Quick start tutorial

Open a new notebook in the editor

1. On the Home page, click the New notebook. You are now redirected to the New notebook page.

2. (Optional) Enter your text in the Title field.

3. Press Enter to finish creating your notebook and open it in the editor.

Edit your notebook

1. In the first cell, enter the following code.

   # Try it now import datetime now_moment = datetime.datetime.now() print('– What is the right time to start?') print('– Now!\n')

2. To run the code of the currently active cell, press Alt+Shift+Enter.

3. Add a Markdown cell by hovering over the middle of the bottom border of the cell and clicking Add markdown cell.

4. Enter a text in your Markdown cell.

5. To run the code of your entire notebook, select Run | Run all from the main menu.

Prepare your dataset

1. Attach your .csv file to your notebook simply by dragging it into the editor.

2. Make sure the downloaded file is attached to the notebook. Click the Attached data icon on the left-hand sidebar. You should find your attached file on the Files tab.

   

View your data as a table

Use pandas, a popular library for Python, to view your dataset.

1. By convention, import pandas as pd:

   import pandas as pd

2. Enter the code below to access the content of your dataset and display it as a table. Make sure you specify the name of your attached .csv file in the quotation marks instead of libraries_by_python_version.csv.

   libraries = pd.read_csv('libraries_by_python_version.csv') libraries

After you run your code cell, you should have a table like this:

Visualize your data set

Now, you can build a chart based on the generated table. There is no need to write any code for it. Use the interface of the cell with the generated table.

1. In the cell with the generated table, switch to the Visualization tab.

2. Customize your visualization:

   1. For the chart type, expand the Plot type list and select one of the options :

      • Point(default)

      • Line

      • Bar

      • Area

      • Correlation

      

   2. To set up a color palette, expand Color list and select a column.

   3. By default, the graph represents the data from the first two columns of your DataFrame. To plot other data, expand the list for axis X or Y and select a column.

      

As you perform the steps above, the chart will be generated dynamically. The result should be similar to the image below.

Share your notebook by creating a link

1. On the editor page, click the Share button in the upper right corner of the editor to open the Share [notebook_title] dialog shown in the picture below.

   

2. Under Share notebook, expand the list and select the access type you want to grant using the link.

   

3. Click the icons next to the notebook link to open it in a new browser tab or copy the link.

   

4. (Optional) To disable the link, repeat steps 1 and 2, and select No access link.