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Lecture 16 notebooks

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%% Cell type:markdown id:72348536 tags:
# List Practice
%% Cell type:code id:ba562f5e tags:
``` python
import csv
```
%% 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
['Lecture',
'Age',
'Primary major',
'Other majors',
'Zip Code',
'Pizza topping',
'Pet owner',
'Runner',
'Sleep habit',
'Procrastinator']
%% 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
[['LEC002',
'19',
'Engineering: Mechanical',
'',
'53711',
'pepperoni',
'Yes',
'No',
'night owl',
'Maybe'],
['LEC002',
'20',
'Science: Physics',
'Astronomy-Physics, History',
'53726',
'pineapple',
'Yes',
'Yes',
'night owl',
'Yes'],
['LEC001',
'20',
'Science: Chemistry',
'',
'53703',
'pepperoni',
'Yes',
'No',
'early bird',
'No']]
%% Cell type:markdown id:4267fe3e tags:
### What is the Sleep habit for the 2nd student?
%% Cell type:code id:4b8dbe8b tags:
``` python
cs220_data[1][8] # bad example: we hard-coded the column index
```
%% Output
'night owl'
%% 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[1][cs220_header.index("Sleep habit")]
```
%% Output
'night owl'
%% 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
'LEC004'
%% Cell type:markdown id:059de363 tags:
### Create a list containing Age of all students 10 years from now
%% Cell type:code id:45909f22 tags:
``` python
ages_in_ten_years = []
for row in cs220_data:
age = row[cs220_header.index("Age")]
if age == '':
continue
age = int(age)
ages_in_ten_years.append(age + 10)
ages_in_ten_years[:3]
```
%% Output
[29, 30, 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)
return val
```
%% Cell type:markdown id:b7c8e726 tags:
### Find average age per lecture.
%% Cell type:code id:f0a05e42 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:
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: 19.93
LEC002 average student age: 19.8
LEC003 average student age: 19.38
LEC004 average student age: 19.27
%% 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] # TODO: Initialize some_list with a list of un-ordered integers
```
%% 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:99803f1e 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:928abc2e 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:2aa9bc02 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:2a561420 tags:
Can you call `sort` method on a set?
%% Cell type:code id:0d616535 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:0349560e tags:
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
%% Cell type:code id:1db6f699 tags:
``` python
sorted(some_set) # works because Python converts the set into a list and then sorts the list
```
%% Output
[10, 20, 30, 40, 50]
%% Cell type:markdown id:7389953d tags:
Can you index / slice into a `set`?
%% Cell type:code id:8b819251 tags:
``` python
# some_set[1] # doesn't work - remember set has no order
```
%% Cell type:code id:d0a48520 tags:
``` python
# some_set[1:] # doesn't work - remember set has no order
```
%% Cell type:markdown id:64fd0945 tags:
### Find all unique zip codes. Arrange them based on ascending order.
%% Cell type:code id:c28e77ce 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 = list(set(zip_codes))
zip_codes.sort()
zip_codes
```
%% Output
['10306',
'19002',
'43706',
'5 3706',
'52706',
'52816',
'53076',
'53089',
'53175',
'53562',
'53575',
'53590',
'53597',
'53701',
'53703',
'53703-1104',
'53704',
'53705',
'53706',
'53706-1127',
'53706-1188',
'53706-1203',
'53706-1406',
'53708',
'53711',
'53713',
'53715',
'53717',
'53719',
'53726',
'54636',
'55416',
'57305',
'59301',
'83001',
'92376',
'internation student']
%% Cell type:markdown id:e354b781 tags:
### Arrange unique zip codes based on descending order.
%% Cell type:code id:ca887135 tags:
``` python
sorted(zip_codes, reverse = True)
```
%% Output
['internation student',
'92376',
'83001',
'59301',
'57305',
'55416',
'54636',
'53726',
'53719',
'53717',
'53715',
'53713',
'53711',
'53708',
'53706-1406',
'53706-1203',
'53706-1188',
'53706-1127',
'53706',
'53705',
'53704',
'53703-1104',
'53703',
'53701',
'53597',
'53590',
'53575',
'53562',
'53175',
'53089',
'53076',
'52816',
'52706',
'5 3706',
'43706',
'19002',
'10306']
%% 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?
%% Cell type:code id:5fcc04f2 tags:
``` python
```
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%% Cell type:markdown id:72348536 tags:
# List Practice
%% Cell type:code id:ba562f5e tags:
``` python
import csv
```
%% 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
```
%% 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 is the Sleep habit for the 2nd student?
%% 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:
### Create a list containing Age of all students 10 years from now
%% 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
```
%% Cell type:markdown id:b7c8e726 tags:
### Find average age per lecture.
%% Cell type:code id:f0a05e42 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:6aeaec34 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:69335f13 tags:
``` python
some_list = # TODO: Initialize some_list with a list of un-ordered integers
```
%% Cell type:code id:62b2f81a tags:
``` python
# TODO: Invoke sort method
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:b5738543 tags:
`sort` method returns `None` because it sorts the values in the original list
%% Cell type:code id:bb93809e 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)
```
%% Cell type:markdown id:0b7fceb6 tags:
TODO: go back to `sort` method call and `sorted` function call and pass keyword argument `reverse = True`.
%% Cell type:markdown id:5c33901b 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:96914953 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:5249e026 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(some_list)
# TODO: convert the set back into a list
print(some_list)
```
%% Cell type:markdown id:245d1dff tags:
Can you call `sort` method on a set?
%% Cell type:code id:321105b7 tags:
``` python
```
%% Cell type:markdown id:5abca57e tags:
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
%% Cell type:code id:14a1a216 tags:
``` python
```
%% Cell type:markdown id:c656510b tags:
Can you index / slice into a `set`?
%% Cell type:code id:a64ec5bd tags:
``` python
```
%% Cell type:code id:4d61e84d tags:
``` python
```
%% Cell type:markdown id:64fd0945 tags:
### Find all unique zip codes. Arrange them based on ascending order.
%% Cell type:code id:c28e77ce 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:d4edf965 tags:
### Arrange unique zip codes based on descending order.
%% Cell type:code id:83926b35 tags:
``` python
```
%% 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?
%% Cell type:code id:5fcc04f2 tags:
``` python
```
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%% Cell type:markdown id:72348536 tags:
# List Practice
%% Cell type:code id:ba562f5e tags:
%% 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[???]
cs220_data???
```
%% Cell type:markdown id:4267fe3e tags:
### What is the Sleep habit for the 2nd student?
### 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:
### Create a list containing Age of all students 10 years from now
### 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:b7c8e726 tags:
### Find average age per lecture.
### Function `avg_age_per_lecture(lecture)`
%% Cell type:code id:f0a05e42 tags:
%% Cell type:code id:fa5598e0 tags:
``` python
# TODO: initialize 4 lists for the 4 lectures
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:
# Iterate over the data and populate the lists
``` python
avg_age_per_lecture("LEC002")
```
%% Cell type:code id:9f2c7e6e tags:
# 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))
``` python
print(avg_age_per_lecture("LEC007"))
```
%% Cell type:markdown id:6aeaec34 tags:
%% 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:69335f13 tags:
%% Cell type:code id:c1e555f9 tags:
``` python
some_list = # TODO: Initialize some_list with a list of un-ordered integers
some_list = [10, 4, 25, 2, -10]
```
%% Cell type:code id:62b2f81a tags:
%% 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:b5738543 tags:
%% Cell type:markdown id:3c0d5e7d tags:
`sort` method returns `None` because it sorts the values in the original list
%% Cell type:code id:bb93809e tags:
%% 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
# 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:0b7fceb6 tags:
%% 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:5c33901b tags:
### set data structure
%% Cell type:markdown id:35894ef5 tags:
- **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`
Can you call `sort` method on a set?
%% Cell type:code id:96914953 tags:
%% Cell type:code id:fc08879e tags:
``` python
some_set = {10, 20, 30, 30, 40, 50, 10} # use a pair of curly braces to define it
some_set
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:code id:5249e026 tags:
%% Cell type:markdown id:99161c42 tags:
``` python
some_list = [10, 20, 30, 30, 40, 50, 10] # Initialize a list containing duplicate numbers
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
# TODO: to find unique values, convert it into a set
print(some_list)
%% Cell type:code id:2549df29 tags:
# TODO: convert the set back into a list
print(some_list)
``` python
# works because Python converts the set into a list and then sorts the list
sorted(some_set)
```
%% Cell type:markdown id:245d1dff tags:
%% Cell type:markdown id:5c7f3489 tags:
Can you call `sort` method on a set?
### Function: `find_majors(phrase)`
%% Cell type:code id:321105b7 tags:
%% 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:5abca57e tags:
%% Cell type:markdown id:1b7f671f tags:
Can you pass a `set` as argument to `sorted` function? Python is intelligent :)
### Find all `major` that contain **either** `"Computer"` **or** `"Science"`.
%% Cell type:code id:14a1a216 tags:
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:c656510b tags:
%% Cell type:markdown id:64fd0945 tags:
Can you index / slice into a `set`?
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using ascending order.
%% Cell type:code id:a64ec5bd tags:
%% 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:4d61e84d tags:
%% Cell type:code id:c28e77ce tags:
``` python
# VERSION 2
computer_and_science_majors.sort()
computer_and_science_majors
```
%% Cell type:markdown id:64fd0945 tags:
%% Cell type:markdown id:e354b781 tags:
### Find all unique zip codes. Arrange them based on ascending order.
### Order the `major` that contain **either** `"Computer"` **or** `"Science"` using descending order.
%% Cell type:code id:c28e77ce tags:
%% Cell type:code id:ca887135 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")
# 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
```
if zip_code != None:
zip_codes.append(zip_code)
%% Cell type:code id:b6c61532 tags:
zip_codes # How do we get the unique values?
``` python
# VERSION 2
computer_and_science_majors.sort(reverse = ???)
computer_and_science_majors
```
%% Cell type:markdown id:d4edf965 tags:
%% Cell type:markdown id:2862160c tags:
### Arrange unique zip codes based on descending order.
### For `major` containing `"other"`, extract the details that come after `"|"`.
%% Cell type:code id:83926b35 tags:
%% Cell type:code id:600fae6c tags:
``` python
other_majors = find_majors("other")
other_major_details = []
for other in other_majors:
print(other)
# TODO: complete the rest of the logic
other_major_details
```
%% 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?
%% Cell type:code id:5fcc04f2 tags:
``` python
```
......
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