Task 1
Objective:
The objective of the task is to write a function to clean data in Python.
Requirements:
- Convert 'value'to a float. Handle non-numeric values gracefully (e.g., replace withNaNor0).
- Replace missing 'category'values with'Unknown'.
- Return a list of cleaned dictionaries.
Examples:
Example Input:
data = [
    {'id': 1, 'value': '10', 'category': 'A'},
    {'id': 2, 'value': '20.5', 'category': 'B'},
    {'id': 3, 'value': 'abc', 'category': 'A'},
    {'id': 4, 'value': '30', 'category': None},
]
Task 2
Objective:
The objective of the task is to write a function to manipulate a string in Python.
Requirements:
Write a function that takes a string as input and returns the number of times a specific substring appears within the string, ignoring case. The function should be efficient for large strings.
Examples:
- input = "This is a test string. This is another test."- substring = "test"
 The function should return 2.
- input = "apple APPLE Apple"- substring = "apple"
 The function should return 3.

Task 3
Objective:
The objective of the task is to write a function to clean data in Python.
Requirements:
You are given a dictionary representing data from a sensor. Some sensor readings might be missing (represented by None).
Write a function that calculates the average of the sensor readings (integer or float), handling missing data gracefully.
The function should return the average as a float. If no valid readings exist, return 0.0.
Some data might be in a string format, which should be interpreted as a numerical value if possible. Any other data types apart from int, float and string should be discarded.
Notes:
- The function should be able to handle any key label values - the key labels can have any value.
- Round your values to a single decimal place.
Examples:
sensor_data = {'reading1': 10, 'rdg2': None, 'reading3': 15, 'reading4': 20}
# Function should return 15.0
sensor_data = {'reading1': None, 'reading2': '2', 'reading3': None}
# Function should return 2.0

Task 4
Objective:
Write a function that parses a JSON string.
The function should handle one of the three errors below:
- Invalid JSON: The input string is not valid JSON.
- Missing keys: The JSON object is missing expected keys. Case sensitive.
- Incorrect data types: The values associated with keys have unexpected data types.
Schema:
The JSON should have the keys:
- "food"(string)
- "category"(string value of either- "Asian"or- "Western")
- "price"(integer)
Return:
The function should return a dictionary containing the parsed data if successful, or a string error message specifying exactly (case insensitive) one of the 3 categories of errors above.
Possible error strings:
- "Invalid JSON"
- "Missing keys"
- "Incorrect data types"
Note:
Each test will only have one error, so don’t worry about ordering which error should take precedence.

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