Siksha Sarovar

Siksha Sarovar (sikshasarovar.com) is a free educational web application that helps students in India learn programming and prepare for academic and competitive exams. The platform offers structured coding courses (C, C++, Python, Java, HTML, CSS, PHP, Power BI, AI, Machine Learning, Data Science), complete university curriculum notes for BCA/MCA students with previous year question papers, Class 10 and Class 12 CBSE/HBSE school notes, and dedicated preparation material for SSC, UPSC, Banking, Railway and other government exams. Browsing the site is completely free and requires no account. Users may optionally sign in with Google solely to save their learning progress, quiz scores and personal preferences across devices.

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Siksha Sarovar is a free e-learning platform for coding courses, BCA university notes and competitive exam preparation. Optional Google sign-in saves your learning progress across devices.

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4. Data Visualization

Lesson 4 of 21 in the free Machine Learning notes on Siksha Sarovar, written by Rohit Jangra.

The Power of Visualization

A picture is worth a thousand rows of data. Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

The Python Visualization Ecosystem

LibraryTypeBest For
MatplotlibLow-levelThe detailed foundation. Can create any plot, but requires more code. Great for publication-quality static plots.
SeabornHigh-levelBuilt on top of Matplotlib. Beautiful default styles, easy statistical plots (Heatmaps, Violin plots).
PlotlyInteractiveWeb-based interactive plots (Zoom, Pan, Hover). Great for dashboards and presentations.

Common Plot Types

  1. Histogram: Shows the distribution of a single numerical variable.
  2. Scatter Plot: Shows the relationship between two numerical variables.
  3. Bar Chart: Compares categories.
  4. Box Plot: Shows summary statistics (median, quartiles, outliers).
  5. Heatmap: Visualizes correlation matrices or 2D density.

Design Principles

  • Clarity: Don't clutter with unnecessary ink.
  • Integrity: Don't distort axes to mislead.
  • Color: Use color to highlight data, not just decoration.