Customize Chart Axes in Presentations with Python

What this page is about

Discover how to use Aspose.Slides for Python via .NET to customize chart axes in PowerPoint and OpenDocument presentations for reports and visualizations.

Overview

This article explains how to customize chart axes with Aspose.Slides for Python via .NET. It covers calculated axis values, switching chart rows and columns, axis visibility, category label and tick-mark intervals, date categories and formatting, title rotation, axis positioning, and display units.

Get the Max Values on the Vertical Axis on Charts

Create a Presentation and add an area chart with default data. Call validate_chart_layout before reading calculated axis values so that the chart layout is up to date.

Read actual_max_value and actual_min_value for the axis limits, and actual_major_unit and actual_minor_unit for the tick intervals. actual_major_unit_scale and actual_minor_unit_scale provide time-unit scales, which are relevant to date axes. The example stores these values in local variables and saves the chart.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.AREA, 100, 100, 500, 350)
    chart.validate_chart_layout()

    max_value = chart.axes.vertical_axis.actual_max_value
    min_value = chart.axes.vertical_axis.actual_min_value

    major_unit = chart.axes.vertical_axis.actual_major_unit
    minor_unit = chart.axes.vertical_axis.actual_minor_unit

    major_unit_scale = chart.axes.vertical_axis.actual_major_unit_scale
    minor_unit_scale = chart.axes.vertical_axis.actual_minor_unit_scale

    presentation.save("AxisValues_out.pptx", slides.export.SaveFormat.PPTX)

Swap the Data between Axes

Use switch_row_column to exchange the roles of series and categories in chart data. Each former category becomes a series, and each former series becomes a category. This changes how the data is grouped; it does not exchange the horizontal and vertical axes. The example uses set_range to bind the default data to Sheet1!A1:D5, including the header row and category column, before switching rows and columns. It saves a chart with four series and three categories.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.CLUSTERED_COLUMN, 100, 100, 400, 300)

    chart.chart_data.set_range("Sheet1!A1:D5")
    chart.chart_data.switch_row_column()

    presentation.save("SwitchChartRowColumns_out.pptx", slides.export.SaveFormat.PPTX)

Disable the Vertical Axis for Line Charts

Set is_visible to False on the vertical axis to hide it. The example creates a line chart with default data and saves it with the vertical axis hidden.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.LINE, 100, 100, 400, 300)
    chart.axes.vertical_axis.is_visible = False

    presentation.save("HiddenVerticalAxis.pptx", slides.export.SaveFormat.PPTX)

Disable the Horizontal Axis for Line Charts

Set is_visible to False on the horizontal axis to hide it. The example creates a line chart with default data and saves it with the horizontal axis hidden.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.LINE, 100, 100, 400, 300)
    chart.axes.horizontal_axis.is_visible = False

    presentation.save("HiddenHorizontalAxis.pptx", slides.export.SaveFormat.PPTX)

Change a Category Axis

Set category_axis_type to choose a date or text category axis. This example requires ExistingChart.pptx, with a chart as the first shape on the first slide and category cells containing numeric Excel date values. It changes the horizontal axis to a date axis. Setting is_automatic_major_unit to False, major_unit to 1, and major_unit_scale to months places major ticks at one-month intervals.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation("ExistingChart.pptx") as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes[0]
    chart.axes.horizontal_axis.category_axis_type = charts.CategoryAxisType.DATE
    chart.axes.horizontal_axis.is_automatic_major_unit = False
    chart.axes.horizontal_axis.major_unit = 1
    chart.axes.horizontal_axis.major_unit_scale = charts.TimeUnitType.MONTHS

    presentation.save("ChangeChartCategoryAxis_out.pptx", slides.export.SaveFormat.PPTX)

Control Category Axis Label Intervals

When a chart has many categories, reduce the number of visible axis labels without removing categories or data points. Set is_automatic_tick_label_spacing to False, then set tick_label_spacing to the desired category interval. For text categories in their normal order, counting starts at the first category:

Interval	Labels displayed in the example
`1`	Category 1, Category 2, Category 3, … Category 24
`2`	Category 1, Category 3, Category 5, … Category 23
`3`	Category 1, Category 4, Category 7, … Category 22

An interval of 3 displays every third label, leaving two labels hidden between displayed labels. It does not remove the corresponding columns. Automatic spacing chooses an interval based on the available space; it does not necessarily display every label.

Tick marks have separate controls. Set is_automatic_tick_marks_spacing to False and use tick_marks_spacing to set their interval. For example, 1 keeps a tick mark at every category interval while labels appear only every third category. Set major_tick_mark to a visible style so you can see the result. Setting either automatic-spacing property back to True lets the chart choose that interval again.

The following self-contained example creates 24 categories and one series, then saves three slides in CategoryAxisIntervals.pptx: automatic spacing, manual label spacing with independent tick marks, and restored automatic spacing. The two copies retain the original chart data. No input presentation is required. Horizontal label text makes the difference in density easy to see.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.CLUSTERED_COLUMN, 30, 40, 660, 320)

    chart.has_legend = False
    chart.chart_data.categories.clear()
    chart.chart_data.series.clear()

    workbook = chart.chart_data.chart_data_workbook
    workbook.clear(0)

    series = chart.chart_data.series.add(charts.ChartType.CLUSTERED_COLUMN)
    for i in range(24):
        category_cell = workbook.get_cell(0, i + 1, 0, f"Category {i + 1}")
        chart.chart_data.categories.add(category_cell)
        value_cell = workbook.get_cell(0, i + 1, 1, 10 + i % 6 * 5)
        series.data_points.add_data_point_for_bar_series(value_cell)

    axis = chart.axes.horizontal_axis
    axis.category_axis_type = charts.CategoryAxisType.TEXT
    axis.text_format.text_block_format.rotation_angle = 0
    axis.text_format.portion_format.font_height = 12
    axis.major_tick_mark = charts.TickMarkType.OUTSIDE
    axis.is_automatic_tick_label_spacing = True
    axis.is_automatic_tick_marks_spacing = True

    # Slide 2: show every third label, but keep a tick mark for every category.
    manual_slide = presentation.slides.add_clone(slide)
    manual_chart = manual_slide.shapes[0]
    manual_axis = manual_chart.axes.horizontal_axis
    manual_axis.is_automatic_tick_label_spacing = False
    manual_axis.tick_label_spacing = 3
    manual_axis.is_automatic_tick_marks_spacing = False
    manual_axis.tick_marks_spacing = 1

    # Slide 3: let the chart choose both intervals again.
    restored_slide = presentation.slides.add_clone(manual_slide)
    restored_chart = restored_slide.shapes[0]
    restored_chart.axes.horizontal_axis.is_automatic_tick_label_spacing = True
    restored_chart.axes.horizontal_axis.is_automatic_tick_marks_spacing = True

    presentation.save("CategoryAxisIntervals.pptx", slides.export.SaveFormat.PPTX)

Automatic spacing (slide 1): In this rendering, every second category label is displayed and wraps onto two lines. The automatic result can vary with chart size, fonts, and the renderer.

Automatic category label spacing with all 24 columns visible

Manual spacing (slide 2): Every third label is displayed on one line, while tick marks remain at every category interval. All 24 columns, including those without labels, remain visible with the same values. Slide 3 restores the automatic appearance shown above.

Manual category label interval of three with all 24 columns visible

Choose the Correct Axis and Interval

Use this category-count interval for a text category axis, such as the category axis of a column, line, area, or bar chart. In a column chart, it is the horizontal axis. In a horizontal bar chart, the category axis is vertical, so apply these settings to vertical_axis. Tick-mark spacing also applies to a series axis in charts that have one.

Do not use category label spacing to set the numeric scale of a value axis. On a value axis, major_unit specifies a difference in values: for example, a major unit of 10 produces ticks at 0, 10, 20, and so on when the axis starts at zero. A category label interval of 3 instead counts category positions, regardless of their data values. Scatter and bubble charts use value axes rather than a text category axis. For a date axis, use time-based major units and scales as described in Change a Category Axis.

Set the Date Format for Category Axis Values

The example replaces the default chart data with four annual values. Dates are stored as OLE Automation serial numbers in the first worksheet (index 0). Set category_axis_type to a date axis, disable is_number_format_linked_to_source, and assign yyyy to number_format so the category labels display four-digit years independently of the cell formatting.

from datetime import date

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.LINE, 50, 50, 450, 300)

    chart.chart_data.categories.clear()
    chart.chart_data.series.clear()

    workbook = chart.chart_data.chart_data_workbook
    workbook.clear(0)

    series = chart.chart_data.series.add(charts.ChartType.LINE)
    for i in range(4):
        category_date = date(2015 + i, 1, 1)
        serial_date = (category_date - date(1899, 12, 30)).days
        category_cell = workbook.get_cell(0, i + 1, 0, serial_date)
        chart.chart_data.categories.add(category_cell)

        value_cell = workbook.get_cell(0, i + 1, 1, i + 1)
        series.data_points.add_data_point_for_line_series(value_cell)

    chart.axes.horizontal_axis.category_axis_type = charts.CategoryAxisType.DATE
    chart.axes.horizontal_axis.is_number_format_linked_to_source = False
    chart.axes.horizontal_axis.number_format = "yyyy"

    presentation.save("DateAxisFormat.pptx", slides.export.SaveFormat.PPTX)

Set a Rotation Angle for a Chart Axis Title

Enable has_title on the vertical axis, provide title text, and set rotation_angle to rotate the title. The angle is measured in degrees; this example saves a column chart with its value-axis title rotated by 90 degrees.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.CLUSTERED_COLUMN, 50, 50, 450, 300)
    chart.axes.vertical_axis.has_title = True
    chart.axes.vertical_axis.title.add_text_frame_for_overriding("Value")
    chart.axes.vertical_axis.title.text_format.text_block_format.rotation_angle = 90

    presentation.save("RotatedAxisTitle.pptx", slides.export.SaveFormat.PPTX)

Set the Axis Position on a Category or Value Axis

Use axis_between_categories to control whether the value axis crosses the category axis between categories or at category tick marks. This property applies to category axes. The example sets it to True on the horizontal category axis of a column chart and saves the result.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.CLUSTERED_COLUMN, 50, 50, 450, 300)
    chart.axes.horizontal_axis.axis_between_categories = True

    presentation.save("AxisBetweenCategories.pptx", slides.export.SaveFormat.PPTX)

Set the Display Unit on a Chart Value Axis

Set display_unit to scale the labels on a value axis without changing the underlying data. With DisplayUnitType set to MILLIONS, a value of 60,000,000 is displayed as 60. The example creates a column chart and applies the millions display unit to its vertical axis.

import aspose.slides as slides
import aspose.slides.charts as charts

with slides.Presentation() as presentation:
    slide = presentation.slides[0]

    chart = slide.shapes.add_chart(charts.ChartType.CLUSTERED_COLUMN, 50, 50, 450, 300)
    chart.axes.vertical_axis.display_unit = charts.DisplayUnitType.MILLIONS

    presentation.save("Result.pptx", slides.export.SaveFormat.PPTX)

FAQ

How do I set the value at which one axis crosses the other (axis crossing)?

Use cross_type to select the crossing behavior. To specify a numeric crossing value, set cross_at. These settings let you move the axis crossing to a suitable baseline.

How can I position tick labels relative to the axis?

Set tick_label_position using TickLabelPositionType: LOW, HIGH, NEXT_TO, or NONE. To control the tick marks themselves, use major_tick_mark or minor_tick_mark; these are separate from label positioning.