Spec-Zone.ru › Matplotlib 3.6

matplotlib.axis.Axis.set_tick_params

Axis.set_tick_params(which='major', reset=False, **kwargs)[source]

Установить параметры отображения делений, меток делений и линий сетки.

Для документации ключевых аргументов см. matplotlib.axes.Axes.tick_params().

Примеры использования matplotlib.axis.Axis.set_tick_params

Настройка диаграмм с размахом

Настройка диаграмм с размахом

Настройка диаграмм с размахом
Знаки доллара на метках

Знаки доллара на метках

Знаки доллара на метках
Диаграмма рассеяния с гистограммами (располагаемые оси)

Диаграмма рассеяния с гистограммами (располагаемые оси)

Диаграмма рассеяния с гистограммами (располагаемые оси)
Pythonic Matplotlib

Pythonic Matplotlib

Pythonic Matplotlib
<img alt="Размещение меток дат с помощью правил повторения" 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</div>
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Установка меток дат с помощью правил повторения

Установка меток дат с помощью правил повторения
Точность дат и эпохи

Точность дат и эпохи

Точность дат и эпохи
END_OF_DOCUMENT_MARKER
<img alt="Выбор цветовых карт в Matplotlib" src="data:image/png;base64,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

Выбор цветовых карт в Matplotlib

Выбор цветовых карт в Matplotlib

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Spec-Zone.ru

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Spec-Zone .ru
спецификации, руководства, описания, API