Class 16 — Wednesday March 10
CSV Chrestomathics and logical values and decision
May the light of peace — For you and your families — Always shine brightly
Look both ways
Riddle me this — what classrooms are viable for scheduling CS 1112
- The School of Engineering and Applied Science (SEAS) has four-tiered classrooms: MEC 205, Olsson Hall 120, Rice 130, and Thornton E316. All four rooms provide WIFI access. Only MEC 205, Olsson Hall 120, and Rice 130 support classroom sizes greater than 100. MEC 205 and Olsson 120 do not provide student power ports.
- The registrar has rules about scheduling 75-minute classes. They can meet anytime on Tuesdays or Thursdays. On Mondays, Wednesdays, or Fridays they cannot be scheduled before 2:00 PM.
- Surveys indicate that on average, students preferred classes whose starting times do not occur before 10:00 AM or after 2:00 PM.
- Tiered seating allows for a better eye contact between an instructor and other members of the class. Better eye contact encourages student engagement.
- Jim Cohoon has several general teaching preferences.
- Maximize student access to his courses.
- Class sessions be 75-minutes.
- 1xxx and 2xxx level courses meet three times a week.
- 3xxx and 4xxx courses meet twice a week.
- Classrooms should provide student access to WIFI and to power ports.
- Maximize student engagement.
Agenda
- Being logical
if
statement exposure
- CSV chrestomathics
Transitioning
- Some problem solving requires the ability to react — depending upon the circumstances different conditions need actions to be performed. Python provides the
if
statement for decision making.
- The
if
statement uses logical test expressions to determine which action to perform. There are variants of theif
statement to make decisions based on one, two, or several possibilities.
Downloads
- Program csv_is_not_a_pharmacy.py
- Program logical_operators.py
- Program can_you_relate.py
- Program acid_test.py
To do
- Review artifacts
- Read epistle on decision making
Program can_you_relate.py
- Introduces the comparison operators
Three program runs
Enter number: 12
Enter number: 11
12 < 11 : False
12 > 11 : True
12 <= 11 : False
12 >= 11 : True
12 == 11 : False
12 != 11 : True
Enter number: 3
Enter number: 14
3 < 14 : True
3 > 14 : False
3 <= 14 : True
3 >= 14 : False
3 == 14 : False
3 != 14 : True
Enter number: 7
Enter number: 7
7 < 7 : False
7 > 7 : False
7 <= 7 : True
7 >= 7 : True
7 == 7 : True
7 != 7 : False
Program logical_operators.py
- Introduces the logical operators
Program run
##### Logical values (bool)
True
False
##### Logical and
True and True = True
True and False = False
False and True = False
False and False = False
##### Logical or
True or True = True
True or False = True
False or True = True
False or False = False
##### Logical negation
not True = False
not False = True
##### Logical includes
1 in [3, 1, 4, 1, 5] = True
2 in [3, 1, 4, 1, 5] = False
##### Logical exclusion
1 not in [3, 1, 4, 1, 5] = False
2 not in [3, 1, 4, 1, 5] = True
Program acid_test.py
- Determine whether its input pH level is acidic; i.e., less than 7.0
Three program runs
Enter pH level: 6.5
True
Enter pH level: 7.0
False
Enter pH level: 7.5
False
Some datasets
Location, Author, Max Height, Min Height
Narnia, Lewis, 4810, -10
Neverland, Milne, 426, -2
Oz, Baum, 1231, 679
Sleepy Hollow, Irving, 1629, 304
Stars Hollow, Sherman-Palladino, 725, 152
Toyland, MacDonough, 6187, 0
Wonderland, Carroll, 5895, -5
Country, Females, Males
Australia, 11175724, 11092660
Fiji, 421365, 439258
French Polynesia, 132082, 138682
New Caledonia, 125322, 125548
New Zealand, 2223281, 2144855
Papua New Guinea, 3359979, 3498287
Solomon Islands, 259909, 278239
Vanuatu, 117573, 122078
Program csv_is_not_a_pharmacy.py — streamlining getting a dataset
- Makes use of module
url.py
to process acquire datasets
-
Some program runs
Enter name of dataset: oceania.csv
dataset:
Country, Females, Males
Australia, 11175724, 11092660
Fiji, 421365, 439258
French Polynesia, 132082, 138682
New Caledonia, 125322, 125548
New Zealand, 2223281, 2144855
Papua New Guinea, 3359979, 3498287
Solomon Islands, 259909, 278239
Vanuatu, 117573, 122078
header:
['Country', 'Females', 'Males']
data:
['Country', 'Females', 'Males']
['Australia', 11175724, 11092660]
['Fiji', 421365, 439258]
['French Polynesia', 132082, 138682]
['New Caledonia', 125322, 125548]
['New Zealand', 2223281, 2144855]
['Papua New Guinea', 3359979, 3498287]
['Solomon Islands', 259909, 278239]
['Vanuatu', 117573, 122078]
Enter name of dataset: elevations.csv
dataset:
Location, Author, Max Height, Min Height
Narnia, Lewis, 4810, -10
Neverland, Milne, 426, -2
Oz, Baum, 1231, 679
Sleepy Hollow, Irving, 1629, 304
Stars Hollow, Sherman-Palladino, 725, 152
Toyland, MacDonough, 6187, 0
Wonderland, Carroll, 5895, -5
header:
['Location', 'Author', 'Max Height', 'Min Height']
data:
['Narnia', 'Lewis', 4810, -10]
['Neverland', 'Milne', 426, -2]
['Oz', 'Baum', 1231, 679]
['Sleepy Hollow', 'Irving', 1629, 304]
['Stars Hollow', 'Sherman-Palladino', 725, 152]
['Toyland', 'MacDonough', 6187, 0]
['Wonderland', 'Carroll', 5895, -5]
Where am I
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