I want to show images var_1.png,,var_40.png in a 2x3 matrix format inside a Jupyter Notebook. However, I only manage to do it manually: import matplotlib.pyplot as plt import matplotlib.image as select the active Cell > Cell Type > Markdown. irrespective of the version of jupyter notebook you use, the following command should work on current cell. As mentioned in the above remarks, use markdown cells. Once in a markdown cell, use #, ##, ###, #### for headings of different fonts. Drop all rows that have duplicates or are duplicates; Mark duplicate rows with flag column; Flag duplicate rows; Arbitrary keep criterion; All code available on this jupyter notebook. Show duplicated rows. I.e. show rows that are duplicates of existing rows. 3. Yes, with JupyterLab you can simply right-click on your active notebook, and then click "New Console for Notebook" to open up a console that's hooked up to the same Python kernel! With this, you can play around with all the dataframes and objects without messing up the notebook outputs. – machine-building. Figure 5: The Command Palette in Jupyter Notebook. 5. Markdown. Markdown is a markup language for formatting text. We can use it to add paragraphs, headers, bullet lists, and more within our Jupyter Notebook. In Command Mode, press the m key to designate a cell as a Markdown cell. If you need to convert a cell to a Python Code cell, press the y Pandas display all index labels in jupyter notebook despite repetition. When displaying a DataFrame in jupyter notebook. The index is displayed in a hierarchical way. So that repeated labels are not shown in the following row. E.g. a dataframe with a Multiindex with the following labels. A bit of Setup. To begin, you’ll need to install one library to make sure you can run SQL directly in the Notebooks, so paste the following into any Jupyter cell: !pip install ipython-sql. When writing the article I was dealing with the Oracle database. If you are also, make sure cx_Oracle is installed. You can easily show the default number of DataFrame columns which your Python IDE will display by using the following code. import pandas as pd pd.get_option('display.max_columns') # The result will be: 20 Display all DataFrame columns in Jupyter. To extend the number of Pandas DataFrame columns displayed in Jupyter, type the code below: To change the number of rows you need to change the max_rows option. pd.set_option("max_columns", 2) #Showing only two columns pd.set_option("max_rows", None) movies All the rows are being shown. Jupyter collapses the cell and creates a scroll bar. | Screenshot: Andryw Marques. Related to rows, there are two settings: max_rows and min_rows. Sum of each row: df.sum(axis=1) Example 1: Summing all the rows of a Dataframe using the sum function and setting the axis value to 1 for summing up the row values and displaying the result as output. ET5o.