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Customize Your Plot | Time Series Visualization
Time Series Analysis
course content

Зміст курсу

Time Series Analysis

Time Series Analysis

1. Time Series: Let's Start
2. Time Series Processing
3. Time Series Visualization
4. Stationary Models
5. Non-Stationary Models
6. Solve Real Problems

bookCustomize Your Plot

Now we will look at how you can diversify and improve the presentation of your graphs. This will improve the perception of the graph and can also be useful when creating presentations and other documents with data analysis.

Let's start by adding headings to the graph:

You can also change the style of the time series chart. If you want the graph to be not a solid line but consist of dots, then change the value of the linestyle argument to "dotted":

And finally, let's figure out how to change the chart's color scheme. You have a huge selection of colormaps, a complete list of which is on the official matplotlib website.

To change the color palette, you just need to change the value of the colormap argument to the name of the palette you are interested in:

Завдання
test

Swipe to show code editor

Visualize the dataset pr_air_quality.csv.

  1. Read the csv file.
  2. Initialize a line plot for the "value" column of df. Set "dotted" linestyle and "cool" colormap.
  3. Add plot title "Air quality analysis".
  4. Add labels on the axis: "Datetime" on the x-axis and "Value" on the y-axis.

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Секція 3. Розділ 2
toggle bottom row

bookCustomize Your Plot

Now we will look at how you can diversify and improve the presentation of your graphs. This will improve the perception of the graph and can also be useful when creating presentations and other documents with data analysis.

Let's start by adding headings to the graph:

You can also change the style of the time series chart. If you want the graph to be not a solid line but consist of dots, then change the value of the linestyle argument to "dotted":

And finally, let's figure out how to change the chart's color scheme. You have a huge selection of colormaps, a complete list of which is on the official matplotlib website.

To change the color palette, you just need to change the value of the colormap argument to the name of the palette you are interested in:

Завдання
test

Swipe to show code editor

Visualize the dataset pr_air_quality.csv.

  1. Read the csv file.
  2. Initialize a line plot for the "value" column of df. Set "dotted" linestyle and "cool" colormap.
  3. Add plot title "Air quality analysis".
  4. Add labels on the axis: "Datetime" on the x-axis and "Value" on the y-axis.

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Секція 3. Розділ 2
toggle bottom row

bookCustomize Your Plot

Now we will look at how you can diversify and improve the presentation of your graphs. This will improve the perception of the graph and can also be useful when creating presentations and other documents with data analysis.

Let's start by adding headings to the graph:

You can also change the style of the time series chart. If you want the graph to be not a solid line but consist of dots, then change the value of the linestyle argument to "dotted":

And finally, let's figure out how to change the chart's color scheme. You have a huge selection of colormaps, a complete list of which is on the official matplotlib website.

To change the color palette, you just need to change the value of the colormap argument to the name of the palette you are interested in:

Завдання
test

Swipe to show code editor

Visualize the dataset pr_air_quality.csv.

  1. Read the csv file.
  2. Initialize a line plot for the "value" column of df. Set "dotted" linestyle and "cool" colormap.
  3. Add plot title "Air quality analysis".
  4. Add labels on the axis: "Datetime" on the x-axis and "Value" on the y-axis.

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Now we will look at how you can diversify and improve the presentation of your graphs. This will improve the perception of the graph and can also be useful when creating presentations and other documents with data analysis.

Let's start by adding headings to the graph:

You can also change the style of the time series chart. If you want the graph to be not a solid line but consist of dots, then change the value of the linestyle argument to "dotted":

And finally, let's figure out how to change the chart's color scheme. You have a huge selection of colormaps, a complete list of which is on the official matplotlib website.

To change the color palette, you just need to change the value of the colormap argument to the name of the palette you are interested in:

Завдання
test

Swipe to show code editor

Visualize the dataset pr_air_quality.csv.

  1. Read the csv file.
  2. Initialize a line plot for the "value" column of df. Set "dotted" linestyle and "cool" colormap.
  3. Add plot title "Air quality analysis".
  4. Add labels on the axis: "Datetime" on the x-axis and "Value" on the y-axis.

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
Секція 3. Розділ 2
Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
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