How to Load a CSV File in Jupyter Notebook | Import CSV in Jupyter Notebook

Need to *load and analyze CSV files* in Jupyter Notebook? 📊 In this tutorial, we’ll walk you through different methods to *import CSV files into Jupyter Notebook* using Python. Whether you're working on **data science, machine learning, or data analysis**, handling CSV files is an essential skill.

By the end of this video, you’ll be able to *read, explore, and manipulate CSV files* in Jupyter Notebook like a pro! 🚀

🔹 *What You’ll Learn in This Video:*
✅ How to open Jupyter Notebook and set up your environment
✅ Methods to *import a CSV file* into Jupyter Notebook
✅ Using *Pandas* to load and manipulate CSV data
✅ Handling CSV file paths (relative & absolute paths)
✅ Dealing with *missing values and data types*
✅ Saving and exporting CSV files after processing
✅ Common errors when loading CSVs and how to fix them

---

*🚀 Step-by-Step Guide to Importing CSV in Jupyter Notebook*

#### *1️⃣ Install Pandas (If Not Installed)*
First, ensure you have *pandas* installed in your Python environment. If not, install it using:
```bash
pip install pandas
```

#### *2️⃣ Open Jupyter Notebook*
To launch Jupyter Notebook, run the following command in your terminal or command prompt:
```bash
jupyter notebook
```

#### *3️⃣ Import Required Libraries*
```python
import pandas as pd
```

#### *4️⃣ Load a CSV File from the Same Directory*
If your CSV file is in the *same directory* as your Jupyter Notebook, use:
```python
df = pd.read_csv("data.csv")
print(df.head()) # Display the first 5 rows
```

#### *5️⃣ Load a CSV File from a Different Directory*
Use an *absolute path* if your file is stored elsewhere:
```python
df = pd.read_csv("C:/Users/YourName/Documents/data.csv") # Windows
df = pd.read_csv("/home/username/documents/data.csv") # Mac/Linux
```

#### *6️⃣ Handling Missing Values & Data Types*
```python
df.info() # Check data types and missing values
df.fillna(0, inplace=True) # Replace missing values with 0
df["column_name"] = df["column_name"].astype(float) # Convert data type
```

#### *7️⃣ Saving Processed Data to a New CSV File*
```python
df.to_csv("cleaned_data.csv", index=False)
```

---

*📌 Useful Links:*
🔗 Pandas Documentation: [https://pandas.pydata.org/docs/](https://pandas.pydata.org/docs/)
🔗 Jupyter Notebook Guide: [https://jupyter.org/](https://jupyter.org/)

🚀 *Have Questions?* Drop a comment below! If you found this tutorial helpful, *LIKE* 👍 this video, *SUBSCRIBE* 🔔 for more Python and Jupyter Notebook tutorials, and *SHARE* with your friends!

📌 *Hashtags:*
#Python #JupyterNotebook #DataScience #Pandas #CSVFiles #PythonDataAnalysis #MachineLearning #PythonTutorial #DataAnalytics #JupyterTips