#TidyTuesday Tweets for week 8
The #TidyTuesday tweets included here are ones that included at least one image, and are arranged by submission date. Many thanks to the 115(!) people who submitted!! This page has been autogenerated as of 2019-02-21 and we hope you enjoy any random “house-cleaning” tips that accidentally may make their way in!
This Week’s Data
The @R4DScommunity welcomes you to week 8 of #TidyTuesday! We're exploring US PhDs awarded by field!!
— Thomas Mock 👨🏼💻 (@thomas_mock) February 18, 2019
📂 https://t.co/sElb4fcv3u
📰 https://t.co/VYVOmAzhMf#r4ds #tidyverse #rstats #dataviz pic.twitter.com/thhuNeEzUR
Submission by sil_aarts
My first #TidyTuesday using #gganimate. Seems like total GDP has a bigger slope, than the FRD budget.
— Sil Aarts (@sil_aarts) February 11, 2019
I wanted to include NIH budget, but the log transformation(log10) I needed to display all lines in one plot, didn't do the data justice in my opinion. #R pic.twitter.com/BPsNMAUwgy
Submission by CraigWangUZH
My first #TidyTuesday submission, and first time using #tidyverse and #gganimate in production! Comparing total Global Climate Change (GCC) Research Program spending vs. other R&D spending by departments in the US. @R4DScommunity .. probably too colorful -.- pic.twitter.com/i05jeJNWQu
— Craig Wang (@CraigWangUZH) February 11, 2019
Submission by SLEBeaufort
My first #SWDchallenge is a two-fer with #TidyTuesday, graphing variability of R&D spending across government agencies pic.twitter.com/bKTHlqKg48
— Stephon Beaufort (@SLEBeaufort) February 11, 2019
Submission by EvaMaeRey
my #ggplot2 flipbook project is online! 😎🤓🤓 Incrementally walks through plotting code (#MakeoverMonday, soon #TidyTuesday plots). Using #xaringan with reveal function; thanks, @statsgen @grrrck. #rstats. https://t.co/bBBzv0iZLw pic.twitter.com/tFtD78IOHZ
— Gina Reynolds (@EvaMaeRey) February 11, 2019
Submission by Amalan_Con_Stat
Scientific notation of numbers and plotting them was fun. Except for the R and D budget, other 3 have a steady increase over the years. Further, the R and D budget is very small than the others. Code: https://t.co/jmzfTGMRaT #tidytuesday pic.twitter.com/3WfBU72kWW
— Amalan Mahendran (@Amalan_Con_Stat) February 12, 2019
Submission by datawithZ
Recession/mortgage rate overlay from last week's #TidyTuesday #rstats pic.twitter.com/uZ5NyN6nUV
— Zachary Hamilton (@datawithZ) February 12, 2019
Submission by JerrickTram
Don't think it's too surprising that the Department of Defense has the biggest budget in every year from 1976 to 2017 although what departments are prioritized are interesting. #TidyTuesday pic.twitter.com/DwH7J4OLB2
— Jerrick Tram (@JerrickTram) February 12, 2019
Submission by ellis_hughes
This weeks #TidyTuesday I am using a variation of a candle plot to highlight changes in R&D Funding ove the years. Also introducing my #tidytuesdayR 📦for pulling in the data/readme from #TidyTuesday into your R environment! #rstats https://t.co/afRYGpJjkj pic.twitter.com/zYC6lgQRLe
— Ellis Hughes (@ellis_hughes) February 12, 2019
Submission by IamMRWani
#TidyTuesday Week 8 pic.twitter.com/AFlqcUpFvE
— M R Wani (@IamMRWani) February 12, 2019
Submission by FiskerBang
This #TidyTuesday explores Federal Budget data! 💵🏛
— Rasmus Fisker Bang (@FiskerBang) February 12, 2019
Nice to see that the US has more than doubled its relative spending on R&D in health 🏥 🤒
Not that nice to see that their relative spending on the Environmental Protection Agency is only 1/4 of what it used to be 🌎🚯 pic.twitter.com/eu0qCv3fqz
Submission by concept401
The word #declutter is a new big topic on radio and TV but what does it actually mean and how can you get started? Head over to my blog where I explain all about it https://t.co/8jIojcvDG0 and if you need help, get in touch.#TidyTuesday #mentalhealth pic.twitter.com/lRxHOfXF4i
— The Lifestyle Concept ~ DestinationHappy (@concept401) February 12, 2019
Submission by harrocyranka
#TidyTuesday Week 7. Interesting to see the changes in climate spending. While NASA only saw a slight increase, NOAA almost quadrupled btw 2000 - 2017.#dataviz #r4ds #tidyverse #ggplot2 #datascience pic.twitter.com/pQ5LwXcKWV
— Harro Cyranka 🔎 (@harrocyranka) February 12, 2019
Submission by DaveBloom11
#TidyTuesday - Week #7
— Dave Bloom (@DaveBloom11) February 12, 2019
Federal R&D Spending by Agency – Global Climate Spending
NASA spends the most - more than 3x any other agency in 2017 - but NOAA has increased their spend the most since 2000…
Code: https://t.co/OMj2q3FQH9#rstats #R4DS #dataviz pic.twitter.com/sdtbQYgDG4
Submission by OmniAnalytics
Did you know that #dplyr includes a set of special #tidyverse-compatible ranking functions? Here we show min_rank(), percent_rank() (re-scaled to [0, 1]), cume_dist() (CDF), and the base::cut()-like ntile() function! #rstats #tidytuesday
— Omni Analytics Group (@OmniAnalytics) February 12, 2019
See more here: https://t.co/1sO5ssusQj pic.twitter.com/M52Kpr6pQS
Submission by BirkinClean
3 Ways to organise your desk and keep it tidy
— BirkinClean (@BirkinClean) February 12, 2019
📌Keep supplies close by
📵Get rid of distractions
🗂Create effective filing systems#organisation #TidyTuesday #office pic.twitter.com/FMUF8YDuxS
Submission by veerlevanson
For this week's #TidyTuesday: NASA's R&D budget and number of space missions. Space mission info was taken from Wikipedia. Quite pleased with how the plot turned out :)
— Veerle van Son 🔎 (@veerlevanson) February 12, 2019
Code: https://t.co/neh4h2slda
Source: https://t.co/pqn3xj6Cbd#rstats #R4DS #dataviz pic.twitter.com/fS5CJ2c4AH
Submission by RSumaiya
First #tidytuesday plot, graphing the trend in R&D expenditure by department in the US. No surprises about the share of defense expenditure, but interesting to see health research going up.#dataviz #r4ds #tidyverse #ggplot2 #datascience pic.twitter.com/Rf3YLZhc74
— Sumaiya Rahman (@RSumaiya) February 12, 2019
Submission by TannerKoomar
Happy #tidytuesday! This is from last week's #mortgage related data. I had no idea that home prices in the midwest and south used to be over the national average, but have fallen below it since the mid 1990's. #rstats
— Tanner Koomar (@TannerKoomar) February 12, 2019
Code at: https://t.co/VAjCTFt26y pic.twitter.com/KTWNkszP2H
Submission by IamSambanthan
plotted the cumulative number of trees purchased of each type, artificial and real, from 2004 to 2014, comparing that to the 2016 U.S. population. Almost one realtree per person was bought over the course of 10 years!#TidyTuesday #ggplot2 #DataAnalytics #Data @dataandme pic.twitter.com/wqKSD0Zbsk
— Sambanthan S (@IamSambanthan) February 12, 2019
Submission by distav921
Yeah this is my son. #TidyTuesday pic.twitter.com/7NpgIw9heu
— Diana Stavrou (@distav921) February 12, 2019
Submission by k_j_norris
Word on the street is that Republican administrations spend more on war and security than Democratic ones. This #TidyTuesday shows it’s complicated. R&D higher at DoD but fairly flat at HHS and EPA. pic.twitter.com/eus2IZYuU2
— Ken Norris (@k_j_norris) February 12, 2019
Submission by JoshuaFeIdman
For this week’s #TidyTuesday – a correlation matrix of R&D budget per US government agency since 1976. High spending on research for the Department of Defence (DOD) is associated with low budget for the Environmental Protection Agency (EPA) and Department of Interior. #rstats pic.twitter.com/wbHOYGWnay
— Joshua Feldman (@JoshuaFeIdman) February 12, 2019
Submission by aimeegott_R
While @grpieces has been teaching intermediate #rstats #Shiny, I have been using this weeks #TidyTuesday data in an app to compare departments and use all the shiny features we are teaching. All the code with comments here: https://t.co/yTaz7HTTRK pic.twitter.com/5ZE22sIWkW
— Aimee Gott (@aimeegott_R) February 12, 2019
Submission by DavideMagno
This week's #TidyTuesday is about federal spending.
— Davide Magno (@DavideMagno) February 12, 2019
I was interested in understanding if spending had shifted towards clean energy sub-agencies in the last 20 years. Spoiler alert: unfortunately no! 😰#Rstats #tidyverse cc @thomas_mock @R4DScommunity pic.twitter.com/AbQzheSagU
Submission by mark_switajski
My first submission for #TidyTuesday takes a look at the R&D funding for the DoD and layered by the presidential party at that point in time. Inspired by @veerlevanson's submission: pic.twitter.com/RTiITPrJ6h
— Mark Switajski (@mark_switajski) February 12, 2019
Submission by othomn
Two clusters of R&D spending for this week #TidyTuesday? #rstats
— Otho (@othomn) February 13, 2019
Coming soon:
1⃣A better way to scale/normalize data?
2⃣What happens if you cluster only the Pres. Obama era?
3⃣A blog post with tidy code
for now:
🗞️https://t.co/SJElIPfJXg
👨💻https://t.co/znoeo6IbvV pic.twitter.com/wd6HivpAE2
Submission by Fernando_UCI
My first #TidyTuesday entry for Feb 12, 2019. I used a stacked area chart to map the percent of climate spending by gov. departments over time. Big thanks to @DaveBloom11 and @DavideMagno for sharing their code (which I borrowed quite a bit from for this entry). Really fun! pic.twitter.com/nhkKYyHcpV
— Dr. Fernando Rodriguez (@Fernando_UCI) February 13, 2019
Submission by EmilioMrno_
This is my first #TidyTuesday collaboration! As we can see NASA spends way more on its global climate change research program than any other agency!
— Emilio Moreno (@EmilioMrno_) February 13, 2019
Con dedicación especial para @jmtoralc por todo lo que me enseñó!#rstats #DataToViz #gganimate pic.twitter.com/av6U2qgzHa
Submission by tanyaneuro
#TidyTuesday is on federal spending. Research budget for defense most variable across GDPs, while all other departments essentially flat. Climate change research spending has decreased, yes, but NASA's share in total fed spending has been hit the most. https://t.co/dVYQdON2QI pic.twitter.com/c9ATrVclmH
— Constanza de Dios (@tanyaneuro) February 13, 2019
Submission by othomn
2⃣nd plot for this #TidyTuesday 😅
— Otho (@othomn) February 13, 2019
I tried to scale the spending between 0 and 1 (to highlight relative patterns), and to visualize clusters with heatmaps.
👨💻https://t.co/yO7S3jQO1D pic.twitter.com/GaotwRsEFr
Submission by Joseph_Mike
Finally got to doing a #TidyTuesday First but certainly not my last. Decided to do a quick trend of NJ House Pricing Index against the National Avg.
— Jose M (@Joseph_Mike) February 13, 2019
Code here: https://t.co/vPiPHRUfPX@thomas_mock pic.twitter.com/bMc47yn2Hk
Submission by apreshill
Last year I did a talk called “Take a Sad Plot & Make It Better” 😭
— Alison Hill (@apreshill) February 13, 2019
Now I'm looking for brave souls (#rstats, #python, #Excel!) to share their sad plots with me for a Sad Plot Showcase.
No shame, just sharing! 🤝https://t.co/E0HNX1CRfU#dataviz #ggplot2 #TidyTuesday pic.twitter.com/T5ildPrDq0
Submission by Alex_Danvers
Depressing data to play with for #TidyTuesday. I guess this is what not investing in the future looks like.
— Alex Danvers (@Alex_Danvers) February 13, 2019
R&D spending as a portion of budget has been decreasing for the last few decades. Zoom in on the failure to spend on health research. pic.twitter.com/EPXcBwRFQg
Submission by ptteresachen
First #TidyTuesday 🥳 Funding resources are not looking bright for biomechanists. DOD has the most share of GDP when it comes to R&D, but the proportion is still small. pic.twitter.com/cFrFiGtPsb
— Teresa Szu-Hua Chen (@ptteresachen) February 13, 2019
Submission by thomas_mock
My week 7 of #tidytuesday submission!
— Thomas Mock 👨🏼💻 (@thomas_mock) February 13, 2019
An exploration into Tufte-style sparkline plots in #ggplot2 with my personal theme.
I did choose to leave in the y-axis rather than direct label. 🤷♂️
Code & Plots: https://t.co/qmrI5uV3Cj pic.twitter.com/IZLNh8uhI3
Submission by jordanpeck89
My first #TidyTuesday submission , looking at US government spending on R&D. Please go easy on me.
— Jordan Peck (@jordanpeck89) February 13, 2019
Most pleased with figuring out how to add in dual Y axes, by normalising them both, in order to show both R&D spending proportion (as a percentage) and total outlays. pic.twitter.com/p4UO2Wa2qk
Submission by noccaea
Unofficial #TidyTuesday on 🚄French High Speed Trains🚄:
— LittleSquirrel (@noccaea) February 13, 2019
* Rate of late departure over time: it sucks to take the train from Macon, Toulon, Valence and Lyon. And 2018 was hell in general…
* Which lines accumulate or reduce delay during the trip: check yours!#R4DS #dataviz pic.twitter.com/5pb51amYCt
Submission by FournierJohanie
My #TidyTuesday week 7 submission. I choose to work on USDA data.#Rstat #dataviz https://t.co/PsEotOunt9 pic.twitter.com/FukbDKPwXf
— Johanie Fournier (@FournierJohanie) February 14, 2019
Submission by trevin_flick
I'm looking at the R&D budget (split into DoD and all other agencies) for #TidyTuesday week 7
— Trevin Flickinger (@trevin_flick) February 14, 2019
code: https://t.co/TTuxdgZe9R#rstats #R4DS pic.twitter.com/c48aZDfCWt
Submission by parkermquinn
Really cool data for this #tidytuesday! I may dive deeper on this subject in a blog post. Overall federal R&D spending (as a percentage of the discretionary budget) has fallen steadily, and climate/energy R&D is WAY behind and not catching up. Code here: https://t.co/7BobwwkCci pic.twitter.com/TuG33VnZg7
— Parker Quinn (@parkermquinn) February 14, 2019
Submission by othomn
I was searching new visualizations for a #TidyTuesday, instead I found some @accidental__aRt 😁 pic.twitter.com/VSiYDODKN6
— Otho (@othomn) February 14, 2019
Submission by WireMonkey
Another #TidyLater #TidyTuesday. This week we're looking at changes in climate change funding from year to year at a several agencies (NASA removed) with party control of the House, Senate and Presidency noted. #rstats #r4ds @thomas_mock pic.twitter.com/E3Ol8dewSk
— Alyssa Goldberg (@WireMonkey) February 14, 2019
Submission by jakekaupp
In this weeks #TidyTuesday data, I noticed a chart on global research intensity from #OECD data was missing Canada. Thought I’d go right to the source. Research in Canada has a way to go to recover from the previous government defunding. https://t.co/1BhlhPnYyC #rstats #r4ds pic.twitter.com/QDPuY8yEDy
— Jake Kaupp (@jakekaupp) February 15, 2019
Submission by srini_meen
For this weeks #TidyTuesday , Federal R&D budget as a percent of GDP seems to be falling, but the actual amounts seem to be constant only. (ie, America is getting richer 😎)
— Meenakshi Srinivasan 🐠 (@srini_meen) February 15, 2019
Tried my hand at #gganimate 😃
Code and stuff - https://t.co/lcUzAZwp2y pic.twitter.com/vQaOtMEaA0
Submission by srini_meen
The other plots #TidyTuesday pic.twitter.com/WTpq07H9fe
— Meenakshi Srinivasan 🐠 (@srini_meen) February 15, 2019
Submission by harrocyranka
Interesting that the series of GDP and R&D spending started to diverge in the 90s. I like how R&D saw a significant bump under Obama.#r4ds #tidyverse #tidytuesday #dataviz pic.twitter.com/gyNaOEtfqe
— Harro Cyranka 🔎 (@harrocyranka) February 15, 2019
Submission by sil_aarts
What to do on a free evening? Creating my own #TidyTuesday but with text!
— Sil Aarts (@sil_aarts) February 15, 2019
Seeing what my favourite subjects and people are @Twitter. I do have a lot of favourite words. Apparently, I love to say I ‘love’ things (or people? 🤔). @Tim_v_d_Stam you're up there!#textmining #data pic.twitter.com/LrSumH7qzC
Submission by PhilipWalsh_ML
#100DaysOfMLCode R1D40 #TidyTuesday #dataviz #r4ds just goofing with this weeks tidy tuesday data and ggplot #rstats pic.twitter.com/zM9h5dhX6u
— Philip Walsh (@PhilipWalsh_ML) February 15, 2019
Submission by Aleponcem
#TidyTuesday in #TidyFriday :P. I use the ideas of @aschinchon from his course in #datacamp and mix with #gganimate pic.twitter.com/euqvcmPnrj
— Alejandro (@Aleponcem) February 16, 2019
Submission by jspairani
Week 2019-02-12 challenge: #TidyTuesday #rstats picked Global Climate Change Research Program by department data. Practice on nest > map > unnest , and plotting ( labeling the outliers ). Variability per department & distribution over time. Enjoy 😄(code: https://t.co/NQfO970WQe) pic.twitter.com/k0kScBPK3R
— Julio Spairani (@jspairani) February 17, 2019
Submission by mattemagisk
Part two of teaching myself purrr with #tidytuesday: Fitting Gaussian processes and generalised additive models to budget data. Code and more at https://t.co/JnSFcL4S0j #R4DS pic.twitter.com/GZe6mz6YgB
— Sean Meling Murray (@mattemagisk) February 17, 2019
Submission by H0Vinicius
My #TidyTuesday contribution, it is interesting to see the behavior over time, I would like to know more about the US education system to have a better interpretation #ggplot2 #rstats #datavizbook #epibookclub pic.twitter.com/Vumaf1EUz4
— Vinícius Félix (@H0Vinicius) February 18, 2019
Submission by mlesheen
My first tardy #TidyTuesday post: a basic animated map of US milk production by state. @LizEisenhauer get at me pic.twitter.com/FSuOchO7Xw
— Emily Sheen (@mlesheen) February 18, 2019
Submission by GDataScience1
I learned a bunch by analyzing this data for PhDs awarded by field from 2008 - 2017. It is a little surprising that the Engineering broad field had the lowest number of PhDs awarded. #TidyTuesday #rstats @R4DScommunity pic.twitter.com/oRKl6uwk6I
— Tony Galvan (@GDataScience1) February 18, 2019
Submission by JerrickTram
What I'd like to know is what the heck happened in 2011 - 2013 for the drop off in Anthropology and Economic PhDs #TidyTuesday pic.twitter.com/hAutC0Y3GD
— Jerrick Tram (@JerrickTram) February 18, 2019
Submission by tanyaneuro
#TidyTuesday wk 8 is v v meta: How many PhDs graduate in each field? Lots of variability in Edu, not so much in Life Sci or Humanities. In Psych, sub-fields pretty stable across the years except where there was no data (like in my field, Cog Neurosci). https://t.co/2CjOFH4OLK pic.twitter.com/e1nMypxkkD
— Constanza de Dios (@tanyaneuro) February 19, 2019
Submission by DaveBloom11
#TidyTuesday - Week #8
— Dave Bloom (@DaveBloom11) February 19, 2019
PhDs Awarded by Field
Although most PhD's are awarded in life sciences, twice as many PhD's are awarded in social sciences compared to Physics (a life science).
Code: https://t.co/6ncV8x7xac#rstats #R4DS #dataviz pic.twitter.com/a7psuUA3ru
Submission by BenMoretti
My first #TidyTuesday with #Rstats - PhDs awarded by Field.
— Ben Moretti (@BenMoretti) February 19, 2019
There's some great visualisations out there so I thought I'd do something different and put it in a hierarchical tree using the great collapsibleTree package. Still have to fix up the colours. pic.twitter.com/SOeVgq7BR8
Submission by sil_aarts
#TidyTuesday. I used an ‘inverted excel file’, not the clean csv, so this week took a lot of ‘cleaning’, but here are the PhD awards in Psychology&Social Sciences. Not equally distributed…
— Sil Aarts (@sil_aarts) February 19, 2019
Source: NSF
Code: Pics pic.twitter.com/cYFGpttBZJ
Submission by BenMoretti
Now a heat map, this time for my old field Ag Science #TidyTuesday #Rstats pic.twitter.com/BVpKvqRkFY
— Ben Moretti (@BenMoretti) February 19, 2019
Submission by othomn
Last minute blogpost on the last week #TidyTuesday.
— Otho (@othomn) February 19, 2019
A bit of scaling and clustering observations :) #rstats
🙌😊https://t.co/0jrwMGbEcX🌙☀️ pic.twitter.com/3Hn6KPrgiV
Submission by IamMRWani
#TidyTuesday pic.twitter.com/c3OCPxEmXB
— M R Wani (@IamMRWani) February 19, 2019
Submission by harrocyranka
#TidyTuesday Week 8: doctorates awarded in the US. Life sciences awarded around 40% of the doctorates each year since 2008.
— Harro Cyranka 🔎 (@harrocyranka) February 19, 2019
Within the biomedical field, Epidemiology is one of the top subjects.#r4ds #tidyverse #epitwitter #datascience #dataviz pic.twitter.com/C4dqwPmjvF
Submission by BenMoretti
Final #TidyTuesday week 8 post: This time I looked at the Ag Science major field, and calculated the % difference in PhDs to the previous year for each field. All look ok but I'd be worried about the Animal research group as they're declining #Rstats pic.twitter.com/9SjX64KJo4
— Ben Moretti (@BenMoretti) February 19, 2019
## Submission by _jwinget
For this week's #TidyTuesday post, I went back and analyzed the incarceration data from week 4 since I couldn’t at the time. I decided to focus a bit more on modeling over data viz. Curious about what’s going on in DC 🤔#rstats #tidyverse
— Jeremy R. Winget (@_jwinget) February 19, 2019
📂 https://t.co/Nusdz930KM pic.twitter.com/1TeO4AxdaX
Submission by Amalan_Con_Stat
Computer science PhDs more than others is that the boom of AI. beginning from 2008 itself !!!!!. My first ridge plot and alluvial diagram.
— Amalan Mahendran (@Amalan_Con_Stat) February 19, 2019
Code: https://t.co/TtWLzNk1ga #tidytuesday pic.twitter.com/AhB01IPuv6
Submission by mistermichaelll
My #TidyTuesday contribution: this graphic made entirely with #ggplot2. I took some inspiration from 538, @BBCWorld, and some plots I saw on The World Bank to make my favorite chart I've done so far! #rstats pic.twitter.com/7ZzpEzZuLV
— michael (@mistermichaelll) February 19, 2019
Submission by lta100163
#TidyTuesday plot - @RideIndego (Philadelphia’s bike share service) 2018 trips. Bimodal distribution peaking at start/end work times. Plus a generally normal distribution for weekend days only (yellow fill colors at bottom). Also, it looks like the Emerald City of Oz. :) pic.twitter.com/Z6pXXzIqyC
— Leonard Armstrong (@lta100163) February 19, 2019
Submission by veerlevanson
A #gganimate graph for #TidyTuesday: PhD degrees awarded per field (2008-2017). Most PhD degrees were in Life sciences. The number of Education PhDs has declined.
— Veerle van Son 🔎 (@veerlevanson) February 19, 2019
Code: https://t.co/6BX3Ty91vj
Source: https://t.co/lTYvPpeuQ3#rstats #R4DS #dataviz #phdlife pic.twitter.com/GejtUzOLK7
Submission by W_R_Chase
Very excited to share my first ever #TidyTuesday #rstats submission! 📊📈 I'll be sharing about this dataset all week. Today I'm getting an overview of the data. 1st chart is an area scaled bump chart showing how field of study popularity has changed over time… (1/2) pic.twitter.com/Ot1wuRaGyM
— William Chase (@W_R_Chase) February 19, 2019
Submission by sauravg94
#TidyTuesday #rstats Here is my sub for Week 8. A comparison of majors in 2008 and 2017 shows that STEM, Psychology, and medical research witnessed positive growth in the number of PhDs, while education and arts witnessed negative growth. pic.twitter.com/vcBl0SE8bi
— Saurav Ghosh (@sauravg94) February 19, 2019
Submission by mark_switajski
A quickie with gganimate that was inspired by an old 538 article. What are young mathematicians studying over the last decade? 📊https://t.co/sTcd7w9jkf#TidyTuesday @R4DScommunity pic.twitter.com/JAn64PGKPY
— Mark Switajski (@mark_switajski) February 19, 2019
Submission by urbaboxx
Keep it clean! and brilliantly organised https://t.co/4O1fTeDgVW #UtilityRoom #Clean #Oraginsaed #TidyTuesday pic.twitter.com/erfGpTnXRm
— Urbaboxx (@urbaboxx) February 19, 2019
Submission by JoshuaFeIdman
A treemap of US PhDs awarded in 2017. #TidyTuesday pic.twitter.com/Z9D27tEDQv
— Joshua Feldman (@JoshuaFeIdman) February 19, 2019
Submission by pootzie_xoxo
Being brave and posting my #TidyTuesday this week using NSF data on % of PhDs awarded to women. In aggregate, the percentage of PhDs going to women is on the rise. However, when I look at fields with traditionally low female representation, we see stagnation and even declines. pic.twitter.com/I83oiQhkt7
— Jenni Putz (@pootzie_xoxo) February 19, 2019
Submission by gathmad
Quick #TidyTuesday showing the relative increase/decrease in popularity of PhD subjects from 2008 - 2017. Education largely on the slide, but Atmospheric Science on the up. Just in time to stop the oceans boiling. Code here: https://t.co/b0TWFQ7PN2 pic.twitter.com/Bb449c0Bmf
— Gareth (@gathmad) February 19, 2019
Submission by theotheredgar
A simple pre-rendered flexdashboard Shiny app is my submission for this week's #TidyTuesday . For the visualizations it uses collapsibleTree and formattable. The source code is embedded in the dashboard: https://t.co/Wfch5Vyq4F #rstats pic.twitter.com/8LlNyxkJro
— Edgar Ruiz (@theotheredgar) February 19, 2019
Submission by kerenxuepi
my first #TidyTuesday with ggalt and bbplot using data from https://t.co/UX0Hn1uSqr pic.twitter.com/GiPKQN42ii
— Keren Xu (@kerenxuepi) February 19, 2019
Submission by parkermquinn
Fascinating combo of hierarchical and time-series data in this week's #tidytuesday! First time making a treemap (for the hierarchy) and bump chart (popularity over time). I focused on engineering for the bump chart, any others worth looking at? Code: https://t.co/5lBEZMi4KZ pic.twitter.com/9HdZOZ2ke5
— Parker Quinn (@parkermquinn) February 19, 2019
Submission by committedtotape
#TidyTuesday week 8, focussing on Maths PhDs. New thing this week: trying to make my plots more mobile-friendly. Heavily inspired by @grssnbchr course on @DataCamp #rstats #dataviz #ggplot2 pic.twitter.com/UFpDC7gY6f
— David Smale 🔎 (@committedtotape) February 19, 2019
Submission by BenMoretti
Now with colour! Thanks to @theotheredgar for the tip - I was not using collapsibleTreeSummary
— Ben Moretti (@BenMoretti) February 19, 2019
Code here https://t.co/t7fENz9F5Z#TidyTuesday #rstats pic.twitter.com/vKs1B7arTJ
Submission by EdudinGonzalo
My first #TidyTuesday - better later than never 😀 pic.twitter.com/vJfSh70g1p
— EduGonzalo (@EdudinGonzalo) February 19, 2019
Submission by noccaea
#TidyTuesday week 7: the U.S. National Science Fundation budget has increased steadily over the years, but has decreased steadily relative to GDP.#R4DS #rstat #dataviz pic.twitter.com/6cSfJuXaog
— LittleSquirrel (@noccaea) February 19, 2019
Submission by noccaea
Playing around quickly with last week' #TidyTuesday.
— LittleSquirrel (@noccaea) February 19, 2019
U.S. budget has invested a huge amount of money in defense, and secondly in health in the past forty years or so..#R4DS #rstat #dataviz pic.twitter.com/tT03pvOuyq
Submission by noccaea
#TidyTuesday week 7: In general, the percentage of the U.S. federal budget invested in research and development has crashed in the past 40 years, even for defense and health!#R4DS #rstat #dataviz pic.twitter.com/I3oEirbR1e
— LittleSquirrel (@noccaea) February 19, 2019
Submission by EmilioMrno_
What are social scientists studying? This is my contribution to #TidyTuesday!
— Emilio Moreno (@EmilioMrno_) February 20, 2019
Number of phDs awarded on each field during the last decade#rstats #gganimate @R4DScommunity pic.twitter.com/9pZl0b2vyI
Submission by Zach31402357
#TidyTuesday first attempt with the Week 8 PhD dataset. I'm new to using R - any tips are always appreciated! pic.twitter.com/vTyWYU4KGu
— Zach (@Zach31402357) February 20, 2019
Submission by GrwllRnc
My #TidyTuesday (2019-02-19) contribution: Fields of Study with Highest Change in Number of Awarded PhDs Over Timehttps://t.co/qUruRYhCG9 #rstats pic.twitter.com/GtH42DJaEd
— Benjamin (@GrwllRnc) February 20, 2019
Submission by FournierJohanie
#TidyTuesday | 2019W8: USA Doctorat field of study#Rstats #dataviz https://t.co/DwveXbobZM pic.twitter.com/PpfALYngGa
— Johanie Fournier (@FournierJohanie) February 20, 2019
Submission by trevin_flick
#TidyTuesday Week 8
— Trevin Flickinger (@trevin_flick) February 20, 2019
I wonder how much impact the great recession had on the increase in PhDs 🤔
code with more plots: https://t.co/sO7rWSSdJC#rstats #R4DS pic.twitter.com/PRMSjx7wCs
Submission by mldebusklane
Educational research PhD trends over the past 10 years. Marked increases in https://t.co/m8ouhyvdKR and policy analysis. Declines in some interesting areas. Thank you for the code @parkermquinn My code: https://t.co/5ZjgxJKZEi #tidytuesday pic.twitter.com/Mx7Ef7Kamw
— Morgan Les DeBusk-Lane (@mldebusklane) February 20, 2019
Submission by Joseph_Mike
Catching up on last week's #TidyTuesday which focuses on the federal R&D spend trends. Not all departments have an upward trend in spend but all of them do show a downward trend as a percent of total spending. @thomas_mock @R4DScommunity pic.twitter.com/vVvaK3KT9Z
— Jose M (@Joseph_Mike) February 20, 2019
Submission by srini_meen
For this weeks #TidyTuesday I first checked out STEM PhDs by sex. Looks like the gender gap in STEM fields is reducing, women have zoomed ahead in life sciences! (Engineering and comp, we are getting there!😎) Got a good data cleaning practice!😅😅
— Meenakshi Srinivasan 🐠 (@srini_meen) February 20, 2019
Code- https://t.co/pUj7aT3UK4 pic.twitter.com/5sFI5lPths
Submission by tanyaneuro
I dug further into #TidyTuesday wk 8 data! Here's how long it takes for PhDs in various fields to finish their degrees. In psych (my field) & related areas, it takes 6 yrs, which is the lowest it's been historically. Taming the raw data was fun btw. https://t.co/2CjOFH4OLK pic.twitter.com/HlPzmF1IDA
— Constanza de Dios (@tanyaneuro) February 20, 2019
Submission by TannerKoomar
I was surprised this #TidyTuesday with just how many more PhDs the life sciences produce. This offshoot from last week's AAAS data may show why: the US government gives universities so much more money for life sciences I had to make a second gif! #rstatshttps://t.co/QLTKXxnuec pic.twitter.com/l3TFx4AfKS
— Tanner Koomar (@TannerKoomar) February 20, 2019
Submission by ellis_hughes
This weeks #TidyTuesday I looked at the 6 majors with the largest increases in graduates. I again used the #tidytuesdayR package to assist in downloading the data for me and showing the readme. Thank you @thomas_mock for your feedback! https://t.co/afRYGpJjkj #rstats pic.twitter.com/ENAGUhgB8n
— Ellis Hughes (@ellis_hughes) February 20, 2019
Submission by Alex_Danvers
#TidyTuesday Number of PhDs data.
— Alex Danvers (@Alex_Danvers) February 20, 2019
Number of PhDs per year for social, I/O, developmental ~200, but ~20 for personality & quant.
Small sample, so don't draw any strong conclusions, but cross correlation indicates that # of social phds is associated w future # quant phds. pic.twitter.com/NJRZXOqitJ
Submission by 1LuisDavid
In somewhere is #TidyTuesday yet…
— Luis David🌀 (@1LuisDavid) February 20, 2019
Comparing data of US PhDs awareded in Social Sciences from 2008 to 2017, looks like people today prefers make a PhD in linguistics rather than in Public Policy.
Thanks for the teaching, @jmtoralc . pic.twitter.com/H84g39FoHV
Submission by TUrdesai
Considering #epibookclub crossover, I had to make sure I posted my first #TidyTuesday this week! I looked at the # of phds from fields related to public health/epi…Couldn't decide whether all the lines on 1 graph or faceting was the better option (or neither?) so here's both! pic.twitter.com/VU5jQfBJkm
— Roshni Desai (@TUrdesai) February 20, 2019
Submission by W_R_Chase
#TidyTuesday day 2, looking closer at PhD demographics. First is the breakdown of gender imbalance and ethnicity by field of study in PhD graduates. Honestly I was expecting better diversity in 2017… kind of depressing. #rstats #dataviz (1/2)… pic.twitter.com/AdTSVDDbsl
— William Chase (@W_R_Chase) February 20, 2019
Submission by k_j_norris
Experimenting with different ways to label and highlight data for #TidyTuesday.
— Ken Norris (@k_j_norris) February 20, 2019
Seeking trends in #IndustrialEngineering (for IE’s like me). Wonder why systems engineering is growing so fast? pic.twitter.com/veHXqMFENJ
Submission by alouiseme
Spent #TidyTuesday comparing PHD programs. Interesting to see the trickery of a free y-scale. See Engineering V Art, as compared to Education v Life Sciences - side by side, it appears Engineering, Art, and Life sciences are all outpacing Ed, but look again at that y axis! pic.twitter.com/1JHvBscezk
— amber medina (@alouiseme) February 20, 2019
Submission by mattemagisk
For this week's #tidytuesday, I've played around with a custom special binary operator and diverging bar plots (again, using #bbplot by @BBCNewsGraphics). Code and more at https://t.co/kNdL13fzy3 #R4DS pic.twitter.com/KLVTL8O6mH
— Sean Meling Murray (@mattemagisk) February 20, 2019
Submission by WireMonkey
#TidyTuesday #TardyTuesday #rstats #r4ds @thomas_mock
— Alyssa Goldberg (@WireMonkey) February 20, 2019
Week 8 tracks changes to the top 20 PhDs awarded to women (as defined by dataset). Partially cleaned the data manually. Learned to expand font options. Added the xkcd and gameofthrones packages. pic.twitter.com/3RQjoHhT6r
Submission by sil_aarts
New #TidyTuesday because I was wondering how long an average PhD trajectory takes. Median years= almost 6. Does it differ per sex? Not that much. GG Girls/women! (men too of course!)
— Sil Aarts (@sil_aarts) February 20, 2019
Source: National Science Foundation
Code: https://t.co/7zmVawPz3G pic.twitter.com/7M8JZ7x8m6
Submission by EpiEllie
The #tidytuesday #epibookclub crossover is amazing! So many really cool data visualizations! And all the code available! I’m definitely gonna have to set aside some time to work through these. Thanks for setting this up, @thomas_mock!! pic.twitter.com/dAqnE1USqZ
— Ellie Murray (@EpiEllie) February 21, 2019
Submission by Joseph_Mike
Here's my #TidyTuesday submissions for this week using the NSF data on number of PHDs awarded. Thanks to @thomas_mock and the @R4DScommunity for making the data available. pic.twitter.com/KfTmOfQZWG
— Jose M (@Joseph_Mike) February 21, 2019
Submission by jakekaupp
Dug a little deeper into the NSF archives for more complete doctoral completion data. Put together a set from 1985 to 2017. Education PhDs look to be quite the commitment. Code @ https://t.co/1BhlhPnYyC #TidyTuesday #epibookclub #rstats #r4ds pic.twitter.com/Oi6CrcCEme
— Jake Kaupp (@jakekaupp) February 21, 2019
Submission by FreyGeospatial
My #TidyTuesday submission for last week's data. The first image shows annual federal government R&D funding for all departments as a percent of GDP. The the second image shows the EPA R&D budget over time. All budget data accounts for inflation. Code: https://t.co/Atddj3WRd3 pic.twitter.com/xA8618SKoo
— Jordan Frey (@FreyGeospatial) February 21, 2019
Submission by htoscano84
Still looking at week 7 of #TidyTuesday. R&D budget in the last three years - Top 5 departments.
— Hugo Toscano 🔎 (@htoscano84) February 21, 2019
code: https://t.co/YyCPEXMVVz#rstats #r4ds #dataviz #waffle pic.twitter.com/Z17dH1UjYm
Submission by W_R_Chase
My 3rd #TidyTuesday submission highlights the gender and ethnicity discrimination in PhD funding. Women and minorities receive fewer assistantships and more often use their own resources to fund their PhDs #dataviz #rstats
— William Chase (@W_R_Chase) February 21, 2019
Code: https://t.co/GH2IOQIuIb pic.twitter.com/jObMXAaXB0
Submission by RLadiesAmes
The #rladies Ames “solution” from this week's #TidyTuesday on PhDs awarded from 2008-2017 is now posted on Github: https://t.co/dZ0tPUYcMU pic.twitter.com/xM0jDmQWyz
— R-Ladies Ames (@RLadiesAmes) February 21, 2019
Submission by IamMRWani
#tidytuesday Week 8, Inspired by @Zach31402357 If you add color, it will look this pic.twitter.com/X292LhoAXy
— M R Wani (@IamMRWani) February 21, 2019
Submission by jakekaupp
I was also tinkering around with a streamgraph-style visualization of the median time to completion data. Not entirely satisfied with it, but wanted to share how the experiment turned out! #TidyTuesday #rstats #r4ds #epibookclub pic.twitter.com/cAP5nsuzDg
— Jake Kaupp (@jakekaupp) February 21, 2019
Submission by nsgrantham
US institutions awarded 50k PhDs in 2017 — that’s 150 doctoral grads per 1 million US residents. Here’s how they break down by field of study. I’m happy (and relieved!) to count myself among the 502 total Statistics grads in 2017. 🙂 #rstats #dataviz #tidytuesday #epibookclub pic.twitter.com/KacApSH7m6
— Neal Grantham (@nsgrantham) February 21, 2019