This repository depicts various types of data visualization techniques with the help of three useful python libraries for data visualization: Matplotlib, Seaborn, and Plotly Express. Following data visualization operations are performed:

1. Basic line plot
2. Scatter plot
3. Pie charts
4. Histograms
5. Multiple plots
6. Subplots
7. 3D plots

1. Scatter plot and count plot
2. Pair plot
3. heatmaps/correlations
4. dist plot

1. Interactive scatter plot
2. Interactive bubble chart
3. Interactive single line plot
4. Interactive multiple line plot
5. Interactive pie charts
6. Interactive bar chart
7. Interactive gantt chart
8. Interactive sunburst

All plots in this notebook are plotted using plotly.express. This plots are useful for visualizing statistical data for data science projects.

1. Interactive box plot
2. Interactive histograms
3. Interactive histograms with marginal plots
4. Interactive density map
5. Interactive scatter matrix
6. Interactive violin plot
7. Interactive 2D histogram contour plot