Free DP-500 Exam Braindumps (page: 12)

Page 12 of 46

You have the following Python code in an Apache Spark notebook.



Which type of chart will the code produce?

  1. a stacked bar chart
  2. an area chart
  3. a bar chart
  4. a pie chart

Answer(s): B

Explanation:

The matplotlib.pyplot.fill_between function fills the area between two horizontal curves.

The curves are defined by the points (x, y1) and (x, y2). This creates one or multiple polygons describing the filled area.


Reference:

https://matplotlib.org/3.5.0/api/_as_gen/matplotlib.pyplot.fill_between.html



You are creating a Python visual in Power BI Desktop.

You need to retrieve the value of a column named Unit Price from a DataFrame.

How should you reference the Unit Price column in the Python code?

  1. dataset[‘Unit Price’]
  2. (‘Unit Price’)
  3. pandas.DataFrame(‘Unit Price’)
  4. data = [Unit Price]

Answer(s): A

Explanation:

dataset[‘Unit Price’], => (return a column)
pandas.DataFrame(‘Unit Price’), => (show the entire table)


Reference:

http://www.learningaboutelectronics.com/Articles/How-to-retrieve-a-column-from-a-pandas-dataframe-object-in-Python.php



You open a Power BI Desktop report that contains an imported data model and a single report page.

You open Performance analyzer, start recording, and refresh the visuals on the page. The recording produces the results shown in the following exhibit.



What can you identify from the results?

  1. When all the visuals refresh simultaneously, the visuals spend most of the time waiting on other processes to finish.
  2. The Actual/Forecast Billable Hrs YTD visual displays the most data.
  3. Unoptimized DAX queries cause the page to load slowly.
  4. The Actual/Forecast Hours by Type visual takes a long time to render on the report page when the data is cross-filtered.

Answer(s): A

Explanation:

Most time is spent in the category Other - time required by the visual for preparing queries, waiting for other visuals to complete, or performing other background processing.

Note: Each visual's log information includes the time spent (duration) to complete the following categories of tasks:

DAX query - if a DAX query was required, this is the time between the visual sending the query, and for Analysis Services to return the results.
Visual display - time required for the visual to draw on the screen, including time required to retrieve any web images or geocoding.
Other - time required by the visual for preparing queries, waiting for other visuals to complete, or performing other background processing.

Incorrect:
Not B: The Actual/Forecast Billable Hrs YTD visual display information is not available in the exhibit.
Not D: Visual display is only 39 ms.


Reference:

https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-performance-analyzer



HOTSPOT (Drag and Drop is not supported)
You use Vertipaq Analyzer to analyze a model.

The Relationships tab contains the results shown in the following exhibit.



Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.

NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: Customer
There are 1804 invalid rows (records) in the Customer table.

Box 2: 22
There are 22 missing keys.

Note: VertiPaq Analyzer in DAX Studio is useful in identifying referential integrity violations which slow down your DAX codes. It helps you determine which table or column needs to be optimized and improved.


Reference:

https://blog.enterprisedna.co/vertipaq-analyzer-tutorial-relationships-referential-integrity/



Page 12 of 46



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