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Added links. Renumber exercises

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David Beazley
2020-05-26 12:54:10 -05:00
parent e26c630082
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Notes/02_Working_with_data/04_Sequences.md
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# 2.4 Sequences
In this part, we look at some common idioms for working with sequence data.
### Sequence Datatypes
### Introduction
Python has three *sequences* datatypes.
Python has three *sequence* datatypes.
* String: `'Hello'`. A string is considered a sequence of characters.
* List: `[1, 4, 5]`.
@@ -266,7 +264,7 @@ d = dict(zip(columns, values))
## Exercises
### (a) Counting
### Exercise 2.13: Counting
Try some basic counting examples:
@@ -286,7 +284,7 @@ Try some basic counting examples:
>>>
```
### (b) More sequence operations
### Exercise 2.14: More sequence operations
Interactively experiment with some of the sequence reduction operations.
@@ -335,13 +333,17 @@ emerged from the depths of a rusty C program.
>>>
```
Don’t do that! Not only does reading it make everyone’s eyes bleed, it’s inefficient with memory and it runs a lot slower.
Just use a normal `for` loop if you want to iterate over data. Use `enumerate()` if you happen to need the index for some reason.
Don’t do that! Not only does reading it make everyone’s eyes bleed,
it’s inefficient with memory and it runs a lot slower. Just use a
normal `for` loop if you want to iterate over data. Use `enumerate()`
if you happen to need the index for some reason.
### (c) A practical `enumerate()` example
### Exercise 2.15: A practical `enumerate()` example
Recall that the file `Data/missing.csv` contains data for a stock portfolio, but has some rows with missing data.
Using `enumerate()` modify your `pcost.py` program so that it prints a line number with the warning message when it encounters bad input.
Recall that the file `Data/missing.csv` contains data for a stock
portfolio, but has some rows with missing data. Using `enumerate()`
modify your `pcost.py` program so that it prints a line number with
the warning message when it encounters bad input.
```python
>>> cost = portfolio_cost('Data/missing.csv')
@@ -361,9 +363,10 @@ for rowno, row in enumerate(rows, start=1):
print(f'Row {rowno}: Bad row: {row}')
```
### (d) Using the `zip()` function
### Exercise 2.16: Using the `zip()` function
In the file `portfolio.csv`, the first line contains column headers. In all previous code, we’ve been discarding them.
In the file `portfolio.csv`, the first line contains column
headers. In all previous code, we’ve been discarding them.
```pycon
>>> f = open('Data/portfolio.csv')
@@ -374,8 +377,9 @@ In the file `portfolio.csv`, the first line contains column headers. In all prev
>>>
```
However, what if you could use the headers for something useful? This is where the `zip()` function enters the picture.
First try this to pair the file headers with a row of data:
However, what if you could use the headers for something useful? This
is where the `zip()` function enters the picture. First try this to
pair the file headers with a row of data:
```pycon
>>> row = next(rows)
@@ -391,7 +395,8 @@ We’ve used `list()` here to turn the result into a list so that you
can see it. Normally, `zip()` creates an iterator that must be
consumed by a for-loop.
This pairing is just an intermediate step to building a dictionary. Now try this:
This pairing is just an intermediate step to building a
dictionary. Now try this:
```pycon
>>> record = dict(zip(headers, row))
@@ -425,7 +430,8 @@ def portfolio_cost(filename):
...
```
Now, try your function on a completely different data file `Data/portfoliodate.csv` which looks like this:
Now, try your function on a completely different data file
`Data/portfoliodate.csv` which looks like this:
```csv
name,date,time,shares,price
@@ -459,7 +465,7 @@ the same technique to pick out column headers.
Try running the `report.py` program on the `Data/portfoliodate.csv` file and see that it
produces the same answer as before.
### (e) Inverting a dictionary
### Exercise 2.17: Inverting a dictionary
A dictionary maps keys to values. For example, a dictionary of stock prices.
@@ -491,7 +497,8 @@ However, what if you wanted to get a list of `(value, key)` pairs instead?
>>>
```
Why would you do this? For one, it allows you to perform certain kinds of data processing on the dictionary data.
Why would you do this? For one, it allows you to perform certain kinds
of data processing on the dictionary data.
```pycon
>>> min(pricelist)
@@ -535,4 +542,4 @@ Also, be aware that `zip()` stops once the shortest input sequence is exhausted.
>>>
```
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