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