For this assignment, you’ll need to write a report on your exploratory analysis of the following data set. Your report should detail your process and present a summary of your initial findings and insights. 

Step 1: Read the business scenario

You work for a company that specialises in last-minute weekend flights in the USA. Your manager has asked you to investigate historical data for domestic flight delays departing from Los Angeles International (LAX) in 2015 to help drive strategic and operational decision-making. Specifically, the company is looking to use data to help inform decision-making around: Common reasons for delays. Are there common types of delays for certain airports/areas/states (or by airline)? What about in certain months? Advice for passengers. Are there certain days/times/airlines that are preferable due to fewer delays? Miscellaneous areas to improve. Are there ways to improve quality, customer experience, reduce costs, reduce landing/departing bottlenecks? Your manager suggested that using Excel (or similar) you should check the datasets for errors and correct any found, before loading it into an SQLite database to run your queries. Any rows with calculation errors involving time points should be deleted, and any calculation errors involving only time durations should be rectified. 

Step 2: Access the dataset Select the following to download the folder which contains flight datasets with errors: Flight datasets [ZIP 2.5MB] Download Flight datasets [ZIP 2.5MB] About the data You have been provided with three data sets in the zipped folder. The first contains details of domestic flights departing from LAX in 2015. You have also been provided reference data sets for US airports and US airlines. 1. The flight data set has several columns, including the following calculated or coded columns: DAY_OF_WEEK – Represents the scheduled day of the week for the flight, where 1 = Monday, 2 = Tuesday, and so on. Airline, origin, and destination airports use the relevant IATA identifiers. SCHEDULEDDEPARTURE_TIME – Planned departure time. SCHEDULEDARRIVAL_TIME – Planned arrival time. Note that ARRIVAL_DELAY =AIR_SYSTEM_DELAY + SECURITY_DELAY + AIRLINE_DELAY + LATE_AIRCRAFT_DELAY + WEATHER_DELAY. The following columns were calculated automatically and may contain errors: DEPARTURE_DELAYInMinutes = ACTUALDEPARTURE_TIME - SCHEDULEDDEPARTURE_TIME ARRIVAL_DELAYInMinutes = ACTUALARRIVAL_TIME - SCHEDULEDARRIVAL_TIME 2. The airline data set includes two columns: IATA_CODE – International Air Transport Association’s airline identifiers. AIRLINE – airline’s name. 3. The airport data set has several columns, including the following: IATA_CODE – International Air Transport Association’s location identifier. AIRPORT – airport name. As you start working with the data, you’ll be able to explore and drill down into one, or more, of these areas, or you might find a new angle to explore.  

Step 3: Complete the exploratory analysis Make sure you use the spreadsheet and database tools in the unit and refer to the examples and supporting material to complete components of your exploratory analysis. In Week 2 you became familiar with calculating different statistical measures, including measures of central value and measures of spread. In Week 3 you explored working with multiple datasets. In Week 4 you applied diagnostic analysis techniques to identify potential causes of irregularities. To complete the exploratory analysis, you should: identify and extract relevant fields from the data set perform any necessary cleaning or transformation of the data create exploratory visualisations or calculate relevant summary statistics to identify patterns, trends, or insights. As you gain insight, you might want to repeat the exploratory process, including more data or using different descriptive or diagnostic techniques as required.  

Step 4: Complete your report In your report, you should: summarise the business problem and identify data to be used in your analysis summarise the steps taken to prepare data for analysis, including your approach to identify and manage outliers describe any transformation of the original data, combination of data sources, or the inclusion of external data sources as required justify the choice of exploratory visualisations, including examples where appropriate justify your choice of descriptive measures and/or diagnostic techniques present your initial findings and insights from the given data set.

Tips for writing the report:

Your report should meet the following standard: Interpreting the business problem Extensive details of the business problem and selected data have been provided. Some discussion of the strengths and limitations of the current data, or areas for further investigation provided. Describing data wrangling steps Summary of the steps taken to prepare data for analysis are clear, well organised, appropriate, and include an approach to identify and manage outliers. Detailed and insightful descriptions of processes and decisions are evident at each stage. Identifying patterns and trends Detailed evidence of exploratory visualisations, descriptive measures or diagnostic techniques has been provided. Extensive examples and detailed written justifications are provided. Describing analytic approaches Detailed and insightful descriptions of processes and decisions made during the analysis are evident at each stage. Descriptions of any failed experiments, or multiple rounds of analysis are included. Communicating findings and insights Insights and findings are clearly articulated in relation to the original business scenario.