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%% Cell type:markdown id:5fef60fd tags:
# Announcements - List Practice
* Download ALL files from Canvas for today's lecture
* Worksheet is online only - great practice for the exam!
* Exam I
* We estimate results will be available this afternoon
* This will tie last semesters turn around time
* [Exam 2 Conflict Form](https://docs.google.com/forms/d/e/1FAIpQLSegJSzTsDHEnygijU3-HQvZDUbTCkHFPKccDkqMt1dGzC67_w/viewform)
* [Regrade Request](https://piazza.com/class/ld8bqui1lgeas/post/105)
* [P6 FAQ](https://piazza.com/class/ld8bqui1lgeas/post/294)
* Quiz 4 due Today at 11:59:00 pm
* We release the answers after the quiz closes so we do not reopen quizzes for students even if something goes wrong.
* We do drop 2 quiz scores (in case something goes wrong)
%% Cell type:markdown id:72348536 tags:
# List Practice
%% Cell type:code id:2bf3c996 tags:
``` python
import csv
```
%% Cell type:markdown id:b34b84ae tags:
### Warmup 1: min / max
%% Cell type:code id:b89c41e1 tags:
``` python
some_list = [45, -4, 66, 220, 10]
min_val = None
for val in some_list:
if min_val == None or val < min_val:
min_val = val
print(min_val)
max_val = None
for val in some_list:
if max_val == None or val > max_val:
max_val = val
print(max_val)
```
%% Output
-4
220
%% Cell type:markdown id:59a689b1 tags:
### Warmup 2: median
%% Cell type:code id:2fd5e101 tags:
``` python
def median(some_items):
"""
Returns median of a list passed as argument
"""
some_items.sort()
n = len(some_items)
if n % 2 == 1:
return some_items[n // 2]
else:
first_middle = some_items[n//2 - 1]
second_middle = some_items[n // 2]
median = (first_middle + second_middle) / 2
return median
nums = [5, 4, 3, 2, 1]
print("Median of", nums, "is" , median(nums))
nums = [6, 5, 4, 3, 2, 1]
print("Median of", nums, "is" , median(nums))
```
%% Output
Median of [1, 2, 3, 4, 5] is 3
Median of [1, 2, 3, 4, 5, 6] is 3.5
%% Cell type:code id:cf14bf7f tags:
``` python
vals = ["A", "C", "B"]
print("Median of", nums, "is" , median(vals))
vals = ["A", "C", "B", "D"]
# print("Median of", nums, "is" , median(vals)) # does not work due to TypeError
```
%% Output
Median of [1, 2, 3, 4, 5, 6] is B
%% Cell type:markdown id:bdbf6f75 tags:
### set data structure
- **not a sequence**
- no ordering of values:
- this implies that you can only store unique values within a `set`
- very helpful to find unique values stored in a `list`
- easy to convert a `list` to `set` and vice-versa.
- ordering is not guaranteed once we use `set`
%% Cell type:code id:52e80a6b tags:
``` python
some_set = {10, 20, 30, 30, 40, 50, 10} # use a pair of curly braces to define it
some_set
```
%% Output
{10, 20, 30, 40, 50}
%% Cell type:code id:2587184f tags:
``` python
some_list = [10, 20, 30, 30, 40, 50, 10] # Initialize a list containing duplicate numbers
# TODO: to find unique values, convert it into a set
print(set(some_list))
# TODO: convert the set back into a list
print(list(set(some_list)))
```
%% Output
{40, 10, 50, 20, 30}
[40, 10, 50, 20, 30]
%% Cell type:markdown id:8a143e1c tags:
Can you index / slice into a `set`?
%% Cell type:code id:ce43cb95 tags:
``` python
# some_set[1] # doesn't work - remember set has no order
```
%% Cell type:code id:cd6473f8 tags:
``` python
# some_set[1:] # doesn't work - remember set has no order
```
%% Cell type:code id:9d936c1c tags:
``` python
# inspired by https://automatetheboringstuff.com/2e/chapter16/
def process_csv(filename):
# open the file, its a text file utf-8
example_file = open(filename, encoding="utf-8")
# prepare it for reading as a CSV object
example_reader = csv.reader(example_file)
# use the built-in list function to convert this into a list of lists
example_data = list(example_reader)
# close the file to tidy up our workspace
example_file.close()
# return the list of lists
return example_data
```
%% Cell type:markdown id:89621c98 tags:
### Student Information Survey data
%% Cell type:code id:d3c252b4 tags:
``` python
# TODO: call the process_csv function and store the list of lists in cs220_csv
cs220_csv = process_csv("cs220_survey_data.csv")
```
%% Cell type:code id:5838ae5f tags:
``` python
# Store the header row into cs220_header, using indexing
cs220_header = cs220_csv[0]
cs220_header
```
%% Output
['section',
'Lecture',
'Age',
'Primary major',
'Other Primary Major',
'Other majors',
'Zip Code',
'Latitude',
'Longitude',
'Pet owner',
'Pizza topping',
'Pet owner',
'Runner',
'Sleep habit',
'Procrastinator',
'Song']
%% Cell type:code id:66fda88d tags:
``` python
# TODO: Store all of the data rows into cs220_data, using slicing
cs220_data = cs220_csv[1:]
# TODO: use slicing to display top 3 rows data
cs220_data[:3]
```
%% Output
[['COMP SCI 220:LAB345, COMP SCI 220:LEC004',
'LEC004',
'',
'Other (please provide details below).',
'',
'',
'53,706',
'22.5726',
'88.3639',
'No',
'pepperoni',
'dog',
'No',
'night owl',
'Yes',
'Island in the Sun - Harry Belafonte'],
['COMP SCI 220:LEC003, COMP SCI 220:LAB332',
'LEC001',
'19',
'Engineering: Mechanical',
'',
'',
'53,703',
'44.5876',
'-71.9466',
'No',
'pepperoni',
'dog',
'No',
'night owl',
'Yes',
'No role modelz by J. Cole'],
['COMP SCI 220:LAB325, COMP SCI 220:LEC002',
'LEC002',
'18',
'Engineering: Mechanical',
'.',
'.',
'53,706',
'40.7128',
'-74.006',
'Maybe',
'none (just cheese)',
'dog',
'No',
'night owl',
'Yes',
'\xa0biggest bird']]
%% Cell type:markdown id:4267fe3e tags:
### What `Pizza topping` does the 13th student prefer?
%% Cell type:code id:4b8dbe8b tags:
``` python
cs220_data[12][6] # bad example: we hard-coded the column index
```
%% Output
'53,703'
%% Cell type:markdown id:4f125240 tags:
What if we decided to add a new column before sleeping habit? Your code will no longer work.
Instead of hard-coding column index, you should use `index` method, to lookup column index from the header variable. This will also make your code so much readable.
%% Cell type:code id:f2e52e06 tags:
``` python
cs220_data[12][cs220_header.index("Pizza topping")]
```
%% Output
'pepperoni'
%% Cell type:markdown id:5d298a4c tags:
### What is the Lecture of the 4th student?
%% Cell type:code id:3617b3de tags:
``` python
cs220_data[3][cs220_header.index("Lecture")]
```
%% Output
'LEC001'
%% Cell type:markdown id:059de363 tags:
### What **unique** `age` values are included in the dataset?
%% Cell type:code id:45909f22 tags:
``` python
ages = []
for row in cs220_data:
age = row[cs220_header.index("Age")]
if age == '':
continue
age = int(age)
if age < 0 or age > 118:
continue
ages.append(age)
ages = list(set(ages))
ages
```
%% Output
[33, 69, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30]
%% Cell type:markdown id:8e18663d tags:
### cell function
- It would be very helpful to define a cell function, which can handle missing data and type conversions
%% Cell type:code id:bba90038 tags:
``` python
def cell(row_idx, col_name):
"""
Returns the data value (cell) corresponding to the row index and
the column name of a CSV file.
"""
# TODO: get the index of col_name
col_idx = cs220_header.index(col_name)
# TODO: get the value of cs220_data at the specified cell
val = cs220_data[row_idx][col_idx]
# TODO: handle missing values, by returning None
if val == '':
return None
# TODO: handle type conversions
if col_name in ["Age",]:
return int(val)
elif col_name in ['Latitude', 'Longitude']:
return float(val)
return val
```
%% Cell type:markdown id:1624fafd tags:
### Find average age per lecture.
%% Cell type:code id:5755511a tags:
``` python
# TODO: initialize 4 lists for the 4 lectures
lec1_ages = []
lec2_ages = []
lec3_ages = []
lec4_ages = []
# Iterate over the data and populate the lists
for row_idx in range(len(cs220_data)):
age = cell(row_idx, "Age")
if age != None and age > 0 and age < 125:
lecture = cell(row_idx, "Lecture")
if lecture == "LEC001":
lec1_ages.append(age)
elif lecture == "LEC002":
lec2_ages.append(age)
elif lecture == "LEC003":
lec3_ages.append(age)
elif lecture == "LEC004":
lec4_ages.append(age)
# TODO: compute average age of each lecture
print("LEC001 average student age:", round(sum(lec1_ages) / len(lec1_ages), 2))
print("LEC002 average student age:", round(sum(lec2_ages) / len(lec2_ages), 2))
print("LEC003 average student age:", round(sum(lec3_ages) / len(lec3_ages), 2))
print("LEC004 average student age:", round(sum(lec4_ages) / len(lec4_ages), 2))
```
%% Output
LEC001 average student age: 19.71
LEC002 average student age: 20.24
LEC003 average student age: 19.41
LEC004 average student age: 19.43
%% Cell type:markdown id:b7c8e726 tags:
### Function `avg_age_per_lecture(lecture)`
%% Cell type:code id:4894d0c7 tags:
``` python
def avg_age_per_lecture(lecture):
'''
avg_age_per_lecture(lecture) returns the average age of
the students in the given `lecture`; if there are no
students in the given `lecture`, it returns `None`
'''
# To compute average you don't need to actually populate a list.
# But here a list will come in handy. It will help you with the None return requirement.
ages = []
for row_idx in range(len(cs220_data)):
curr_lecture = cell(row_idx, "Lecture")
if lecture == curr_lecture:
age = cell(row_idx, "Age")
if age != None and age > 0 and age <= 125:
ages.append(age)
if len(ages) > 0:
return sum(ages) / len(ages)
else:
return None
```
%% Cell type:code id:f0a05e42 tags:
``` python
avg_age_per_lecture("LEC003")
```
%% Output
19.405228758169933
%% Cell type:code id:ec9af3da tags:
``` python
print(avg_age_per_lecture("LEC007"))
```
%% Output
None
%% Cell type:markdown id:0a4d313c tags:
### Find all unique zip codes.
%% Cell type:code id:bf8f0ecc tags:
``` python
# TODO: initialize list of keep track of zip codes
zip_codes = []
for row_idx in range(len(cs220_data)):
zip_code = cell(row_idx, "Zip Code")
if zip_code != None:
zip_codes.append(zip_code)
list(set(zip_codes))
```
%% Output
['53,713',
'53,589',
'53,558',
'53,719',
'53,563',
'53,711',
'53,572',
'53,051',
'98,607',
'53,121',
'-53,703',
'93,703',
'533,706',
'53,521',
'53,575',
'1,520',
'53.715',
'8,820',
'53,562',
'53,716',
'53,705',
'53,590',
'94,596',
'53,527',
'53,726',
'53,150',
'53,701',
'57,303',
'56,511',
'53,703',
'53,715',
'53,704',
'60,517',
'53.706',
'54,703',
'53,706',
'95,030',
'52,703',
'50,376',
'51,735']
%% Cell type:markdown id:94548bf4 tags:
### `sort` method versus `sorted` function
- `sort` (and other list methods) have an impact on the original list
- `sorted` function returns a new list with expected ordering
- default sorting order is ascending / alphanumeric
- `reverse` parameter is applicable for both `sort` method and `sorted` function:
- enables you to specify descending order by passing argument as `True`
%% Cell type:code id:c1e555f9 tags:
``` python
some_list = [10, 4, 25, 2, -10]
```
%% Cell type:code id:152297bb tags:
``` python
# TODO: Invoke sort method
rv = some_list.sort()
print(some_list)
# What does the sort method return?
# TODO: Capture return value into a variable rv and print the return value.
print(rv)
```
%% Output
[-10, 2, 4, 10, 25]
None
%% Cell type:markdown id:3c0d5e7d tags:
`sort` method returns `None` because it sorts the values in the original list
%% Cell type:code id:c06d8976 tags:
``` python
# TODO: invoke sorted function and pass some_list as argument
# TODO: capture return value into sorted_some_list
sorted_some_list = sorted(some_list)
# What does the sorted function return?
# It returns a brand new list with the values in sorted order
print(sorted_some_list)
```
%% Output
[-10, 2, 4, 10, 25]
%% Cell type:markdown id:ded0304c tags:
TODO: go back to `sort` method call and `sorted` function call and pass keyword argument `reverse = True`.
%% Cell type:markdown id:3579e061 tags:
Can you call `sort` method on a set?
%% Cell type:code id:14d8a670 tags:
``` python
# some_set.sort()
# doesn't work: no method named sort associated with type set
# you cannot sort a set because of the lack of ordering
```
%% Cell type:markdown id:1fb64b44 tags:
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
%% Cell type:code id:03b1183f tags:
``` python
# works because Python converts the set into a list and then sorts the list
sorted(some_set)
```
%% Output
[10, 20, 30, 40, 50]
%% Cell type:markdown id:efa2869e tags:
### Function: `find_majors(phrase)`
%% Cell type:code id:655f876d tags:
``` python
def find_majors(phrase):
"""
find_majors(phrase) returns a list of all the room names that contain the
substring (case insensitive match) `phrase`.
"""
# TODO: initialize the target list here
majors = []
# TODO: iterate over row indices
for row_idx in range(len(cs220_data)):
major = cell(row_idx, "Primary major")
if phrase.lower() in major.lower():
majors.append(major)
return majors
```
%% Cell type:markdown id:ed19265f tags:
### Find all `major` that contain **either** `"Computer"` **or** `"Science"`.
Your output **must** be a *list*. The order **does not** matter, but if a `major` contains **both** `"Computer"` and `"Science"`, then the room must be included **only once** in your list.
%% Cell type:code id:ab656189 tags:
``` python
computer_majors = find_majors("Computer")
science_majors = find_majors("Science")
computer_and_science_majors = computer_majors + science_majors
# TODO: Now find just the unique values
computer_and_science_majors = list(set(computer_and_science_majors))
computer_and_science_majors
```
%% Output
['Data Science',
'Science: Other',
'Science: Chemistry',
'Science: Biology/Life',
'Computer Science',
'Science: Physics']
%% Cell type:markdown id:64fd0945 tags:
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using ascending order.
%% Cell type:code id:d4e2e6fc tags:
``` python
# VERSION 1
# Be very careful: if you use sorted, make sure your return value
# variable matches with the variable for that project question
sorted_computer_and_science_majors = sorted(computer_and_science_majors)
sorted_computer_and_science_majors
```
%% Output
['Computer Science',
'Data Science',
'Science: Biology/Life',
'Science: Chemistry',
'Science: Other',
'Science: Physics']
%% Cell type:code id:c28e77ce tags:
``` python
# VERSION 2
computer_and_science_majors.sort()
computer_and_science_majors
```
%% Output
['Computer Science',
'Data Science',
'Science: Biology/Life',
'Science: Chemistry',
'Science: Other',
'Science: Physics']
%% Cell type:markdown id:e354b781 tags:
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using descending order.
%% Cell type:code id:ca887135 tags:
``` python
# VERSION 1
# Be very careful: if you use sorted, make sure your return value
# variable matches with the variable for that project question
reverse_sorted_computer_and_science_majors = sorted(computer_and_science_majors, reverse = True)
reverse_sorted_computer_and_science_majors
```
%% Output
['Science: Physics',
'Science: Other',
'Science: Chemistry',
'Science: Biology/Life',
'Data Science',
'Computer Science']
%% Cell type:code id:1606075f tags:
``` python
# VERSION 2
computer_and_science_majors.sort(reverse = True)
computer_and_science_majors
```
%% Output
['Science: Physics',
'Science: Other',
'Science: Chemistry',
'Science: Biology/Life',
'Data Science',
'Computer Science']
%% Cell type:markdown id:31a381fe tags:
## Self-practice
%% Cell type:markdown id:8ac26620 tags:
### How many students are both a procrastinator and a pet owner?
%% Cell type:markdown id:172141ea tags:
### What percentage of 18-year-olds have their major declared as "Other"?
%% Cell type:markdown id:d9a7a2b1 tags:
### How old is the oldest basil/spinach-loving Business major?
......
s23/Gurmail_lecture_notes/16_List_Practice/lec_16_list_practice_template_Gurmail_lec1.ipynb
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− 2
View file @ 27622921
%% Cell type:markdown id:2cceab19 tags:
# Announcements - List Practice
* Download ALL files from Canvas for today's lecture
* Worksheet is online only - great practice for the exam!
* Exam I
* We estimate results will be available this afternoon
* This will tie last semesters turn around time
* [Exam 2 Conflict Form](https://docs.google.com/forms/d/e/1FAIpQLSegJSzTsDHEnygijU3-HQvZDUbTCkHFPKccDkqMt1dGzC67_w/viewform)
* [Regrade Request](https://piazza.com/class/ld8bqui1lgeas/post/105)
* [P6 FAQ](https://piazza.com/class/ld8bqui1lgeas/post/294)
* Quiz 4 due Today at 11:59:00 pm
* We release the answers after the quiz closes so we do not reopen quizzes for students even if something goes wrong.
* We do drop 2 quiz scores (in case something goes wrong)
%% Cell type:markdown id:72348536 tags:
# List Practice
%% Cell type:code id:d21a94b5 tags:
``` python
import csv
```
%% Cell type:markdown id:cd8a434c tags:
### Warmup 1: min / max
%% Cell type:code id:baa730ba tags:
``` python
some_list = [45, -4, 66, 220, 10]
min_val = None
for val in some_list:
if min_val == None or val < min_val:
min_val = val
print(min_val)
max_val = None
for val in some_list:
if max_val == None or val > max_val:
max_val = val
print(max_val)
```
%% Cell type:markdown id:3502c700 tags:
### Warmup 2: median
%% Cell type:code id:414ae09e tags:
``` python
def median(some_items):
"""
Returns median of a list passed as argument
"""
pass
nums = [5, 4, 3, 2, 1]
print("Median of", nums, "is" , median(nums))
nums = [6, 5, 4, 3, 2, 1]
print("Median of", nums, "is" , median(nums))
```
%% Cell type:code id:73fa337e tags:
``` python
vals = ["A", "C", "B"]
print("Median of", nums, "is" , median(vals))
vals = ["A", "C", "B", "D"]
# print("Median of", nums, "is" , median(vals)) # does not work due to TypeError
```
%% Cell type:markdown id:050fd57c tags:
### set data structure
- **not a sequence**
- no ordering of values:
- this implies that you can only store unique values within a `set`
- very helpful to find unique values stored in a `list`
- easy to convert a `list` to `set` and vice-versa.
- ordering is not guaranteed once we use `set`
%% Cell type:code id:7d4a693f tags:
``` python
some_set = {10, 20, 30, 30, 40, 50, 10} # use a pair of curly braces to define it
some_set
```
%% Cell type:code id:baef596c tags:
``` python
some_list = [10, 20, 30, 30, 40, 50, 10] # Initialize a list containing duplicate numbers
# TODO: to find unique values, convert it into a set
print(set(some_list))
# TODO: convert the set back into a list
print(list(set(some_list)))
```
%% Cell type:markdown id:2be52d13 tags:
Can you index / slice into a `set`?
%% Cell type:code id:f622a5eb tags:
``` python
some_set[1] # doesn't work - remember set has no order
```
%% Cell type:code id:e679d3a7 tags:
``` python
some_set[1:] # doesn't work - remember set has no order
```
%% Cell type:code id:9d936c1c tags:
``` python
# inspired by https://automatetheboringstuff.com/2e/chapter16/
def process_csv(filename):
# open the file, its a text file utf-8
example_file = open(filename, encoding="utf-8")
# prepare it for reading as a CSV object
example_reader = csv.reader(example_file)
# use the built-in list function to convert this into a list of lists
example_data = list(example_reader)
# close the file to tidy up our workspace
example_file.close()
# return the list of lists
return example_data
```
%% Cell type:markdown id:89621c98 tags:
### Student Information Survey data
%% Cell type:code id:d3c252b4 tags:
``` python
# TODO: call the process_csv function and store the list of lists in cs220_csv
cs220_csv = process_csv(???)
```
%% Cell type:code id:5838ae5f tags:
``` python
# Store the header row into cs220_header, using indexing
cs220_header = ???
cs220_header
```
%% Cell type:code id:66fda88d tags:
``` python
# TODO: Store all of the data rows into cs220_data, using slicing
cs220_data = ???
# TODO: use slicing to display top 3 rows data
cs220_data???
```
%% Cell type:markdown id:4267fe3e tags:
### What `Pizza topping` does the 13th student prefer?
%% Cell type:code id:4b8dbe8b tags:
``` python
# bad example: we hard-coded the column index
```
%% Cell type:markdown id:4f125240 tags:
What if we decided to add a new column before sleeping habit? Your code will no longer work.
Instead of hard-coding column index, you should use `index` method, to lookup column index from the header variable. This will also make your code so much readable.
%% Cell type:code id:f2e52e06 tags:
``` python
```
%% Cell type:markdown id:5d298a4c tags:
### What is the Lecture of the 4th student?
%% Cell type:code id:3617b3de tags:
``` python
```
%% Cell type:markdown id:059de363 tags:
### What **unique** `age` values are included in the dataset?
%% Cell type:code id:45909f22 tags:
``` python
```
%% Cell type:markdown id:8e18663d tags:
### cell function
- It would be very helpful to define a cell function, which can handle missing data and type conversions
%% Cell type:code id:bba90038 tags:
``` python
def cell(row_idx, col_name):
"""
Returns the data value (cell) corresponding to the row index and
the column name of a CSV file.
"""
# TODO: get the index of col_name
# TODO: get the value of cs220_data at the specified cell
# TODO: handle missing values, by returning None
# TODO: handle type conversions
return val
```
%% Cell type:markdown id:e2278e4c tags:
### Find average age per lecture.
%% Cell type:code id:09e90e94 tags:
``` python
# TODO: initialize 4 lists for the 4 lectures
# Iterate over the data and populate the lists
# TODO: compute average age of each lecture
print("LEC001 average student age:", round(sum(lec1_ages) / len(lec1_ages), 2))
print("LEC002 average student age:", round(sum(lec2_ages) / len(lec2_ages), 2))
print("LEC003 average student age:", round(sum(lec3_ages) / len(lec3_ages), 2))
print("LEC004 average student age:", round(sum(lec4_ages) / len(lec4_ages), 2))
```
%% Cell type:markdown id:b7c8e726 tags:
### Function `avg_age_per_lecture(lecture)`
%% Cell type:code id:fa5598e0 tags:
``` python
def avg_age_per_lecture(lecture):
'''
avg_age_per_lecture(lecture) returns the average age of
the students in the given `lecture`; if there are no
students in the given `lecture`, it returns `None`
'''
# To compute average you don't need to actually populate a list.
# But here a list will come in handy. It will help you with the None return requirement.
pass
```
%% Cell type:code id:f0a05e42 tags:
``` python
avg_age_per_lecture("LEC003")
```
%% Cell type:code id:9f2c7e6e tags:
``` python
print(avg_age_per_lecture("LEC007"))
```
%% Cell type:markdown id:c07f9cfc tags:
### Find all unique zip codes.
%% Cell type:code id:a6df8ef5 tags:
``` python
# TODO: initialize list of keep track of zip codes
zip_codes = []
for row_idx in range(len(cs220_data)):
zip_code = cell(row_idx, "Zip Code")
if zip_code != None:
zip_codes.append(zip_code)
zip_codes # How do we get the unique values?
```
%% Cell type:markdown id:94548bf4 tags:
### `sort` method versus `sorted` function
- `sort` (and other list methods) have an impact on the original list
- `sorted` function returns a new list with expected ordering
- default sorting order is ascending / alphanumeric
- `reverse` parameter is applicable for both `sort` method and `sorted` function:
- enables you to specify descending order by passing argument as `True`
%% Cell type:code id:c1e555f9 tags:
``` python
some_list = [10, 4, 25, 2, -10]
```
%% Cell type:code id:152297bb tags:
``` python
# TODO: Invoke sort method
rv = ???
print(some_list)
# What does the sort method return?
# TODO: Capture return value into a variable rv and print the return value.
print(rv)
```
%% Cell type:markdown id:3c0d5e7d tags:
`sort` method returns `None` because it sorts the values in the original list
%% Cell type:code id:c06d8976 tags:
``` python
# TODO: invoke sorted function and pass some_list as argument
# TODO: capture return value into sorted_some_list
???
# What does the sorted function return?
# It returns a brand new list with the values in sorted order
print(sorted_some_list)
```
%% Cell type:markdown id:ded0304c tags:
TODO: go back to `sort` method call and `sorted` function call and pass keyword argument `reverse = True`.
%% Cell type:markdown id:35894ef5 tags:
Can you call `sort` method on a set?
%% Cell type:code id:fc08879e tags:
``` python
some_set.sort()
# doesn't work: no method named sort associated with type set
# you cannot sort a set because of the lack of ordering
```
%% Cell type:markdown id:99161c42 tags:
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
%% Cell type:code id:2549df29 tags:
``` python
# works because Python converts the set into a list and then sorts the list
sorted(some_set)
```
%% Cell type:markdown id:5c7f3489 tags:
### Function: `find_majors(phrase)`
%% Cell type:code id:b6adbfe0 tags:
``` python
def find_majors(phrase):
"""
find_majors(phrase) returns a list of all the room names that contain the
substring (case insensitive match) `phrase`.
"""
# TODO: initialize the target list here
# TODO: iterate over row indices
for row_idx in range(len(cs220_data)):
major = cell(row_idx, "Major")
# TODO: write the actual logic here
return majors
```
%% Cell type:markdown id:1b7f671f tags:
### Find all `major` that contain **either** `"Computer"` **or** `"Science"`.
Your output **must** be a *list*. The order **does not** matter, but if a `major` contains **both** `"Computer"` and `"Science"`, then the room must be included **only once** in your list.
%% Cell type:code id:ed895a3b tags:
``` python
computer_majors = ???
science_majors = ???
computer_and_science_majors = ???
# TODO: Now find just the unique values
computer_and_science_majors = ???
computer_and_science_majors
```
%% Cell type:markdown id:64fd0945 tags:
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using ascending order.
%% Cell type:code id:efcdf514 tags:
``` python
# VERSION 1
# Be very careful: if you use sorted, make sure your return value
# variable matches with the variable for that project question
sorted_computer_and_science_majors = sorted(computer_and_science_majors)
sorted_computer_and_science_majors
```
%% Cell type:code id:c28e77ce tags:
``` python
# VERSION 2
computer_and_science_majors.sort()
computer_and_science_majors
```
%% Cell type:markdown id:e354b781 tags:
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using descending order.
%% Cell type:code id:ca887135 tags:
``` python
# VERSION 1
# Be very careful: if you use sorted, make sure your return value
# variable matches with the variable for that project question
reverse_sorted_computer_and_science_majors = sorted(computer_and_science_majors, reverse = ???)
reverse_sorted_computer_and_science_majors
```
%% Cell type:code id:b6c61532 tags:
``` python
# VERSION 2
computer_and_science_majors.sort(reverse = ???)
computer_and_science_majors
```
%% Cell type:markdown id:31a381fe tags:
## Self-practice
%% Cell type:markdown id:8ac26620 tags:
### How many students are both a procrastinator and a pet owner?
%% Cell type:markdown id:172141ea tags:
### What percentage of 18-year-olds have their major declared as "Other"?
%% Cell type:markdown id:d9a7a2b1 tags:
### How old is the oldest basil/spinach-loving Business major?
......
s23/Gurmail_lecture_notes/16_List_Practice/lec_16_list_practice_template_Gurmail_lec2.ipynb
+ 22
− 2
View file @ 27622921
%% Cell type:markdown id:6850fba1 tags:
# Announcements - List Practice
* Download ALL files from Canvas for today's lecture
* Worksheet is online only - great practice for the exam!
* Exam I
* We estimate results will be available this afternoon
* This will tie last semesters turn around time
* [Exam 2 Conflict Form](https://docs.google.com/forms/d/e/1FAIpQLSegJSzTsDHEnygijU3-HQvZDUbTCkHFPKccDkqMt1dGzC67_w/viewform)
* [Regrade Request](https://piazza.com/class/ld8bqui1lgeas/post/105)
* [P6 FAQ](https://piazza.com/class/ld8bqui1lgeas/post/294)
* Quiz 4 due Today at 11:59:00 pm
* We release the answers after the quiz closes so we do not reopen quizzes for students even if something goes wrong.
* We do drop 2 quiz scores (in case something goes wrong)
%% Cell type:markdown id:72348536 tags:
# List Practice
%% Cell type:code id:d21a94b5 tags:
``` python
import csv
```
%% Cell type:markdown id:cd8a434c tags:
### Warmup 1: min / max
%% Cell type:code id:baa730ba tags:
``` python
some_list = [45, -4, 66, 220, 10]
min_val = None
for val in some_list:
if min_val == None or val < min_val:
min_val = val
print(min_val)
max_val = None
for val in some_list:
if max_val == None or val > max_val:
max_val = val
print(max_val)
```
%% Cell type:markdown id:3502c700 tags:
### Warmup 2: median
%% Cell type:code id:414ae09e tags:
``` python
def median(some_items):
"""
Returns median of a list passed as argument
"""
pass
nums = [5, 4, 3, 2, 1]
print("Median of", nums, "is" , median(nums))
nums = [6, 5, 4, 3, 2, 1]
print("Median of", nums, "is" , median(nums))
```
%% Cell type:code id:73fa337e tags:
``` python
vals = ["A", "C", "B"]
print("Median of", nums, "is" , median(vals))
vals = ["A", "C", "B", "D"]
# print("Median of", nums, "is" , median(vals)) # does not work due to TypeError
```
%% Cell type:markdown id:050fd57c tags:
### set data structure
- **not a sequence**
- no ordering of values:
- this implies that you can only store unique values within a `set`
- very helpful to find unique values stored in a `list`
- easy to convert a `list` to `set` and vice-versa.
- ordering is not guaranteed once we use `set`
%% Cell type:code id:7d4a693f tags:
``` python
some_set = {10, 20, 30, 30, 40, 50, 10} # use a pair of curly braces to define it
some_set
```
%% Cell type:code id:baef596c tags:
``` python
some_list = [10, 20, 30, 30, 40, 50, 10] # Initialize a list containing duplicate numbers
# TODO: to find unique values, convert it into a set
print(set(some_list))
# TODO: convert the set back into a list
print(list(set(some_list)))
```
%% Cell type:markdown id:2be52d13 tags:
Can you index / slice into a `set`?
%% Cell type:code id:f622a5eb tags:
``` python
some_set[1] # doesn't work - remember set has no order
```
%% Cell type:code id:e679d3a7 tags:
``` python
some_set[1:] # doesn't work - remember set has no order
```
%% Cell type:code id:9d936c1c tags:
``` python
# inspired by https://automatetheboringstuff.com/2e/chapter16/
def process_csv(filename):
# open the file, its a text file utf-8
example_file = open(filename, encoding="utf-8")
# prepare it for reading as a CSV object
example_reader = csv.reader(example_file)
# use the built-in list function to convert this into a list of lists
example_data = list(example_reader)
# close the file to tidy up our workspace
example_file.close()
# return the list of lists
return example_data
```
%% Cell type:markdown id:89621c98 tags:
### Student Information Survey data
%% Cell type:code id:d3c252b4 tags:
``` python
# TODO: call the process_csv function and store the list of lists in cs220_csv
cs220_csv = process_csv(???)
```
%% Cell type:code id:5838ae5f tags:
``` python
# Store the header row into cs220_header, using indexing
cs220_header = ???
cs220_header
```
%% Cell type:code id:66fda88d tags:
``` python
# TODO: Store all of the data rows into cs220_data, using slicing
cs220_data = ???
# TODO: use slicing to display top 3 rows data
cs220_data???
```
%% Cell type:markdown id:4267fe3e tags:
### What `Pizza topping` does the 13th student prefer?
%% Cell type:code id:4b8dbe8b tags:
``` python
# bad example: we hard-coded the column index
```
%% Cell type:markdown id:4f125240 tags:
What if we decided to add a new column before sleeping habit? Your code will no longer work.
Instead of hard-coding column index, you should use `index` method, to lookup column index from the header variable. This will also make your code so much readable.
%% Cell type:code id:f2e52e06 tags:
``` python
```
%% Cell type:markdown id:5d298a4c tags:
### What is the Lecture of the 4th student?
%% Cell type:code id:3617b3de tags:
``` python
```
%% Cell type:markdown id:059de363 tags:
### What **unique** `age` values are included in the dataset?
%% Cell type:code id:45909f22 tags:
``` python
```
%% Cell type:markdown id:8e18663d tags:
### cell function
- It would be very helpful to define a cell function, which can handle missing data and type conversions
%% Cell type:code id:bba90038 tags:
``` python
def cell(row_idx, col_name):
"""
Returns the data value (cell) corresponding to the row index and
the column name of a CSV file.
"""
# TODO: get the index of col_name
# TODO: get the value of cs220_data at the specified cell
# TODO: handle missing values, by returning None
# TODO: handle type conversions
return val
```
%% Cell type:markdown id:e2278e4c tags:
### Find average age per lecture.
%% Cell type:code id:09e90e94 tags:
``` python
# TODO: initialize 4 lists for the 4 lectures
# Iterate over the data and populate the lists
# TODO: compute average age of each lecture
print("LEC001 average student age:", round(sum(lec1_ages) / len(lec1_ages), 2))
print("LEC002 average student age:", round(sum(lec2_ages) / len(lec2_ages), 2))
print("LEC003 average student age:", round(sum(lec3_ages) / len(lec3_ages), 2))
print("LEC004 average student age:", round(sum(lec4_ages) / len(lec4_ages), 2))
```
%% Cell type:markdown id:b7c8e726 tags:
### Function `avg_age_per_lecture(lecture)`
%% Cell type:code id:fa5598e0 tags:
``` python
def avg_age_per_lecture(lecture):
'''
avg_age_per_lecture(lecture) returns the average age of
the students in the given `lecture`; if there are no
students in the given `lecture`, it returns `None`
'''
# To compute average you don't need to actually populate a list.
# But here a list will come in handy. It will help you with the None return requirement.
pass
```
%% Cell type:code id:f0a05e42 tags:
``` python
avg_age_per_lecture("LEC003")
```
%% Cell type:code id:9f2c7e6e tags:
``` python
print(avg_age_per_lecture("LEC007"))
```
%% Cell type:markdown id:c07f9cfc tags:
### Find all unique zip codes.
%% Cell type:code id:a6df8ef5 tags:
``` python
# TODO: initialize list of keep track of zip codes
zip_codes = []
for row_idx in range(len(cs220_data)):
zip_code = cell(row_idx, "Zip Code")
if zip_code != None:
zip_codes.append(zip_code)
zip_codes # How do we get the unique values?
```
%% Cell type:markdown id:94548bf4 tags:
### `sort` method versus `sorted` function
- `sort` (and other list methods) have an impact on the original list
- `sorted` function returns a new list with expected ordering
- default sorting order is ascending / alphanumeric
- `reverse` parameter is applicable for both `sort` method and `sorted` function:
- enables you to specify descending order by passing argument as `True`
%% Cell type:code id:c1e555f9 tags:
``` python
some_list = [10, 4, 25, 2, -10]
```
%% Cell type:code id:152297bb tags:
``` python
# TODO: Invoke sort method
rv = ???
print(some_list)
# What does the sort method return?
# TODO: Capture return value into a variable rv and print the return value.
print(rv)
```
%% Cell type:markdown id:3c0d5e7d tags:
`sort` method returns `None` because it sorts the values in the original list
%% Cell type:code id:c06d8976 tags:
``` python
# TODO: invoke sorted function and pass some_list as argument
# TODO: capture return value into sorted_some_list
???
# What does the sorted function return?
# It returns a brand new list with the values in sorted order
print(sorted_some_list)
```
%% Cell type:markdown id:ded0304c tags:
TODO: go back to `sort` method call and `sorted` function call and pass keyword argument `reverse = True`.
%% Cell type:markdown id:35894ef5 tags:
Can you call `sort` method on a set?
%% Cell type:code id:fc08879e tags:
``` python
some_set.sort()
# doesn't work: no method named sort associated with type set
# you cannot sort a set because of the lack of ordering
```
%% Cell type:markdown id:99161c42 tags:
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
%% Cell type:code id:2549df29 tags:
``` python
# works because Python converts the set into a list and then sorts the list
sorted(some_set)
```
%% Cell type:markdown id:5c7f3489 tags:
### Function: `find_majors(phrase)`
%% Cell type:code id:b6adbfe0 tags:
``` python
def find_majors(phrase):
"""
find_majors(phrase) returns a list of all the room names that contain the
substring (case insensitive match) `phrase`.
"""
# TODO: initialize the target list here
# TODO: iterate over row indices
for row_idx in range(len(cs220_data)):
major = cell(row_idx, "Major")
# TODO: write the actual logic here
return majors
```
%% Cell type:markdown id:1b7f671f tags:
### Find all `major` that contain **either** `"Computer"` **or** `"Science"`.
Your output **must** be a *list*. The order **does not** matter, but if a `major` contains **both** `"Computer"` and `"Science"`, then the room must be included **only once** in your list.
%% Cell type:code id:ed895a3b tags:
``` python
computer_majors = ???
science_majors = ???
computer_and_science_majors = ???
# TODO: Now find just the unique values
computer_and_science_majors = ???
computer_and_science_majors
```
%% Cell type:markdown id:64fd0945 tags:
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using ascending order.
%% Cell type:code id:efcdf514 tags:
``` python
# VERSION 1
# Be very careful: if you use sorted, make sure your return value
# variable matches with the variable for that project question
sorted_computer_and_science_majors = sorted(computer_and_science_majors)
sorted_computer_and_science_majors
```
%% Cell type:code id:c28e77ce tags:
``` python
# VERSION 2
computer_and_science_majors.sort()
computer_and_science_majors
```
%% Cell type:markdown id:e354b781 tags:
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using descending order.
%% Cell type:code id:ca887135 tags:
``` python
# VERSION 1
# Be very careful: if you use sorted, make sure your return value
# variable matches with the variable for that project question
reverse_sorted_computer_and_science_majors = sorted(computer_and_science_majors, reverse = ???)
reverse_sorted_computer_and_science_majors
```
%% Cell type:code id:b6c61532 tags:
``` python
# VERSION 2
computer_and_science_majors.sort(reverse = ???)
computer_and_science_majors
```
%% Cell type:markdown id:31a381fe tags:
## Self-practice
%% Cell type:markdown id:8ac26620 tags:
### How many students are both a procrastinator and a pet owner?
%% Cell type:markdown id:172141ea tags:
### What percentage of 18-year-olds have their major declared as "Other"?
%% Cell type:markdown id:d9a7a2b1 tags:
### How old is the oldest basil/spinach-loving Business major?
......
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