Welcome to PyDataForge 🤖

A fusion of Python data libraries

Your go-to resource for learning Pandas, NumPy, and Matplotlib.

Pandas

import pandas as pd

Pandas is a powerful data analysis tool used to manipulate and analyze data. It's perfect for data cleaning, transforming, and analysis.

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NumPy

import numpy as np

NumPy is the fundamental package for numerical computing in Python. It provides support for arrays, matrices, and mathematical functions.

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Matplotlib

import matplotlib.pyplot as plt

Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. It's widely used for plotting data.

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Setup

Before diving into Pandas, NumPy, and Matplotlib, you need to set up your environment:

Download and install Anaconda - It includes Python and essential packages.
Set up a virtual environment using Anaconda or pip.
Install Pandas, NumPy, and Matplotlib using the following commands:

pip install pandas numpy matplotlib

For detailed setup instructions, click here.

Cheatsheet

Quick reference guides for Pandas, NumPy, and Matplotlib.

Pandas Cheatsheet

Importing: import pandas as pd
Read CSV: pd.read_csv('file.csv')
Create DataFrame: df = pd.DataFrame(data)
Head: df.head()
Describe: df.describe()

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NumPy Cheatsheet

Importing: import numpy as np
Create Array: np.array([1, 2, 3])
Zeros Array: np.zeros((3, 3))
Ones Array: np.ones((3, 3))
Arange: np.arange(0, 10, 2)

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Matplotlib Cheatsheet

Importing: import matplotlib.pyplot as plt
Basic Plot: plt.plot(x, y)
Show Plot: plt.show()
Title: plt.title('Title')
X-Label: plt.xlabel('X-axis')
Y-Label: plt.ylabel('Y-axis')

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Practice Datasets

Here are some datasets for you to practice your skills with Pandas, NumPy, and Matplotlib.

Dataset 1: Titanic

This dataset contains information about the passengers aboard the Titanic. Practice your data analysis skills by exploring survival rates, passenger demographics, and more.

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Dataset 2: Iris

This dataset includes measurements of sepal length, sepal width, petal length, and petal width for three species of Iris flowers. Use this dataset for classification practice.

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Dataset 3: MNIST

The MNIST dataset contains images of handwritten digits. Use this dataset to practice your machine learning and image processing skills.

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Get Certified

Ready to showcase your skills? Here are some great resources to get you certified in Pandas, NumPy, and Matplotlib.

FreeCodeCamp

FreeCodeCamp offers a variety of certifications that cover a wide range of topics including data analysis with Python.

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Coursera

Coursera provides comprehensive courses and certifications from top universities and companies in data science and machine learning.

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edX

edX offers certifications in data science and analytics, taught by leading institutions around the world.

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