Question

You are working on an engineering project where you need to analyze a set of temperature readings in real-time. The temperature readings are provided as a NumPy array temp_data of shape (m,n), where m is the number of sensors and n is the number of readings. You need to perform the following tasks on the temperature data using NumPy: Convert the temperature data from Celsius to Fahrenheit. Identify the sensor that has the highest temperature across all readings. Compute the average of the temperature readings. Write a NumPy code snippet to perform the above tasks on the temp_data array

Answer 1

To analyze the temperature data in a NumPy array, convert from Celsius to Fahrenheit, identify the sensor with the highest temperature, and compute the average temperature using the respective NumPy methods and functions.

Step-by-step explanation:

To analyze the temperature data from an array temp_data using NumPy, perform the following tasks:Convert the temperature data from Celsius to Fahrenheit by applying the formula (9/5) * temp_data + 32.Identify the sensor with the highest temperature by using numpy.argmax on the maximum values across all readings.Compute the average temperature by using numpy.mean on the temp_data array.To convert the temperature data from Celsius to Fahrenheit, you can use the formula F = C * 9/5 + 32, where F is the temperature in Fahrenheit and C is the temperature in Celsius. You can apply this formula to each element of the NumPy array using array broadcasting. Here is an example code snippet:

temp_data_fahrenheit = temp_data * 9/5 + 32To identify the sensor that has the highest temperature across all readings, you can use the argmax() function along the appropriate axis. Here is an example:highest_sensor = np.argmax(temp_data, axis=0)To compute the average of the temperature readings, you can use the mean() function along the appropriate axis. Here is an example:average_temperature = np.mean(temp_data, axis=1)