I am using Jupyter Notebook to write my report and it would be convenient to include an output in my markdown.
The question below is a simillar question.
Jupyter notebook output in markdown
For example, I have a code cell with the code
In[1]: import random
a = random.randint(1,4);a
and the output was
Out[1]: 2
in my report, I would realy like to include this output just like
'the chosen number was 2'
however, as the 2 is a random number, it would be very convenient to have a way to include the variation a in my markdown like;
'the chosen number was %a'
kind of way.
Is there any way to achieve this?
It's not possible in the main notebook yet (although there are discussions about it) but there is an extension which should suit your purposes:
http://jupyter-contrib-nbextensions.readthedocs.io/en/latest/nbextensions/python-markdown/readme.html
It's contained within the ipython-contrib-extensions package, for which the install instructions are here:
http://jupyter-contrib-nbextensions.readthedocs.io/en/latest/install.html
Related
Is there a convenient way to render all markdown cells in a Jupyter notebook at once without running the code cells?
I find it quite annoying that while moving through my notebook and doing some little corrections the markdown cells "loose" their formatting. Is there an extension or a command with which I can "run" (i.e. render) all and only the markdown cells? If not, is there a way to at least update the table of content from the markdown cells. My table of content is realized via nbextensions.
You could use JupyterLab which provides a Render all Markdown cells action if you are not limited to plain Jupyter notebooks. Doing this programmatically within the notebook seems to be not trivial to do as we can derive from this GitHub issue. We might be able to implement this ourselves, but I am not aware of any resources that provide something similar.
I have read previously asked similar questions here, here, and here (among many more).
Unfortunately, none of the solutions offered to those questions seem to solve my issue.
I tried the function written by #bryanshalloway here but that did not have the desired result.
For more context, I am producing scientific manuscripts using an R Markdown workflow. I perform EDA in one notebook and later come back to write the manuscript in a different notebook. I import the data, wrangle it, create tables, and do some basic visualizations in the EDA notebook and include narrative text (mostly for myself).
I then create a separate notebook to write the manuscript. To keep it reproducible, I want to include all of the steps from the EDA with respect to data import, tidying, and wrangling, however I do not need the commentary that went along with it. Additionally, I may want some (but definitely not all) of the tables and basic visualizations I created during the EDA, but I would need to build them up substantially to get them publication ready.
My current workflow is just copying and pasting the relevant code chunks and then adding to those where necessary for tables and figures (i.e., adding labels and captions to a ggplot).
Is there a way to "source" these individual code chunks from one R Markdown file/R Notebook into another? Perhaps using knit_child (but not bring the entire R Markdown file into the current parent file)?
I would like to avoid copying the desired code chunks into separate R scripts.
Thanks!
It is very possible with knitr purl and spin:
Ok lets say this is your initial Rmarkdown report:
call the file report1.Rmd
---
title: Use `purl()` to extract R code
---
The function `knitr::purl()` extracts R code chunks from
a **knitr** document and save the code to an R script.
Below is a simple chunk:
```{r, simple, echo=TRUE}
1 + 1
```
Inline R expressions like `r 2 * pi` are ignored by default.
If you do not want certain code chunks to be extracted,
you can set the chunk option `purl = FALSE`, e.g.,
```{r, ignored, purl=FALSE}
x = rnorm(1000)
```
Then you go to the console and purl the file:
> knitr::purl("report1.Rmd")
this creates an R file called report1.R in the same directory you are in,
with only the chunks that are not purl=false.
Its an simple R script looking like this:
## ---- simple, echo=TRUE----------------------------------------------------------------------------
1 + 1
Lets rename the file for safety purposes:
> file.rename("report1.R", "report_new.R")
Finally lets spin it back to report_new.Rmd :
> knitr::spin("report_new.R", format = "Rmd", knit=F)
This gives you a new Rmd file called report_new.Rmd containing only the relevant chunks and nothing else
```{r simple, echo=TRUE}
1 + 1
```
In org-mode, I can name the output of a code block and include it elsewhere in the document.
Is it possible to do this (or something similar) in a colab .ipynb file, or within a Jupyter notebook in general?
For example, I can make a cell with some Python code that generates a plot:
import matplotlib.pyplot as plt
plt.plot([0,2,1,4,9])
After executing, the plot appears below the code cell. So far so good.
But how do I capture this plot and to use it elsewhere in the notebook?
My hope is there is some syntax so that I can include the plot in a markdown cell, for example:
# this is my title
As you can see, the numbers go up and down in the plot:
![][some_magic_link_here]
Here is some more text to explain the plot.
Does such a feature exist in colab?
Good news - embedding an image in another markdown cell is self-service. Here's an example:
Full notebook:
https://colab.research.google.com/drive/1PF-hT-m8eZN2CBzFkMp9Bvzj9pSBQVYn
The key bits are:
Using IPython.display.Markdown is order to programmatically construct the markdown.
In addition to rendering, save the matplotlib figure using savefig.
Include the image data in the markdown after base64 encoding.
I am working on ipython notebook to apply tf-idf and knn model. I want to save the output of below command in excel: knn_model.query(Var, k = 20) . I can see it in the notebook but dont know how to save this output in my system. Please help.
Easiest answer: Copy paste the result to a file, which you could use as input to where you want to use the result?! Using any text-editor where you opened a new file to copy into.
More complicated answer: you forget to tell where the out put has to go ... Python has lots of possibilities to export Python created output to.
my question(s) might be less general than the title suggests. I am running R on Mac OS X with a MySQL database to store the data. I have been working with the Komodo / Sciviews-R for some time. Recently I had the need for auto-generated reports and looked into Sweave. I guess StatET / Eclipse appears to be the "standard" solution for Sweavers.
1) Is it reasonable to switch from Komodo to StatET Eclipse? I tried StatET before but chose Komodo over StatET because I liked the calltip / autosuggest and the more convenient config from Komodo so much.
2) What´s a reasonable workflow to generate Sweave files? Usually I develop my R code first and then care about the report later. I just learned today that there is one file in Sweave that contains R code and Latex code at once and that from this file the .tex document is created. While the example files look handily and can't really imagine how to enter my 250 + lines of R code to a file and mixed it up with Latex.
Is it possible to just enter the qplot() and ggplot() statements to a such a document and source the functionality like database connection and intermediate results somehow?
Or is it just a matter of being used to the mix of Latex and R code?
Thx for any suggestions, hints, links and back-to-the-roots-shout-outs…
You've asked several questions, so here's several answers;
Is StatEt/Eclipse the right way to do Sweave ?
Not nessarily (note: I'm an avid StatEt/Eclipse user, and use it for both pure R and Sweave/R and love it, I haven't used Komodo / sciviews-R). You should be able to run the sweave command from any R command line which will generate a .tex file. You can then turn the .tex file into something readable (like pdf) from any tex environment.
What's a good Sweave workflow ?
When I have wanted to turn an r script into a sweave report I generaly start with an empty sweave template and copy/paste my entire R script into a sweave R block just after the title, i.e;
<<label=myEntireRScript, echo=false, include=false>>
#Insert code here
myTable<-dataframe(...)
myPlot<-qplot(....)
#
Then I go through and find the parts I want to report. For instance, if i want to put a table into the report, I'll cut the R block and put an xtable block in, and the same for variables and plots.
<<label=myEntireRScript, echo=false, include=false>>=
#Insert code here
#
Put any text I want before my table here, maybe with a \Sexpr{print(variable)} named variable
<<label=myTable, result=Tex>>=
myTable<-dataframe(...)
print(xtable(mytable,...),...)
#
Any text I want before my figure
<label=myplot, result=figure>>=
myPlot<-qplot(....)
print(qplot)
#
You may want to look at these related SO posts. The rest of my post relates to your question 2.
When creating reports with Sweave, I usually keep most of the R code and the report text separate. If the R code is fast to run, then I prefer I will include something like the following at the start of the .Rnw file:
<<>>
source('/path/to/script.r')
#
On the other hand, if the R code takes a long time, I will often include something like the following at the end of the R script:
Sweave('/path/to/report.Rnw'); system('pdflatex report.tex')
That way, I can re-generate the report quickly, without needing to run all the R code again. Then, the only work R has to do in the Sweave file is print tables, make graphs and maybe extract a few figures.
Like nullglob, I prefer to keep the R and Sweave files separate, but I prefer to save the workspace with save.image() rather than to source() the file. This avoids running the R calculations with each .Rnw file compiling (and I always end up tinkering with the typesetting more than I'd like).
My general work flow is to do each paper/project in it's own folder with it's own R file(s). When the calculation side is "done", I save.image() to store all the workspace variables as-is.
Then, in the .Rnw file in the same directory I set the working directory with setwd() and load all variables with load(".Rdata"). Of course, you can change the name you use for your workspace, but I do one workspace per folder and keep the default name. Oh, and if you tinker with the R file, be sure save the workspace image and watch out for variables that linger in the workspace and .Rnw file, but are no longer part of the R file... this is where the save.image() approach can cause some headaches.
I am on a Mac and I suggest TextMate if you're mildly geeky and emacs/ess if you're really geeky. I use vim and command line R, but emacs/ess works best for most. If you're in this for the long haul, I doubt you'll regret learning emacs/ess for R, Sweave, and LaTeX.