Intro to Python

Put the process for web scraping using Python in the correct order.

1. Identify the URL to scrape. 2. Identify the data that needs to be scraped. 3. Inspect the page. 4. Locate the data that needs to be extracted. 5. Write/use Python code to extract the data. 6. Run the code and extract the data. 7. Compile structured reports/visualizations of the data.

Which of the following are business uses of the Python programming language?

Accounting Finance Sales and marketing

Python is used in quantitative and qualitative financial processes in which of the following areas?

Analytics Banking Cryptocurrency

Web scraping is the automation of the extraction of large volumes of data from websites. Using Python, which of the following web scraping activities can be conducted?

Conduct research and development (R&D) Conduct price comparisons. Collect data from social media sites.

Because many business executives desire to create a data-driven decision-making culture, which three of the following are competencies organizations invest in to support DDDM?

Data proficiency Building a data-driven community Agility in analytics and data analysis

The process of data analytics includes which of the following?

Descriptive analytics Predictive analytics Prescriptive analytics

Accountants use Python to automate which of the following repetitive tasks?

Input customer information Input of invoices Calculate taxes owed

Which of the following Python libraries are commonly used for data processing and data visualization?

Matplotlib Seaborn

Microsoft Excel was first introduced in 1982 as a program called

Multiplan

Select the true statements about the scalability of Python.

Python can handle data sets of almost any scale. The number of columns or rows used in a data set does not impact the Python user because they are not operating in a data interface environment. When working in Python, users can save data in separate files, which allows for simultaneous work and coding.

When compared to Microsoft Excel, which of the following are considered limitations of using Python for data analysis?

Steep learning curve associated with learning Python for data analysis. Not as friendly a user interface when compared to Microsoft Excel.

Which of the following Python libraries are used in marketing analytics and SEO?

TensorFlow ExPan

Select the true statements about the scalability of Microsoft Excel.

The management of small and medium scale data sets can be accomplished relatively smoothly. When large volumes of data are introduced into Microsoft Excel, issues may occur. As the amount of spreadsheet tabs in a workbook increases, so does potential data management issues.

Select the true statements about how Python is used in the banking industry.

There is a Python script that allows for the creation of automatic recurring payment requests via Venmo. Python is used by financial institutions to provide online banking and payment processing systems. Banks use Python to get financial models out of Microsoft Excel.

In Microsoft Excel, Blank______ is used to create custom macros and functions that are designed to accomplish organizational specific tasks.

VBA

The process of investigating raw data of various types to uncover trends and correlations, and to answer specifically crafted questions is the role of data

analysis

Search Engine Optimization (SEO) involves the design (and improvement) of websites to increase non-paid visibility on search engines including Google and Bing. There is a Python script called the SEO _____ that is a web crawler designed to collect data from websites.

analyzer

The three-step data visualization process consists of exploring the data sets for pattern, then planning for visuals, and finally ___.

creating your visuals

The information technology (IT) architecture and infrastructure, software applications, programming languages, and storage technologies used for the collection, storage, analysis, and interpretation of meaningful data is referred to as the ___ ecosystem.

data

Similar to how mining recovers small amounts of precious metals from large amounts of ore or earth, Blank______ is the process of extracting information from large data sets.

data mining

In Microsoft Excel, a statement written by a user that is designed for a specific calculation is referred to as a

formula

In Microsoft Excel, a predefined formula that is built into the software for ease of use and deployment is referred to as a

function

In Python, a collection of related programming modules that include precompiled bundles of code that can be used repetitively in different programs and applications are referred to as a Python Blank______. They often contain configuration data, templates, classes, values, and documentation.

library

The process of collecting, cleansing, transforming, and classifying data is referred to as data processing and

modeling

Python is Blank______ software based on community-based development that runs optimally on Windows and Linux operating systems.

open-source

Derived from the term "panel data" that is used in econometrics, Blank______ includes a variety of modules designed to work with data.

pandas

Which of the following Python libraries are commonly used to automate accounting tasks?

pandas NumPy

One way to visualize a data ecosystem is to apply it to the data project life cycle. The Data Science Ready project outlines the five steps of the data project life cycle. The final stage in this life cycle is Blank______.

storage

A subset of data analysis that covers creating visual representations of data is referred to as data Blank______.

visualization

The graphical and structured representation of data is known as data

visualization

Marketing analytics are used to measure marketing performance and effectiveness and to make decisions on different strategies to increase marketing efficiency and impact. The analysis of marketing performance data can be enhanced using Python. Python is used for the analysis of which marketing related tasks? Multiple select question. A/B Testing Creation of cryptocurrency Predictive analytics Customer segmentation analysis

A/B Testing Predictive analytics Customer segmentation analysis

Short for Financial Technology, FinTech refers to the use of technology and innovative solutions to automate and increase efficiency in which industries?

Banking Insurance Payment systems

Data visualization is a strength of using Python for data analysis. Which of the following are types of data visualization that can be created using Python?

Charts Interactive plots Graphics

Which Python web frameworks identified in the text assist in the development of scalable and secure FinTech web applications?

Django Flask

According to Tableau, data-driven decision making (DDDM) uses which of the following to guide strategic business decisions that align with organizational goals, objectives, and initiatives?

Metrics Facts Data

Which of the following are popular Python IDEs?

PyCharm Visual Studio Code Spyder

A multi-purpose programming language that relies extensively on libraries and modules, Blank______ is suitable for the automation of various tasks and processes.

Python

Select the true statements about the Python programming language.

Python is completely free to use. Many people consider Python to be an ideal first programming language to learn. Python syntax is considered by many to be relatively simple.

Select the true statements about how Python is used in finance.

Python is used in quantitative and qualitative financial processes in many financial areas including analytics, banking, and cryptocurrency. Analytics in finance provides high-level and granular-level views of an organization's financial data. Banks use Python to get financial models out of Excel and into an environment that allows for more data analysis and visualization.

Python was specifically designed to rely on which of the following?

Python libraries Modules

Select the true statements about connectivity in Python.

Python libraries such as pandas can interpret and merge data sets from different sources including Excel, CSV, and JASON. Connections to external and internal data sources can be accomplished using Python. Importing and exporting data is streamlined.

The steps in the data project life cycle, according to Harvard University's Data Science Ready project include which three of the following?

Sensing Collection Wrangling