Hotels Analysis

Input:

Json file about hotels in India with which has 9 fields and 305 rows.Rows are subjecct to change and the code must scale to size of data. The fields are as below:

• HOTEL NAME
• ADDRESS
• STATE
• PHONE
• FAX
• EMAIL ID
• WEBSITE
• TYPE
• Rooms

Functionality:

The solution would process the json file and form a pandas dataframe by extracting the data. From the dataframe, hotels with maximum of rooms under each type would be computed. Below are possible approaches:

• Naive approach is to fit entire data into the memory and do the computation.
• Increase the number of machines and process the data by distributing among them.
• Divide the data into chunks which could be fit into memory and process the data sequentially.

Submitted solution contains first and third approach. First approach is in the notebook hotels_analysis.ipynb and second approach is in the notebook hotels_analysis_large_files.ipynb

Output:

The computed output dataframe is stored as csv file. result.csv and result_1.csv files are output files.