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PROJECT
Analyze Time Series Data Using Markov Transition Fields
In this project, we will analyze time series data using the Markov transition field to observe its temporal properties. We will implement the project stepwise. These steps include the construction of the Markov matrix, the construction of the Markov transition field, and the extraction of valuable properties.
You will learn to:
Plot data using dedicated Python libraries.
Extract useful information from a time series dataset.
Create and analyze a Markov transition field.
Extract and process data using dedicated tools and techniques.
Skills
Data Plotting
Data Statistics
Data Visualization
Prerequisites
Basic understanding of Linear Algebra
Experience with Python
Technologies
Pyts
NumPy
Pandas
Matplotlib
Scikit-image
Project Description
Time series data is of significant importance in fields like data science and control systems, where predictive data analysis is used to improve the performance of systems. This makes various numerical tools and techniques essential for analyzing time series data.
There are several methods to encode time series data in images. This allows the data to be processed in various frameworks, for example, neural networks. The Markov Transition Field (MTF) is one of the methods used to encode the data in a matrix in which the transition probability of a datapoint from one time step to another time step is encoded in matrix entries.
In this project, we will analyze the Electricity Transformer Temperature (ETT) by constructing its Markov transition field. We will start by constructing its adjacency matrix, and then we’ll evaluate its Markov matrix and Markov transition field. We will visualize the obtained matrices and observe the properties of the time series data revealed by the plots.
Project Tasks
1
Construct the Markov Transition Matrix
Task 1: Import Required Libraries and Packages
Task 2: Import the Time Series Dataset
Task 3: Truncate and Plot the DataFrame
Task 4: Discretize the Data
Task 5: Create the Adjacency Matrix
Task 6: Calculate the Markov Matrix
Task 7: Create the Markov Transition Field
2
Analyze the Markov Transition Field
Task 8: Visualize the Markov Transition Field
Task 9: Downsample the Markov Transition Field
Task 10: Plot Self-Transition Probabilities on Time Series Data
Congratulations!