Data Visualization with VScode, Jupyter Notebooks and Python.

When working with data, it can be challenging to fully comprehend your data if it is just presented in tabular form. We must visualize or represent our data visually in order to fully comprehend what it means, to properly clean it, and to choose the best models for it. This makes patterns, correlations, and trends more obvious that cannot be seen in data that is presented as a table or CSV file.

Data visualization is the act of using visual representations of our data to identify trends and relationships. We can utilize a variety of Python data visualization libraries, like Matplotlib, Seaborn, Plotly, etc., to do data visualization.We will go over how to use some of these modules for data visualization in Python and go into great detail about the following subjects in this post, The Complete Guide to Data Visualization in Python.

What is Data Visualization?
Data Visualization in Python
Matplotlib and Seaborn
Line Charts
Bar Graphs
Histograms
Scatter Plots
Heat Maps
Below is the link to the different types of data visualization(https://github.com/jvicmaina/Vscode-Jupyter-python)