Countplot in Python Tutorial with example

Countplot in Python Tutorial

Seaborn countplot in Python : In this point we have to create a counter plot in seaborn with python. Seaborn is a module in python that is built on top of matplotlib that is designed for plotting. Seaborn can plot all types of graphs. One graph to create is the counterplot using seaborn with the python. The seaborn is module in python that is build on top of matplotlib that is designed for statistical plotting. In counter plot the histogram or bar for some graph area is seen. It is very simple to show number of occurrence of item and is based on certain type of category. Bar graph is used for displaying relationship between data at least one numerical variable. Seaborn.countplot is the barplot and the dependent variable is number of instance of each independent variable. The countplot can be through a histogram across a categorical instead of variable. The API and option are identical to barplot() so you compare counts across nested variable. The vectors of data are the list, arrays, or pandas and directly passed to x, y and hue parameters. A wide dataframe in which numeric column will be plotted and array,list.
The function will always treat as categorical at position (0, 1…n).

Parameters:-

x, y, hue : names of variables in data or vector data, optional
Inputs for plotting long-form data.
data :
Dataset for plotting. If x and y are absent this is interpreted as wide-form.
order, hue_order :
Order to plot the categorical levels in otherwise the levels are inferred from the data objects.
orient :
This is usually inferred from the dtype of the input variables, but can be used to specify when the “categorical” variable is a numeric or when plotting wide-form data.
color :
Color for all of the elements or seed for a gradient palette.
palette :
Colors to use for the different levels of the hue variable.
saturation :
Proportion of the original saturation to draw colors at. Large patches often look better with slightly desaturated colors but set this to 1 if you want the plot colors to perfectly match the input color spec.
dodge :
When hue nesting is used whether elements should be shifted along the categorical axis.
ax :
Axes object to draw the plot onto otherwise uses the current Axes.
kwargs :
Other keyword arguments are passed to plt.bar.

Return:

ax :
Returns the Axes object with the plot drawn onto it.

Show point estimates and confidence intervals using bars.

Example:-
Show value that counts for a single categorical variable,
Import seaborn as sns
Sns.set (style=”darkgrid”)
titanic=sns.load_dataset(“titanic”)
ax=sns.countplot(x=”class”, data=titanic)
Output:-
seaborn countplot in Python