Statistics and Linear Algebra 1

Posted 2020-08-21 阿难的机器学习计划

1. Add a value to each element in a list:

　　degrees_zero = [f + 459.67 for f in fahrenheit_degrees]

2. Assign the index of a list into the list:

　　survey_responses = ["none", "some", "a lot", "none", "a few", "none", "none"]

　　survey_scale = ["none", "a few", "some", "a lot"]

　　survey_numbers = [survey_scale.index(response) for response in survey_responses]

　　average_smoking = sum(smoke_dic)/len(smoke_dic)

3. Categorize scales: here we need to filter gender list into categorizes and find the corresponse saving.　　

　　gender = ["male", "female", "female", "male", "male", "female"]
　　savings = [1200, 5000, 3400, 2400, 2800, 4100]

//////////////////////////////////Solutions one////////////////////////////////////////

　　male_saving_list = []

　　for i in range(len(gender)):
　　　　if gender[i] == "male":
　　　　　　male_saving_list.append(savings[i])
　　　　　　male_savings = sum(male_savings_list)/ len(male_savings_list)

//////////////////////////////////Solutions two////////////////////////////////////////

　　female_saving_list = [savings[i] for i in range(len(gender)) if gender[i] == "female"] # Here we use square bracket to replace append function. savings[i] is the value we want, if conditions have to follow the for loop like solution one.
　　female_savings = sum(female_saving_list)/len(female_saving_list)

4.