Using the $2019-2022$ Queensland Household Travel Survey $($HTS$)$ data provided in this course, perform the following tasks with Python to analyse the mode split by gender in the Sunshine Coast region. Refer to Week $6$ Tutorial and ICT slides for guidance.

Specifically, we are interested in calculating the number of trips by gender and transport mode based on the HTS data.

Load the five main HTS survey data files into seperate Pandas DataFrames.

Convert all column names and string data to lowercase to ensure ease of access and consistency.

Merge the 'trip' DataFrame with the 'household' DataFrame to associate each trip with its household's Local Government Area $($LGA$).$

Merge the resulting DataFrame with the 'person' DataFrame to link each trip with the trip maker's gender $($sex$)$ information.

Filter this merged DataFrame to identify the number of bicycle trips made by males in the Sunshine Coast region.

Print this value.

What is the number of bicycle trips made by males in the Sunshine Coast region?