Problem Statement:

Have you ever wondered when the best time of year to book a hotel room is? Or the optimal length of stay in order to get the best daily rate? What if you wanted to predict whether or not a hotel was likely to receive a disproportionately high number of special requests? This hotel booking dataset can help you explore those questions! This data set contains booking information for a city hotel and a resort hotel, and includes information such as when the booking was made, length of stay, the number of adults, children, and/or babies, and the number of available parking spaces, among other things.

To Achieve insight over the data we will divide the operations into below parts:

1. Data Analysis- Investigating the dataset, structure of data,pattern of data and finding any discripancies presents in data.

2. Duplicate data reduction: Finding and removing duplicate data.

3. Null Value Processing: Cleaning up unwanted null values, rows and columns.

4. Outlier Treatment: Finding and removing outliers (anamoly treatment).

5. Structure Correction: Converting data to relevant data type.

6. Insights: Get a deep visualization on cleaned data for better analysis.