add c7 week1

07_data-analysis-r/01_programming-and-data-analytics/activity/activity.r

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+4+5
+5-4
+10*5
+10/2

07_data-analysis-r/01_programming-and-data-analytics/activity/install_package.r

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+install.packages("tidyverse")
+library(tidyverse)
+library(lubridate)

07_data-analysis-r/01_programming-and-data-analytics/graded-assessments/weekly-challenge-1.md

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+## Weekly challenge 1
+
+Latest Submission Grade: 100%
+
+ 
+
+### Question 1
+
+A data analyst uses words and symbols to give instructions to a computer. What are the words and symbols known as? 
+
+* Syntax language 
+* Function language 
+* **Programming language**
+* Coded language 
+
+> Programming languages are the words and symbols you use to write instructions for computers to follow.
+
+ 
+
+### Question 2
+
+Many data analysts prefer to use a programming language for which of the following reasons? Select all that apply. 
+
+* To choose a topic for analysis 
+* **To easily reproduce and share an analysis**
+* **To clarify the steps of an analysis**
+* **To save time**
+
+> Many data analysts prefer to use a programming language in order to easily reproduce and share an analysis, save time, and clarify the steps of an analysis. 
+
+ 
+
+### Question 3
+
+Which of the following are benefits of open-source code? Select all that apply. 
+
+* **Anyone can fix bugs in the code**
+* **Anyone can create an add-on package for the code**
+* Anyone can pay a fee for access to the code
+* **Anyone can use the code for free** 
+
+> The benefits of open-source code include the following: anyone can use the code for free, fix bugs in the code, and create add-on packages for the code. 
+
+ 
+
+### Question 4
+
+Fill in the blank: The benefits of using _____ for data analysis include the ability to quickly process lots of data and create high quality visualizations.
+
+* **the R programming language**
+* a dashboard
+* a spreadsheet 
+* structured query language
+
+> The benefits of using the R programming language for data analysis include the ability to quickly process lots of data and create high quality visualizations. 
+
+ 
+
+### Question 5
+
+A data analyst needs to quickly create a series of scatterplots to visualize a very large dataset. What should they use for the analysis? 
+
+* Structured query language
+* A slide presentation 
+* A dashboard
+* **R programming language**
+
+> The analyst should use the R programming language to quickly create a series of scatterplots to visualize a very large dataset. R can quickly process lots of data and create high quality visualizations. 
+
+ 
+
+### Question 6
+
+RStudio’s integrated development environment lets you perform which of the following actions? Select all that apply. 
+
+* **Install R packages**
+* **Create data visualizations**
+* **Import data from spreadsheets**
+* Stream online videos 
+
+> RStudio’s integrated development environment lets you install R packages, import data from spreadsheets, and create data visualizations. 
+
+ 
+
+### Question 7
+
+In which two parts of RStudio can you execute code? Select all that apply.
+
+* The environment pane
+* The plots pane 
+* **The source editor pane**
+* **The R console pane**
+
+> In RStudio, you can execute code in the R console pane and the source editor pane. 
+
+ 
+
+### Question 8
+
+Fill in the blank: In RStudio, the _____ is where you can find all the data you currently have loaded, and can easily organize and save it.
+
+* **environment pane**
+* plots pane
+* R console pane
+* source editor pane
+
+> In RStudio, the environment pane is where you can find all the data you currently have loaded, and can easily organize and save it.

07_data-analysis-r/01_programming-and-data-analytics/practice-quiz-programming-languages.md

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+## L2 Programming languages
+
+ 
+
+### Question 1
+
+Fill in the blank: Programming involves _____ a computer to perform an action or set of actions.
+
+* updating
+* **instructing**
+* training
+* filtering
+
+> Programming means giving instructions to a computer to perform an action or set of actions.
+
+ 
+
+### Question 2
+
+What are Python, JavaScript, SAS, Scala, and Julia? 
+
+* Integrated development environments 
+* Databases
+* **Programming languages**
+* Web applications 
+
+> Python, JavaScript, SAS, Scala, and Julia are examples of programming languages. 
+
+ 
+
+### Question 3
+
+What are the benefits of using a programming language to work with your data? Select all that apply.
+
+* **Clarify the steps of your analysis**
+* **Easily reproduce and share your work**
+* **Save time**
+* Choose a business task for analysis
+
+> There are three main benefits of using a programming language to work with your data. You can easily reproduce and share your work, save time, and clarify the steps of your analysis.

07_data-analysis-r/01_programming-and-data-analytics/practice-quiz-programming-with-rstudio.md

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+## L4 Programming with RStudio
+
+ 
+
+### Question 1
+
+What type of software application is RStudio?
+
+* Data visualization tool 
+* Source editor 
+* Database 
+* **Integrated development environment**
+
+> RStudio is a type of software application known as an integrated development environment (IDE). An IDE brings together all the tools you may want to use in a single place.
+
+ 
+
+### Question 2
+
+RStudio includes which of the following panes? Select all that apply. 
+
+* **Environment pane** 
+* **Source editor pane**
+* Command pane
+* R console pane
+
+> RStudio includes an R console pane for executing commands, a source editor pane for writing code, and an environment pane for managing loaded data. RStudio does not include a Command pane. 
+
+ 
+
+### Question 3
+
+If you write code directly in the R console, RStudio will automatically save your code when you close your current session.
+
+* True
+* **False**
+
+> If you write code directly in the R console, RStudio will automatically forget your code when you close your current session. To save your code, use the source editor. 

07_data-analysis-r/01_programming-and-data-analytics/practice-quiz-r-programming-languages.md

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+## L3 R programming language
+
+ 
+
+### Question 1
+
+Open-source code is only available to people who pay a subscription fee. 
+
+* True
+* **False** 
+
+> Open-source code is freely available to anyone. 
+
+ 
+
+### Question 2
+
+The R programming language can be used for which of the following tasks? Select all that apply. 
+
+* **Data analysis**
+* **Visualization** 
+* **Statistical analysis**
+* Gaming
+
+> The R programming language can be used for statistical analysis, visualization, and data analysis.
+
+ 
+
+### Question 3
+
+Which of the following terms best describes the R programming language? 
+
+* Open-data 
+* **Data-centric**
+* Closed-source 
+* Open-ended 
+
+> The term data-centric best describes the R programming language. R is designed to make data analysis easier, more efficient, and more powerful. 

07_data-analysis-r/01_programming-and-data-analytics/readme.md

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+## Programming and data analytics
+
+R is a programming language that can help you in your data analysis process. In this part of the course, you’ll learn about R and RStudio, the environment you’ll use to work in R. You’ll explore the benefits of using R and RStudio as well as the components of RStudio that will help you get started.
+
+ 
+
+### Learning Objectives
+
+* Compare and contrast the R programming environment and the RStudio programming environment
+* Describe the RStudio programming environment including its components and benefits
+* Describe the R programming language and its programming environment
+* Describe programming languages and appropriate use including examples
+* Download and install R assets to a computer
+* Open R and execute a command
+* Differentiate between the R Console and R programming environments
+* Execute operations in R using mathematical operators such as +, -, *, and /
+* Download and use RStudio Desktop

07_data-analysis-r/01_programming-and-data-analytics/resources.md

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+## Resources
+
+ 
+
+* [R download page](https://cran.r-project.org/mirrors.html).
+* [RStudio Desktop download page](https://rstudio.com/products/rstudio/download/#download).
+* [R vs. Python, a comprehensive guide for data professionals](https://medium.com/analytics-and-data/r-vs-python-a-comprehensive-guide-for-data-professionals-321e8dead598): This article is written by a data professional with extensive experience using both languages and provides a detailed comparison. 
+* [R vs. Python, an objective comparison](https://www.dataquest.io/blog/python-vs-r/): This article provides a comparison of the languages using examples of code use. 
+* [R vs. Python: What’s the best language for data science?](https://blog.rstudio.com/2019/12/17/r-vs-python-what-s-the-best-for-language-for-data-science/): This blog article provides RStudio’s perspective on the R vs. Python debate.
+* [RStudio: A Single Home for R & Python](https://www.rstudio.com/solutions/r-and-python/)
+* [The Advantages of RStudio](https://www.theanalysisfactor.com/the-advantages-of-rstudio/): This web page explains some of the reasons why RStudio is many analysts’ preferred choice for interfacing with R. You’ll learn about the advantages of using RStudio for data analysis, from ease of use to accessibility of graphics and more. 
+* [Data analysis and R programming](https://lgatto.github.io/2017_11_09_Rcourse_Jena/before-we-start.html): This online introduction to data analysis and R programming is a good starting point for R and RStudio users. It also includes a list of detailed explanations about the advantages of using R and RStudio. You’ll also find a helpful guide for getting set up with RStudio.
+* [Ways to learn about programming](https://www.coursera.org/learn/data-analysis-r/supplement/y8zTf/ways-to-learn-about-programming) for a better idea of popular programming languages by job role
+* [RStudio Community](https://community.rstudio.com/): The RStudio Community forum is a great place to get help and find solutions to challenges you have with R–and maybe help someone else out, too!
+* [r/RLanguage](https://www.reddit.com/r/Rlanguage/): The R language subreddit is an active online community on the social media platform Reddit, where R users go to discuss R, ask questions, and share tips. 
+* [rOpenSci](https://discuss.ropensci.org/): rOpenSci has a community forum where R users can ask questions and search for solutions. It also includes links to their Best Practices guide and support pages. 
+* [KaggleNoobs Slack channel](https://kagglenoobs.slack.com/): This is a highly active, global channel that is specifically set up for new Kaggle users to ask questions and share news. In order to join, you’ll need to create a Slack account. 
+* [R4DS Online Learning Community and Slack channel](https://www.rfordatasci.com/): This is a community with another Slack channel where R learners and mentors can gather and connect. This is a great place to chat about using R for data science.