To ensure all rows appear in a Python visual in Power BI, what should you do?

To ensure all rows appear in a Python visual in Power BI, referencing the columns by index in the Python code is effective because it directly corresponds to how data is structured in DataFrames, which are commonly used in Python for data manipulation. By using column indices, you can specifically select and manipulate the required data without worrying about any potential inconsistencies in column names. This method allows you to access data points precisely, ensuring that the visual captures every necessary row unambiguously.

Adding a unique field to each row, while useful for certain types of data processing and analysis, does not inherently guarantee visibility of rows in visuals. It may simply add more complexity without addressing the core issue of displaying all rows.

Modifying the Sort Column By property affects the order in which data is displayed, rather than providing a solution for ensuring that all rows are shown.

Changing the Summarize By property would aggregate data, which may result in losing individual rows depending on how the data is structured or the type of aggregation used. Hence, this choice would also not help in ensuring that all rows appear in the visual.