Do not use CHATGPT, I can also do this.

You are given a dataset containing measurements of temperature, humidity, and air pressure recorded hourly over a period of one month. The dataset is stored in a CSV file named weather$\_$data.csv with the following columns:

Time: The timestamp of the measurement in the format YYYY$-$MM$-$DD HH:MM:SS$.$

Temperature: The temperature in degrees Celsius.

Humidity: The humidity percentage.

Pressure: The air pressure in hPa.

Your task is to perform the following steps using MATLAB:

Load the Data: Read the dataset from the CSV file into MATLAB.

Data Cleaning:

Check for any missing values in the dataset and replace them with the mean of their respective columns.

Convert the Time column to MATLAB's datetime format.

Data Analysis:

Calculate the daily average temperature, humidity, and pressure.

Identify the day with the highest average temperature and the day with the lowest average temperature.

Calculate the standard deviation of temperature, humidity, and pressure for each day.

Visualization:

Plot the daily average temperature, humidity, and pressure on the same graph with different colors and appropriate labels.

Plot a histogram of the temperature data.

Advanced Analysis:

Perform a linear regression analysis to determine if there is any significant relationship between temperature and humidity. Provide the equation of the regression line and the R$-$squared value.

Generate a scatter plot of temperature vs$.$ humidity and overlay the regression line.

Provide the MATLAB code for each step and summarize your findings in a report.