How to add , remove and select cells in jupyter notebook?
In order to add cells you need to know the answer of one question .
1.Adding Cells Markdown and Code
- Adding a Code Cell: In order to add a new cell under the current cell you can press ‘B’ while in command mode or click the “+” button in toolbar for adding new cell under the current cell.
click on plus sign to add below
new cell has been added below
- In order to add a new cell above the current cell you can press ‘A’ while in command mode or click ‘+’ button in toolbar for adding new cell above the current cell.
click on left side + button as in picture to add above the cell new cell
new cell get added above it
- Adding Markdown Cell: In order to add a new markdown below the current cell you can press ‘B’ and change cell to markdown pressing ‘M’.
new markdown cell get added below
In order to add a new markdown above the current cell you can press ‘A’ and change cell to markdown pressing ‘M’.
2.Removing Cells
Let’s learn how to remove the cells with following methods:
- First you need to select the cell click anywhere inside cell it will get selected .
- Now go in command mode pressing ‘Esc’ key . Now press D twice quickly . This will delete the cell . You can even use toolbar to delete the particular cell.
select delete icon from toolbar to delete cell
3.Select Cells
As for now we have learn you can select a cell by pressing anywhere inside it , but you can even select multiple cells, let’s see how?
- You can select single cell by pressing anywhere inside it.
- Selecting multiple cells: To select multiple cells consecutively hold down ‘Shift’ key and click on cells you want to select.
Selected multiple cells are in blue shade
- Selecting All cells: Go in command mode pressing ‘Esc’ and press ‘Ctrl’+ ‘A’ it will select all cells in notebook .
All cells get selected whether code or markdown
How to Write and Run Code in Jupyter Notebook
Jupyter Notebook is an open-source web application. It allows to generate and share documents that contain live code, equations, visualized data, and many more features. Nowadays it has become the first choice of many of the data scientists due to it’s immense data visualization and analysis capability. It has various packages which makes it easy to visualize data efficiently.
The Jupyter project has continued to evolve, and it includes a family of tools, such as JupyterLab and JupyterHub, which extend the capabilities of the original Jupyter Notebook. These tools cater to different use cases and make Jupyter an even more powerful platform for interactive computing and data science.
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