📊 Comprehensive Methods for Uploading & Loading Data in Python

This repository presents a comprehensive guide to loading and importing various data types into Python using practical examples. Whether you're working with CSV files, Excel sheets, images, audio, or entire directories, this project provides clean, reusable code snippets to help you get started quickly.

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📁 Data Types Covered

✅ CSV & TSV ✅ Excel (.xlsx, .xls) ✅ Images (individual + folders) ✅ Audio files (e.g., .wav) ✅ JSON ✅ ZIP files ✅ Google Sheets ✅ URLs and web resources ✅ Files from Google Drive (for Colab users)

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🚀 Why This Project?

This notebook is ideal for:

• 📚 Data science and machine learning beginners
• 🧪 Rapid prototyping and experimentation
• 🔄 Streamlining repetitive data-loading tasks
• 🧰 Building up a personalized toolbox of I/O methods

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📓 Notebook Overview

• Step-by-step examples with explanations
• 🧼 Basic error handling
• 📌 Library references and best practices
• 🔧 Integration with pandas, os, cv2, scipy, requests, openpyxl, and more

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📦 Requirements

Install essential libraries with:

pip install pandas numpy opencv-python openpyxl requests gdown librosa

For Colab users, most packages are pre-installed. You can also use:

!pip install -r requirements.txt

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💻 How to Use

1. Clone the repository:

   git clone https://github.com/saharnazyp/Comprehensive-Methods-for-Uploading-Loading-Data.git
   cd Comprehensive-Methods-for-Uploading-Loading-Data

2. Open the notebook in Jupyter or Colab:

   jupyter notebook Load_Data_Guide.ipynb

   or use the Colab badge if you add one:

   [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/saharnazyp/Comprehensive-Methods-for-Uploading-Loading-Data/blob/main/Load_Data_Guide.ipynb)
   

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📌 Example Snippets

# Load CSV
import pandas as pd
df = pd.read_csv("data.csv")

# Load image from folder
import cv2
img = cv2.imread("images/sample.jpg")

# Load audio
import librosa
y, sr = librosa.load("audio/track.wav")

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🧑‍💻 Author

Created with 🧠 by Saharnaz Yaghoobpour 🎓 Data Science | Python | Machine Learning 📫 LinkedIn

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📄 License

This project is licensed under the MIT License. Feel free to use, share, or build on it.