Laboratory Notebook Skills [pdf]

#1

Post by Tomte » Wed, Apr 24, 2019, 5:12 PM UTC

Laboratory Notebook Skills [pdf]
dur.ac.uk

Re: Laboratory Notebook Skills [pdf]

#2

Post by neoluddite » Wed, Apr 24, 2019, 6:16 PM UTC

would love to hear input from people with both lab and software dev experience to compare and contrast the two notetaking experiences

Re: Laboratory Notebook Skills [pdf]

#3

Post by Odenwaelder » Wed, Apr 24, 2019, 6:18 PM UTC

"Draw your figures in Excel" No no no no no no no! Do not draw your figures in Excel. Yes, they can be drawn quicly, but Excel figures suck, are a pain to customize and will introduce bad habits. Learn to draw figures in R using ggplot2.

Re: Laboratory Notebook Skills [pdf]

#4

Post by ska » Wed, Apr 24, 2019, 6:21 PM UTC

Odenwaelder wrote: post #3

"Draw your figures in Excel" No no no no no no no! Do not draw your figures in Excel. Yes, they can be drawn quicly, but Excel figures suck, are a pain to customize and will introduce bad habits. Learn to draw figures in R using ggplot2.

   Learn to draw figures in R using ggplot2.

Or any other of the handful of good tools.

Re: Laboratory Notebook Skills [pdf]

#5

Post by Odenwaelder » Wed, Apr 24, 2019, 6:22 PM UTC

neoluddite wrote: post #2

would love to hear input from people with both lab and software dev experience to compare and contrast the two notetaking experiences

These are excellent suggestions and are taught in science classes. Except for the use of Excel. Yes, Excel is easy, but its flexibility will lead to sloppiness, and drawing figures sucks. Excels statistical functions are also wrong in some cases. For data analysis, learn R or Python, period. If you have lots of data, learn to use SQLite in addition. The learning curve is steep, but well worth it.

Source: I have a decade of experience in science, and some 5 years in software development.

Re: Laboratory Notebook Skills [pdf]

#6

Post by Odenwaelder » Wed, Apr 24, 2019, 6:24 PM UTC

ska wrote: post #4

Odenwaelder wrote: post #3

"Draw your figures in Excel" No no no no no no no! Do not draw your figures in Excel. Yes, they can be drawn quicly, but Excel figures suck, are a pain to customize and will introduce bad habits. Learn to draw figures in R using ggplot2.

Learn to draw figures in R using ggplot2. Or any other of the handful of good tools.

R + ggplot2 was the road I took and taught my students. There are other good tools indeed.

Re: Laboratory Notebook Skills [pdf]

#7

Post by wodenokoto » Wed, Apr 24, 2019, 6:41 PM UTC

Have we reach a point where there are similar guides for Jupyter notebooks? Or just for the domain of data science / exploratory statistics

Like, conceptually, what should I keep, and how should I organise my notebook(s)?

Most guides are focused on what you can do (Here's how you draw a graph, here's how you load a kernel), I'd rather read about what I should store in my notebooks, and how many I should have.

Re: Laboratory Notebook Skills [pdf]

#8

Post by laughingman2 » Wed, Apr 24, 2019, 6:48 PM UTC

I started using Org mode in emacs. I use it to record the next tasks (Todos), expected results, and actual results. Its damn convinent that I can run code inside org file and say "cat" out the result of an experiment output as JSON by another script into my notebook. I can even embed and run multiple languages using org-babel.

I think I will be coming up with workflows and checkboxes soon for organizing a experiment and easily integrating results of the experiments I am running from disparate software.

I think its very easy to incorporate the stuff in this post, and create a new template in org mode for this. And its so flexible that it will fit all usecases.

Emacs is too awesome.

Re: Laboratory Notebook Skills [pdf]

#9

Post by zwieback » Wed, Apr 24, 2019, 6:52 PM UTC

Odenwaelder wrote: post #3

"Draw your figures in Excel" No no no no no no no! Do not draw your figures in Excel. Yes, they can be drawn quicly, but Excel figures suck, are a pain to customize and will introduce bad habits. Learn to draw figures in R using ggplot2.

Pure opinion until you explain why Excel figures suck and which bad habits it introduces?

Re: Laboratory Notebook Skills [pdf]

#10

Post by dhruvmittal » Wed, Apr 24, 2019, 6:55 PM UTC

Odenwaelder wrote: post #5

neoluddite wrote: post #2

would love to hear input from people with both lab and software dev experience to compare and contrast the two notetaking experiences

These are excellent suggestions and are taught in science classes. Except for the use of Excel. Yes, Excel is easy, but its flexibility will lead to sloppiness, and drawing figures sucks. Excels statistical functions are also wrong in some cases. For data analysis, learn R or Python, period. If you have lots of data, learn to use SQLite in addition. The learning curve is steep, but well worth it. Source: I have a dec…

So I had the opposite experience-- learned to do all my data processing in undergrad+grad school for physics using Python. Moved out to my first industry job developing simulations and learned that everyone (other scientists, management, etc) would rather me process results in excel (unless we were working on a database scale, in which case we used postgres). I actually had to learn excel properly for the first time for this job.

I'm now at another large university-affiliated research lab and excel is king here as well, though I can get away with using Matlab generated plots in my slides when I'm working solo. People still don't like python for some reason.

I had a similar experience with paper writing-- in academics it was conventional to do everything in LaTeX from my first lab courses in freshman year. In both workplaces, we've just been using word.

And it's not that people don't know python/latex here-- we've just apparently developed a culture of using these matlab/excel/word tools instead.