Exploratory Time Series Analysis with Autocorrelation and Lag Plots using Python
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In order to predict the future, we need to know how we are today compared to the past. This philosophy is applied by two visual techniques for exploratory data analysis for time series. In particular, lag and autocorrelation plots. This video explains both techniques and how to generate their graphs with python. 👉 Xiperia offers business consulting that transforms data into actionable knowledge to achieve your business goals. Learn more at https://www.xiperia.com To cite this educational resource, use the following reference: Gutiérrez-García, JO [Machine Code]. (2023, June 26). Exploratory Analysis of Time Series with Autocorrelation and Lag Plots using Python [Video]. YouTube. [Include video URL here] ********************************************** To guide your learning, in this link ( • Artificial Intelligence (AI) Course... ) you will find a sequential guide to learn: 1. Basic Programming with Python; 2. Data Handling; 3. Data Visualization; 4. Data Analysis; and 5. Machine Learning and Data Science. ********************************************** Video Index: 0:00 Introduction 1:02 Exploratory analysis 2:12 Lag plots 16:34 Autocorrelation plots (Correlogram) 24:00 Positive vs negative autocorrelation 32:06 Autocorrelation and Confidence Interval 34:00 Autocorrelation formula 36:43 White noise in time series 38:40 Autocorrelation and lag plot with python ⭐ Support Código Máquina by giving a Like, Commenting, Sharing or with a Super Thanks. ⭐ From the co-founder of Código Máquina, SINHAKI natural cosmetics products: https://www.amazon.com.mx/stores/sinH... #statistics #datascience #python #datascience #timeseries #timeseries #forecasting #forecast #dataanalysis #econometrics
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