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data-visualisation

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bokeh
baeolophus
baeolophus commented Jan 22, 2019

I suggest either adding a short code piece to use the rename() function to change the column "genus" to "genera" (thus alerting the learners to their relationship here, while adding a new function) or changing the column name in the original dataset. Otherwise, I've found that using the correct plural for genus confuses learners who are not biologists. Although it's the R ecology lesson and one

mhog025
mhog025 commented Aug 4, 2020

Hi there,

I've been working through the materials as part of instructor training and just have a few suggestions for edits and corrections for the Writing Good Software episode text (https://swcarpentry.github.io/r-novice-gapminder/16-wrap-up/index.html).

Structure your project folder: First paragraph

'This' in place of 'It':

ItThis can be done completely manually, or with th

umnik20
umnik20 commented May 4, 2020

Dear Community,

There is a typo in the section titled "The StringsAsFactors argument" after the second block of code that demonstrates the use of the str() function. Right after the code boxes is written "We can see that the $Color and $State columns are factors and $Speed is a numeric column", but the box shows that the $Color column is a vector of strings.

Regards,

Rodolfo

caesoma
caesoma commented Feb 7, 2020

In episode 3 (https://datacarpentry.org/python-ecology-lesson/03-index-slice-subset/index.html, actually listed as 4. in https://datacarpentry.org/python-ecology-lesson/ ), the distinction between .iloc method for accessing entries by position and .loc to access them by identifier is made, but a third possibility is shown with surveys_df[0:3], which accesses the indices by position.

That

Talishask
Talishask commented May 12, 2020

I'm a member of The Carpentries staff and I'm submitting this issue on behalf of another member of the community. In most cases I won't be able to follow up or provide more details other that what I'm providing below.


Hi,

As part of the checkout process for carpentries, it is encouraged that we provide feedback to one of the modules. Going through the Python Novice Mindgap section on li

zblz
zblz commented Aug 15, 2017

Currently all of the metrics computed are independent of a target variable or column, but if lens.summarise took the name of a column as the target variable, the output of some metrics could be more interpretable even if the target variable is not used in any kind of predictive modelling.

A good example of this could be PCA (see #14), which could plot the different categories of the target va

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