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+
+# Intro to Computing
+
+Welcome to Introduction to Python! Each week, we cover a chapter, which consists of a lesson and exercise. In our first week together, we will look at big conceptual themes in programming, see how code is run, and learn some basic grammar structures of programming.
+
+## Goals of the course
+
+In the next 6 weeks, we will explore:
+
+-   Fundamental concepts in high-level programming languages (Python, R, Julia, etc.) that is transferable: *How do programs run, and how do we solve problems using functions and data structures?*
+
+-   Beginning of data science fundamentals: *How do you translate your scientific question to a data wrangling problem and answer it?*
+
+    ![Data science workflow. Image source: [R for Data Science](https://r4ds.hadley.nz/whole-game).](https://d33wubrfki0l68.cloudfront.net/571b056757d68e6df81a3e3853f54d3c76ad6efc/32d37/diagrams/data-science.png){width="450"}
+
+-   Find a nice balance between the two throughout the course: we will try to reproduce a figure from a scientific publication using new data.
+
+## What is a computer program?
+
+-   A sequence of instructions to manipulate data for the computer to execute.
+
+-   A series of translations: English \<-\> Programming Code for Interpreter \<-\> Machine Code for Central Processing Unit (CPU)
+
+We will focus on English \<-\> Programming Code for Python Interpreter in this class.
+
+More importantly: **How we organize ideas \<-\> Instructing a computer to do something**.
+
+## A programming language has following elements: {#a-programming-language-has-following-elements}
+
+-   Grammar structure to construct expressions; combining expressions to create more complex expressions
+
+-   Encapsulate complex expressions via **functions** to create modular and reusable tasks
+
+-   Encapsulate complex data via **data structures** to allow efficient manipulation of data
+
+## Google Colab Setup
+
+Google Colab is a Integrated Development Environment (IDE) on a web browser. Think about it as Microsoft Word to a plain text editor. It provides extra bells and whistles to using Python that is easier for the user.
+
+Let's open up the KRAS analysis in Google Colab. If you are taking this course while it is in session, the project name is probably named "KRAS Demo" in your Google Classroom workspace. If you are taking this course on your own time, open up...
+
+Today, we will pay close attention to:
+
+-   Python Console (Execution): Open it via View -\> Executed code history. You give it one line of Python code, and the console executes that single line of code; you give it a single piece of instruction, and it executes it for you.
+
+-   Notebook: in the central panel of the website, you will see Python code interspersed with word document text. This is called a Python Notebook (other similar services include Jupyter Notebook, iPython Notebook), which has chunks of plain text *and* Python code, and it helps us understand better the code we are writing.
+
+-   Variable Environment: Open it by clicking on the "{x}" button on the left-hand panel. Often, your code will store information in the Variable Environment, so that information can be reused. For instance, we often load in data and store it in the Variable Environment, and use it throughout rest of your Python code.
+
+The first thing we will do is see the different ways we can run Python code. You can do the following:
+
+1.  Type something into the Python Console (Execution) and type enter, such as `2+2`. The Python Console will run it and give you an output.
+2.  Look through the Python Notebook, and when you see a chunk of Python Code, click the arrow button. It will copy the Python code chunk to the Python Console and run all of it. You will likely see variables created in the Variables panel as you load in and manipulate data.
+3.  Run every single Python code chunk via Runtime -\> Run all.
+
+Remember that the *order* that you run your code matters in programming. Your final product would be the result of Option 3, in which you run every Python code chunk from start to finish. However, sometimes it is nice to try out smaller parts of your code via Options 1 or 2. But you will be at risk of running your code out of order!
+
+To create your own content in the notebook, click on a section you want to insert content, and then click on "+ Code" or "+ Text" to add Python code or text, respectively.
+
+Python Notebook is great for data science work, because:
+
+-   It encourages reproducible data analysis, when you run your analysis from start to finish.
+
+-   It encourages excellent documentation, as you can have code, output from code, and prose combined together.
+
+-   It is flexible to use other programming languages, such as R.
+
+Now, we will get to the basics of programming grammar.
+
+## Grammar Structure 1: Evaluation of Expressions
+
+-   **Expressions** are be built out of **operations** or **functions**.
+
+-   Functions and operations take in **data types**, do something with them, and return another data type.
+
+-   We can combine multiple expressions together to form more complex expressions: an expression can have other expressions nested inside it.
+
+For instance, consider the following expressions entered to the Python Console:
+
+
+``` python
+18 + 21
+```
+
+```
+## 39
+```
+
+``` python
+max(18, 21)
+```
+
+```
+## 21
+```
+
+``` python
+max(18 + 21, 65)
+```
+
+```
+## 65
+```
+
+``` python
+18 + (21 + 65)
+```
+
+```
+## 104
+```
+
+``` python
+len("ATCG")
+```
+
+```
+## 4
+```
+
+Here, our input **data types** to the operation are **integer** in lines 1-4 and our input data type to the function is **string** in line 5. We will go over common data types shortly.
+
+Operations are just functions in hiding. We could have written:
+
+
+``` python
+from operator import add
+
+add(18, 21)
+```
+
+```
+## 39
+```
+
+``` python
+add(18, add(21, 65))
+```
+
+```
+## 104
+```
+
+Remember that the Python language is supposed to help us understand what we are writing in code easily, lending to *readable* code. Therefore, it is sometimes useful to come up with operations that is easier to read. (Because the `add()` function isn't typically used, it is not automatically available, so we used the import statement to load it in.)
+
+### Data types
+
+Here are some common data types we will be using in this course.
+
+| Data type name | **Data type shorthand** |      **Examples**       |
+|----------------|:-----------------------:|:-----------------------:|
+| Integer        |           int           |          2, 4           |
+| Float          |          float          |      3.5, -34.1009      |
+| String         |           str           | "hello", "234-234-8594" |
+| Boolean        |          bool           |       True, False       |
+
+A nice way to summarize this first grammar structure is using the function machine schema, way back from algebra class:
+
+![Function machine from algebra class.](images/function_machine.png)
+
+Here are some aspects of this schema to pay attention to:
+
+-   A programmer should not need to know how the function is implemented in order to use it - this emphasizes abstraction and modular thinking, a foundation in any programming language.
+
+-   A function can have different kinds of inputs and outputs - it doesn't need to be numbers. In the `len()` function, the input is a String, and the output is an Integer. We will see increasingly complex functions with all sorts of different inputs and outputs.
+
+## Grammar Structure 2: Storing data types in the Variable Environment
+
+To build up a computer program, we need to store our returned data type from our expression somewhere for downstream use. We can assign a variable to it as follows:
+
+
+``` python
+x = 18 + 21
+```
+
+If you enter this in the Console, you will see that in the Variable Environment, the variable `x` has a value of `39`.
+
+### Execution rule for variable assignment
+
+> Evaluate the expression to the right of `=`.
+>
+> Bind variable to the left of `=` to the resulting value.
+>
+> The variable is stored in the Variable Environment.
+
+The Variable Environment is where all the variables are stored, and can be used for an expression anytime once it is defined. Only one unique variable name can be defined.
+
+The variable is stored in the working memory of your computer, Random Access Memory (RAM). This is temporary memory storage on the computer that can be accessed quickly. Typically a personal computer has 8, 16, 32 Gigabytes of RAM. When we work with large datasets, if you assign a variable to a data type larger than the available RAM, it will not work. More on this later.
+
+Look, now `x` can be reused downstream:
+
+
+``` python
+x - 2
+```
+
+```
+## 37
+```
+
+``` python
+y = x * 2
+```
+
+It is quite common for programmers to not know what data type a variable is while they are coding. To learn about the data type of a variable, use the `type()` function on any variable in Python:
+
+
+``` python
+type(y)
+```
+
+```
+## <class 'int'>
+```
+
+We should give useful variable names so that we know what to expect! Consider `num_sales` instead of `y`.
+
+## Grammar Structure 3: Evaluation of Functions
+
+Let's look at functions a little bit more formally: A function has a **function name**, **arguments**, and **returns** a data type.
+
+### Execution rule for functions:
+
+> Evaluate the function by its arguments, and if the arguments are functions or contains operations, evaluate those functions or operations first.
+>
+> The output of functions is called the **returned value**.
+
+Often, we will use multiple functions, in a nested way, or use parenthesis to change the order of operation. Being able to read nested operations, nested functions, and parenthesis is very important. Think about what the Python is going to do step-by--step in the line of code below:
+
+
+``` python
+(len("hello") + 4) * 2
+```
+
+```
+## 18
+```
+
+If we don't know how to use a function, such as `pow()` we can ask for help:
+
+```         
+?pow
+
+pow(base, exp, mod=None)
+Equivalent to base**exp with 2 arguments or base**exp % mod with 3 arguments
+ 
+Some types, such as ints, are able to use a more efficient algorithm when
+invoked using the three argument form.
+```
+
+This shows the function takes in three input arguments: `base`, `exp`, and `mod=None`. When an argument has an assigned value of `mod=None`, that means the input argument already has a value, and you don't need to specify anything, unless you want to.
+
+The following ways are equivalent ways of using the `pow()` function:
+
+
+``` python
+pow(2, 3)
+```
+
+```
+## 8
+```
+
+``` python
+pow(base=2, exp=3)
+```
+
+```
+## 8
+```
+
+``` python
+pow(exp=3, base=2)
+```
+
+```
+## 8
+```
+
+but this will give you something different:
+
+
+``` python
+pow(3, 2)
+```
+
+```
+## 9
+```
+
+And there is an operational equivalent:
+
+
+``` python
+2 ** 3
+```
+
+```
+## 8
+```
+
+## Tips on writing your first code
+
+`Computer = powerful + stupid`
+
+Even the smallest spelling and formatting changes will cause unexpected output and errors!
+
+-   Write incrementally, test often
+
+-   Check your assumptions, especially using new functions, operations, and new data types.
+
+-   Live environments are great for testing, but not great for reproducibility.
+
+-   Ask for help!
+
+To get more familiar with the errors Python gives you, take a look at this [summary of Python error messages](https://betterstack.com/community/guides/scaling-python/python-errors/).