Individual cells

These options address specific cells by reference ("B7") rather than by column, and they are applied after the DataFrame is written -- so a cells entry can deliberately overwrite a value that came from the data.

Arbitrary Cell Writes

Write values to specific cells, optionally overwriting DataFrame data:

import xlsxturbo
import pandas as pd

df = pd.DataFrame({
    'product': ['Widget A', 'Widget B'],
    'price': [19.99, 29.99]
})

# Write simple values to specific cells
xlsxturbo.df_to_xlsx(df, "report.xlsx",
    cells={
        'D1': 'Notes',          # String
        'D2': 'Reviewed',       # String
        'D3': 42,               # Number
        'E1': True              # Boolean
    }
)

# Write with number formatting (e.g., force text format for long numbers)
xlsxturbo.df_to_xlsx(df, "report.xlsx",
    cells={
        'C5': 'Total',
        'C6': {'value': '934728173849', 'num_format': '@'},  # Text format
        'C7': {'value': 0.15, 'num_format': '0.00%'}         # Percentage
    }
)

# Overwrite DataFrame cells (cells are written after data)
xlsxturbo.df_to_xlsx(df, "report.xlsx",
    cells={
        'A2': 'OVERRIDE',  # Replaces 'Widget A' in the output
    }
)

Cell value format: - Simple: {'A1': 'text'}, {'B2': 42}, {'C3': True} - With formatting: {'A1': {'value': '...', 'num_format': '@'}} - Additional format options: align_horizontal, align_vertical, wrap_text - font_name selects a font family, for example 'Arial'. - quote_prefix=True sets Excel's quote marker without inserting an apostrophe into the stored value. To keep leading zeros, pass a string value; use num_format='@' for text formatting. The marker itself does not convert numbers to strings.

Notes: - Cells are written after all DataFrame data, so they can overwrite existing values - Works with both df_to_xlsx and dfs_to_xlsx (global or per-sheet) - Not available in constant memory mode

For full styling, pass a format dictionary using the same keys as column_formats: fonts, fills, borders, alignment and number formats. For example:

xlsxturbo.df_to_xlsx(df, "report.xlsx", cells={
    "D1": {"value": "Summary", "format": {
        "bold": True, "font_size": 14, "font_color": "#FFFFFF",
        "bg_color": "#336699", "border_bottom": "thick",
    }},
    "D2": {"value": "000123", "format": {
        "font_name": "Arial", "num_format": "@", "quote_prefix": True,
    }},
})

Existing shorthand fields (num_format, font_name, quote_prefix, align_horizontal, align_vertical, wrap_text) override the corresponding format fields when supplied with a non-None value, including explicit False. An omitted or None format leaves the existing shorthand behavior unchanged. The format dictionary is never modified, so it can be shared between cells.

Hyperlinks

Add clickable links to cells:

import xlsxturbo
import pandas as pd

df = pd.DataFrame({
    'company': ['Anthropic', 'Google', 'Microsoft'],
    'product': ['Claude', 'Gemini', 'Copilot'],
})

# Add hyperlinks to a new column (C) after the data columns (A, B with header)
xlsxturbo.df_to_xlsx(df, "companies.xlsx",
    autofit=True,
    hyperlinks=[
        # Header for the links column
        ('C1', 'https://example.com', 'Website'),
        # Links with company names as display text
        ('C2', 'https://anthropic.com', 'anthropic.com'),
        ('C3', 'https://google.com', 'google.com'),
        ('C4', 'https://microsoft.com', 'microsoft.com'),
    ]
)

Hyperlink format: - Tuple of (cell, url) or (cell, url, display_text) - Cell uses Excel notation: 'A1', 'B5', etc. - Display text is optional; if omitted, the URL is shown

Notes: - Hyperlinks write to the specified cell position (overwrites existing content) - To add a "links column", target cells beyond your DataFrame columns (as shown above) - Works with both df_to_xlsx and dfs_to_xlsx (global or per-sheet) - Not available in constant memory mode

Comments/Notes

Add cell annotations (hover to view):

import xlsxturbo
import pandas as pd

df = pd.DataFrame({
    'product': ['Widget A', 'Widget B'],
    'price': [19.99, 29.99]
})

xlsxturbo.df_to_xlsx(df, "report.xlsx",
    comments={
        # Simple text comment
        'A1': 'This column contains product names',
        # Comment with author
        'B1': {'text': 'Prices in USD', 'author': 'Finance Team'}
    }
)

Comment format: - Simple: {'A1': 'Note text'} - With author: {'A1': {'text': 'Note text', 'author': 'Name'}}

Notes: - Comments appear as small red triangles in the cell corner - Hover over the cell to see the comment - Works with both df_to_xlsx and dfs_to_xlsx (global or per-sheet) - Not available in constant memory mode

Checkboxes

Add interactive checkboxes to cells (Excel for Microsoft 365, Sept 2024+). Renders as TRUE or FALSE that can be toggled in Excel:

import xlsxturbo
import pandas as pd

df = pd.DataFrame({'Task': ['Write docs', 'Run tests', 'Ship release']})

xlsxturbo.df_to_xlsx(df, "checklist.xlsx",
    checkboxes={
        # Bare bool - simplest form
        'B2': True,
        'B3': False,
        'B4': False,
        # Dict form with cell format
        'C2': {'checked': True, 'format': {'bg_color': '#C6EFCE', 'bold': True}},
    }
)

Checkbox format: - Simple: {'A1': True} or {'A1': False} - With format: {'A1': {'checked': True, 'format': {...}}}

Available options (dict form): - checked (bool, required): Initial state - format (dict): Optional cell format. Accepts the same keys as Column Formatting (bg_color, font_color, border, bold, etc.)

Notes: - Checkboxes are written AFTER DataFrame data — use cell refs that don't collide with data rows - Requires Excel for Microsoft 365 (Sept 2024 or later); older versions will display the underlying boolean value instead - Works with both df_to_xlsx and dfs_to_xlsx (global or per-sheet) - Not available in constant memory mode