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