"A picture is worth a thousand words".
Most of us are familiar with this expression.(Images or visuals are powerful form of communication)
Data visualization plays an essential role in the representation of both small and large-scale data. It especially applies when trying to explain the analysis of increasingly large datasets.
Data Visualization basically refers to the graphical or visual rep. of
information and data using visual elements like chart/graphs and maps etc.
Several data visualization libraries are available in Python, namely Matplotlib, Seaborn, and Folium etc.
Purpose of Data visualization
• Better analysis
• Quick action
• Identifying patterns
• Finding errors
• Understanding the story
• Exploring / building business strategies.
• Grasping the Latest Trends
Plotting library
• Matplotlib is the whole python package/ library used to create 2D graphs and plots by using python scripts.
• Pyplot is a module in matplotlib, which supports a very wide variety of graphs and plots namely - histogram, bar charts, power spectra, error charts etc. It is used along with NumPy to provide an environment for MatLab.
Types of Visualization
• There are many types of visualizations available with Matplotlib.
Some of the most famous are:
Line plot, bar chart, histogram, scatter chart, box plot and pie chart etc.
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