It is such a pleasure to see amazing things being shared in our community. Sometimes, I worry about what might happen if we donāt get any good stuff shared in Share category one week. But every week I find amazing things in there!
Here are the Community Champions who shared amazing things with our Community last week:
āWhile bar charts, histograms, scatter plots, line charts, and box plots are wide-spread and efficient tools for displaying data and finding patterns in it, there are other graphs, less popular but still very useful for creating excellent visualizations. Letās explore some of them on another type of less known objects: those unidentified flying saucers.ā
" Generation Z cannot afford to alone in this fight. Support from older generations is needed to bring about meaningful change in policy because they outweigh Gen Z in terms of voting power and political influence. How much intergenerational support does climate issues have? In this blog, I analyze the 2016 European Social Survey data in R to explore generational differences in attitudes toward climate change."
Personal Project sharer:
@refucetola shared their personal project with us where they try to inspect what types of energy different countries use over time and compare that to the annual carbon emmissions for those countries.
Most liked:
@masterryan.profreshared an insightful article on āhow depending on too many open source libraries (esp. in enterprises is not always a good thing) and how making typos may lead you to downloading a malicious package (so check the spelling ).ā
Guided Project sharers:
@BunterTheMage shared for the first time his guided project on NYC Schools SAT Scores, which stands out for its great structure, profound data analysis, smooth and coherent storytelling, nice visualizations, and curious side materials.
@gosaints shared another amazing well-structured and well-commented project on Best Markets To Advertise In. @gosaints applied 2 different approaches to data analysis and illustrated their insights with cool perfectly annotated visualizations.
Guided Project reviewer:
@brayanopiyo18 and @Elena_Kosourova continue to give immensely helpful feedback on the Guided Projects that learners share in our Community!
Thank you all for participating in our Community!
I am glad to reward each of you with:
A 7 day extension on your current Dataquest subscription
An exclusive Community Champions badge in our Community
Better late than never they say!! Iāve been bogged down for a while. Thanks @nityesh for the recognition. To the reviewers, sincerely appreciate your contributions. To the other winnersā¦ Onward and Upward!
In this article, she deciphers the origins of popular Python libraries that we hear everyday like Pandas, Seaborn and Beautiful Soup.
Crazy fact: When Elena couldnāt find the source of Seabornās name anywhere on the Internet, she hunted down the creator and shot him an email asking about the origins of the name! And he replied!! Check out their conversation in the article above.
Guided Project sharer:
This week both the notable Guided Projects come from the same person - @ywbadri
The first one is on Star Wars, and it stands out for its very profound data analysis, curious insights, awesome plots, clean code, and perfect code comments. Whatās more, @ywbadri writes that she is actually a fan of Star Wars, so her observations are the ones from a knowledgeable and involved person - thatās really cool!
Her second project is on CIA Factbook Data Analysis . Itās characterized by a smooth storytelling, interesting observations. perfect SQL code style, Another great thing is that @ywbadri took into account the suggestions from the Community and updated her project accordingly
Thanks a lot @nityesh for the recognition, am glad to be part of the champions. To other champions, congratulations! and letās continue making the community great.
Thanks a lot, Nityesh! And yes, now we know the secret of Seabornās name, which was vividly discussed on the Internet but with no precise answer Congratulations to the other champions!
Thanks @nityesh for the recognition! This is a much needed confidence boost for me as Iām constantly feeling the struggle with learning Data Science! Glad you liked my projects!
Things have started heating up in the 3rd week of the March Writers contest - weāve published 4 new articles this week!
With only 8 days left in the contest, Iām confident weāll publish even more articles this week. In fact, I know weāll publish more because I have 4 new drafts sitting with me for review as Iām writing this.
Keep 'em coming, folks!
Here are our Community Champions for this week:
Writers
@theparidhi0 has written a great piece discussing how she created a cool Twitter bot that allows people to play chessā¦ on Twitter!
Making a Twitter bot might seem like a complex thing but all I needed for making this bot was:
To know a little bit about chess
A Twitter account
Basic knowledge of Python
@veratsien also wrote an article walking us through a bot she created - a Discord bot. She talks about creating a Discord bot does web scraping for us.
Before we get our hands dirty, I want to make it clear that while it seems like Iām complicating web-scraping by throwing in building a Discord bot. The bot is actually really simple to make thanks to the awesome Discord package.
It is currently estimated that there are about 5,000 independently-run animal shelters in the world. I personally feel there might be more. The efficiency of operations at these shelters depend largely on their ability to satisfy their main objective, usually to optimize select metrics. And in order to calculate these metrics, there is a requirement to collect, maintain and analyze data.
CONGRATULATIONS! You just finished your Dataquest career path. But now what?! In this post, I will go over 7 tips on what to do after you have completed the Dataquest analyst/scientist/engineer career path. The best part is you do not even have to be finished with the career path to start using these tips. These tips can be helpful at any skill level.
Guided Project sharer
@jesmaxavier has done it again - they have shared another awesome Guided Project!
This time on Answering Business Questions using SQL. It stands out for its wonderful and even intriguing subheadings, original and capturing storytelling style, very in-depth data analysis, and amazing visualizations.
Guided Project reviewers
This week, Iād like to call out some of the new budding reviewers who are helping folks in our community - @vinigomesaraujo and @clarkebacharach.
Yāall are providing helpful, actionable feedback to your peersā Guided Projects. Great job!
Iād love to see you continue checking out and commenting on other peopleās projects as you progress through the path.
Thank you all for participating in our Community!
I am glad to reward each of you with:
A 7 day extension on your current Dataquest subscription
An exclusive Community Champions badge in our Community
Thank you so much for the mention, @nityesh! Iām trying to be more active in the community, and I surely will give more feedbacks
Congratulations, champions of the week, and awesome articles from the March contest.
"Itās very common to run into HTML tables while scraping a webpage, and without the right approach, it can be a little tricky to extract useful, consistent data from them.
In this article, youāll see how to perform a quick, efficient scraping of these elements with two main different approaches: using only the Pandas library and using the traditional scraping library BeautifulSoup."
āWhile I donāt condone it, letās see what would happen if I use my model to make bets on fights. A quick look at the payouts using the picks derived from my predictive model, it appears that if I were to place a $100 wager for each fight, I would stand to make a net $269.07 profit from wagering $1000.ā
1. How to get weather data from OpenWeather API
2. How to create a Telegram Bot
3. How to send a personalized message through Telegram API
4. How to make the bot remind you to take an umbrella
5. How to upload your script on an AWS server and make it run every morning"
"As someone living in Vancouver, one of the most populous cities in Canada, I believe urban municipalities need to be prepared to welcome these newcomers. Although Canada is a relatively safe country, it is not without crime. Newcomers should understand the crime scene and choose carefully about where to live.
My goal for this project is to help migrants understand the safety of the urban neighborhoods in Canada by categorizing them."
@artur.sannikov96ās Guided Project called Are Fandango Movie Ratings Biased? stands out for its amazing visualizations (including the combination of colors), perfect project structure, very detailed and informative background context to the problem, and the conclusion.
Guided Project reviewers:
@brayanopiyo18 and @Elena_Kosourova did a great job of leaving encouraging and actionable feedback on their peersā projects this week!
Thank you very much @nityesh , for the special recognition and the appreciation, To the other champions, congrats! and letās continue making the community great.
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Iām always happy to be helpful to the Community! 
Congratulations to the other champions! 
This is a much needed confidence boost for me as Iām constantly feeling the struggle with learning Data Science! Glad you liked my projects!
