Course Synopsis

Advanced Data Visualization [Matplotlib, Seaborn & Plotly]

Become a Data Visualization Expert. Learn advanced techniques of data visualization using Matplotlib, Seaborn & Plotly.

*It is assumed that the learner is familiar with writing Python code.

Part 1: Data Visualization using Matplotlib

Introduction to Visualisation

Overview of Python Data Visualization Tools

Introduction to Matplotlib

Displaying Plots in Matplotlib

Data Manipulation With PANDAS

Matplotlib interfaces

Pyplot API

Figure and Subplots

First plot with Matplotlib

Line & Multiline Plots

Scatter Plot, Histogram, Bar Chart, Pie Chart, Box Plot, Area Chart, Contour Plot Adding a grid, Handling axes, Handling X and Y ticks

Sub Plotting

Part 2: Exploratory Data Analysis [Seaborn]

Visualize distribution of Age variable with Seaborn distplot() function

Seaborn Kernel Density Estimation (KDE) plot

Histograms

Visualize distribution of values in Preferred Foot variable with Seaborn countplot() function

Descriptive plots using catplot() function

Stripplot, Boxplot, Violinplot, Pointplot, Barplot, Facetgrid

Statistical relationship with Seaborn relplot() function

Part 3: Plotly Plots

Plotly's graphing library makes interactive, publication-quality graphs

Plotting interactive line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms

Heatmaps, subplots, bubble charts, stacked plotting, tree map plotting merging multiple plot graphs

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Advanced Data Visualization [Matplotlib, Seaborn & Plotly]

Course Highlights

Career Prospects

Advanced Data Visualization [Matplotlib, Seaborn & Plotly]

Part 1: Data Visualization using Matplotlib

Part 2: Exploratory Data Analysis [Seaborn]

Part 3: Plotly Plots

Digital Certificate

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