Microsoft DP-500 Practice Test - Questions Answers, Page 4

Reference: https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-report-themes

You can retrieve a column in a pandas DataFrame object by using the DataFrame object name, followed by the label of the column name in brackets.

So if the DataFrame object name is dataframe1 and the column we are trying to retrieve the 'X' column, then we retrieve the column using the statement, dataframe1['X'].

Here's a simple Python script that imports pandas and uses a data frame:

import pandas as pd data = [['Alex',10],['Bob',12],['Clarke',13]] df = pd.DataFrame(data,columns=['Name','Age'],dtype=float) print (df)

When run, this script returns:

Name Age

0 Alex 10.0

1 Bob 12.0

2 Clarke 13.0

Reference: http://www.learningaboutelectronics.com/Articles/How-to-retrieve-a-column-from-a-

Enable personalization in a report

You can enable the feature either in Power BI Desktop or the Power BI service. You can also enable it in embedded reports.

To enable the feature in Power BI Desktop, go to File > Options and settings > Options > Current file > Report settings. Make sure Personalize visuals is turned on.

Themes, contrast and colorblind-friendly colors

You should ensure that your reports have enough contrast between text and any background colors.

Certain color combinations are particularly difficult for users with color vision deficiencies to distinguish. These include the following combinations:

**---> green and black

green and red

green and brown

blue and purple

green and blue

light green and yellow

blue and grey

green and grey

Avoid using these colors together in a chart, or on the same report page.

Reference: https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-accessibility-creating-reports

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

Matplotlib

You can render standard plotting libraries, like Matplotlib, using the built-in rendering functions for each library.

Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.

Additional libraries

Beyond these libraries, the Azure Synapse Analytics Runtime also includes the following set of libraries that are often used for data visualization:

Seaborn Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.

Reference: https://docs.microsoft.com/en-us/azure/synapse-analytics/spark/apache-spark-datavisualization

https://seaborn.pydata.org/

The aggregating statistic can be calculated for multiple columns at the same time with the describe function.

Example:

titanic[["Age", "Fare"]].describe()

Out[6]:

Age Fare

count 714.000000 891.000000

mean 29.699118 32.204208

std 14.526497 49.693429

min 0.420000 0.000000

25% 20.125000 7.910400

50% 28.000000 14.454200

75% 38.000000 31.000000

max 80.000000 512.329200

Reference:

https://pandas.pydata.org/docs/getting_started/intro_tutorials/06_calculate_statistics.html

Automatic page refresh in Power BI enables your active report page to query for new data, at a predefined cadence, for DirectQuery sources.

Automatic page refresh is available for DirectQuery sources and some LiveConnect scenarios, so it will only be available when you are connected to a supported data source. This restriction applies to both automatic page refresh types.

Reference: https://docs.microsoft.com/en-us/power-bi/create-reports/desktop-automatic-pagerefresh