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Content added to pandas #196

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f323833
Fixed & UI Enhancement: Makes the Sidebar Sticky
sandy088 Oct 22, 2023
6dc781d
Fixed: Made main content Responsive
sandy088 Oct 23, 2023
c019908
Add: Content added to Numpy Page + responsive
sandy088 Oct 24, 2023
a70ff09
docs: Write PandasBasics Page Content + Styling
sandy088 Oct 24, 2023
c6e0dfe
Merge branch 'main' into Content-Added-to-Pandas
sandy088 Oct 24, 2023
e8b1c69
Merge branch 'main' into Content-Added-to-Pandas
sandy088 Oct 24, 2023
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3 changes: 2 additions & 1 deletion index.html
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<head>
<meta charset="UTF-8" />
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<script type="module" src="https://unpkg.com/[email protected]/dist/ionicons/ionicons.esm.js"></script>
<script nomodule src="https://unpkg.com/[email protected]/dist/ionicons/ionicons.js"></script>
<title> PyLibLog</title>
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2 changes: 1 addition & 1 deletion src/Python_Library_Pages/Matplotlib/Intro-to-Matplotlib.jsx
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Expand Up @@ -2,7 +2,7 @@ import React from "react";

const MatplotlibBasics = () => {
return (
<div>
<div className=" break-words w-screen lg:w-auto overflow-x-hidden px-7 my-10">
<h1>Introduction to Matplotlib</h1>

<p>Development can start for Matplotlib from here</p>
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73 changes: 69 additions & 4 deletions src/Python_Library_Pages/Numpy/Intro-to-Numpy.jsx
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const NumpyBasics = () => {
return (
<div>
<h1>Introduction to NumPy</h1>
<div className="w-full lg:w-auto p-6 lg:p-10">
<h1 className="text-3xl font-bold text-gray-700">Introduction to NumPy</h1>

<p>Development can start for NumPy from here</p>
<p className="mt-4 text-gray-600 text-lg">
NumPy, short for Numerical Python, is a fundamental library in the Python ecosystem for numerical and scientific computing. It provides support for large, multi-dimensional arrays and matrices, along with a collection of high-level mathematical functions to operate on these arrays. NumPy is a must-know tool for anyone involved in data analysis, machine learning, scientific research, and more.
</p>

<h2 className="text-2xl font-bold text-gray-700 mt-6">Why NumPy?</h2>

<p className="mt-4 text-gray-600 text-lg">
You might be wondering why you should use NumPy when Python itself has a rich set of data structures and functions. Here are some compelling reasons:
</p>

<ul className="list-disc ml-6 text-gray-600 text-lg">
<li>
<b>Efficiency:</b> NumPy is implemented in C, which makes it faster and more efficient than pure Python code. It leverages pre-compiled functions and avoids the overhead of interpreting Python code.
</li>
<li>
<b>Multi-dimensional Arrays:</b> NumPy provides a powerful <code>ndarray</code> data structure, which allows you to work with arrays of any dimension (vectors, matrices, tensors) efficiently.
</li>
<li>
<b>Mathematical Functions:</b> NumPy includes a wide range of mathematical functions, including linear algebra, statistics, Fourier analysis, and more.
</li>
<li>
<b>Broadcasting:</b> NumPy's broadcasting feature allows you to perform operations on arrays of different shapes, making your code more concise and readable.
</li>
<li>
<b>Interoperability:</b> NumPy integrates seamlessly with other scientific libraries in Python, such as SciPy, Matplotlib, and Pandas.
</li>
</ul>

<h2 className="text-2xl font-bold text-gray-700 mt-6">Getting Started</h2>

<p className="mt-4 text-gray-600 text-lg">
Before you dive into NumPy, you'll need to ensure that Python and NumPy are installed on your system. Let's go through the installation process:
</p>

<h3 className="text-xl font-bold text-gray-700 mt-6">Python Installation (if needed)</h3>
<p className="mt-2 text-gray-600 text-lg">
If you haven't installed Python, follow these steps to get it up and running on your system:
</p>

<div className="bg-gray-100 p-4 rounded-lg mt-4">
<h4 className="text-lg font-bold text-gray-700">For Windows:</h4>
<ol className="list-decimal ml-6 text-gray-600">
<li>Visit the official Python website at <a href="https://www.python.org/" className="text-blue-500">python.org</a></li>
<li>Navigate to the "Downloads" section.</li>
<li>Click on the latest version of Python for Windows.</li>
<li>Run the downloaded installer.</li>
<li>Check the box that says "Add Python to PATH" during installation.</li>
<li>Click "Install Now" to start the installation process.</li>
<li>Open a Command Prompt or PowerShell.</li>
<li>Type <code>python --version</code> or <code>python -V</code> and press Enter to verify the installation.</li>
</ol>
</div>

<h2 className="text-2xl font-bold text-gray-700 mt-8">Installing NumPy</h2>

<p className="mt-4 text-gray-600 text-lg">
Once Python is installed, it's straightforward to install NumPy. Open your terminal or command prompt and run the following command:
</p>

<div className="bg-gray-800 p-4 text-white rounded-lg mt-4">
<code>pip install numpy</code>
</div>

<p className="mt-4 text-gray-600 text-lg">
This command will install NumPy on your system. Once NumPy is installed, you're ready to dive into the world of numerical computing with Python. Let's start exploring NumPy and its capabilities!
</p>
</div>
);
};

export default NumpyBasics;
export default NumpyBasics;
92 changes: 88 additions & 4 deletions src/Python_Library_Pages/Pandas/Intro-to-Pandas.jsx
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Expand Up @@ -2,12 +2,96 @@ import React from "react";

const PandasBasics = () => {
return (
<div>
<h1>Introduction to Pandas</h1>
<div className="w-full lg:w-auto p-6 lg:p-10">
<h1 className="text-3xl font-bold text-gray-700">Introduction to Pandas</h1>

<p>Development can start for Pandas from here</p>
<p className="mt-4 text-gray-600 text-lg">
Welcome to the world of Pandas, where you'll learn to wield the power of data with ease. Pandas is more than just a cute bear; it's also a versatile Python library that empowers you to manipulate, analyze, and visualize data effortlessly. Let's dive deeper into Pandas basics.
</p>

<h2 className="text-2xl font-bold text-gray-700 mt-6">What is Pandas?</h2>

<p className="mt-4 text-gray-600 text-lg">
Pandas is a data manipulation and analysis library for Python. It provides you with easy-to-use data structures and functions that enable you to work with structured data effectively. If you've ever worked with data in spreadsheets or databases, Pandas will feel like a familiar friend.
</p>
<p className="mt-2 text-gray-600 text-lg">
At its core, Pandas introduces two main data structures: the <strong>Series</strong> and the <strong>DataFrame</strong>. A Series is like a one-dimensional array with labels, while a DataFrame is a two-dimensional table like a spreadsheet or SQL table. These structures open up endless possibilities for data manipulation.
</p>

<h2 className="text-2xl font-bold text-gray-700 mt-6">Key Features of Pandas:</h2>
<ul className="list-disc ml-6 text-gray-600 text-lg">
<li>
<b>Data Structures:</b> Pandas provides the Series and DataFrame data structures to store and work with data. These structures are highly flexible and can handle various data types.
</li>
<li>
<b>Data Cleaning:</b> Data is rarely perfect. Pandas offers powerful tools to clean and preprocess data, such as handling missing values, removing duplicates, and more.
</li>
<li>
<b>Data Selection:</b> You can easily select and filter data, allowing you to focus on the information relevant to your analysis.
</li>
<li>
<b>Data Aggregation:</b> Pandas enables you to summarize data, create pivot tables, and aggregate information based on specific criteria.
</li>
<li>
<b>Data Visualization:</b> While not a dedicated visualization library, Pandas can work seamlessly with libraries like Matplotlib and Seaborn to create insightful plots and charts.
</li>
</ul>

<h2 className="text-2xl font-bold text-gray-700 mt-6">Why Use Pandas?</h2>

<p className="mt-4 text-gray-600 text-lg">
You might be wondering, "Why should I bother with Pandas when I can work with data in other ways?" The answer lies in Pandas' efficiency and user-friendliness.
</p>
<p className="mt-2 text-gray-600 text-lg">
Without Pandas, you'd find yourself writing numerous lines of code to perform even the simplest data operations. Pandas simplifies data manipulation tasks, streamlining the process and making it more intuitive.
</p>
<p className="text-gray-600 text-lg mt-2">
Here are a few scenarios where Pandas shines:
</p>
<ul className="list-disc ml-6 text-gray-600 text-lg">
<li>
<b>Data Exploration:</b> Quickly get an overview of your dataset by inspecting its structure and contents.
</li>
<li>
<b>Data Cleaning:</b> Address issues like missing values, outliers, and duplicate records without the headache of manual data wrangling.
</li>
<li>
<b>Data Transformation:</b> Shape your data to suit your analysis needs, whether it's reshaping, pivoting, or aggregating.
</li>
<li>
<b>Data Analysis:</b> Dive into in-depth analysis by selecting, filtering, and aggregating data, and create visualizations for better insights.
</li>
</ul>

<h2 className="text-2xl font-bold text-gray-700 mt-6">How to Get Started with Pandas:</h2>
<p className="mt-4 text-gray-600 text-lg">
Are you excited to harness the power of Pandas? Let's get you started with some foundational steps:
</p>
<ol className="list-decimal ml-6 text-gray-600 text-lg">
<li>
<b>Install Pandas:</b> First, ensure you have Python installed on your system. Then, open your terminal or command prompt and install Pandas using pip:
<div className="bg-gray-800 p-4 rounded-lg mt-2">
<pre className="text-gray-100">pip install pandas</pre>
</div>
</li>
<li>
<b>Import Pandas:</b> In your Python script or Jupyter Notebook, import Pandas to access its functionality:
<div className="bg-gray-800 p-4 rounded-lg mt-2">
<pre className="text-gray-100">import pandas as pd</pre>
</div>
</li>
<li>
<b>Create a DataFrame:</b> You can create a DataFrame from various data sources, such as Python dictionaries or by reading data from files like CSV, Excel, or a SQL database.
</li>
<li>
<b>Start Exploring:</b> Dive into your data. Use Pandas functions to examine your dataset's structure, clean it if necessary, and begin your analysis.
</li>
</ol>
<p className="text-gray-600 text-lg mt-6">
Get ready to embark on your journey into the world of data analysis and manipulation with Pandas. Whether you're working on business data, scientific research, or any data-related project, Pandas simplifies your path to success. Remember, practice and experimentation are key to mastering Pandas, so don't hesitate to get your hands dirty with real data.
</p>
</div>
);
};

export default PandasBasics;
export default PandasBasics;
2 changes: 1 addition & 1 deletion src/Python_Library_Pages/Python_Basics/Intrduction-to-Operators.jsx
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Expand Up @@ -2,7 +2,7 @@ import React from "react";

const OperatorsBasics = () => {
return (
<div>
<div className=" break-words w-screen lg:w-auto overflow-x-hidden px-7 my-10">
<h1>Introduction to Operators in Python</h1>

<p>Development can start for Python from here</p>
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2 changes: 1 addition & 1 deletion src/Python_Library_Pages/Python_Basics/Introduction-to-Functions.jsx
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Expand Up @@ -2,7 +2,7 @@ import React from "react";

const FunctionsBasics = () => {
return (
<div>
<div className=" break-words w-screen lg:w-auto overflow-x-hidden px-7 my-10">
<h1>Introduction to Functions in Python</h1>

<p>Development can start for Python from here</p>
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55 changes: 29 additions & 26 deletions src/Python_Library_Pages/Python_Basics/Introduction-to-Python.jsx
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Expand Up @@ -2,45 +2,48 @@ import React from "react";

const PythonBasics = () => {
return (
<div>
<div className=" break-words w-screen lg:w-auto overflow-x-hidden px-7 my-10">

<h1><b>1. Introduction to Python</b></h1>
<br />
<pre>
<code>
{`Python is a high-level, interpreted programming language known for its readability and simplicity. It:
- Supports multiple programming paradigms.
- Has a large standard library.
- Python is free and easy to learn.

<pre className="text-sm overflow-x-auto p-5">
<code>
{`Python is a high-level, interpreted programming language known for its readability and simplicity. It:
- Supports multiple programming paradigms.
- Has a large standard library.
- Python is free and easy to learn.

This doc will help you to get all the knowledge you want for getting started with Python.
If you have never programmed anything before and are just getting started, this might be the blog for you.
Python has many use cases in different industries such as

Web Development:
- Frameworks like Django and Flask make Python a popular choice for building web applications.
Web Development:
- Frameworks like Django and Flask make Python a popular choice for building web applications.

Data Science and Machine Learning:
- Python is extensively used for data analysis, machine learning, and artificial intelligence.
- Libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch are widely employed.
Data Science and Machine Learning:
- Python is extensively used for data analysis, machine learning, and artificial intelligence.
- Libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch are widely employed.

Finance:
- Python is used in finance for quantitative analysis, risk management, and algorithmic trading.
- Libraries such as Pandas and NumPy are particularly useful in this domain.
Finance:
- Python is used in finance for quantitative analysis, risk management, and algorithmic trading.
- Libraries such as Pandas and NumPy are particularly useful in this domain.

Education:
- Python is widely used in teaching programming due to its simplicity.
- It's often the first language taught in many computer science courses.
Education:
- Python is widely used in teaching programming due to its simplicity.
- It's often the first language taught in many computer science courses.

Game Development:
- Python is used in the game development industry, and libraries like Pygame make it
easier to develop 2D games.

GIS (Geographic Information System):
- Python is used for GIS applications, and libraries like Geopandas and ArcPy are popular
in this field.`}
</code>
</pre>

Game Development:
- Python is used in the game development industry, and libraries like Pygame make it
easier to develop 2D games.

GIS (Geographic Information System):
- Python is used for GIS applications, and libraries like Geopandas and ArcPy are popular
in this field.`}
</code>
</pre>
<br />
<br />

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