Facets Interview Questions

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1. What is the Facet Visualization tool?

Ans: Facet is an open-source visualization tool used to understand and analyze the machine learning datasets by comparing the training datasets and test sets for model debugging.

2. Name the use cases for using the Facet Visualization tools.

Ans: Use Cases are

  • To view the number of images and variation in each labeled class.
  • To display the scatter plots for the shape of icons and object bounding box sizes.
  • Spotting anomalies.
  • Checking the image labels for the correctness.
  • To visualize the comparison of train and test sets.

3. How does the Facet overview help the users?

Ans: The Facet overview helps the users visualize the distribution of values and its properties in the datasets.

4. Why do the users use facet Dive?

Ans: The Facet Dive provides the users with custom interfaces through which they can able to find the relationship among the data points and can control the color, position to visualize the data points representation based on its characteristic values.

5. What are the options available for running the Facets Dive?

Ans: There are many options available to run the Facets Dive such as

  1. Jupyter Notebook.
  2. Google Colab.
  3. Facets demo website.

6. Name the dependencies used in the HTML file used by Facets.

Ans: The HTML file has two dependencies.

  1. Facets Dive javascript library.
  2. webcomponents.jar.

7. What is the data limit and loading speed while using Facets?

Ans: Facets Dive can handle the data upto 10,000 records, and there is no limit for loading speed for large memory data files, the user should have the patience to wait until the file opens.

8. Can you display the datasets having millions of images?

Ans: Probably not. You can randomly select subsets of samples from the dataset.

9. Can you display high-resolution images?

 Ans: It depends on the size of the sprite atlas that you generate and read into Facets Dive. You could display only fewer high-resolution images depending on the PC's memory and browser capabilities.

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10. What is sprite atlas?

Ans: A sprite atlas is a big image that contains many small images at predictable coordinates. The sprite coordinates start from the top-left corner of the image and proceed across and down from left-to-right and top-to-bottom.

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11. Name any two properties of sprites in the visualization?


  1. spriteImageWidth - Rendering the width of sprite backing image in pixels.
  2. spriteImageHeight - Rendering the height of sprite backing image in pixels.

12. What are atlasUrl and spriteUrl?

Ans: atlasUrl - It is the URL of an atlas image that is used for backing sprites. Each sprite is mapped with the index of a data array to a rectangle of an atlas image.

spriteUrl - It is the URl of an image, the default sprite image used for backing sprites. Each sprite has the same image.

13. What are the stylistic properties?

Ans: It is an optional property which controls the elements with stylistic aspects of FacetDive.

14. Name two stylistic properties used by Facet?


  1. itemPositioningVerticalLabelColor - It is used in labeling the color for item positioning in the vertical direction.
  2. itemPositioningHorizontalLabelColor - It is used in labeling the color for item positioning in the horizontal direction.

15. What is Facets Atlasmaker?

Ans: The Facets Atlasmaker is a command-line utility and library used to create the sprite atlases.

16. What are the functionalities of Atlasmaker?

Ans: The functionalities of Atlasmaker are

  • To read the input image files from URL and local file.
  • Using default image file during unsuccessful conversion or retrieval of images in atlas.
  • Image resizing and conversion.
  • Parallelization of image fetch/conversion.

17. What are the four Facet Dive controls?

Ans: The four Dive controls are 

  • Faceting controls - which lays the records out in a grid information.
  • Positioning controls - arranges the items in each cell grid by stacking them to place it in a scatter plot.
  • Color controls - enables to specify the color for individual items.
  • Display controls - lets you specify the dive to render on each point.

18. Name the data properties of FacetsDive polymer.

Ans: The FacetsDive visualizations has two properties

  1. data - Array<{}> - An array of data objects to visualize.
  2. filteredDataIndicies - number[] - An array of indices into data object array.

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19. What are the interactive properties?

Ans: The properties that drive the interactivity of FacetDive are the interactive properties controlled by the user.

20. Name any four interactive properties in FacetDive.


  1. vertical Facet - Name of the field of the data to facet vertically.
  2. vertical bucket - Number of buckets to use when faceting vertically.
  3. horizontalFacet - Name of the area of the data to facet horizontally.
  4. horizontal bucket - Number of buckets to use when faceting horizontally.


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21. Which attribute is used to position the items in grid cells?

Ans: The interactive "position mode" attribute used in positioning items within a grid cell with stacked and scatter choices.

22. Which attribute is used to generate the data-specific color palette?

Ans: The "palette choice" attribute is used to generate the data-specific color palette with the four values standard, warm, cool and assist.

23. How can you position the items along the axis with Facet interactions?

Ans: The "vertical position" and "horizontal position" are the two attributes.

  1. vertical position - is used to position the items along the vertical axis.
  2. horizontal position - is used to position the items along the horizontal axis.

24. What are the things that an overview tool displays after uploading the data?

Ans: The overview tool displays the following four things:

  1. Statistics of data - This includes statistics of Min, Max, Median, and Standard Deviation.
  2. Missing values - The number of rows which has no data.
  3. Zero values - what percentage of data is zero.
  4. Train/test split - A plot which displays the dataset split between training and testing data.

25. What is a Seaborn FacetGrid?

Ans: The Seaborn FacetGrid is a class that helps in visualizing the distribution of one variable and the relationship between multiple variables separately. FacetGrid object considers the data frame as input and names the variables that form a row, column, and hue dimensions.

26. Name any two methods that are used by Seaborn FacetGrid.


  1. facet_axis (self,row_i,col_j) - Make the axis identified by these indices active and return it.
  2. facet_data (self) - Generator for name indices and data subsets for each Facet.

27. What Seaborn FacetGrid map method does?

 Ans: The Seaborn FacetGrid.map() method applies the plotting function to each Facet's subset of data.

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28. Name the parameters of Seaborn FacetGrid map method.

Ans: The parameters include

  1. func - A plotting function which takes data and arguments.
  2. args - The column names in self.data which identifies variable with data to plot. 
  3. Kwargs - The keyword arguments which are passed to the plotting function.

Syntax: FacetGrid.map(self, func, *args, **kwargs)

29. What are Facets in Health Care systems?

Ans: The Facets is mainly developed for Health Care systems for providing advanced care management capabilities. The Facets platform automates data points in training the healthcare datasets to produce better outcomes through visualizations.

30. What are the Trizetto Facets?

Ans: Trizetto Facets are the number of functionalities that assist in managing an application group's business operations. The Trizetto Facets includes the business rules which process the client/server systems.

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