Question
Task :: Data Exploration Given the dataset and the starting code answer the questions stated on this task. Questions + Analysis 2. Data Cleaning Write
Task :: Data Exploration
- Given the dataset and the starting code answer the questions stated on this task.
Questions + Analysis
2. Data Cleaning
Write cleaning function such that:
- Preserves the name of the candy as a string
- Turns all strings of 1s and 0s to a True or False
- Turns all string percentiles into float
3. How many candies are multi-featured?
Multi-featured A candy that is more than 1 type of candy (eg. Chocolate + Caramel)
4. Clustering
Cluster/group the candies by their type.
- Which group has the highest win percentile?
- Which group has the lowest win percentile?
- Does the sugar percentile of the group matter?
- Does the price percentile matter?
- Should candies be clustered/grouped based on multi-feature or on their single features?
- Should candy be allowed to exist in multiple groups since some are multi-featured?
main.py
#########################################################
# Do Not Edit the Python Code Underneath #
# These lines of codes are written for the assignment #
#########################################################
dataset = None # Global Dataset variable initialization
with open('candy.csv', 'r') as datafile:
# Reading the Dataset File --> candy.csv; must be in the same directory
dataset = datafile.readlines()
# New Line removing function + map operation
removeNewLine = lambda x : x.replace(' ', '')
dataset = list(map(removeNewLine, dataset))
# Split strings to list by commas functions + map operation
commaSplit = lambda x : x.split(',')
dataset = list(map(commaSplit, dataset))
# end of file read
print('Our Candy Dataset ', dataset) # Uncomment this line to see your dataset
# You may start your code underneath this line.
# the dataset variable is accessible. You may choose to use it, or you can
# copy it via dataset.copy()
data link: https://docs.google.com/spreadsheets/d/14t9c8uqW0kFjrBjWGuQwom-IR76WbfKXT50qRtl46Kk/edit#gid=0
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