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6 changes: 3 additions & 3 deletions source/acknowledgements-python.md
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# Acknowledgments for the Python Edition

We'd like to thank everyone that has contributed to the development of
We'd like to thank everyone that has contributed to the development of
[*Data Science: A First Introduction (Python Edition)*](https://ubc-dsci.github.io/introduction-to-datascience-python/).
This is an open source Python translation of the original [*Data Science: A First Introduction*](https://datasciencebook.ca);
the original focused on the R programming language. Both of these books are
used to teach DSCI 100, a new introductory data science course
the original focused on the R programming language. Both of these books are
used to teach DSCI 100, a new introductory data science course
at the University of British Columbia (UBC).

We will finalize this acknowledgements section after the book is complete!
16 changes: 8 additions & 8 deletions source/acknowledgements.md
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# Acknowledgments

We'd like to thank everyone that has contributed to the development of
We'd like to thank everyone that has contributed to the development of
[*Data Science: A First Introduction*](https://datasciencebook.ca).
This is an open source textbook that began as a collection of course readings
for DSCI 100, a new introductory data science course
for DSCI 100, a new introductory data science course
at the University of British Columbia (UBC).
Several faculty members in the UBC Department of Statistics
were pivotal in shaping the direction of that course,
and as such, contributed greatly to the broad structure and
Several faculty members in the UBC Department of Statistics
were pivotal in shaping the direction of that course,
and as such, contributed greatly to the broad structure and
list of topics in this book. We would especially like to thank Matías
Salibían-Barrera for his mentorship during the initial development and roll-out
of both DSCI 100 and this book. His door was always open when
we needed to chat about how to best introduce and teach data science to our first-year students.

We would also like to thank all those who contributed to the process of
We would also like to thank all those who contributed to the process of
publishing this book. In particular, we would like to thank all of our reviewers for their feedback and suggestions:
Rohan Alexander, Isabella Ghement, Virgilio Gómez Rubio, Albert Kim, Adam Loy, Maria Prokofieva, Emily Riederer, and Greg Wilson.
The book was improved substantially by their insights.
Expand All @@ -37,8 +37,8 @@ for his support and encouragement throughout the process, and to
Roger Peng for graciously offering to write the Foreword.

Finally, we owe a debt of gratitude to all of the students of DSCI 100 over the past
few years. They provided invaluable feedback on the book and worksheets;
they found bugs for us (and stood by very patiently in class while
few years. They provided invaluable feedback on the book and worksheets;
they found bugs for us (and stood by very patiently in class while
we frantically fixed those bugs); and they brought a level of enthusiasm to the class
that sustained us during the hard work of creating a new course and writing a textbook.
Our interactions with them taught us how to teach data science, and that learning
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---

# Downloading files from JupyterHub
# Downloading files from JupyterHub

This section will help you
save your work from a JupyterHub web-based platform to your own computer.
save your work from a JupyterHub web-based platform to your own computer.
Let's say you want to download everything inside a folder called `your_folder`
in your home directory.
First open a terminal \index{JupyterHub!file download} by clicking "terminal" in the Launcher tab.
Next, type the following in the terminal to create a
First open a terminal \index{JupyterHub!file download} by clicking "terminal" in the Launcher tab.
Next, type the following in the terminal to create a
compressed `.zip` archive for the work you are interested in downloading:

```
Expand All @@ -29,6 +29,6 @@ zip -r hub_folder.zip your_folder

After the compressing process is complete, right-click on `hub_folder.zip`
in the JupyterHub file browser
and click "Download". After the download is complete, you should be
and click "Download". After the download is complete, you should be
able to find the `hub_folder.zip` file on your own computer,
and unzip the file (typically by double-clicking on it).
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