http://datacamp-community-prod.s3.amazonaws.com/72771032-0653-4d87-a798-4a83879e99c8

Tackle time series in R with this xts (Extensible Time Series) cheat sheet! 

xts Cheat Sheet: Time Series in R

http://datacamp-community-prod.s3.amazonaws.com/21fdc814-3f08-4aa9-90fa-247eedefd655

This Jupyter Notebook cheat sheet will help you to find your way around the well-known Jupyter Notebook App, a subproject of Project Jupyter.

Jupyter Notebook Cheat Sheet

https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Jupyter_Notebook_Cheat_Sheet.pdf

https://www.datacamp.com/community/podcast/successful-digital-transformation-puts-people-first

<p><em>Bhavin Patel, Director of Analytics and Innovation at Johnson &amp; Johnson, discusses how to drive success with digital and data transformation, why investing in people is the most important aspect of becoming a digital-first organization, how data science accelerates outcomes in supply chain, and more.</em></p>

Bhavin Patel, Director of Analytics and Innovation at Johnson & Johnson, discusses how to drive success with digital and data transformation and more.

Successful Digital Transformation Puts People First

https://www.datacamp.com/blog/successful-digital-transformation-puts-people-first

https://www.datacamp.com/community/podcast/the-gradual-process-of-building-a-data-strategy

<p>Vijay Yadav, Director of Quantitative Sciences &amp; Head of Data Science at Center for Mathematical Sciences at <a target="_blank" rel="noopener noreferrer" href="https://www.linkedin.com/company/merck/">Merck</a> breaks down the different pillars of a scalable data strategy.</p>

Vijay Yadav, Director of Quantitative Sciences & Head of Data Science at Center for Mathematical Sciences at Merck breaks down the different pillars of a scalable data strategy.

The Gradual Process of Building a Data Strategy

https://www.datacamp.com/blog/the-gradual-process-of-building-a-data-strategy

https://www.datacamp.com/community/news/creating-smart-cities-with-data-science-ofs0psrh048

Amen Ra Mashariki deep dives into the state of data literacy in government agencies, the use cases he worked on to make the City of New York smarter, and more!

Creating Smart Cities With Data Science

https://www.datacamp.com/community/news/the-credibility-crisis-in-data-science-with-skipper-seabold-6bbmgpwy1qm

Skipper Seabold, a Director of Data Science at Civis Analytics, discusses the current and looming credibility crisis in data science.

The Credibility Crisis in Data Science (with Skipper Seabold)

https://www.datacamp.com/community/news/choosing-r-or-python-for-data-analysis-an-infographic-rhcw8x3m5wa

Wondering whether you should use R or Python for your next data analysis post? Check our infographic "Data Science Wars: R vs Python".

Choosing R or Python for Data Analysis? An Infographic

https://www.datacamp.com/community/news/understanding-blockchains-by-coding-one-in-r-l9k0ynh6ho8

Implement a small blockchain in R and learn more about what a blockchain looks like and some of the core concepts behind it!

Understanding Blockchains by Coding One in R

https://www.datacamp.com/community/blog/how-data-culture-unlock-digital-transformation

Chief Data & Innovation Officer at Gulf Bank, Mai AlOwaish, outlines how a people and data-first approach can unlock the value of digital transformation for organizations across industries.

How Data & Culture Unlock Digital Transformation

<center><a target="_blank" href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1624651228/schedule_a_demo_bfhlx1.png" /></a></center><br>
<p>In a recent episode of <a target="_blank" href="https://www.datacamp.com/community/blog/the-data-storytelling-skills-data-teams-need">DataFramed</a>, Andy Cotgrave, technical evangelist at Tableau, shared the importance of data storytelling in driving change with analytics. In this two-part blog post, we deep dive into seven concrete tips that Andy provided on telling better data stories.</p>
<p>Read <a target="_blank" href="https://www.datacamp.com/community/blog/seven-tricks-for-better-data-storytelling-1">Part I</a> if you haven't already!</p>
<h2 id="4-use-a-narrative-structure-in-data-stories-">4. Use a narrative structure in data stories.</h2>
<p>Stories generally follow a common arc – the protagonist faces a challenge, goes on to resolve it, then returns to normalcy. An example of this arc is the Hero’s Journey.</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1643320567/image8_grp6ly.png" />Figure 1: The hero’s journey</center><br>

<p>The audience is <a target="_blank" href="https://www.forbes.com/sites/kateharrison/2015/01/20/a-good-presentation-is-about-data-and-story/?sh=7599eca6450f">22 times more likely</a> to remember a fact when told a story. Clearly, data visualizations stand to benefit from adopting the age-old narrative structure.</p>
<p>Adopting the narrative structure, a data story starts with a background on the current situation, continues with evidence that builds up to the central insight, and ends with a call to action. (Figure 2)</p>
<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1643320742/image4_nnm9k9.png" />Figure 2. The narrative structure of a data story</center><br>


<p>An excellent example of a data story, the <a target="_blank" href="https://www.gatesfoundation.org/goalkeepers/report/2021-report/#LongTermInvestmentsPayOff">Goalkeeper’s Report by the Gates Foundation</a> demonstrated how the pandemic exacerbated inequality. (Figures 3A, 3B, and 3C)</p>
<br><center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1643320251/poverty_s2wd18.gif" />Figure 3A: To set the scene, the data story first established the impact of COVID-19 on poverty-stricken countries. [<a target="_blank" href="https://www.gatesfoundation.org/goalkeepers/report/2021-report/#LongTermInvestmentsPayOff">Source</a>]</center><br>

<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1643320508/image7_bmdtdx.png" />Figure 3B: The data story provided rising insights by highlighting the widening chasm between the haves and the have-nots pre-pandemic and post-pandemic.</center><br>

<center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1643319219/image2_lyw5ro.png" />Figure 3C: The data story closes with a call to action–for greater investments in women, communities, and innovations.</center>

<h2 id="5-adapt-data-stories-to-the-medium">5. Adapt data stories to the medium</h2>
<p>It is tempting to reuse existing charts across multiple mediums. Data storytellers who do so are doing themselves a disservice.</p>
<p>Charts that are not optimized for their medium might fail to deliver their message effectively. A chart originally designed for email might contain minuscule texts that cannot be read on a screen.</p>
<p>The Economist portrayed how data stories can be adapted from print media to social media. The printed chart (designed for serious readers) was dense in information. It was streamlined for Instagram (designed for casual scrollers).</p>
<br><center><img src="https://res.cloudinary.com/dyd911kmh/image/upload/v1643320591/image5_qjtkiu.png" />Figure 4: The Economist’s printed chart (left) is adapted for social media (right) [<a target="_blank" href="https://medium.economist.com/charting-new-territory-7f5afb293270">Source</a>]</center>

<h2 id="6-declutter-your-data-stories">6. Declutter your data stories</h2>
<p>Clutter makes data stories harder to read. The additional cognitive load distracts the audience from the main message.</p>
<p>The onus is on the data storyteller to identify and remove superfluous elements that do not contribute to the intended message. The result of decluttering is striking.</p>
<p>In particular, our whitepaper “<a target="_blank" href="https://www.datacamp.com/resources/whitepapers/8-rules-for-better-data-storytelling">8 Rules for Better Data Storytelling</a>” suggests data storytellers to:</p>
<ul>
<li>Remove chart borders</li>
<li>Remove gridlines or axes</li>
<li>Clean up axis labels</li>
<li>Label data directly (as opposed to using a legend)</li>
<li>Remove data markers</li>
<li>Use special effects (bold, underline, italics, shadows) sparingly</li>
</ul>
<h2 id="7-explain-data-stories-in-stages">7. Explain data stories in stages</h2>
<p>When presenting complex data stories, one practical tip is to reveal the elements of the chart gradually. When the information is presented in digestible pieces, the audience is more likely to engage with the presentation.</p>
<p>A prime example is the talk “<a target="_blank" href="https://www.youtube.com/watch?v=jbkSRLYSojo">The Joy of Stats</a>” by Hans Rosling. Watch how Rosling masterfully told his data story.</p>
<iframe width="560" height="315" src="https://www.youtube.com/embed/jbkSRLYSojo" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<h2 id="data-storytelling-is-here-to-stay">Data storytelling is here to stay</h2>
<p>Data storytelling will soon <a target="_blank" href="https://www.forbes.com/sites/brentdykes/2020/01/22/why-data-storytellers-will-define-the-next-decade-of-data/?sh=56a32d24fb9c">become a necessary skill set</a> for all in the coming decade as data insights become a cornerstone of organizations. To learn more tips and tricks on data storytelling, listen to Andy’s podcast, or learn from his most recent webinar on DataCamp.</p>
<br><center><a target="_blank" href="https://www.datacamp.com/groups/business"><img src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1624651228/schedule_a_demo_bfhlx1.png" /></a></center>

https://www.datacamp.com/community/blog/seven-tricks-for-better-data-storytelling-2

Seven Tricks for Better Data Storytelling: Part II

<h2>Introduction to Instrumental Variables</h2><p>This chapter will introduce you to Instrumental Variables (IV) analysis, a tricky but powerful method to find causality through indirect inference</p><h2>Instrumental Variables in Practice</h2><p>This chapter covers more details about Instrumental Variables Analysis, and allows you to practice instrumental variables for yourself</p><h2>Regression Discontinuity Design</h2><p>This chapter introduces you to Regression Discontinuity Design (RDD), which is often considered a more flexible relative of Instrumental Variables</p><h2>The Local Average Treatment Effect of IV</h2><p>This chapter explains the treatment effect we are estimating with the instrumental variables method - LATE, or the Local Average Treatment Effect</p>

https://www.datacamp.com/community/open-courses/causal-inference-with-r-instrumental-variables-rdd

A look at using Instrumental Variables and Regression Discontinuity to estimate causal effects

Causal Inference with R - Instrumental Variables & RDD

<h2>Regressions 1: Introduction to Regression As Causality</h2><p>This chapter will introduce you to using regression analysis to find causal effects</p><h2>Regressions 2: Using Regression to Estimate Causal Effects</h2><p>This chapter will introduce you to using regression analysis to find causal effects</p><h2>Regressions 3: Introduction to Matching Methods</h2><p>This chapter will introduce you to using matching methods to find causal effects</p>

https://www.datacamp.com/community/open-courses/causal-inference-with-r-regression

Welcome to the 3rd course in our series on causal inference concepts and methods created by Duke University with support from eBay, Inc. 

Causal Inference with R - Regression

https://www.datacamp.com/community/tutorials/tutorial-how-to-execute-sql-queries-in-r-and-python

Learn easy and effective ways to run SQL queries in Python and R for data analysis and database management. 

How to Execute SQL Queries in Python and R Tutorial 

<p>The&nbsp;data.table R package provides an enhanced version of <code>data.frame</code> that allows you to do <a href="https://github.com/Rdatatable/data.table/wiki/Benchmarks-%3A-Grouping" target="_blank">blazing fast</a> data manipulations. The <code>data.table</code> R package is being used in different fields such as finance and genomics&nbsp;and is especially useful for those of you that are working with large data sets (for example, 1GB to 100GB in RAM).</p>

<p>Although its typical syntax structure is not hard to master, it is unlike other things you might have seen in R. Hence the reason to create this cheat sheet. <a href="https://www.datacamp.com/courses/data-analysis-the-data-table-way/?utm_source=blog&amp;utm_medium=blog&amp;utm_content=cheat%20sheet%20blog&amp;utm_campaign=data.table%20cheat%20sheet" target="_blank" title="data.table tutorial">DataCamp</a>&rsquo;s <code>data.table</code> cheat sheet is a quick reference for doing data manipulations in R with the <code>data.table</code> R package and syntax</p>

<p>The cheat sheet will guide you from doing simple data manipulations using <code>data.table</code>&rsquo;s basic <code>i, j, by </code> syntax, to chaining expressions, to using the famous <code>set()</code>-family.</p>

<p>(To practice using the <code>data.table</code> package, try the free first chapter of this <a href="https://www.datacamp.com/courses/data-analysis-the-data-table-way/?utm_source=blog&amp;utm_medium=blog&amp;utm_content=cheat%20sheet%20blog&amp;utm_campaign=data.table%20cheat%20sheet">course</a>, which includes exercises in subsetting a <code>data.table</code> and manipulating data with <code>data.table</code>&#39;s&nbsp;<code>by</code>, <code>.N</code>, and <code>j</code> syntax. )</p>

<p><a href="http://datacamp-community-prod.s3.amazonaws.com/008e41e8-7526-4bbc-806b-8c828dfb81d4" target="_blank" title="data table cheat sheet"><img alt="data.table R package tutorial cheat sheet" class="aligncenter wp-image-437 size-medium" src="https://res.cloudinary.com/dyd911kmh/image/upload/f_auto,q_auto:best/v1625839980/The_data.table_R_Package_Cheat_Sheet_fdbgnt.png" style="width: 800px; height: 551px;" /></a></p>


https://www.datacamp.com/community/tutorials/data-table-cheat-sheet

The data.table cheat sheet helps you master the syntax of this R package, and helps you to do data manipulations.

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