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Charts are essential tools for data visualization, transforming abstract numbers into intuitive graphical representations. Embedding charts in Word documents makes reports, proposals, and analysis documents more compelling. The traditional approach of manually inserting charts in Word and editing data one by one is inefficient and prone to inconsistency. By creating charts programmatically with Python, you can build an automated pipeline from data to documents, generating standardized reports with charts in batch. This article introduces how to create multiple chart types in Word documents using Python, including setting chart titles, data series, and axis formats.

Why Create Charts Programmatically

Compared to manual operation, the programmatic approach offers the following advantages:

Batch generation: Automatically generate multiple report documents with charts from data sources
Data synchronization: Chart data comes directly from program variables or database queries, ensuring real-time accuracy
Consistent styling: Uniformly define chart dimensions, title formats, and axis styles through code, eliminating human inconsistency
Pipeline integration: Embed chart creation into document automation workflows, achieving end-to-end automation from data collection to report generation

Environment Setup

This article uses Spire.Doc for Python, which provides APIs for inserting and customizing charts in Word documents.

pip install Spire.Doc

After installation, you can import the relevant modules in your Python script and start working.

Creating a Column Chart

Column charts are one of the most commonly used chart types, suitable for comparing values across categories. The following code demonstrates how to create a column chart with a data series:

from spire.doc import *

outputFile = "ColumnChart.docx"

# Create a document and add a section
document = Document()
section = document.AddSection()

# Add descriptive text
section.AddParagraph().AppendText("Column chart.")

# Add a paragraph to host the chart
newPara = section.AddParagraph()

# Append a column chart with specified width and height
shape = newPara.AppendChart(ChartType.Column, float(500), float(300))
chart = shape.Chart

# Clear default data series
chart.Series.Clear()

# Add a custom data series
chart.Series.Add("Test Series",
                 ["Word", "PDF", "Excel", "GoogleDocs", "Office"], [
                     float(1900000),
                     float(850000),
                     float(2100000),
                     float(600000),
                     float(1500000)
                 ])

# Set Y-axis number format
chart.AxisY.NumberFormat.FormatCode = "#,##0"

# Save the document
document.SaveToFile(outputFile, FileFormat.Docx)
document.Dispose()

The generated Word document:

Key steps in the code:

Append chart: The AppendChart(ChartType.Column, width, height) method adds a chart shape to the paragraph and returns a chart shape object.
Data series: The Series.Add() method accepts three parameters — series name, category list (X-axis), and value list (Y-axis).
Axis format: AxisY.NumberFormat.FormatCode sets the display format for Y-axis labels. "#,##0" applies thousand separators.

Creating a Line Chart with Title

Line charts are ideal for showing trends over time or categories. The following code creates a line chart with multiple data series and a chart title:

from spire.doc import *

outputFile = "LineChart.docx"

document = Document()
section = document.AddSection()
section.AddParagraph().AppendText("Line chart.")

newPara = section.AddParagraph()

# Append a line chart
shape = newPara.AppendChart(ChartType.Line, 500.0, 300.0)
chart = shape.Chart

# Set chart title
title = chart.Title
title.Text = "My Chart"
title.Show = True
title.Overlay = True

# Add multiple data series
seriesColl = chart.Series
seriesColl.Clear()

categories = ["C1", "C2", "C3", "C4", "C5", "C6"]

seriesColl.Add("AW Series 1", categories, [1.0, 2.0, 2.5, 4.0, 5.0, 6.0])
seriesColl.Add("AW Series 2", categories, [2.0, 3.0, 3.5, 6.0, 6.5, 7.0])

document.SaveToFile(outputFile, FileFormat.Docx)
document.Dispose()

The generated Word document:

Title settings explained:

title.Text: Sets the title text content
title.Show: Controls whether the title is displayed
title.Overlay: When set to True, the title overlays the chart without taking up additional space

Creating a Pie Chart

Pie charts display the proportional relationship of parts to a whole. A pie chart requires only one data series:

from spire.doc import *

outputFile = "PieChart.docx"

document = Document()
section = document.AddSection()
section.AddParagraph().AppendText("Pie chart.")

newPara = section.AddParagraph()

# Append a pie chart
shape = newPara.AppendChart(ChartType.Pie, 500.0, 300.0)
chart = shape.Chart

# Add a data series
chart.Series.Add("Test Series", ["Word", "PDF", "Excel"],
                          [2.7, 3.2, 0.8])

document.SaveToFile(outputFile, FileFormat.Docx)
document.Dispose()

The data series addition works the same way as with column charts. ChartType.Pie specifies the chart type as a pie chart.

Creating Scatter and Bubble Charts

Scatter charts show the correlation between two sets of data, while bubble charts add a third dimension to represent data weight.

Scatter chart:

from spire.doc import *

outputFile = "ScatterChart.docx"

document = Document()
section = document.AddSection()
section.AddParagraph().AppendText("Scatter chart.")

newPara = section.AddParagraph()

# Append a scatter chart
shape = newPara.AppendChart(ChartType.Scatter, 450.0, 300.0)
chart = shape.Chart
chart.Series.Clear()

# Add a data series with X and Y value lists
chart.Series.Add("Scatter chart", [1.0, 2.0, 3.0, 4.0, 5.0],
                 [1.0, 20.0, 40.0, 80.0, 160.0])

document.SaveToFile(outputFile, FileFormat.Docx)
document.Dispose()

Bubble chart:

from spire.doc import *

outputFile = "BubbleChart.docx"

document = Document()
section = document.AddSection()
section.AddParagraph().AppendText("Bubble chart.")

newPara = section.AddParagraph()

# Append a bubble chart
shape = newPara.AppendChart(ChartType.Bubble, float(500), float(300))
chart = shape.Chart
chart.Series.Clear()

# Add a data series with X, Y, and bubble size lists
chart.Series.Add("Test Series",
                 [2.9, 3.5, 1.1, 4.0, 4.0],
                 [1.9, 8.5, 2.1, 6.0, 1.5],
                 [9.0, 4.5, 2.5, 8.0, 5.0])

document.SaveToFile(outputFile, FileFormat.Docx)
document.Dispose()

The key difference lies in the number of parameters passed to Series.Add(): scatter charts take X and Y lists, while bubble charts take an additional third list for bubble sizes.

Creating a 3D Surface Chart

3D surface charts are suitable for displaying the three-dimensional distribution of multivariate data. The following code creates a surface chart with three data series:

from spire.doc import *

outputFile = "Surface3DChart.docx"

document = Document()
section = document.AddSection()
section.AddParagraph().AppendText("Surface3D chart.")

newPara = section.AddParagraph()

# Append a 3D surface chart
shape = newPara.AppendChart(ChartType.Surface3D, 500.0, 300.0)
chart = shape.Chart
chart.Series.Clear()

# Set title
chart.Title.Text = "My chart"

# Add multiple data series
categories = ["Word", "PDF", "Excel", "GoogleDocs", "Office"]

chart.Series.Add("Series 1", categories,
                 [1900000.0, 850000.0, 2100000.0, 600000.0, 1500000.0])
chart.Series.Add("Series 2", categories,
                 [900000.0, 50000.0, 1100000.0, 400000.0, 250000.0])
chart.Series.Add("Series 3", categories,
                 [500000.0, 820000.0, 1500000.0, 400000.0, 100000.0])

document.SaveToFile(outputFile, FileFormat.Docx)
document.Dispose()

By adding multiple data series, the surface chart can simultaneously display the 3D distribution of multiple data groups, making it suitable for comparative analysis.

Practical Tips

Auto-Selecting Chart Types Based on Data

In practice, you can encapsulate chart creation in a function to quickly add multiple charts to a single document:

def create_chart(document, chart_type, title, categories, values):
    section = document.AddSection()
    section.AddParagraph().AppendText(title)
    para = section.AddParagraph()
    shape = para.AppendChart(chart_type, 500.0, 300.0)
    chart = shape.Chart
    chart.Series.Clear()
    chart.Title.Text = title
    chart.Title.Show = True
    chart.Series.Add("Data", categories, values)
    return chart

# Usage example
doc = Document()
create_chart(doc, ChartType.Column, "Quarterly Sales",
             ["Q1", "Q2", "Q3", "Q4"], [120.0, 150.0, 180.0, 200.0])
create_chart(doc, ChartType.Line, "Monthly Growth Trend",
             ["Jan", "Feb", "Mar", "Apr", "May", "Jun"],
             [10.0, 15.0, 22.0, 28.0, 35.0, 42.0])
doc.SaveToFile("Report.docx", FileFormat.Docx)
doc.Dispose()

After encapsulating chart creation as a function, you can quickly add various chart types to the same document, which is useful for generating comprehensive reports with multiple data views.

Setting Axis Number Formats

For large numerical data, setting axis number formats improves readability:

# Thousand separator format
chart.AxisY.NumberFormat.FormatCode = "#,##0"

# Percentage format
chart.AxisY.NumberFormat.FormatCode = "0%"

# Thousand separator with decimal places
chart.AxisY.NumberFormat.FormatCode = "#,##0.00"

Conclusion

This article covered the complete workflow for creating charts in Word documents using Python, including six chart types: column, line, pie, scatter, bubble, and 3D surface charts.

Key takeaways:

Use AppendChart(ChartType, width, height) to append a chart to a paragraph, specifying the chart type via the ChartType enum
Add data series with chart.Series.Add() — the number of parameters varies by chart type (scatter charts need X/Y lists, bubble charts need X/Y/size lists)
Set chart title text, visibility, and overlay using chart.Title
Customize axis number display format with chart.AxisY.NumberFormat.FormatCode

With these skills, you can integrate chart creation into report generation pipelines, automatically producing Word documents with visualized charts from business data, significantly improving the efficiency and consistency of data report generation.