🖌 Matplotlib Mastery Portfolio

Welcome to my Matplotlib Projects Repository! This repository showcases my hands-on expertise in Python visualization, using Matplotlib for creating line charts, bar charts, histograms, scatter plots, and customized plots for real-world inspired data. The projects demonstrate my ability to visualize, compare, and analyze data effectively.

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📂 Repository Overview

Folder	File Name	Highlights
Matplotlib	matplotlib 1.ipynb	Basic line plots: colors, markers, linestyles, axis labels, titles, and simple bar charts.
Matplotlib	MATPOLTLIB.ipynb	Advanced line plots with multiple datasets, legends, customized markers, X-ticks customization, and error handling for multi-dimensional arrays.
Matplotlib	MATPOLTLIB line and bar.ipynb	Combined line & bar charts, multiple lines, horizontal and vertical bar plots, grid addition, sales comparison, random data plotting using NumPy, and multi-product comparisons.
Matplotlib	MATPOLILIB 2 PART.ipynb	Histograms (single & multiple), scatter plots (single, multiple, customized), color mapping, bar charts, and data distribution visualization.

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🚀 Skills Demonstrated

• Line Plots

  • Multiple lines on a single chart
  • Custom markers, colors, and linestyles
  • Legends and grid placement
  • X-ticks & Y-ticks customization

• Bar Charts

  • Vertical & horizontal bars
  • Single & multiple datasets comparison
  • Color customization and width adjustment

• Scatter Plots & Histograms

  • Single, multiple, and customized scatter plots
  • Histograms with bins, labels, and legends
  • Color intensity mapping with cmap

• Random Data Visualization

  • Using NumPy arrays for dynamic plotting
  • Understanding plotting restrictions for multi-dimensional arrays

• Data Analysis & Visualization

  • Comparing sales growth across months
  • Multi-product sales analysis
  • Department-wise comparison of personnel counts

• Professional Plot Customization

  • Axis labels, labelpad, and titles
  • Legends positioning and styling
  • Grid and figure customization for clarity

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📊 Example Visuals

Line Chart Example

import matplotlib.pyplot as plt
months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
sales = [120, 150, 170, 160, 180, 210]

plt.plot(months, sales, marker='o', color='green', linestyle='-.')
plt.xlabel("Months", labelpad=2)
plt.ylabel("Sales (in units)", labelpad=2)
plt.title("Sales Growth Over 6 Months")
plt.grid()
plt.show()