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Data-Visualizations

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About Data-Visualizations

Data Visualizations is a comprehensive educational resource designed to teach data visualization techniques essential for professionals in both IT and non-IT sectors. By transforming raw data into visual insights, users can make informed decisions, analyze customer behavior, identify root causes, and drive business profitability. The repository provides in-depth tutorials covering fundamental chart types including line plots, bar charts, scatter plots, and pie charts, as well as advanced visualizations such as scientific plots, 3D graphs, animated sequences, and interactive dashboards. Built using the Python ecosystem, the content teaches major libraries like Matplotlib, Seaborn, Plotly, Plotly Express, Bubbly, and Ipywidgets. These tutorials are hosted within Jupyter Notebooks and include a dedicated folder containing all necessary datasets for practical experimentation. A key highlight of the training is the use of Dash, enabling users to construct dynamic, interactive live dashboards without requiring prio

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Data-Visualizations

Data Visualizations is emerging as one of the most essential skills in almost all of the IT and Non IT Background Sectors and Jobs. Using Data Visualizations to make wiser decisions which could land the Business to make bigger profits and understand the root cause and behavioral analysis of people and customers associated to it. In this Repository I have deeply discussed about Line Plots, Bar plots, Scatter Plots, and Pie Charts, Apart from that I have Discussed scientific plots, 3d plots, animated plots, interactive plots to visualize any kind of business problem and that too of any complexity.

Data Visualizations using Python Data Visualization Library is the easiest way to perform Data Visualizations, and with the use of Dash, we can also, build up Dynamic and Interactive Live Dashboards without the help of Front end or backend javascript.

In this Tutorial, I have discussed all the Important and prominent Charts and their variations so that anybody can understand it easily. I have covered Matplotlib, seaborn, Plotly, Plotly-express, bubbly, ipywidgets. All the Tutorials are built upon JUpyter Notebooks, and the Datasets used for these Notebooks are already uploaded in a folder named Datasets.

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Contents

    1. Line Plots
    1. Bar Plots
    1. Pie Charts
    1. Scatter Charts
    1. Improving the Visibility of Charts
    1. Introduction to seaborn
    1. Introduction to Plotly
    1. Introduction to Plotly Express
    1. Introduction to Animated Visualizations
    1. Introduction to Interactive Visualizations

If any doubts or suggestions, please leave a message for me on linkedin.