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# Engineering 1020: Introduction to Programming

.title[
  .lecture[Lecture \20\:]
  .title[Tuples]
  
  
]

.footer[[/lecture/20/](/lecture/20/)]

---

# Recall:

### Objects

### Methods

### Common methods of:

* `list`
* `str`

---

# Tuples

### You've heard these before?

.floatleft[
* quadruple
* quintuple
* sextuple
* septuple
]

.floatright[
### Mathematically:
## $n$-tuple
]

---

# Python tuple

### An ordered collection

So... what's different about this vs a list?

### An _immutable_ ordered collection

```python
l = [1, 2, 3]
t = (1, 2, 3)

l[1] = 42
t[1] = 42
```

---

# Where do we use tuples?

### Storing simple sequences

### Returning multiple things from functions

* let's write a `divide(num, denom)` function!
--

* other functions you might bump into

---

# More tuple syntax

### Single-element tuples:

```python
x = (1,)
```

### *Destructuring* tuples:

```python
p = get_a_cartesian_point()
x, y = p

# or just:
x, y = get_a_cartesian_point()
```

Helpful for explicitly stating expected number of elements!

---

# matplotlib example

```python
>>> help(plt.subplots)
Help on function subplots in module matplotlib.pyplot:

subplots(nrows=1, ncols=1, sharex=False, sharey=False, squeeze=True, subplot_kw=
None, gridspec_kw=None, **fig_kw)
    Create a figure and a set of subplots

This utility wrapper makes it convenient to create common layouts of
    subplots, including the enclosing figure object, in a single call.
    [...]

Returns
    -------
    fig : :class:`matplotlib.figure.Figure` object

ax : Axes object or array of Axes objects.
    [...]
```

???

Returns **two** values: **`fig` and `ax`**

---

# Using subplots

.footnote[
Data: http://bit.ly/covid19-nl  
Code: https://gist.github.com/trombonehero/b7b2ec2667dab2bf3bb09399984a8046
]

```python
fig, ax = plt.subplots(2, # ...
fig.suptitle('COVID-19 cases in # ...

ax[0].set_title('New and total cases')
ax[0].plot(total)
ax[0].plot(new)
ax[0].legend(['Total', 'New'])

ax[1].set_title('Total cases by category')
ax[1].stackplot(range(len(total)), deaths, # ...
ax[1].legend(['Deceased', 'Recovered', # ...

plt.show()
```

---

# Using tuples

### Just like lists:

* iteration
--

* `count()` method
--

* `index()` method
--

* ... but that's all!

---

# Argument tuples

### Slightly more advanced usage

```python
def foo(*args):
    for a in args:
        print(a)

foo(1, 2, 3)
```

### Or even:

```python
def multiply(x, y):
    return x * y

t = (1, 2)
result = multiply(*t)
```

---

# Summary

### Tuples

* simple ordered _immutable_ collections
* syntax
* usage

---
class: big, middle

(here endeth the lesson)