“A picture is worth a thousand words”. We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large data sets. Data visualization plays an essential role in the representation of both small and large scale data.
One of the key skills of a data scientist is the ability to tell a compelling story, visualizing data and findings in an approachable and stimulating way. Learning how to leverage a software tool to visualize data will also enable you to extract information, better understand the data, and make more effective decisions.
The main goal of this course is to teach you how to take data that at first glance has little meaning and present that data in a form that makes sense to people. Various techniques have been developed for presenting data visually but in this course, we will be using several data visualization libraries in Python, namely Matplotlib, seaborn, and Folium.
Question: 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: Using the inline backend, you can modify a figure after it is rendered.
False
True
Question: Which of the following are examples of Matplotlib magic functions? Choose all that apply.
%matplotlib inline
#matplotlib notebook
$matplotlib outline
%matplotlib notebook
#matplotlib inline
Basic Visualization Tools
Question: Area plots are stacked by default.
False
True
Question: 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?
Question: In Python, creating a waffle chart is straightforward since we can easily create one using the scripting layer of Matplotlib.
False
True
Question: 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.
Creating Maps and Visualizing Geospatial Data
Question: What tile style of Folium maps is usefule for data mashups and exploring river meanders and coastal zones?
OpenStreetMap
Mapbox Bright
Stamen Toner
Stamen Terrain
River and Coastal
Question: You cluster markers superimposed onto a map in Folium using a feature group object.
False
True
Question: 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?
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: The following are tile styles of folium maps (choose all that apply).
Stamen Terrain
River Coastal
Stamen Toner
Mapbox Bright
Open Stamen
Question: You cluster markers superimposed onto a map in Folium using a marker cluster object.
False
True
Question: 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?
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