0_python_intro.ipynb

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  {
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   "source": [
    "#### Datatypes and functions\n",
    "\n",
    "We can assign values to variables using `=`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_variable = 5"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Functions in Python take some input and return some output. One default Python function is `type`, it tells you what the datatype of the input is. We can use the function like this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "another_variable = type(my_variable)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the `print` function, we can see what `another_variable` contains."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(another_variable)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Functions can take variables as input, transform them and return a new variable. We can also create our own functions. The function below requires one input argument and returns the value multiplied by 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def my_first_function(some_value):\n",
    "    multiplied_value = some_value * 2\n",
    "    return multiplied_value"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    "> \n",
    "> Try to use the function to multiply some value (or use `my_variable` as input)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run the function we defined above here."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some functions take optional inputs, defined through keyword-arguments. Like the function below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def another_function(some_value, multiplier = 3):\n",
    "    multiplied_value = some_value * multiplier\n",
    "    return multiplied_value"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    "> \n",
    "> * Try to run the function without the keyword argument.\n",
    "> \n",
    "> * Then try to run it using another value as multiplier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Run another_function here."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The variable we created above was an integer. Some other common datatypes are `floats`, `lists` and `strings`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_float = 5.67\n",
    "my_string = \"i_love_pywapor\"\n",
    "my_list = [\"lists\", my_variable, \"can_contain\", my_float, \"different_types\", my_string]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another default Python function is called `len`. It tells you the \"length\" of a variable. You can see that `my_list` contains 6 items."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(my_list)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    ">\n",
    "> * What is the length of `my_string`?\n",
    ">\n",
    "> * What happens when you try to get the length of `my_float`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Figure out what the length of my_string and my_float is here."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Only variables that are _\"iterable\"_ have a length. Variables that have a length (and are iterable) can be _\"indexed\"_ or _\"looped\"_.\n",
    "\n",
    "#### Indexing\n",
    "\n",
    "When a variable is \"iterable\", you can ask Python for a specific item of the variable. For example, we can get the item in our lists at index 2 like this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_list[2]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    "> \n",
    "> Try to index the first item in the list. Which index number do you need to use to do that?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use indexing to get the first item from my_list here."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We saw that strings are iterable too. Instead of indexing a single item, we also index a range using two index numbers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_string[1:7]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **question**\n",
    "> \n",
    "> Can you index the first 4 items from my_list?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Index the first 4 items from my_list here"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Looping\n",
    "\n",
    "By looping over an iterable, we can process the items in the iterable seperatly. For example, we can loop over all the items in `my_list` and print the datatype of each item."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for x in my_list:\n",
    "    dtype = type(x)\n",
    "    print(dtype)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Importing functions\n",
    "\n",
    "Besides the default functions (such as `type`, `len` and `print`), we can also use functions developed by other people/organizations. A common _\"library\"_ of Python function is called `numpy`. Before we can use its function we need to import them."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Numpy contains many functions, for example a function to calculate the sine of a number."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "numpy.sin(my_float)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or the function `numpy.mean` can calculate the mean of a list of numbers. So first we'll define a list of numbers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_list_of_numbers = [1, 3.5, 5.6, 4, 8.0]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    "> \n",
    "> Can you use the function to calculate the mean of the list of numbers?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# use the numpy.mean function here to calculate the mean of the list of numbers."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Dictionaries\n",
    "\n",
    "Just like lists, dictionaries in Python can contain other variables. Instead of storing these variables in a fixed order however, in dictionaries they are assigned to \"keys\". Dictionaries can be created using curly brackets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_dict = {\n",
    "    \"this_is_a_key\": my_list_of_numbers,\n",
    "    \"another_key\": \"hello_world\",\n",
    "    \"key_3\": \"bye!\"\n",
    "}"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    "> \n",
    "> What is the length of `my_dict`?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write some code here to figure out the length of my_dict."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can request the value associated with a key like this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_dict[\"key_3\"]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After you have created the dictionary, you can easily add new key-value pairs to it or overwrite an existing pair."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_dict[\"my_new_key\"] = my_float\n",
    "print(len(my_dict))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> **Question**\n",
    "> \n",
    "> Overwrite the key `key_3` so that it contains the mean of `my_list_of_numbers`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Overwrite key_3 here."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can also make a list of all the keys in a dictionary like this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_dict.keys()"
   ]
  }
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