Welcome to the Data Analysis with Python MCQs Page

Dive deep into the fascinating world of Data Analysis with Python with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Data Analysis with Python, a crucial aspect of Data Science. In this section, you will encounter a diverse range of MCQs that cover various aspects of Data Analysis with Python, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Science.

Check out the MCQs below to embark on an enriching journey through Data Analysis with Python. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Science.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Data Analysis with Python. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Data Analysis with Python MCQs | Page 6 of 7

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Data Science Basics

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Machine Learning

06

Developing Data Products

Q51.

Quandl API for Python wraps the ________ REST API to return Pandas DataFrames with time series indexes.

Quandl

PyDatastream

PyData

None of the mentioned

Discuss

Answer: (a).Quandl

Q52.

Point out the correct statement.

Statsmodels provides powerful statistics, econometrics, analysis and modeling functionality that is out of panda’s scope

Vintage leverages pandas objects as the underlying data container for computation

Bokeh is a Python interactive visualization library for small datasets

All of the mentioned

Discuss

Answer: (a).Statsmodels provides powerful statistics, econometrics, analysis and modeling functionality that is out of panda’s scope

Q53.

Which of the following library is used to retrieve and acquire statistical data and metadata disseminated in SDMX 2.1?

pandaSDMX

freedapi

geopandas

all of the mentioned

Discuss

Answer: (a).pandaSDMX

Q54.

Which of the following provides a standard API for doing computations with MongoDB?

Blaze

Geopandas

FRED

All of the mentioned

Discuss

Answer: (a).Blaze

Q55.

Point out the wrong statement.

qgrid is an interactive grid for sorting and filtering DataFrames

Pandas DataFrames implement _repr_html_ methods which are utilized by IPython Notebook

Spyder is a cross-platform Qt-based open-source R IDE

None of the mentioned

Discuss

Answer: (c).Spyder is a cross-platform Qt-based open-source R IDE

Q56.

Which of the following makes use of pandas and returns data in a series or dataFrame?

pandaSDMX

freedapi

OutPy

none of the mentioned

Discuss

Answer: (b).freedapi

Q57.

Spyder can introspect and display Pandas DataFrames.

True

False

May be True or False

Can't say

Discuss

Answer: (b).False

Q58.

Which of the following is used for machine learning in python?

scikit-learn

seaborn-learn

stats-learn

none of the mentioned

Discuss

Answer: (a).scikit-learn

Q59.

The ________ project builds on top of pandas and matplotlib to provide easy plotting of data.

yhat

Seaborn

Vincent

None of the mentioned

Discuss

Answer: (b).Seaborn

Q60.

x-ray brings the labeled data power of pandas to the physical sciences.

True

False

May be True or False

Can't say

Discuss

Answer: (a).True

Page 6 of 7

Welcome to the Data Analysis with Python MCQs Page

Data Analysis with Python MCQs | Page 6 of 7

Explore more Topics under Data Science

Data Science Basics

Data Manipulation

Data Analysis and Research

Statistical Inference and Regression Models

Machine Learning

Developing Data Products

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