Question

Enlist 2 differences between matplotlib vs Seaborn

and for what type of visualization would you use one over the other?

Answer 1

.Python is one of the most popular languages for visualization with its variety of tools.

Two of Python’s greatest visualization tools are Matplotlib and Seaborn. Seaborn library is basically based on

Matplotlib.

Here is a detailed comparison between the two:

==> Handling Multiple Figures:

Matplotlib: Matplotlib has multiple figures can be opened, but need to be closed explicitly. plt.close() only closes the current figure. plt.close(‘all’) would close em all.

Seaborn: Seaborn automates the creation of multiple figures. This sometimes leads to out of memory issues.

==> Data frames and Arrays

Matplotlib: Matplotlib works with data frames and arrays. It has different stateful APIs for plotting.

The figures and aces are represented by the object and therefore plot() like calls without parameters suffices, without having to manage parameters.

Seaborn: Seaborn works with the dataset as a whole and is much more intuitive than Matplotlib.

For Seaborn, replot() is the entry API with ‘kind’ parameter to specify the type of plot which could be line, bar, or many of the other types. Seaborn is not stateful. Hence, plot() would require passing the object.

==> Use Cases:
Matplotlib: Pandas uses Matplotlib.

Seaborn: Seaborn is for more specific use cases. Also, it is Matplotlib under the hood.

Matplotlib: It is a Python library used for plot the  graphs with help of other libraries like Numpy and Pandas. It is  powerful tool for visualizing data in Python. It is capable of dealing with various operating systems and their graphical backends.t is used for creating statical interferences and plotting 2D graphs of arrays.

Seaborn:

• It is also a Python library used for plotting graphs with the help of Matplotlib, Pandas, and Numpy.
• It is built on the roof of Matplotlib and is considered as a superset of the Matplotlib library.
• It helps in visualizing univariate and bivariate data.
• It serves in making graphs of statical Time-Series data.
• It uses beautiful themes for decorating Matplotlib graphics.
• It acts as an important tool in picturing Linear Regression Models.

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==> Which One Should You Use
Both the popular visualization tools used in Python have differences in use cases, scalability and many other things. Based on these one should select the best visualization tool for a particular work. If one is doing statistics then Seaborn is good choice because it has a lot of things suitable for statistical tasks, built-in.