DATA VISULIZATION

Data visualization is the graphical representation of data and information. It involves creating visual elements such as charts, graphs, and maps

to help understand

• trends,
• patterns,
• insights in the data.

WORKING:

1. Data Preparation:

Gather and preprocess the data to ensure it's in a suitable format for visualization.

2. Choose Visualization Type:

Select the appropriate type of chart or graph based on the data and the insights you want to convey.

3. Plotting:

Use a data visualization library to create the visual representation of the data.

4. Customize:

Enhance the visualization by adding labels, titles, colors, and other visual cues to improve readability.

5. Interpretation:

Analyze the visualization to draw meaningful conclusions and communicate the findings effectively to the audience.

Data visualization lab tools:

1. Matplotlib
2. Seaborn
3. Power BI
4. Tableau
5. Excel
6. Google Data Studio
7. QlikView