# Assessing a Dataset A client has reached out to your team for assistance in analyzing the seasonal spending habits of taxi customers in New York City. They want to know: **Do yellow taxi passengers in New York City tip drivers more in the winter or summer?** Your team is currently in the [Capturing](Readme.md#Capturing) phase of the Data Science Lifecycle, and you are responsible for managing the dataset. You have been provided with a notebook and [data](../../../../data/taxi.csv) to examine. In this directory, there is a [notebook](../../../../4-Data-Science-Lifecycle/14-Introduction/notebook.ipynb) that uses Python to load yellow taxi trip data from the [NYC Taxi & Limousine Commission](https://docs.microsoft.com/en-us/azure/open-datasets/dataset-taxi-yellow?tabs=azureml-opendatasets). You can also open the taxi data file using a text editor or spreadsheet software like Excel. ## Instructions - Evaluate whether the data in this dataset is sufficient to answer the question. - Explore the [NYC Open Data catalog](https://data.cityofnewyork.us/browse?sortBy=most_accessed&utf8=%E2%9C%93). Identify an additional dataset that might be useful in addressing the client's question. - Formulate 3 questions to ask the client for further clarification and a deeper understanding of the problem. Refer to the [dataset's dictionary](https://www1.nyc.gov/assets/tlc/downloads/pdf/data_dictionary_trip_records_yellow.pdf) and [user guide](https://www1.nyc.gov/assets/tlc/downloads/pdf/trip_record_user_guide.pdf) for more details about the data. ## Rubric Exemplary | Adequate | Needs Improvement --- | --- | --- | --- **Disclaimer**: This document has been translated using the AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). While we aim for accuracy, please note that automated translations may include errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is advised. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.