Table of Contents

1. Challenge

   Sensor Data Files: Load Raw Data

   Data is being generated all the time by the IoT devices around us. Python is a great tool to analyze this data. In this lab, you will learn some of the Python data types and modules to read, interpret, and convert data from one form to another. Users will also learn how to work with date timestamps.

   In this first module, you will write a function to load the sensor data stored in the data files. The sensor data is stored in different numeric forms and the records are formatted in CSV format. ### Solution The solution can be found in the solution directory.

2. Challenge

   Home Data Class

   In this module, you will create a HouseInfo class that will help us process the sensor data records. This class will later serve as base class for other classes.

3. Challenge

   Analyze Temperature Data

   In this module, you will create a TemperatureData class that will process the temperature data field. This field information needs to be converted to an integer with base 10.

4. Challenge

   Analyze Humidity & Air Quality Data

   Now that most of the heavy lifting has been done, in this module, you will create HumidityData and ParticleData classes that will process the humidity and particle count data fields. We will reuse a lot of the code written so far. The humidity field needs to be converted from percentage to a float number, and the particle field needs to be converted from scientific notation also to a float number.

5. Challenge

   Analyze Energy Consumption Data

   The final data field we analyze is the energy usage. In this module, you will create an EneryData class that will process the energy consumption. Again, we will reuse a lot of the code written so far. The energy field comes as a hexadecimal number, so we will first convert the field to an integer to be able to apply bitwise operation to isolate the relevant bits.