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3-plotting-data-visualizations

README.md

Data Analysis Using Python: A Beginner’s Guide Featuring NYC Open Data

Part 3: Plotting and Visualizations

Mark Bauer

Introduction
Part 3 demonstrates various examples of plotting and data visualizations. The project is located in my notebook 3_plotting_visualizations.ipynb. Additionally, you can view the notebook as a static webpage here. Below, you will find the data visualization gallery.

Data Visualization Gallery

3. Seaborn Library

3.1 Distribution Plots

3.1.1 Histograms

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3.1.2 Kernel Density Estimate (KDE) Plot

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3.1.3 Empirical Cumulative Distribution Functions (ECDF)

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3.1.4 Distribution Plots onto a Facet Grid

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3.2 Relational Plots

3.2.1 Line Plots

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3.2.2 Scatter Plot

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3.2.3 Relational Plots onto a Facet Grid

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3.3 Joint Grids

3.3.1 Scatter Plot

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3.3.2 Hexagonal Bin Plots

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3.3.3 Kernel Density Estimate (KDE) Plot

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3.4 Visualizing Pairwise Relationships in a Dataset

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3.5 Heat Map

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3.6 Categorial Plots

3.6.1 Count Plots

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3.6.2 Bar Plots

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3.6.3 Scatter Plots

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3.6.4 Swarm Plots

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3.6.5 Box Plots

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3.6.6 Boxen Plots

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3.6.7 Violin Plots

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3.6.8 Point Plots

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3.6.9 Facets

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4. pandas and Matplotlib Libraries

4.1 Line Plot

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4.2 Bar Plot

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4.3 Histogram

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4.4 Box Plot

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4.5 Kernel Density Estimate (KDE) Plot

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4.6 Area Plot

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4.7 Scatter Plot

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4.8 Hexagonal Bin Plot

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4.9 Pie Plot

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