Scatter PlotsĪ scatter plot is a graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present.īefore plotting the scatter plot using Maplotlib and Seaborn, let us first load the dataset. Print("Matplotlib :", matplotlib._version_)Īs you can see, I have 3.6.0 and 0.12.0 versions of Matplotlib and Seaborn, respectively. To check whether the installation has been successful, run the following code, showing the installed versions of modules. However, strictly speaking, we could have gotten away with installing just Seaborn, because it includes Matplotlib as a dependency. We’ve shown how to install both tools above if you want to install matplotlib independently. You can use the pip command to install the modules: # installing the required modules Before going to the implementation part, ensure that you have installed Matplotlib and Seaborn modules on your system. We will directly jump into the practical part and create basic plots using Matplotlib and Seaborn modules. Seaborn is the extended version of Matplotlib, which uses Matplotlib, Numpy, and Pandas to plot graphs. Matplotlib plots various graphs using Pandas and Numpy. With the help of its default themes, Seaborn prevents overlapping plots. Matplotlib is highly customized and robust. It utilizes simple sets of techniques to produce lovely images in Python. Seaborn is more comfortable with Pandas data frames. Similar capabilities and syntax are available in Pyplot as in MATLAB, and users of MATLAB can readily understand it. Matplotlib is a Python graphics package for data visualization and integrates nicely with Numpy and Pandas. However, it may lead to (OOM) memory issues. You can close the current figure using the syntax ().Ĭlose all the figures using this syntax: (“all”) Seaborn sets the time for the creation of each figure. We can open and work with many figures at once. It has relatively simple syntax, making it simpler to learn and comprehend.Įxample: seaborn.barplot(x axis, y-axis) syntax for a bar graph. It utilizes syntax that is relatively complicated and extensive.Įxample: (x-axis, y-axis) is the syntax for a bar graph. Additionally, it offers data distribution. ![]() It employs engaging themes, and it helps in the integration of all data into a single plot. There are numerous patterns and graphs for data visualization in Seaborn. ![]() The following table compares the Matplotlib and Seaborn modules: Matplotlib Seaborn Matplotlib creates simple graphs, including bar graphs, histograms, pie charts, scatter plots, lines, and other visual representations of data. Moreover, you can use it to create static Time-Series data graphs. It helps in the visualization of univariate and bivariate data. It is a superset of the Matplotlib library and is constructed on top of it. Seaborn is also a Python library that utilizes Matplotlib, Pandas, and Numpy to plot graphs.It can work with different operating systems and their graphical front ends. Moreover, it also uses Pyplot to offer a free and open-source MATLAB-like interface. ![]() It is an effective Python tool for data visualization and is mainly used to plot 2D graphs of arrays.
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