Welcome to Data and Notebooks in Jupyter!
In this video we'll cover the many things
you can do with data in Jupyter.
First, let's talk about downloading.
You can download your Jupyter notebooks if
needed, by clicking on File > Download As
> IPython Notebook.
Please note that "IPython" is actually
the former name of Jupyter, but they are one
and the same, and they both use the ".ipynb"
filetype.
Next, there's the "Insert path", which
is very helpful in knowing where your data
is stored on your account.
For example, you can open up the options for
your recent data, and see where they're
stored, so you can import into your notebook.
In terms of uploading data, you have a few
options.
The easiest way is to just drag-and-drop from
your computer into your workbench.
Your data simply gets uploaded into the "/resources/"
filepath.
You can also upload your data in the My Data
tool.
This allows you to see exactly where you're
uploading to, and you can even create folders.
Keep track of your filepaths by checking the
path at the top.
And remember, to use the data in the notebooks,
all you need to do is use the filepath with
the appropriate code.
In Jupyter, you can also connect to your databases.
Jupyter even includes tutorials that show
you how.
Let's briefly take a look at how to connect
to a MySQL database.
As you can see, when we click on the R tutorial,
it's automatically loaded in your recent
notebooks.
And this is the loaded tutorial, as seen in
Jupyter that shows you how to access MySQL
with R
The first step is to import the RMySQL library.
Let's execute the first cell just click
the cell that you wish to run and then click
the Cell-Run button, as shown here.
After you run the cell, you get a message
letting you know that the required DBI package
is loaded.
Then, in the next cell, simply enter the values
for the database you want to connect to, and
run it.
Next, continue running the few other steps
in this notebook that actually connect to
the database, which include.
Creating the database connection
Creating a table, if needed
Querying the data, and
Closing the connection.
To exit the tutorial and return to the Jupyter
notebook, select File > Close and Halt.
Doing so shuts down this notebook's kernel
and closes this window.
This takes you back to the list of Jupyter
tutorials.
From here, you can either create a new notebook
by clicking the blue button at the top right
and then selecting the language you want to
use, or you can click on the Home button,
situated at the top left, to return to the
Data Scientist Workbench home page.
For now, we'll go back to the Data Scientist
Workbench home page.
We hope you'll take some time to practice
what you've learned here.
After all, practice makes perfect!
This brings us to the end of this video.
Thanks for watching!
