Writing Code in Jupyter Notebook

In jupyter notebook the block which you are seeing is called as cell where the cursor is right now. A cell in jupyter notebook is where you write the code . You can have multiple cells at a time and even you can run multiple cells at a time .

Adding Multiple Cells

To add a cell just below the cell you can press the add button in cell at right corner

If you want to add cell just above the current cell you can click on the button which is just left to the button for adding cell below. If you press Esc you can go to command mode and then if you will press B it will automatically add a new cell below the current cell or if you will presss A it will add above the current cell and that new cell will become the new current cell. So you can try either way.

Now it’s time to code ,select any of the cell

Now your half the job has been done all you have to do is run the code. To run the code you can click on the run button in the toolbar above and a dropdown will get open like that:

Select the “Run Selected Cell” option and it will run the code . You can the code even by pressing the Shift+Enter Shortcut which will also run the selected cell.

Moreover you can see that you can run cells below the current selected or cell above the current selected cell , you can even run multiple cells as you can see there is also an option saying ” Run All cells”.

You will also learn to run multiple cells . For that insert some cells and then write some code in them . Now select Run All Cells option from Run button dropdown.

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.