Time series is a collection of data instances that are ordered according to a time stamp. Stock prices, temperature, etc are examples of time series data in real life. Time series data are used for forecasting sales, predicting trends. Visualization is the process of visually representing data or the relationship between features of a data either in a two-dimensional plot or a three-dimensional plot. Visualizing the time series data constitutes an important part of the process for working with a time series dataset. Visualizing the data not only helps in the modelling process but it can also be used to identify trends and features that cause those trends. In this work, we take a real-life time series dataset and analyse how the target feature relates to other features of the dataset through visualization. From the work that has been carried out, we present an effective method of visualization for time series data which will be much useful for machine learning modelling with such datasets.

翻译：时间序列是按时间戳排序的数据实例集合。股票价格、温度等是现实生活中的时间序列数据示例。时间序列数据用于销售预测、趋势预测。可视化是以二维或三维图形方式展示数据或数据特征之间关系的过程。可视化时间序列数据是处理时间序列数据集工作流程中的重要组成部分。数据可视化不仅有助于建模过程，还可用于识别趋势及其成因特征。本研究选取真实时间序列数据集，通过可视化分析目标特征与数据集中其他特征的关系。基于已完成的工作，我们提出了一种有效的时间序列数据可视化方法，该方法将对此类数据集的机器学习建模大有裨益。