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Simple Date and Time Analysis Data
Data Science and Analytics
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About
Structured data is provided to facilitate exploration and understanding of date and time analysis principles. This resource is a simple dataset ideal for honing knowledge related to the datetime datatype. It is split into two distinct files to offer varied contexts for temporal data handling, supporting introductory work and educational scenarios.
Columns
The data product includes two separate files:
message.csv:
- date: Records the specific date and time information for the corresponding message entry.
- msg: Contains the textual content of the message itself.
order.csv:
- date: Records the date when the transaction or placement occurred.
- product_id: An identifier associated with the item being transacted.
- city_id: An identifier representing the geographic location related to the order.
- order: Details specific to the order transaction.
Distribution
The material is delivered in the standard CSV format. The
messages.csv file contains 1,000 valid records, with 100% data validity recorded. There are no missing or mismatched entries in this file. The dataset is expected to receive updates annually.Usage
This dataset is excellently suited for practicing fundamental data science and programming skills related to temporal information. Ideal applications include:
- Date Time Handling: Exploring and manipulating the date and time datatype in programming languages.
- Library Practice: Gaining experience using libraries such as pandas and NumPy for data preparation.
- Beginner Training: Utilizing a straightforward structure for educational modules focused on time series foundations.
Coverage
The primary temporal scope spans approximately five years, running from 1 January 2012 through to 18 January 2017. While the
order.csv file provides a city_id column, specific geographic or demographic details are not detailed within the provided source information.License
CC0: Public Domain
Who Can Use It
- Students and Learners: Individuals looking to master the use of the
datetimelibrary in coding environments. - Beginner Data Scientists: Those who require a clean, structured sample to practice fundamental data cleaning and preparation techniques.
- Data Analysts: Professionals seeking a simple testing ground for new functions or basic time-based queries.
Dataset Name Suggestions
- Simple Date and Time Analysis Data
- Temporal Data Exploration Kit
- Date Time Handling Practice Files
- Beginner Temporal Data Set
Attributes
Original Data Source: Simple Date and Time Analysis Data
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