Home Certification Data Visualization with Python Exam Answers – Cognitive Class

Data Visualization with Python Exam Answers – Cognitive Class

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Module 1: Introduction to Visualization Tools

Question 1: What are the layers that make up the Matplotlib architecture?

  • FigureCanvas Layer, Renderer Layer, and Artist Layer.
  • Backend_Bases Layer, Artist Layer, Scripting Layer.
  • Backend Layer, Artist Layer, and Scripting Layer.
  • Backend Layer, FigureCanvas Layer, Renderer Layer, Artist Layer, and Scripting Layer.
  • Figure Layer, Artist Layer, and Scripting Layer

Question 2: Using the inline backend, you can modify a figure after it is rendered.

  • False
  • True

Question 3: Which of the following are examples of Matplotlib magic functions? Choose all that apply.

  • %matplotlib inline
  • #matplotlib notebook
  • $matplotlib outline
  • %matplotlib notebook
  • #matplotlib inline

Module 2: Basic Visualization Tools

Question 1: Area plots are stacked by default.

  • False
  • True

Question 2: Given a pandas series, series_data, which of the following will create a histogram of series_data and align the bin edges with the horizontal tick marks?

  • count, bin_edges = np.histogram(series_data)
    • series_data.plot(kind=’hist’, xticks = count, bin_edges)
  • count, bin_edges = np.histogram(series_data)
    • series_data.plot(kind=’hist’, xticks = count)
  • count, bin_edges = np.histogram(series_data)
    • series_data.plot(kind=’hist’, xticks = bin_edges)
  • series_data.plot(kind=’hist’)
  • count, bin_edges = np.histogram(series_data)
    • series_data.plot(type=’hist’, xticks = bin_edges)

Question 3: Given a pandas dataframe, question, which of the following will create a horizontal barchart of the data in question?

  • question.plot(type=’bar’, rot=90)
  • question.plot(kind=’bar’, orientation=’horizontal’)
  • question.plot(kind=’barh’)
  • question.plot(kind=’bar’)
  • question.plot(kind=’bar’, type=’horizontal’)

Module 3: Specialized Visualization Tools

Question 1: Pie charts are less confusing than bar charts and should be your first attempt when creating a visual.

  • False
  • True

Question 2: What do the letters in the box plot above represent?

  • A = Mean, B = Upper Mean Quartile, C = Lower Mean Quartile, D = Inter Quartile Range, E = Minimum, and F = Outliers
  • A = Mean, B = Third Quartile, C = First Quartile, D = Inter Quartile Range, E = Minimum, and F = Outliers
  • A = Median, B = Third Quartile, C = First Quartile, D = Inter Quartile Range, E = Minimum, and F = Outliers
  • A = Median, B = Third Quartile, C = Mean, D = Inter Quartile Range, E = Lower Quartile, and F = Outliers
  • A = Mean, B = Third Quartile, C = First Quartile, D = Inter Quartile Range, E = Minimum, and F = Maximum

Question 3: What is the correct combination of function and parameter to create a box plot in Matplotlib?

  • Function = box, and Parameter = type, with value = “plot”
  • Function = boxplot, and Parameter = type, with value = “plot”
  • Function = plot, and Parameter = type, with value = “box”
  • Function = plot, and Parameter = kind, with value = “boxplot”
  • Function = plot, and Parameter = kind, with value = “box”

Module 4: Advanced Visualization Tools

Question 1: Which of the choices below will create the following regression line plot, given a pandas dataframe, data_dataframe?

  • import seaborn as sns
    • ax = sns.regplot(x=”year”, y=”total”, data=data_dataframe, color=”green”)
  • data_dataframe.plot(kind=”regression”, color=”green”, marker=”+”)
  • import seaborn as sns
    • ax = sns.regplot(x=”year”, y=”total”, data=data_dataframe, color=”green”, marker=”+”)
  • data_dataframe.plot(kind=”regplot”, color=”green”, marker=”+”)
  • import seaborn as sns
    • ax = sns.regplot(x=”total”, y=”year”, data=data_dataframe, color=”green”)

Question 2: In Python, creating a waffle chart is straightforward since we can easily create one using the scripting layer of Matplotlib.

  • False
  • True

Question 3: A word cloud (choose all that apply)

  • is a depiction of the frequency of different words in some textual data.
  • is a depiction of the frequency of the stopwords, such as a, the, and, in some textual data.
  • is a depiction of the meaningful words in some textual data, where the more a specific word appears in the text, the bigger and bolder it appears in the word cloud.
  • can be generated in Python using the word_cloud library that was developed by Andreas Mueller.
  • can be easily created using Matplotlib using the scripting layer.

Module 5: Creating Maps and Visualizing Geospatial Data

Question 1: What tile style of Folium maps is usefule for data mashups and exploring river meanders and coastal zones?

  • OpenStreetMap incorrect
  • Mapbox Bright
  • Stamen Toner
  • Stamen Terrain
  • River and Coastal incorrect

Question 2: You cluster markers superimposed onto a map in Folium using a feature group object.

  • False
  • True

Question 3:  If you are interested in generating a map of Spain to visualize its hill shading and natural vegetation, which of the following lines of code will create the right map for you?

  • folium.Map(location=[40.4637, 3.7492], zoom_start=6, tiles=’Stamen Toner’) incorrect
  • folium.Map(location=[40.4637, 3.7492], zoom_start=6, tiles=’Stamen Terrain’) incorrect
  • folium.Map(location=[40.4637, -3.7492], zoom_start=6, tiles=’Stamen Terrain’)
  • folium.Map(location=[-40.4637, -3.7492], zoom_start=6, tiles=’Stamen Terrain’)
  • folium.Map(location=[40.4637, 3.7492], zoom_start=6)

Data Visualization with Python Final Exam Answers

Question 1: Data visualizations are used to (check all that apply)

  • explore a given dataset.
  • perform data analytics and build predictive models.
  • train and test a machine learning algorithm.
  • share unbiased representation of data.
  • support recommendations to different stakeholders.

Question 2: Matplotlib was created by John Hunter, an American neurobiologist, and was originally developed as an EEG/ECoG visualization tool.

  • False
  • True

Question 3: What are the layers that make up the Matplotlib architecture?

  • FigureCanvas Layer, Renderer Layer, and Artist Layer.
  • Backend_Bases Layer, Artist Layer, Scripting Layer.
  • Backend Layer, Artist Layer, and Scripting Layer. correct
  • Backend Layer, FigureCanvas Layer, Renderer Layer, Artist Layer, and Scripting Layer.
  • Figure Layer, Artist Layer, and Scripting Layer.

Question 4: Using the notebook backend, you can modify a figure after it is rendered.

  • False
  • True

Question 5: The scripting layer is (check all that apply)

  • comprised mainly of pyplot.
  • an area on which the figure is drawn.
  • a handler of user inputs such as keyboard strokes and mouse clicks.
  • lighter that the Artist layer, and is intended for scientists whose goal is to perform quick exploratory analysis.
  • comprised one one main object – Artist.

Question 6: Which of the following are instances of the Artist object? (check all that apply)

  • Titles
  • Event
  • FigureCanvas
  • Tick Labels
  • Images

Question 7: There are three types of Artist objects.

  • False
  • True

Question 8: Each primitive artist may contain other composite artists as well as primitive artists.

  • False
  • True

Question 9: Given a pandas dataframe, question, which of the following will create a horizontal barchart of the data in question?

  • question.plot(type=’bar’, rot=90)
  • question.plot(kind=’bar’, orientation=’horizontal’)
  • question.plot(kind=’barh’)
  • question.plot(kind=’bar’)
  • question.plot(kind=’bar’, type=’horizontal’)

Question 10: Pie charts are relevant only in the rarest of circumstances, and bar charts are far superior ways to quickly get a message across.

  • False
  • True

Question 11: What do the letters in the box plot above represent?

  • A = Mean, B = Upper Mean Quartile, C = Lower Mean Quartile, D = Inter Quartile Range, E = Minimum, and F = Outliers
  • A = Mean, B = Third Quartile, C = First Quartile, D = Inter Quartile Range, E = Minimum, and F = Outliers
  • A = Median, B = Third Quartile, C = First Quartile, D = Inter Quartile Range, E = Minimum, and F = Outliers correct
  • A = Median, B = Third Quartile, C = Mean, D = Inter Quartile Range, E = Lower Quartile, and F = Outliers
  • A = Mean, B = Third Quartile, C = First Quartile, D = Inter Quartile Range, E = Minimum, and F = Maximum

Question 12: What is the correct combination of function and parameter to create a box plot in Matplotlib?

  • Function = plot, and Parameter = kind, with value = “boxplot”
  • Function = plot, and Parameter = type, with value = “box”
  • Function = plot, and Parameter = kind, with value = “box” correct
  • Function = box, and Parameter = type, with value = “plot”
  • Function = boxplot, and Parameter = type, with value = “plot”

Question 13: Which of the lines of code below will create the following scatter plot, given the pandas dataframe, df_total?

import matplotlib.pyplot as plt

plot(kind=’scatter’, x=’year’, y=’total’, data=df_total)

plt.title(‘Total Immigrant population to Canada from 1980 – 2013’)

plt.label (‘Year’)

plt.label(‘Number of Immigrants’)

import matplotlib.pyplot as plt

df_total.plot(type=’scatter’, x=’year’, y=’total’)

plt.title(‘Total Immigrant population to Canada from 1980 – 2013’)

plt.label (‘Year’)

plt.label(‘Number of Immigrants’)

import matplotlib.pyplot as plt

df_total.plot(kind=’scatter’, x=’year’, y=’total’)

plt.title(‘Total Immigrant population to Canada from 1980 – 2013’)

plt.xlabel (‘Year’)

plt.ylabel(‘Number of Immigrants’)

import matplotlib.scripting.pyplot as plt

df_total.plot(kind=’scatter’, x=’year’, y=’total’)

plt.title(‘Total Immigrant population to Canada from 1980 – 2013’)

plt.label (‘Year’)

plt.label(‘Number of Immigrants’)

import matplotlib.scripting.pyplot as plt

df_total.plot(type=’scatter’, y=’year’, x=’total’)

plt.title(‘Total Immigrant population to Canada from 1980 – 2013’)

plt.xlabel (‘Year’)

plt.ylabel(‘Number of Immigrants’)

Question 14: A bubble plot is a variation of the scatter plot that displays three dimensions of data.

  • False
  • True

Question 15: Seaborn is a Python visualization library that is built on top of Matplotlib.

  • False
  • True

Question 16: Which of the choices below will create the following regression line plot, given a pandas dataframe, data_dataframe?

  • import seaborn as sns
    • ax = sns.regplot(x=”year”, y=”total”, data=data_dataframe, color=”green”)
  • data_dataframe.plot(kind=”regression”, color=”green”, marker=”+”)
  • import seaborn as sns
    • ax = sns.regplot(x=”year”, y=”total”, data=data_dataframe, color=”green”, marker=”+”)
  • data_dataframe.plot(kind=”regplot”, color=”green”, marker=”+”)
  • import seaborn as sns
    • ax = sns.regplot(x=”total”, y=”year”, data=data_dataframe, color=”green”)

Question 17: A word cloud (choose all that apply):

  • is a depiction of the frequency of different words in some textual data.
  • is a depiction of the frequency of the stopwords, such as a, the, and, in some textual data.
  • is a depiction of the meaningful words in some textual data, where the more a specific word appears in the text, bigger and bolder it appears in the word cloud.
  • can be generated in Python using the word_cloud library that was developed by Andreas Mueller.
  • can be easily created using Matplotlib using the scripting layer.

Question 18: The following are tile styles of folium maps (choose all that apply).

  • Stamen Terrain
  • River Coastal
  • Stamen Toner
  • Mapbox Bright
  • Open Stamen

Question 19: You cluster markers superimposed onto a map in Folium using a marker cluster object.

  • False
  • True

Question 20: If you are interested in generating a map of Spain to explore its river meanders and coastal zones. Which of the following lines of code will create the right map for you?

  • folium.Map(location=[40.4637, 3.7492], zoom_start=6, tiles=’Stamen Terrain’)
  • folium.Map(location=[40.4637, 3.7492], zoom_start=6, tiles=’Stamen Toner’)
  • folium.Map(location=[40.4637, -3.7492], zoom_start=6, tiles=’Stamen Toner’) correct
  • folium.Map(location=[-40.4637, -3.7492], zoom_start=6, tiles=’Stamen Terrain’)
  • folium.Map(location=[40.4637, 3.7492], zoom_start=6)

5 COMMENTS

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