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Plotting, GUI and Databases

  Plotting Matplotlib is a Python library for data visualization . It helps you create charts, graphs, and plots to better understand and present data.  You can use it to draw: Line charts Bar charts Pie charts Scatter plots Histograms First, we have to import matplotlib. import matplotlib.pyplot as plt Here, matplotlib → main library pyplot → module that contains functions for creating plots pyplot provides a state-based interface — it keeps track of the current figure and axes, so you can create and modify plots easily with simple function calls. Commonly Used pyplot Functions: Function Description plt.plot() Draws line plots plt.scatter() Creates scatter plots plt.bar() Creates bar charts plt.hist() Plots histograms plt.pie() Creates pie charts plt.title() Adds a title to the plot plt.xlabel() / plt.ylabel() Labels axes plt.legend() Adds a legend plt.grid() Adds a grid plt.show() Displays the plot 1️⃣ Li...
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Numpy and Data Handling using Pandas

  Numpy NumPy is a Python tool that helps you work with numbers and arrays easily. It allows you to create and use multi-dimensional arrays, which are like lists but can have many rows and columns. NumPy is very fast and useful for handling large amounts of data. You can do many math operations with NumPy, like multiplying matrices, adding or subtracting numbers in arrays, and applying functions like squares or logarithms to each number.  It also has special functions for math related to linear algebra and random number generation. NumPy works well with other programming languages like C and C++, and it’s faster than regular Python lists because it uses precompiled code.  To start using it, you just need to install it with a simple command and then import it in your Python program. So, NumPy is a powerful and easy-to-use package for mathematic and data tasks in Python. Array In Python, an array is a collection of elements that all have the same data type, such as all inte...
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