From 24ddec74c6ec85706e096666d00fccc40bda98fe Mon Sep 17 00:00:00 2001 From: markur <98951648+markur4@users.noreply.github.com> Date: Fri, 8 Mar 2024 13:41:06 +0100 Subject: [PATCH] paper changes --- paper.bib | 5 +++++ paper.pdf | Bin 449935 -> 449930 bytes 2 files changed, 5 insertions(+) diff --git a/paper.bib b/paper.bib index 90a7a71..59def55 100644 --- a/paper.bib +++ b/paper.bib @@ -5,6 +5,7 @@ @misc{charlierTrevismdStatannotationsV02022 year = {2022}, month = oct, doi = {10.5281/ZENODO.7213391}, + url = {https://zenodo.org/record/7213391}, urldate = {2023-11-16}, abstract = {Add scipy's Brunner-Munzel test Fix applying statannotations for non-string group labels (Issue \#65) Get Zenodo DOI}, copyright = {Open Access}, @@ -23,6 +24,7 @@ @article{hunterMatplotlib2DGraphics2007 pages = {90--95}, issn = {1558-366X}, doi = {10.1109/MCSE.2007.55}, + url = {https://ieeexplore.ieee.org/document/4160265}, urldate = {2023-11-15}, abstract = {Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems}, file = {/Users/martinkuric/Zotero/storage/W4FJZDNY/ยง-hunterMatplotlib2DGraphics2007.pdf;/Users/martinkuric/Zotero/storage/GW3HZZHR/4160265.html} @@ -70,6 +72,7 @@ @article{vallatPingouinStatisticsPython2018 pages = {1026}, issn = {2475-9066}, doi = {10.21105/joss.01026}, + url = {https://joss.theoj.org/papers/10.21105/joss.01026}, urldate = {2023-05-29}, abstract = {Vallat, (2018). Pingouin: statistics in Python. Journal of Open Source Software, 3(31), 1026, https://doi.org/10.21105/joss.01026}, langid = {english}, @@ -88,6 +91,7 @@ @article{waskomSeabornStatisticalData2021 pages = {3021}, issn = {2475-9066}, doi = {10.21105/joss.03021}, + url = {https://joss.theoj.org/papers/10.21105/joss.03021}, urldate = {2023-03-26}, abstract = {Waskom, M. L., (2021). seaborn: statistical data visualization. Journal of Open Source Software, 6(60), 3021, https://doi.org/10.21105/joss.03021}, langid = {english}, @@ -104,6 +108,7 @@ @article{wickhamTidyData2014a pages = {1--23}, issn = {1548-7660}, doi = {10.18637/jss.v059.i10}, + url = {https://doi.org/10.18637/jss.v059.i10}, urldate = {2023-11-15}, abstract = {A huge amount of effort is spent cleaning data to get it ready for analysis, but there has been little research on how to make data cleaning as easy and effective as possible. This paper tackles a small, but important, component of data cleaning: data tidying. Tidy datasets are easy to manipulate, model and visualize, and have a specific structure: each variable is a column, each observation is a row, and each type of observational unit is a table. This framework makes it easy to tidy messy datasets because only a small set of tools are needed to deal with a wide range of un-tidy datasets. This structure also makes it easier to develop tidy tools for data analysis, tools that both input and output tidy datasets. The advantages of a consistent data structure and matching tools are demonstrated with a case study free from mundane data manipulation chores.}, copyright = {Copyright (c) 2013 Hadley Wickham}, diff --git a/paper.pdf b/paper.pdf index 1cae41d7ceb7f3eaf7da3491760cba81c22f3b6a..d324341c9c81c3faae150696b2d9e55b5544fcda 100644 GIT binary patch delta 4946 zcmV-Y6RqrzyBmtT8-RoXgaU*Ev;;7b0yZ$0p|1fHw?>f!DGPt85+39^jT?DQkn6LT0@N$~Y-E3!fYO(u0Z{AgAo#*-qX?3O|>^iQSw|NGwbJ!L(g=QQYL-4W~ zzwE7sx)EHIx}4M?^H={1uRCWR%GJ4)M7G`(!`A|fxXs9IDL$+0>(9a1V7C34&hYY# z^w#bE&D>Vfa0?U>{XJruCAMX>G6`1p#+Lzh=MZjnVDKj(|YK4Plx5aMNc1Jlc)P460&z$G6M>3gdq~MI&T@*3suui&1pU2^|~dPq5@=oGirtgn3=l2)@d?$le9|oM+Psi#Ouv zy4b2LR(e{)y20;R`#04Vg`Q#Pi={fxWuOio(>ccXD&0Y>hV96s=E5~ED^9Z94G$m} zGxTHOfrJYT6}-f?V`irGQpAYRJ>9k{uGLwMyb*uq!kJMaC;c;uiFezdmdu%Na#AGd?aY!w(-X_^SdWXr zZU%oL@=LPm<{GTQhMxA8sjNE+Y$v-7la{=B%-UB^abX+M4iT_Yx-*YB3+9Q1w4))# z%xJGb)GRy@R#h;hZ;j;Ti04h&TC0rNjQT~;zh@tqf*HSd%5vZ{#&rcvs85NNi~lP* z(dz#O>f_z)scG`kmqXe5o!gNf$->v7HJyKT?y|$Wm%72ui;G6gOKdPNw6%{0-nFZa z59fir%CTBM?YWJr4$k2kT$y%MDZq6X>v^%yswTGZkJxzc#fDUI?DdN6#|!(VZ2@1s${43lMaHak6<$Otsn=0^{peM|M3Y(N35zN}Js4m)Wjz>u6EO>0bSQtj zWRw*rRz5geS%cQP9QASBzAX&n8>wZyWHU@qDs0 zie|G=+7CxivzTQ`s0RQ4-hwD7P_L%6HclG{|a9ABry)JLK$+m&Gr;0}%_EJ2*@ z2$0NNR)5#PkhZH~o10}MNfwIN7(Rcz%1~^aF&EO|MG-F&WD4TU&qyidRX9tc4{XlO zXpP>n664CYpAb*TZJUVK?K(zBafOad)f%v$HVm;nxI5cb!$;-3`MF6$w0`Y4h%8#x zxYzdrZ1gS18-`=uotZF$97U|O!6-9pW6wM@A6MdCoa1(~B4YKb+;htqcV>T-cHW9m z&LFtru|GCZ-7WEXV^zd>W=DKq2#eMb&p5AKp57@lZ3d1cP0zdg*iy%T01)U^bdghp+tMdW?jhG=n0%u$OT&j=#uElIs zdG(q!_7^+lr!g13`)-dx$68-6Ueog8%Bzo-=#jO;uUbKG9rN~4-fn+kJ$amu6Q@lD zLLhZ121@>6UKQ6=XVx*mUj;lb`)4Z4Pmf&Sbn z(0Tn*lLhj%TGyR&+cIfy@A!rd?AYK3bARCs(4l+&K4w`qnRRRO+`n9LUGE7OoPuOl z>Du`K=CngnaZZk*>)^TuN>+Ef*LyZ>4?<2bXJP``14U$g#Qr7+lfu(NpIf@ z-e}Hs_;L!_^x+>YLaM73bAyn^3;nJ`5qZA~NXbI|@G)4|j%yZy=~hV}>Y;S{Hs?F# zGsXb&)Gfnz9o#>j>RnVZt`?@fL}%CH{RbrUkuVBnZe+LLqXdvg3p6k~GB_(RF*-0X zm*DFJ7?%sl1PiyF>je1$1T-)@GMAd|1U&>aFgh}q+wBBD1T-)@GPfS?1Ren-F=S&o zHD)q4EjKkZHZ3$`Wo9j5He)$0FfcV{H(@w9WHC56w_xuC!2tp?Hn$`31QnA3Gnb*S z0Th45SWAx^Hw?b}SIi$+MWQH50u~1RSQpJL?cRc%QnZ&YiuTgKUy^#vSROyN2@n_q zk2DfVQQt>WvXkZCKY!?-oqqXgV=sD~zPQOHW09s9tpS+6zHR>An4B}BeqX%mCl^Q? 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