# How to Make Barplots with Seaborn (With Examples)

A barplot is a type of plot that displays the numerical values for different categorical variables.

This tutorial explains how to create heatmaps using the Python visualization library Seaborn with the built-in tips dataset:

```import seaborn as sns

#view first five rows of tips dataset

total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4```

### Make a Basic Barplot

The following syntax shows how to make a simple barplot that displays the time of day along the x-axis and the mean tip along the y-axis:

```sns.barplot(x="time", y="tip", data=data)
``` The barplot displays the standard error of the mean for each bar by default, but we can turn these off by using the argument ci=None as follows:

`sns.barplot(x="time", y="tip", data=data, ci=None)` ### Order the Bars in the Barplot

We can use the order argument to quickly put the bars in a certain order:

`sns.barplot(x="time", y="tip", data=data, order=["Dinner", "Lunch"])` ### Make a Grouped Barplot

We can make a grouped barplot by using the hue argument. For example, we can use the following syntax to display the mean tip grouped by day and sex:

`sns.barplot(x="time", y="tip", hue="sex", data=data)`

### Make a Horizontal Barplot

To create a horizontal barplot, we simply need to pass a categorical variable to the y argument and a numerical variable to the x argument:

`sns.barplot(x="tip", y="time", data=data)` ### Modify the Colors of the Barplot

We can use the palette argument to pass a list of colors to use for the bars in the barplot:

`sns.barplot(x="tip", y="time", palette=["pink", "green"], data=data)` 