How do I preprocess sensor data for analysis?

How do I preprocess sensor data for analysis?

Preprocessing sensor data involves cleaning, normalizing, and transforming the data to make it suitable for analysis. What specific type of sensor data are you working with?

I'm working with temperature and humidity data from IoT sensors.

Great! You should start by handling missing values, then normalize the data to a common scale, and finally, you might want to apply techniques like smoothing or filtering to reduce noise.

What methods can I use to handle missing values?

Common methods include imputation (filling in missing values with the mean, median, or mode), interpolation, or simply removing the records with missing data. The choice depends on your dataset and analysis goals.

How can I normalize the data?

You can normalize data using techniques like Min-Max scaling or Z-score normalization. Min-Max scales the data to a range of [0, 1], while Z-score standardization centers the data around the mean with a standard deviation of 1.