Commit 9bffe662 by Maxim Belkin Committed by GitHub

### 01-numpy: add section headers. General improvements.

`Closes swcarpentry/python-novice-inflammation#538`
parent f961d0df
 ... ... @@ -29,34 +29,68 @@ keypoints: - "Use the `pyplot` library from `matplotlib` for creating simple visualizations." --- In this lesson we will learn how to manipulate the inflammation dataset with Python. Before we discuss how to deal with many data points, we will show how to store a single value on the computer. In this lesson we will learn how to work with arthritis inflammation datasets in Python. However, before we discuss how to deal with many data points, let's learn how to work with single data values. You can get output from python by typing math into the console: ## Variables Any Python interpreter can be used as a calculator: ~~~ 3 + 5 * 4 ~~~ {: .language-python} ~~~ 3+5 12/7 23 ~~~ {: .output} However, to do anything useful and/or interesting we need to assign values to _variables_ (or link _objects_ to names/variables). The line below [assigns]({{ page.root }}/reference/#assign) the value `60` to a [variable]({{ page.root }}/reference/#variable) `weight_kg`: This is great but not very interesting. To do anything useful with data, we need to assign its value to a _variable_. In Python, we can [assign]({{ page.root }}/reference/#assign) a value to a [variable]({{ page.root }}/reference/#variable), using the equals sign `=`. For example, to assign value `60` to a variable `weight_kg`, we would execute: ~~~ weight_kg = 60 ~~~ {: .language-python} A variable is a name for a value, such as `x_val`, `current_temperature`, or `subject_id`. Python's variables must begin with a letter and are [case sensitive]({{ page.root }}/reference/#case-sensitive). We can create a new variable by assigning a value to it using `=`. When we are finished typing and press Shift+Return, the notebook runs our command. From now on, whenever we use `weight_kg`, Python will substitute the value we assigned to it. In essence, **a variable is just a name for a value**. In Python, variable names: - must begin with a letter, and - are [case sensitive]({{ page.root }}/reference/#case-sensitive). Once a variable has a value, we can print it to the screen: This means that, for example: - `weight0` is a valid variable name, whereas `0weight` is not - `weight` and `Weight` are different variables ## Types of data Python knows various types of data. The most common ones are: * integer numbers * floating point numbers, and * strings. In the example above, variabe `weight_kg` has an integer value of `60`. To create a variable with a floating point value, we can execute: ~~~ weight_kg = 60.0 ~~~ {: .language-python} And to create a string we simply have to add single or double quotes around some text, for example: ~~~ weight_kg_text = 'weight in kilograms:' ~~~ {: .language-python} ## Using Variables in Python To display the value of a variable to the screen in Python, we can use `print` function: ~~~ print(weight_kg) ... ... @@ -68,7 +102,18 @@ print(weight_kg) ~~~ {: .output} and do arithmetic with it (remember, there are 2.2 pounds per kilogram): We can display multiple things at once using only one `print` command: ~~~ print(weight_kg_text, weight_kg) ~~~ {: .language-python} ~~~ weight in kilograms: 60 ~~~ {: .output} Moreover, we can do arithmetics with variables right inside the `print` function: ~~~ print('weight in pounds:', 2.2 * weight_kg) ... ... @@ -80,10 +125,18 @@ weight in pounds: 132.0 ~~~ {: .output} As the example above shows, we can print several things at once by separating them with commas. The above command, however, did not change the value of `weight_kg`: ~~~ print(weight_kg) ~~~ {: .language-python} ~~~ 60 ~~~ {: .output} We can also change a variable's value by assigning it a new one: To change variable's value, we have to assign it a new one: ~~~ weight_kg = 65.0 ... ... @@ -96,19 +149,18 @@ weight in kilograms is now: 65.0 ~~~ {: .output} If we imagine the variable as a sticky note with a name written on it, assignment is like putting the sticky note on a particular value: A variable is analoguous to a sticky note with a name written on it: assigning value to a variable is like putting that sticky note on a particular value. ![Variables as Sticky Notes](../fig/python-sticky-note-variables-01.svg) This means that assigning a value to one variable does *not* change the values of other variables. For example, let's store the subject's weight in pounds in a variable: This means that assigning a value to one variable does **not** change the values of other variables. For example, let's store the subject's weight in pounds in its own variable: ~~~ # There are 2.2 pounds per kilogram weight_lb = 2.2 * weight_kg print('weight in kilograms:', weight_kg, 'and in pounds:', weight_lb) print(weight_kg_text, weight_kg, 'and in pounds:', weight_lb) ~~~ {: .language-python} ... ... @@ -119,7 +171,7 @@ weight in kilograms: 65.0 and in pounds: 143.0 ![Creating Another Variable](../fig/python-sticky-note-variables-02.svg) and then change `weight_kg`: Let's now change `weight_kg`: ~~~ weight_kg = 100.0 ... ... @@ -136,28 +188,8 @@ weight in kilograms is now: 100.0 and weight in pounds is still: 143.0 Since `weight_lb` doesn't remember where its value came from, it isn't automatically updated when `weight_kg` changes. This is different from the way spreadsheets work. > ## Who's Who in Memory > > You can use the `%whos` command at any time to see what > variables you have created and what modules you have loaded into the computer's memory. > As this is an IPython command, it will only work if you are in an IPython terminal or the > Jupyter Notebook. > > ~~~ > %whos > ~~~ > {: .language-python} > > ~~~ > Variable Type Data/Info > -------------------------------- > weight_kg float 100.0 > weight_lb float 143.0 > ~~~ > {: .output} {: .callout} Words are useful, but what's more useful are the sentences and stories we build with them. Similarly, while a lot of powerful, general tools are built into languages like Python, ... ... @@ -165,12 +197,12 @@ specialized tools built up from these basic units live in [libraries]({{ page.root }}/reference/#library) that can be called upon when needed. In order to load our inflammation data, we need to access ([import]({{ page.root }}/reference/#import) in Python terminology) a library called [NumPy](http://docs.scipy.org/doc/numpy/ "NumPy Documentation"). In general you should use this library if you want to do fancy things with numbers, especially if you have matrices or arrays. We can import NumPy using: ## Loading data into Python In order to load our inflammation data, we need to access ([import]({{ page.root }}/reference/#import) in Python terminology) a library called [NumPy](http://docs.scipy.org/doc/numpy/ "NumPy Documentation"). In general you should use this library if you want to do fancy things with numbers, especially if you have matrices or arrays. We can import NumPy using: ~~~ import numpy ... ...
 ... ... @@ -5,6 +5,28 @@ permalink: /extra_material/ --- A collection of facts about Python that do not fit into the main lesson either due to the scope or time constraints of the main lesson. ## Jupyter Notebook/IPython: Who's Who in Memory You can use the `%whos` command at any time to see what variables you have created and what modules you have loaded into the computer's memory. As this is an IPython command, it will only work if you are in an IPython terminal or the Jupyter Notebook. ~~~ %whos ~~~ {: .language-python} ~~~ Variable Type Data/Info -------------------------------- weight_kg float 100.0 weight_lb float 143.0 ~~~ {: .output}
## Integer Division ... ...
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