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‎Notes/00_Setup.md‎

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@@ -86,7 +86,7 @@ exercises. Feel free to look at this if you need a hint. To get the
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most out of the course however, you should try to create your own
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solutions first.
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[Contents](Contents.md)
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[Contents](Contents.md) \| [Next (1 Introduction to Python)](01_Introduction/00_Overview.md)
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‎Notes/01_Introduction/02_Hello_world.md‎

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Let's take a closer look at the elements of the REPL:
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- `>>>` is the interpreter prompt for starting a new statement.
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- `...` is the interpreter prompt for continuing a statements. Enter a blank line to finish typing and run the statements.
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- `...` is the interpreter prompt for continuing a statement. Enter a blank line to finish typing and run what you've entered.
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The `...` prompt may or may not be shown depending on your environment. For this course,
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it is shown as blanks to make it easier to cut/paste code samples.
@@ -241,7 +241,7 @@ while num_bills * bill_thickness < sears_height:
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day = day + 1
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num_bills = num_bills * 2
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print('Number of days', days)
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print('Number of days', day)
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```
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The statements indented below the `while` will execute as long as the expression after the `while` is `true`.
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day = day + 1
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num_bills = num_bills * 2
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print('Number of days', days)
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print('Number of days', day)
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```
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Indentation groups the following statements together as the operations that repeat:

‎Notes/01_Introduction/03_Numbers.md‎

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Floats are represented as double precision using the native CPU representation [IEEE 754](https://en.wikipedia.org/wiki/IEEE_754).
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This is the same as the `double` type in the programming language C.
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> 17 digits or precision
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> 17 digits of precision
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> Exponent from -308 to 308
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Be aware that floating point numbers are inexact when representing decimals.
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abs(x) Absolute Value
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```
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Theses are the same operators as Integers, except for the bit-wise operators.
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These are the same operators as Integers, except for the bit-wise operators.
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Additional math functions are found in the `math` module.
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```python
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Make it so that the user can set these variables:
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```python
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extra_payment_start_month = 60
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extra_payment_start_month = 61
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extra_payment_end_month = 108
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extra_payment = 1000
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```
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Make the program look at these variables and calculate the total paid appropriately.
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How much will Dave pay if he pays an extra $1000/month for 4 years starting in year 5 of the mortgage?
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How much will Dave pay if he pays an extra $1000/month for 4 years starting after the first
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five years have already been paid?
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### Exercise 1.10: Making a table
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4 10736.44 497581.83
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5 13420.55 496970.98
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...
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308 875705.88 674.44
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309 878389.99 -2006.86
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Total paid 878389.99
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Months 309
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308 874705.88 3478.83
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309 877389.99 809.21
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310 880074.1 -1871.53
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Total paid 880074.1
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Months 310
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```
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### Exercise 1.11: Bonus
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While you’re at it, fix the program to correct the for overpayment that occurs in the last month.
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While you’re at it, fix the program to correct for the overpayment that occurs in the last month.
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### Exercise 1.12: A Mystery
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‎Notes/01_Introduction/04_Strings.md‎

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# 1.4 Strings
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This section introduces way to work with text.
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This section introduces ways to work with text.
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### Representing Literal Text
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including all formatting.
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There is no difference between using single (') versus double (")
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quotes. The same type of quote used to start a string must be used to
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terminate it.
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quotes. *However, the same type of quote used to start a string must be used to
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terminate it*.
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### String escape codes
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**More string methods:**
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Strings have a wide variety of other methods for testing and manipulating the text data.
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This is small sample of methods:
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This is a small sample of methods:
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```python
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s.endswith(suffix) # Check if string ends with suffix
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s.isdigit() # Check if characters are numeric
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s.islower() # Check if characters are lower-case
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s.isupper() # Check if characters are upper-case
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s.join(slist) # Joins lists using s as delimiter
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s.join(slist) # Join a list of strings using s as delimiter
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s.lower() # Convert to lower case
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s.replace(old,new) # Replace text
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s.rfind(t) # Search for t from end of string

‎Notes/01_Introduction/05_Lists.md‎

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>>> nums * 2
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[1, 2, 3, 4, 5, 1, 2, 3, 4, 5]
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>>> nums + [10, 11, 12, 13, 14]
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[1, 2, 3, 4, 5, 10, 11, 12, 13, 14] >>>
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[1, 2, 3, 4, 5, 10, 11, 12, 13, 14]
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```
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Specifically, lists don't represent vectors/matrices as in MATLAB, Octave, R, etc.

‎Notes/01_Introduction/06_Files.md‎

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```python
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>>> import gzip
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>>> with gzip.open('Data/portfolio.csv.gz') as f:
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>>> with gzip.open('Data/portfolio.csv.gz', 'rt') as f:
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for line in f:
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print(line, end='')
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... look at the output ...
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>>>
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```
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Note: Including the file mode of `'rt'` is critical here. If you forget that,
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you'll get byte strings instead of normal text strings.
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### Commentary: Shouldn't we being using Pandas for this?
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Data scientists are quick to point out that libraries like

‎Notes/02_Working_with_data/01_Datatypes.md‎

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s = ('GOOG', 100, 490.1)
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```
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Sometimes the `()` are ommitted in the syntax.
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Sometimes the `()` are omitted in the syntax.
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```python
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s = 'GOOG', 100, 490.1
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```
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Special cases (0-tuple, 1-typle).
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Special cases (0-tuple, 1-tuple).
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```python
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t = () # An empty tuple
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```python
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>>> d['shares'] = 75
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>>> d
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{'name': 'AA', 'shares': 75, 'price': 75}
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{'name': 'AA', 'shares': 75, 'price': 32.2 }
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>>>
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```
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‎Notes/02_Working_with_data/02_Containers.md‎

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records = [] # Initial empty list
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with open('Data/portfolio.csv', 'rt') as f:
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next(f) # Skip header
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for line in f:
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row = line.split(',')
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records.append((row[0], int(row[1])), float(row[2]))
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records.append((row[0], int(row[1]), float(row[2])))
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### Dicts as a Container
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prices[row[0]] = float(row[1])
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```
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Note: If you try this on the `Data/prices.csv` file, you'll find that
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it almost works--there's a blank line at the end that causes it to
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crash. You'll need to figure out some way to modify the code to
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account for that (see Exercise 2.6).
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### Dictionary Lookups
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You can test the existence of a key.
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```python
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tech_stocks = { 'IBM','AAPL','MSFT' }
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# Alternative sintax
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# Alternative syntax
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```
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Additional set operations:
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```python
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names.add('CAT') # Add an item
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names.remove('YHOO') # Remove an item
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s1 | s2 # Set union
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s1 & s2 # Set intersection
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s1 - s2 # Set difference
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unique.add('CAT') # Add an item
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unique.remove('YHOO') # Remove an item
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s1 = { 'a', 'b', 'c'}
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s2 = { 'c', 'd' }
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s1 | s2 # Set union { 'a', 'b', 'c', 'd' }
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s1 & s2 # Set intersection { 'c' }
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s1 - s2 # Set difference { 'a', 'b' }
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## Exercises
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Exercise 2.4.
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```python
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>>> portfolio = read_portfolio('portfolio.csv')
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>>> portfolio = read_portfolio('Data/portfolio.csv')
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>>> portfolio
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[{'name': 'AA', 'shares': 100, 'price': 32.2}, {'name': 'IBM', 'shares': 50, 'price': 91.1},
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{'name': 'CAT', 'shares': 150, 'price': 83.44}, {'name': 'MSFT', 'shares': 200, 'price': 51.23},
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often preferred because the resulting code is easier to read later.
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Viewing large dictionaries and lists can be messy. To clean up the
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output for debugging, considering using the `pprint` function.
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output for debugging, consider using the `pprint` function.
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```python
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>>> from pprint import pprint
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### Exercise 2.7: Finding out if you can retire
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Tie all of this work together by adding a few additional statements to
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your `report.py` program that compute gain/loss. These statements
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your `report.py` program that computes gain/loss. These statements
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should take the list of stocks in Exercise 2.5 and the dictionary of
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prices in Exercise 2.6 and computes the current value of the portfolio
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prices in Exercise 2.6 and compute the current value of the portfolio
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along with the gain/loss.
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[Contents](../Contents.md) \| [Previous (2.1 Datatypes)](01_Datatypes.md) \| [Next (2.3 Formatting)](03_Formatting.md)

‎Notes/02_Working_with_data/03_Formatting.md‎

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x Hexadecimal integer
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f Float as [-]m.dddddd
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e Float as [-]m.dddddde+-xx
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g Float, but selective use of E notation s String
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g Float, but selective use of E notation
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s String
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c Character (from integer)
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```
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```code
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:>10d Integer right aligned in 10-character field
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:<10d Integer left aligned in 10-character field
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:^10d Integer centered in 10-character field :0.2f Float with 2 digit precision
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:^10d Integer centered in 10-character field
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:0.2f Float with 2 digit precision
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```
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### Dictionary Formatting
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*Note: This is the only formatting available on byte strings.*
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```python
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>>> b'%s has %n messages' % (b'Dave', 37)
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>>> b'%s has %d messages' % (b'Dave', 37)
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b'Dave has 37 messages'
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>>>
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```

‎Notes/02_Working_with_data/04_Sequences.md‎

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>>> s = [1, 2, 3, 4]
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>>> sum(s)
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>>> min(s) 1
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>>> max(s) 4
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>>> min(s)
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1
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>>> max(s)
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4
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>>> t = ['Hello', 'World']
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>>> max(t)
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'World'
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```
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When using multiple variables, each tuple is *unpacked* into a set of iteration variables.
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The number of variables must match the of items in each tuple.
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The number of variables must match the number of items in each tuple.
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### zip() function
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```python
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columns = ['name', 'shares', 'price']
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values = ['GOOG', 100, 490.1 ]
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pairs = zip(a, b)
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pairs = zip(columns, values)
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# ('name','GOOG'), ('shares',100), ('price',490.1)
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```
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Modify the `report.py` program you wrote in Section 2.3 that it uses
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Modify the `report.py` program you wrote in Section 2.3 so that it uses
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the same technique to pick out column headers.
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Try running the `report.py` program on the `Data/portfoliodate.csv`

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