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Free DP-500 Exam Braindumps (page: 20)

Page 19 of 46
PDF with 194 Questions

HOTSPOT (Drag and Drop is not supported)
You have the following code in an Azure Synapse notebook.




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

NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: stacked bar chart
matplotlib.pyplot.bar makes a bar plot.

The bars are positioned at x with the given alignment. Their dimensions are given by height and width. The vertical baseline is bottom (default 0).

Many parameters can take either a single value applying to all bars or a sequence of values, one for each bar.

Stacked bars can be achieved by passing individual bottom values per bar.

Stacked bar chart
This is an example of creating a stacked bar plot with error bars using bar. Note the parameters yeer used for error bars, and bottom to stack the women's bars on top of the men's bars.


import matplotlib.pyplot as plt


labels = ['G1', 'G2', 'G3', 'G4', 'G5']
men_means = [20, 35, 30, 35, 27]
women_means = [25, 32, 34, 20, 25]
men_std = [2, 3, 4, 1, 2]
women_std = [3, 5, 2, 3, 3]
width = 0.35 # the width of the bars: can also be len(x) sequence

fig, ax = plt.subplots()

ax.bar(labels, men_means, width, yerr=men_std, label='Men')
ax.bar(labels, women_means, width, yerr=women_std, bottom=men_means,
label='Women')

ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.legend()

plt.show()

Box 2: two items
Blue item and Green Item.

matplotlib.legend
The legend module defines the Legend class, which is responsible for drawing legends associated with axes and/or figures.

Note: A Diagram Legend is an element that you can add to your diagram to provide information about the colors and/or line thicknesses and styles that have been used in the current diagram, where those colors and other styles have some particular meaning.


Reference:

https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.bar.html
https://matplotlib.org/stable/gallery/lines_bars_and_markers/bar_stacked.html
https://matplotlib.org/stable/api/legend_api.html



HOTSPOT (Drag and Drop is not supported)
You have the following code in an Azure Synapse notebook.



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

NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: three scatterplots
Compare Plots
Example, Draw two plots on the same figure:
import matplotlib.pyplot as plt
import numpy as np

#day one, the age and speed of 13 cars:
x = np.array([5,7,8,7,2,17,2,9,4,11,12,9,6])
y = np.array([99,86,87,88,111,86,103,87,94,78,77,85,86])
plt.scatter(x, y)

#day two, the age and speed of 15 cars:
x = np.array([2,2,8,1,15,8,12,9,7,3,11,4,7,14,12])
y = np.array([100,105,84,105,90,99,90,95,94,100,79,112,91,80,85])
plt.scatter(x, y)

plt.show()

Result:

Box 2: three marker symbols
One for each scatterplot. One default, and two defined.

Default is point.
v is triangle down.
^ is triangle up.


Reference:

https://www.w3schools.com/python/matplotlib_scatter.asp
https://matplotlib.org/stable/api/markers_api.html



HOTSPOT (Drag and Drop is not supported)
You use Advanced Editor in Power Query Editor to edit a query that references two tables named Sales and Commission.

A sample of the data in the Sales table is shown in the following table.



A sample of the data in the Commission table is shown in the following table.



You need to merge the tables by using Power Query Editor without losing any rows in the Sales table.

How should you complete the query? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: Join

Box 2: LeftOuter
Left outer join
One of the join kinds available in the Merge dialog box in Power Query is a left outer join, which keeps all the rows from the left table and brings in any matching rows from the right table.


Reference:

https://docs.microsoft.com/en-us/power-query/merge-queries-left-outer



You have a Power BI dataset named Dataset1 that uses DirectQuery against an Azure SQL database named DB1.

DB1 is a transactional database in the third normal form.

You need to recommend a solution to minimize how long it takes to execute the query. The solution must maintain the current functionality.

What should you include in the recommendation?

  1. Remove the relationships from Dataset1.
  2. Normalize the tables in DB1.
  3. Create calculated columns in Dataset1.
  4. Denormalize the tables in DB1.

Answer(s): D

Explanation:

Denormalize to improve query performance.

Note: Normalization prevents data duplications, preserves disk space, and improves the performance of the disk I/O operations. The downside of the normalization is that the queries based on these normalized tables require more table joins.
Schema denormalization (i.e. consolidation of some dimension tables) for such databases can significantly reduce costs of the analytical queries and improve the performance.


Reference:

https://www.mssqltips.com/sqlservertip/7114/denormalization-dimensions-synapse-mapping-data-flow/






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