파이썬을 사용한 프레젠테이션에서 차트 데이터 레이블 관리
소개
데이터 레이블은 차트 시리즈와 개별 데이터 포인트에 대한 정보를 표시하여 독자가 값을 식별하고 차트를 이해할 수 있도록 도와줍니다. 이 문서에서는 값 서식 지정, 백분율 표시, 레이블 텍스트 읽기, 축 최대값을 초과하는 레이블 제어, 범주 축 레이블 간격 조정, 파이 차트 레이블 위치 지정 방법을 설명합니다.
차트 데이터 레이블에서 데이터 정밀도 설정
Use number_format_of_values to format series values. This example creates a line chart with default data, displays its data table, and enables value labels for the first series. The format #,##0.00 displays a thousands separator and two decimal places without changing the underlying values.
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.has_data_table = True
series = chart.chart_data.series[0]
series.number_format_of_values = "#,##0.00"
series.labels.default_data_label_format.show_value = True
presentation.save("PrecisionOfDatalabels_out.pptx", slides.export.SaveFormat.PPTX)
To format the numeric cells in a chart’s embedded workbook, see 워크북 셀에 대한 사용자 정의 숫자 형식 설정. That example also shows value labels following their source cell formats while preserving the stored numeric values.
백분율을 레이블로 표시
For a stacked column chart, calculate each value as a percentage of its category total and assign the text to text_frame_for_overriding. This example uses the default chart data and displays percentages with two decimal places in an 8-point font. Categories with a total of zero are skipped to avoid division by zero. Recalculate the custom label text if the chart data changes.
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.STACKED_COLUMN, 20, 20, 400, 400)
category_totals = [0.0] * len(chart.chart_data.categories)
for k in range(len(chart.chart_data.categories)):
for series in chart.chart_data.series:
point_value = float(series.data_points[k].value.data)
category_totals[k] += point_value
for series in chart.chart_data.series:
series.labels.default_data_label_format.show_legend_key = False
for j in range(len(series.data_points)):
label = series.data_points[j].label
if category_totals[j] == 0:
continue
point_value = float(series.data_points[j].value.data)
data_point_percent = point_value / category_totals[j] * 100
portion = slides.Portion()
portion.text = f"{data_point_percent:.2f} %"
portion.portion_format.font_height = 8
label.text_frame_for_overriding.text = ""
paragraph = label.text_frame_for_overriding.paragraphs[0]
paragraph.portions.add(portion)
label.data_label_format.show_value = True
label.data_label_format.show_series_name = False
label.data_label_format.show_percentage = False
label.data_label_format.show_legend_key = False
label.data_label_format.show_category_name = False
label.data_label_format.show_bubble_size = False
presentation.save("DisplayPercentageAsLabels_out.pptx", slides.export.SaveFormat.PPTX)
차트 데이터 레이블에 백분율 기호 설정
When values are stored as fractions, use number_format to display percentages. Set is_number_format_linked_to_source to False to apply the label format independently of the source cells.
This example creates a 100% stacked column chart with red and blue series across four categories. Each pair of values adds up to 1. The label format 0.0% displays 0.30 as 30.0%, while the vertical axis uses two decimal places. Both series use white, 10-point label text.
import aspose.slides as slides
import aspose.slides.charts as charts
import aspose.pydrawing as drawing
with slides.Presentation() as presentation:
slide = presentation.slides[0]
chart = slide.shapes.add_chart(charts.ChartType.PERCENTS_STACKED_COLUMN, 20, 20, 500, 400)
chart.axes.vertical_axis.is_number_format_linked_to_source = False
chart.axes.vertical_axis.number_format = "0.00%"
chart.chart_data.series.clear()
chart.chart_data.categories.clear()
workbook = chart.chart_data.chart_data_workbook
worksheet_index = 0
for i in range(4):
category_cell = workbook.get_cell(worksheet_index, i + 1, 0, f"Category {i + 1}")
chart.chart_data.categories.add(category_cell)
series_names = ["Reds", "Blues"]
series_colors = [drawing.Color.red, drawing.Color.blue]
values = [[0.30, 0.50, 0.80, 0.65], [0.70, 0.50, 0.20, 0.35]]
for i in range(len(series_names)):
series_cell = workbook.get_cell(worksheet_index, 0, i + 1, series_names[i])
series = chart.chart_data.series.add(series_cell, chart.type)
for j in range(4):
value_cell = workbook.get_cell(worksheet_index, j + 1, i + 1, values[i][j])
series.data_points.add_data_point_for_bar_series(value_cell)
series.format.fill.fill_type = slides.FillType.SOLID
series.format.fill.solid_fill_color.color = series_colors[i]
label_format = series.labels.default_data_label_format
label_format.show_value = True
label_format.is_number_format_linked_to_source = False
label_format.number_format = "0.0%"
label_format.text_format.portion_format.font_height = 10
label_format.text_format.portion_format.fill_format.fill_type = slides.FillType.SOLID
label_format.text_format.portion_format.fill_format.solid_fill_color.color = drawing.Color.white
presentation.save("SetDataLabelsPercentageSign_out.pptx", slides.export.SaveFormat.PPTX)
데이터 레이블의 실제 텍스트 읽기
Use get_actual_label_text to retrieve the text produced by a data label’s settings. This is useful when extracting labels for reports, searching presentation content, or validating generated charts. In the example below, the default data label format combines each category name, series name, and value. One point formats its value as a percentage, and another uses custom text from text_frame_for_overriding.
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, 20, 20, 500, 300)
chart.chart_data.series.clear()
chart.chart_data.categories.clear()
workbook = chart.chart_data.chart_data_workbook
for i, category_name in enumerate(["Q1", "Q2"]):
category_cell = workbook.get_cell(0, i + 1, 0, category_name)
chart.chart_data.categories.add(category_cell)
north_cell = workbook.get_cell(0, 0, 1, "North")
north = chart.chart_data.series.add(north_cell, chart.type)
for i, value in enumerate([0.25, 0.75]):
value_cell = workbook.get_cell(0, i + 1, 1, value)
north.data_points.add_data_point_for_bar_series(value_cell)
south_cell = workbook.get_cell(0, 0, 2, "South")
south = chart.chart_data.series.add(south_cell, chart.type)
for i, value in enumerate([0.40, 0.60]):
value_cell = workbook.get_cell(0, i + 1, 2, value)
south.data_points.add_data_point_for_bar_series(value_cell)
for series in chart.chart_data.series:
label_format = series.labels.default_data_label_format
label_format.show_category_name = True
label_format.show_series_name = True
label_format.show_value = True
north.labels[1].data_label_format.is_number_format_linked_to_source = False
north.labels[1].data_label_format.number_format = "0%"
south.labels[0].text_frame_for_overriding.text = "Reviewed"
for series in chart.chart_data.series:
for point in series.data_points:
label = point.label
if not label.is_visible:
continue
label_text = label.get_actual_label_text()
print(f"Value: {point.value.data}; label: {label_text}")
The number stored in a data point remains 0.75, even when its label shows 75% along with the category and series names. Custom text replaces the generated label text. get_actual_label_text returns the resulting label string in either case. Check is_visible separately, as shown above, when you want to extract only visible labels.
축 최대값을 초과하는 데이터 레이블 제어
When you limit an axis range manually, some data points may exceed its maximum. Use show_data_labels_over_maximum to control whether their data labels are shown. This setting changes label visibility; it does not change the axis range or the underlying data values.
The example below creates a 2D clustered column chart with values of 60 and 120. It sets is_automatic_max_value to False and max_value to 100 on the vertical axis. The first slide allows labels beyond the maximum; a copy of that slide disables them. Both slides are saved in DataLabelsOverMaximum.pptx.
Enable value labels with show_value. The chart-level setting does not enable value display by itself or override an individual label’s disabled value display. This example enables values for the entire series and uses position to place labels at the outside end of each column.
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, 600, 400)
chart.has_legend = False
chart.chart_data.series.clear()
chart.chart_data.categories.clear()
workbook = chart.chart_data.chart_data_workbook
first_category = workbook.get_cell(0, 1, 0, "Within range")
second_category = workbook.get_cell(0, 2, 0, "Above maximum")
chart.chart_data.categories.add(first_category)
chart.chart_data.categories.add(second_category)
series_name = workbook.get_cell(0, 0, 1, "Values")
series = chart.chart_data.series.add(series_name, chart.type)
first_value = workbook.get_cell(0, 1, 1, 60)
second_value = workbook.get_cell(0, 2, 1, 120)
series.data_points.add_data_point_for_bar_series(first_value)
series.data_points.add_data_point_for_bar_series(second_value)
series.labels.default_data_label_format.show_value = True
series.labels.default_data_label_format.position = charts.LegendDataLabelPosition.OUTSIDE_END
chart.axes.vertical_axis.is_automatic_max_value = False
chart.axes.vertical_axis.max_value = 100
chart.show_data_labels_over_maximum = True
second_slide = presentation.slides.add_clone(slide)
second_chart = second_slide.shapes[0]
second_chart.show_data_labels_over_maximum = False
presentation.save("DataLabelsOverMaximum.pptx", slides.export.SaveFormat.PPTX)
The following images show the saved slides rendered by Microsoft PowerPoint. With True, the label 120 is visible at the upper boundary; with False, it is hidden. The label 60 remains visible, the axis maximum stays at 100, and the second data point remains 120 in both cases.
| show_data_labels_over_maximum = True | show_data_labels_over_maximum = False |
|---|---|
 |
 |
Chart Type
This example uses a 2D column chart with a value axis. Charts without a value axis, such as pie and doughnut charts, do not have an axis maximum to limit in this way.축에서 레이블 거리 설정
Use label_offset to control the distance between category axis labels and the axis. The value is a percentage of the maximum font size of the axis labels. This example creates a clustered column chart and sets the horizontal axis label offset to 500. This setting affects category axis labels rather than labels attached to individual data points.
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, 20, 20, 500, 300)
chart.axes.horizontal_axis.label_offset = 500
presentation.save("SetCategoryAxisLabelDistance_out.pptx", slides.export.SaveFormat.PPTX)
레이블 위치 조정
On a pie chart, adjust data label positions to improve spacing and make room for leader lines.
This example displays the value of the first data point, places its label outside the slice, and adjusts its x and y offsets. These offsets are relative to the chart width and height, respectively.
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.PIE, 50, 50, 200, 200)
series = chart.chart_data.series
label = series[0].labels[0]
label.data_label_format.show_value = True
label.data_label_format.position = charts.LegendDataLabelPosition.OUTSIDE_END
label.x = 0.71
label.y = 0.04
presentation.save("presentation.pptx", slides.export.SaveFormat.PPTX)
리더 라인 서식 지정
When pie chart labels sit outside their slices, leader lines help readers match each value to the correct slice. A contrasting color and a slightly thicker line can make these connections easier to follow, while transparency and a dashed style keep the lines visually unobtrusive.
Use leader_lines_format to format leader lines at the series' data label collection level. The settings in series.labels.leader_lines_format.line apply to the collection, rather than to an individual label.
This example creates a pie chart with default data, displays values outside the slices, and enables show_leader_lines. It moves two labels farther from their slices using x and y offsets, expressed as fractions of the chart width and height. No input presentation is required.
The line’s fill_format sets a solid blue color with an alpha value of 191 out of 255, giving approximately 25% transparency. width sets the thickness to 2 points, and dash_style makes the line dashed.
import aspose.slides as slides
import aspose.slides.charts as charts
import aspose.pydrawing as drawing
with slides.Presentation() as presentation:
slide = presentation.slides[0]
chart = slide.shapes.add_chart(charts.ChartType.PIE, 80, 50, 560, 400)
chart.has_legend = False
series = chart.chart_data.series[0]
label_format = series.labels.default_data_label_format
label_format.show_value = True
label_format.position = charts.LegendDataLabelPosition.OUTSIDE_END
label_format.show_leader_lines = True
# 두 레이블을 슬라이스에서 더 멀리 이동합니다.
series.labels[0].x = 0.10
series.labels[0].y = -0.05
series.labels[1].x = -0.10
series.labels[1].y = 0.05
line = series.labels.leader_lines_format.line
line.fill_format.fill_type = slides.FillType.SOLID
line.fill_format.solid_fill_color.color = drawing.Color.from_argb(191, 30, 90, 160)
line.width = 2
line.dash_style = slides.LineDashStyle.DASH
presentation.save("FormattedLeaderLines.pptx", slides.export.SaveFormat.PPTX)
Enabling leader lines does not guarantee that a line will appear for every label. Visibility depends on label placement and the chart’s layout behavior. In this example, the two displaced labels have visible leader lines; the labels that remain close to their slices do not need them.
The following image shows the saved FormattedLeaderLines.pptx rendered with Aspose.Slides:
열 차트 위에 데이터 레이블 여러 행 추가
This example creates a column chart with two rows of data labels above the plot area. Series A displays the visible columns, while Series B and Series C provide the additional labels. Their columns are hidden by removing the fill and outline. The overlap property aligns all three series with the same category centers.
The plot_area settings reserve space for the label rows. After validate_chart_layout calculates the default positions, x and y preserve the horizontal alignment and apply vertical offsets to arrange the labels in two rows. The numbers remain data labels linked to the series values; only the row headings are separate text shapes.
import aspose.slides as slides
import aspose.slides.charts as charts
import aspose.pydrawing as drawing
with slides.Presentation() as presentation:
slide = presentation.slides[0]
chart = slide.shapes.add_chart(charts.ChartType.CLUSTERED_COLUMN, 40, 40, 640, 200)
chart.has_title = False
chart.has_legend = False
chart.text_format.portion_format.font_height = 12
chart.chart_data.series.clear()
chart.chart_data.categories.clear()
workbook = chart.chart_data.chart_data_workbook
workbook.clear(0)
categories = ["North", "South", "East", "West"]
series_names = ["Series A", "Series B", "Series C"]
series_values = [
[35, 42, 28, 47],
[22, 31, 19, 26],
[12, 16, 14, 18]
]
for category_index, category_name in enumerate(categories):
category_cell = workbook.get_cell(0, category_index + 1, 0, category_name)
chart.chart_data.categories.add(category_cell)
for series_index, series_name in enumerate(series_names):
series_cell = workbook.get_cell(0, 0, series_index + 1, series_name)
series = chart.chart_data.series.add(series_cell, charts.ChartType.CLUSTERED_COLUMN)
for category_index in range(len(categories)):
value_cell = workbook.get_cell(0, category_index + 1, series_index + 1, series_values[series_index][category_index])
series.data_points.add_data_point_for_bar_series(value_cell)
if series_index > 0:
# B와 C의 열을 숨기지만 데이터 레이블은 유지합니다.
series.format.fill.fill_type = slides.FillType.NO_FILL
series.format.line.fill_format.fill_type = slides.FillType.NO_FILL
label_format = series.labels.default_data_label_format
label_format.show_value = True
label_format.text_format.portion_format.font_height = 12
label_fill = label_format.text_format.portion_format.fill_format
label_fill.fill_type = slides.FillType.SOLID
label_fill.solid_fill_color.color = drawing.Color.black
label_format.position = charts.LegendDataLabelPosition.INSIDE_BASE
# 세 시리즈 모두 동일한 범주 중심에 맞춥니다.
chart.chart_data.series[0].parent_series_group.overlap = 100
# 이 간결한 예제에서는 눈금선을 적게 사용합니다.
chart.axes.vertical_axis.is_automatic_major_unit = False
chart.axes.vertical_axis.major_unit = 10
# 플롯 위에 두 행의 데이터 레이블을 위한 공간을 확보합니다.
chart.plot_area.layout_target_type = charts.LayoutTargetType.INNER
chart.plot_area.x = 0.15
chart.plot_area.y = 0.32
chart.plot_area.width = 0.80
chart.plot_area.height = 0.48
chart.validate_chart_layout()
for series_index in range(1, len(series_names)):
series = chart.chart_data.series[series_index]
row_top = 0.15 if series_index == 1 else 0.03
for category_index in range(len(categories)):
data_label = series.data_points[category_index].label
# 기본 수평 위치를 유지합니다. Y는
# 기본 레이블 위치이며, 차트 높이 비율로 표현됩니다.
data_label.x = 0
data_label.y = row_top - data_label.actual_y / chart.height
# 행 머리글만 별도의 텍스트 도형입니다.
row_heading = slide.shapes.add_auto_shape(slides.ShapeType.RECTANGLE, chart.x, chart.y + row_top * chart.height, 85, 18)
row_heading.fill_format.fill_type = slides.FillType.NO_FILL
row_heading.line_format.fill_format.fill_type = slides.FillType.NO_FILL
row_heading.add_text_frame(series_names[series_index])
row_heading.text_frame.text_frame_format.margin_top = 0
row_heading.text_frame.text_frame_format.margin_bottom = 0
heading_format = row_heading.text_frame.paragraphs[0].portions[0].portion_format
heading_format.font_height = 12
heading_format.fill_format.fill_type = slides.FillType.SOLID
heading_format.fill_format.solid_fill_color.color = drawing.Color.black
presentation.save("multiple-rows-of-labels.pptx", slides.export.SaveFormat.PPTX)
FAQ
데이터 레이블이 빽빽한 차트에서 겹치는 것을 어떻게 방지할 수 있나요?
자동 레이블 배치, 리더 라인, 작은 글꼴 크기를 결합하고 필요하면 일부 필드(예: 범주)를 숨기거나 극값 또는 핵심 포인트에만 레이블을 표시합니다.
값이 0이거나 음수, 비어 있는 경우에만 레이블을 비활성화하려면 어떻게 해야 하나요?
레이블을 활성화하기 전에 데이터 포인트를 필터링하고 0, 음수 또는 누락된 값에 대해 표시를 끄는 규칙을 적용합니다.
PDF/이미지로 내보낼 때 레이블 스타일을 일관되게 유지하려면 어떻게 해야 하나요?
글꼴 패밀리와 크기를 명시적으로 설정하고 렌더링 환경에 해당 글꼴이 존재하는지 확인하여 대체 글꼴 사용을 방지합니다.