Difference between revisions of "Jupyter"

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(Starting Up)
(Tutorial)
Line 8: Line 8:
  
 
== Tutorial ==
 
== Tutorial ==
There's a great tutorial at [https://www.dataquest.io/blog/jupyter-notebook-tutorial/ https://www.dataquest.io/blog/jupyter-notebook-tutorial/]!  A few notes:
+
There's a great tutorial at [https://www.dataquest.io/blog/jupyter-notebook-tutorial/ https://www.dataquest.io/blog/jupyter-notebook-tutorial/]!  You do not need to sign in or click the Start Free button to follow the tutorial.
* CTRL-Enter runs the current cell; SHIFT-Enter runs the current cell and provides a new empty cell below it.  SHIFT-Enter is generally the way to go
+
 
* ESC and ENTER toggle between command mode and edit mode.  In edit mode, there is a pencil icon at the top right; in command mode, there isn't.  Also, if you click in the edit part of a cell you enter edit mode; if you click in the space between the In []: and the >| you enter command mode.
+
A few notes:
* In addition to the commands shown, Markdown understands basic LaTeX (Greek letters, fractions, integrals, etc).  Use single $ around commands for inline and $$ around commands for displaymath.
+
* What is a Jupyter Notebook?
* For the commands that print formatted strings, the tutorial uses the string modulo method.  To relate this to using format, and also to using the new (as of Python 3.6) f-string, here are three ways of printing the same information:<syntaxhighlight lang=python>
+
** Nothing to add
 +
* How to Follow This Tutorial
 +
** Nothing to add
 +
* Installation
 +
** You can skip this if you already have Anaconda and have already started Jupyter Notebook in a browser.
 +
* Creating Your First Notebook
 +
** You should already be at the '''Running Jupyter''' phase.
 +
** The New-> Python 3 might look like New->Python 3 (ipykernel)
 +
** In the '''Cells''' part:
 +
*** CTRL-Enter or the $$\blacktriangleright\!\shortmid$$ runs the current cell; SHIFT-Enter runs the current cell and provides a new empty cell below it.  SHIFT-Enter is generally the way to go as it runs the cell and gives you a new input line (rather than having to insert a new one)
 +
*** ESC and ENTER toggle between command mode and edit mode.  In edit mode, there is a pencil icon at the top right; in command mode, there isn't.  Also, if you click in the edit part of a cell you enter edit mode; if you click in the space between the In []: and the >| you enter command mode.
 +
** In the '''Markdown''' part:
 +
*** In addition to the commands shown, Markdown understands basic LaTeX (Greek letters, fractions, integrals, etc).  Use single $ around commands for inline and $$ around commands for displaymath.
 +
** In the '''Kernels''' part:
 +
*** For the commands that print formatted strings, the tutorial uses the string modulo method.  To relate this to using format, and also to using the new (as of Python 3.6) f-string, here are three ways of printing the same information:<syntaxhighlight lang=python>
 +
a = 2
 +
b = 4
 +
c = 2.5
 +
d = 6.25
 
# string modulo
 
# string modulo
 
print('%d squared is %d and %0.2e squared is %0.2e' % (a, b, c, d))
 
print('%d squared is %d and %0.2e squared is %0.2e' % (a, b, c, d))
Line 20: Line 38:
 
print(f'{a:d} squared is {b:d} and {c:0.2e} squared is {d:0.2e}')
 
print(f'{a:d} squared is {b:d} and {c:0.2e} squared is {d:0.2e}')
 
</syntaxhighlight>You can see that all three are similar; the f-string puts the variable at the same location it will end up printing in the string rather than way at the end.
 
</syntaxhighlight>You can see that all three are similar; the f-string puts the variable at the same location it will end up printing in the string rather than way at the end.
* The "Setup" section in the middle of the page starts to go into some advanced data analysis with Pandas; they always give you the code, but it may be confusing!  Also:
+
 
** You will need to have saved their data file to the folder where you are saving your notebook.  The file is in the "Example Data Analysis in a Jupyter Notebook" section way at the top of the page, or you can get it from [https://s3.amazonaws.com/dq-blog-files/fortune500.csv https://s3.amazonaws.com/dq-blog-files/fortune500.csv].
+
* Example Analysis
** There needs to be a carriage return after "import seaborn as sns"
+
** The "Setup" section in the middle of the page starts to go into some advanced data analysis with Pandas; they always give you the code, but it may be confusing!  Also:
 +
*** You will need to have saved their data file to the folder where you are saving your notebook.  The file is in the "Example Data Analysis in a Jupyter Notebook" section way at the top of the page, or you can get it from [https://s3.amazonaws.com/dq-blog-files/fortune500.csv https://s3.amazonaws.com/dq-blog-files/fortune500.csv].
 +
*** There needs to be a carriage return after "import seaborn as sns"

Revision as of 03:35, 13 January 2023

This page is meant to be a startup guide for using Jupyter Notebooks with Python. It assumes you have installed Anaconda from https://www.anaconda.com/. Most of this guide was written running Python 3.9 and Jupyter Notebooks 6.4.12.

Starting Up

  • To start Jupyter Notebooks with Anaconda:
    • On Windows, go to the Anaconda folder in the Start Menu or open the Anaconda Navigator and start Jupyter Notebooks from there.
    • On macOS, open the Anaconda Navigator and start Jupyter Notebooks from there.

Depending on your settings, you may get a new browser that points to your localhost or you may get a window with a web address that you need to copy and paste into a web browser (in which case, do that). In either case, the end result should be a web page open to the jupyter page with tabs for Files, Running, and Clusters.

Tutorial

There's a great tutorial at https://www.dataquest.io/blog/jupyter-notebook-tutorial/! You do not need to sign in or click the Start Free button to follow the tutorial.

A few notes:

  • What is a Jupyter Notebook?
    • Nothing to add
  • How to Follow This Tutorial
    • Nothing to add
  • Installation
    • You can skip this if you already have Anaconda and have already started Jupyter Notebook in a browser.
  • Creating Your First Notebook
    • You should already be at the Running Jupyter phase.
    • The New-> Python 3 might look like New->Python 3 (ipykernel)
    • In the Cells part:
      • CTRL-Enter or the $$\blacktriangleright\!\shortmid$$ runs the current cell; SHIFT-Enter runs the current cell and provides a new empty cell below it. SHIFT-Enter is generally the way to go as it runs the cell and gives you a new input line (rather than having to insert a new one)
      • ESC and ENTER toggle between command mode and edit mode. In edit mode, there is a pencil icon at the top right; in command mode, there isn't. Also, if you click in the edit part of a cell you enter edit mode; if you click in the space between the In []: and the >| you enter command mode.
    • In the Markdown part:
      • In addition to the commands shown, Markdown understands basic LaTeX (Greek letters, fractions, integrals, etc). Use single $ around commands for inline and $$ around commands for displaymath.
    • In the Kernels part:
      • For the commands that print formatted strings, the tutorial uses the string modulo method. To relate this to using format, and also to using the new (as of Python 3.6) f-string, here are three ways of printing the same information:
        a = 2
        b = 4
        c = 2.5
        d = 6.25
        # string modulo
        print('%d squared is %d and %0.2e squared is %0.2e' % (a, b, c, d))
        # format
        print('{:d} squared is {:d} and {:0.2e} squared is {:0.2e}'.format(a, b, c, d))
        # f-string
        print(f'{a:d} squared is {b:d} and {c:0.2e} squared is {d:0.2e}')
        
        You can see that all three are similar; the f-string puts the variable at the same location it will end up printing in the string rather than way at the end.
  • Example Analysis
    • The "Setup" section in the middle of the page starts to go into some advanced data analysis with Pandas; they always give you the code, but it may be confusing! Also:
      • You will need to have saved their data file to the folder where you are saving your notebook. The file is in the "Example Data Analysis in a Jupyter Notebook" section way at the top of the page, or you can get it from https://s3.amazonaws.com/dq-blog-files/fortune500.csv.
      • There needs to be a carriage return after "import seaborn as sns"