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Notes/02_Working_with_data/02_Containers.md
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[Contents](../Contents) \| [Previous (2.1 Datatypes)](01_Datatypes) \| [Next (2.3 Formatting)](03_Formatting)
# 2.2 Containers
This section discusses lists, dictionaries, and sets.
### Overview
Programs often have to work with many objects.
@@ -11,11 +15,11 @@ There are three main choices to use.
* Lists. Ordered data.
* Dictionaries. Unordered data.
* Sets. Unordered collection
* Sets. Unordered collection of unique items.
### Lists as a Container
Use a list when the order of the data matters. Remember that lists can hold any kind of objects.
Use a list when the order of the data matters. Remember that lists can hold any kind of object.
For example, a list of tuples.
```python
@@ -47,7 +51,7 @@ An example when reading records from a file.
```python
records = [] # Initial empty list
with open('portfolio.csv', 'rt') as f:
with open('Data/portfolio.csv', 'rt') as f:
for line in f:
row = line.split(',')
records.append((row[0], int(row[1])), float(row[2]))
@@ -69,7 +73,7 @@ prices = {
Here are some simple lookups:
```pycon
```python
>>> prices['IBM']
93.37
>>> prices['GOOG']
@@ -95,7 +99,7 @@ An example populating the dict from the contents of a file.
```python
prices = {} # Initial empty dict
with open('prices.csv', 'rt') as f:
with open('Data/prices.csv', 'rt') as f:
for line in f:
row = line.split(',')
prices[row[0]] = float(row[1])
@@ -143,12 +147,13 @@ holidays = {
Then to access:
```pycon
>>> holidays[3, 14] 'Pi day'
```python
>>> holidays[3, 14]
'Pi day'
>>>
```
*Neither a list nor another dictionary can serve as a dictionary key, because lists and dictionaries are mutable.*
*Neither a list, a set, nor another dictionary can serve as a dictionary key, because lists and dictionaries are mutable.*
### Sets
@@ -162,7 +167,7 @@ tech_stocks = set(['IBM', 'AAPL', 'MSFT'])
Sets are useful for membership tests.
```pycon
```python
>>> tech_stocks
set(['AAPL', 'IBM', 'MSFT'])
>>> 'IBM' in tech_stocks
@@ -194,6 +199,9 @@ s1 - s2 # Set difference
## Exercises
In these exercises, you start building one of the major programs used
for the rest of this course. Do your work in the file `Work/report.py`.
### Exercise 2.4: A list of tuples
The file `Data/portfolio.csv` contains a list of stocks in a
@@ -227,7 +235,8 @@ that file, define a function `read_portfolio(filename)` that opens a
given portfolio file and reads it into a list of tuples. To do this,
you’re going to make a few minor modifications to the above code.
First, instead of defining `total_cost = 0`, you’ll make a variable that’s initially set to an empty list. For example:
First, instead of defining `total_cost = 0`, you’ll make a variable
that’s initially set to an empty list. For example:
```python
portfolio = []
@@ -251,7 +260,7 @@ interpreter):
*Hint: Use `-i` when executing the file in the terminal*
```pycon
```python
>>> portfolio = read_portfolio('Data/portfolio.csv')
>>> portfolio
[('AA', 100, 32.2), ('IBM', 50, 91.1), ('CAT', 150, 83.44), ('MSFT', 200, 51.23),
@@ -291,14 +300,15 @@ That said, you can also rewrite the last for-loop using a statement like this:
### Exercise 2.5: List of Dictionaries
Take the function you wrote in part (a) and modify to represent each
Take the function you wrote in Exercise 2.4 and modify to represent each
stock in the portfolio with a dictionary instead of a tuple. In this
dictionary use the field names of "name", "shares", and "price" to
represent the different columns in the input file.
Experiment with this new function in the same manner as you did in Exercise 2.4.
Experiment with this new function in the same manner as you did in
Exercise 2.4.
```pycon
```python
>>> portfolio = read_portfolio('portfolio.csv')
>>> portfolio
[{'name': 'AA', 'shares': 100, 'price': 32.2}, {'name': 'IBM', 'shares': 50, 'price': 91.1},
@@ -327,7 +337,7 @@ often preferred because the resulting code is easier to read later.
Viewing large dictionaries and lists can be messy. To clean up the
output for debugging, considering using the `pprint` function.
```pycon
```python
>>> from pprint import pprint
>>> pprint(portfolio)
[{'name': 'AA', 'price': 32.2, 'shares': 100},
@@ -346,7 +356,7 @@ A dictionary is a useful way to keep track of items where you want to
look up items using an index other than an integer. In the Python
shell, try playing with a dictionary:
```pycon
```python
>>> prices = { }
>>> prices['IBM'] = 92.45
>>> prices['MSFT'] = 45.12
@@ -388,7 +398,7 @@ A few little tips that you’ll need for this part. First, make sure you
use the `csv` module just as you did before—there’s no need to
reinvent the wheel here.
```pycon
```python
>>> import csv
>>> f = open('Data/prices.csv', 'r')
>>> rows = csv.reader(f)
@@ -409,7 +419,8 @@ an empty list—meaning no data was present on that line.
There’s a possibility that this could cause your program to die with
an exception. Use the `try` and `except` statements to catch this as
appropriate.
appropriate. Thought: would it be better to guard against bad data with
an `if`-statement instead?
Once you have written your `read_prices()` function, test it
interactively to make sure it works:
@@ -425,10 +436,11 @@ interactively to make sure it works:
### Exercise 2.7: Finding out if you can retire
Tie all of this work together by adding the statements to your
`report.py` program. It takes the list of stocks in Exercise 2.5 and
the dictionary of prices in Exercise 2.6 and computes the current
value of the portfolio along with the gain/loss.
Tie all of this work together by adding a few additional statements to
your `report.py` program that compute gain/loss. These statements
should take the list of stocks in Exercise 2.5 and the dictionary of
prices in Exercise 2.6 and computes the current value of the portfolio
along with the gain/loss.
[Contents](../Contents) \| [Previous (2.1 Datatypes)](01_Datatypes) \| [Next (2.3 Formatting)](03_Formatting)