Question

#Write a function called clean_data. clean_data takes one
#parameter, a dictionary. The dictionary represents the
#observed rainfall in inches on a particular calendar day
#at a particular location. However, the data has some
#errors.
#
#clean_data should delete any key-value pair where the value
#has any of the following issues:
#
# - the type is not an integer or a float. Even if the value
# is a string that could be converted to an integer (e.g.
# "5") it should be deleted.
# - the value is less than 0: it's impossible to have a
# negative rainfall number, so this must be bad data.
# - the value is greater than 100: the world record for
# rainfall in a day was 71.8 inches
#
#Return the dictionary when you're done making your changes.
#
#Remember, the keyword del deletes items from lists
#and dictionaries. For example, to remove the key "key!" from
#the dictionary my_dict, you would write: del my_dict["key!"]
#Or, if the key was the variable my_key, you would write:
#del my_dict[my_key]
#
#Hint: If you try to delete items from the dictionary while
#looping through the dictionary, you'll run into problems!
#We should never change the number if items in a list or
#dictionary while looping through those items. Think about
#what you could do to keep track of which keys should be
#deleted so you can delete them after the loop is done.
#
#Hint 2: To check if a variable is an integer, use
#type(the_variable) == int. To check if a variable is a float,
#use type(the_variable) == float.

#Write your function here!

#Below are some lines of code that will test your function.
#You can change the value of the variable(s) to test your
#function with different inputs.
#
#If your function works correctly, this will originally
#print (although the order of the keys may vary):
#{"20190101": 5, "20190103": 7.5, "20190104": 0, "20190107": 1}
rainfall = {"20190101": 5, "20190102": "6", "20190103": 7.5,
"20190104": 0, "20190105": -7, "20190106": 102,
"20190107": 1}
print(clean_data(rainfall))

Answer 1

# Write a function called clean_data. clean_data takes one
# parameter, a dictionary. The dictionary represents the
# observed rainfall in inches on a particular calendar day
# at a particular location. However, the data has some
# errors.
#
# clean_data should delete any key-value pair where the value
# has any of the following issues:
#
# - the type is not an integer or a float. Even if the value
# is a string that could be converted to an integer (e.g.
# "5") it should be deleted.
# - the value is less than 0: it's impossible to have a
# negative rainfall number, so this must be bad data.
# - the value is greater than 100: the world record for
# rainfall in a day was 71.8 inches
#
# Return the dictionary when you're done making your changes.
#
# Remember, the keyword del deletes items from lists
# and dictionaries. For example, to remove the key "key!" from
# the dictionary my_dict, you would write: del my_dict["key!"]
# Or, if the key was the variable my_key, you would write:
# del my_dict[my_key]
#
# Hint: If you try to delete items from the dictionary while
# looping through the dictionary, you'll run into problems!
# We should never change the number if items in a list or
# dictionary while looping through those items. Think about
# what you could do to keep track of which keys should be
# deleted so you can delete them after the loop is done.
#
# Hint 2: To check if a variable is an integer, use
# type(the_variable) == int. To check if a variable is a float,
# use type(the_variable) == float.


def clean_data(rain):
    keys = list(rain.keys())
    for key in keys:
        if (type(rain[key]) != int and type(rain[key]) != float) or rain[key] < 0 or rain[key] > 100:
            del rain[key]
    return rain


# Below are some lines of code that will test your function.
# You can change the value of the variable(s) to test your
# function with different inputs.
#
# If your function works correctly, this will originally
# print (although the order of the keys may vary):
# {"20190101": 5, "20190103": 7.5, "20190104": 0, "20190107": 1}
rainfall = {"20190101": 5, "20190102": "6", "20190103": 7.5,
            "20190104": 0, "20190105": -7, "20190106": 102,
            "20190107": 1}
print(clean_data(rainfall))