How to import csv data in Jupyter?

To import CSV data into Jupyter Notebook, you can follow these steps:

1. First, make sure you have installed the pandas library. You can install it using the following command: !pip install pandas
2. Create a new code cell in Jupyter Notebook.
3. Import the pandas library as pd.
4. Use the function pd.read_csv() to read a CSV file, and the parameter of this function is the path of the CSV file. For example, if the CSV file is located in the file “data.csv” within the current working directory, you can import it using the following code: data = pd.read_csv(‘data.csv’)
5. If the path of the CSV file is not in the current working directory, you can provide the full path of the file. For example, if the CSV file is located at “C:/Users/username/Documents/data.csv”, you can use the following code to import it: data = pd.read_csv(‘C:/Users/username/Documents/data.csv’)
6. After the import is complete, you can perform various operations on the data, such as viewing the first few rows of the data or summarizing the statistics of the data. For example, you can use the data.head() function to view the first few rows of the data, with the default display showing the first 5 rows of data.

These are the basic steps for importing CSV data in Jupyter Notebook. You can further process and analyze the data as needed.