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Time Series Analysis
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Course Content

Time Series Analysis

Time Series Analysis

1. Time Series: Let's Start
IntroductionPractical ExamplesModel TypesImplementation in PythonVisualization
2. Time Series Processing
Reading and Visualizing DataStationarityAutocorrelationDecomposition
3. Time Series Visualization
Simple Time SeriesCustomize Your PlotChallenge
4. Stationary Models
Examples of Stationary Time SeriesSimple Moving AverageAutoregressionAutoregressive-Integrated-Moving-Average ModelChallenge
5. Non-Stationary Models
Examples of Non-Stationary Time SeriesConvert Non-Stationary Data to StationaryChallenge 1Challenge 2
6. Solve Real Problems
Weather ForecastingStore Demand ForecastFinancial MarketsPredict the Emergence of Repeat CustomersMedicine: EEG Forecasting

Challenge

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 3. Chapter 3
toggle bottom row

Challenge

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 3. Chapter 3
toggle bottom row

Challenge

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Task

You are faced with the task of creating a visualization of the aapl.csv dataset:

  1. Read the dataset. Convert the "Date" column of df to datetime type, and set them as df indexes.
  2. Initialize a line plot for the "Open" column values of the df. Set colormap to "gray".
  3. Add a title to the plot. In this order, it should contain the "Open" column's max and min values.
  4. Add labels on an axis: "Datetime" on the x-axis and "Price" on the y-axis.

Switch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 3
Switch to desktop for real-world practiceContinue from where you are using one of the options below
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