styleframe#

A library that wraps pandas and openpyxl and allows easy styling of dataframes.

Contents:

Installation and testing#

$ pip install styleframe

To make sure everything works as expected, run styleframe’s unittests:

from styleframe import tests

tests.run()

Basic Usage Examples#

StyleFrame’s init supports all the ways you are used to initiate pandas dataframe. An existing dataframe, a dictionary or a list of dictionaries:

from styleframe import StyleFrame, Styler, utils

sf = StyleFrame({'col_a': range(100)})

Applying a style to rows that meet a condition using pandas selecting syntax. In this example all the cells in the col_a column with the value > 50 will have blue background and a bold, sized 10 font:

sf.apply_style_by_indexes(
    indexes_to_style=sf[sf['col_a'] > 50],
    cols_to_style=['col_a'],
    styler_obj=Styler(
        bg_color=utils.colors.blue,
        bold=True,
        font_size=10
    )
)

Creating ExcelWriter object:

ew = StyleFrame.ExcelWriter(r'C:\my_excel.xlsx')
sf.to_excel(ew)
ew.close()

It is also possible to style a whole column or columns, and decide whether to style the headers or not:

sf.apply_column_style(
    cols_to_style=['a'],
    styler_obj=Styler(bg_color=utils.colors.green),
    style_header=True
)

Accessors#

.style#

Combined with .loc, allows easy selection/indexing based on style. For example:

only_rows_with_yellow_bg_color = sf.loc[sf['col_name'].style.bg_color == utils.colors.yellow]
only_rows_with_non_bold_text = sf.loc[~sf['col_name'].style.bold]

API Documentation#

styleframe#

The styleframe module contains a single class StyleFrame which servers as the main interaction point.

class StyleFrame(obj, styler_obj: Styler | None = None, columns: List[str] | None = None)[source]#

A wrapper class that wraps a pandas.DataFrame object and represent a stylized dataframe. Stores container objects that have values and styles that will be applied to excel

Parameters:

  • obj – Any object that pandas’ dataframe can be initialized with: an existing dataframe, a dictionary, a list of dictionaries or another StyleFrame.

  • styler_obj (Styler) – Will be used as the default style of all cells.

  • columns (None or list[str]) – Names of columns to use. Only applicable if obj is numpy.ndarray

classmethod ExcelWriter(path, **kwargs)[source]#

A shortcut for pandas.ExcelWriter, and accepts any argument it accepts except for engine

add_color_scale_conditional_formatting(start_type: str, start_value: int | float, start_color: str, end_type: str, end_value: int | float, end_color: str, mid_type: str | None = None, mid_value: int | float | None = None, mid_color: str | None = None, columns_range=None)[source]#
Parameters:

  • start_type (str: one of utils.conditional_formatting_types or any other type Excel supports) – The type for the minimum bound

  • start_value – The threshold for the minimum bound

  • start_color (str: one of utils.colors, hex string or color name ie ‘yellow’ Excel supports) – The color for the minimum bound

  • end_type (str: one of utils.conditional_formatting_types or any other type Excel supports) – The type for the maximum bound

  • end_value – The threshold for the maximum bound

  • end_color (str: one of utils.colors, hex string or color name ie ‘yellow’ Excel supports) – The color for the maximum bound

  • mid_type (None or str: one of utils.conditional_formatting_types or any other type Excel supports) – The type for the middle bound

  • mid_value – The threshold for the middle bound

  • mid_color (None or str: one of utils.colors, hex string or color name ie ‘yellow’ Excel supports) – The color for the middle bound

  • columns_range (None or list[str or int] or tuple[str or int])) – A two-elements list or tuple of columns to which the conditional formatting will be added to. If not provided at all the conditional formatting will be added to all columns. If a single element is provided then the conditional formatting will be added to the provided column. If two elements are provided then the conditional formatting will start in the first column and end in the second. The provided columns can be a column name, letter or index.

Returns:

self

Return type:

StyleFrame

apply_column_style(cols_to_style: str | List[str] | Tuple[str] | Set[str], styler_obj: Styler, style_header: bool = False, use_default_formats: bool = True, width: int | float | None = None, overwrite_default_style: bool = True)[source]#

Apply style to a whole column

Parameters:

  • cols_to_style (str or list or tuple or set) – The column names to style.

  • styler_obj (Styler) – A Styler object.

  • style_header (bool) – If True, the column(s) header will also be styled.

  • use_default_formats (bool) – If True, the default formats for date and times will be used.

  • width (None or int or float) – If provided, the new width for the specified columns.

  • overwrite_default_style (bool) – (bool) If True, the default style (the style used when initializing StyleFrame) will be overwritten. If False then the default style and the provided style wil be combined using Styler.combine() method.

Returns:

self

Return type:

StyleFrame

apply_headers_style(styler_obj: Styler, style_index_header: bool = True, cols_to_style: str | List[str] | Tuple[str] | Set[str] | None = None)[source]#

Apply style to the headers only

Parameters:

styler_obj (Styler) – The style to apply

New in version 1.6.1.

Parameters:

style_index_header (bool) – If True then the style will also be applied to the header of the index column

New in version 2.0.5.

Parameters:

cols_to_style (None or str or list[str] or tuple[str] or set[str]) – the columns to apply the style to, if not provided all the columns will be styled

Returns:

self

Return type:

StyleFrame

apply_style_by_indexes(indexes_to_style: list | tuple | int | Container, styler_obj: Styler, cols_to_style: str | List[str] | Tuple[str] | Set[str] | None = None, height: int | float | None = None, complement_style: Styler | None = None, complement_height: int | float | None = None, overwrite_default_style: bool = True)[source]#

Applies a certain style to the provided indexes in the dataframe in the provided columns

Parameters:

  • indexes_to_style (list or tuple or int or Container) –

    Indexes to which the provided style will be applied. Usually passed as pandas selecting syntax. For example,

    sf[sf['some_col'] == 20]

  • styler_obj (Styler) – Styler object that contains the style that will be applied to indexes in indexes_to_style

  • cols_to_style (None or str or list[str] or tuple[str] or set[str]) – The column names to apply the provided style to. If None all columns will be styled.

  • height (None or int or float) – If provided, set height for rows whose indexes are in indexes_to_style.

New in version 1.5.

Parameters:

  • complement_style (None or Styler) – Styler object that contains the style which will be applied to indexes not in indexes_to_style

  • complement_height (None or int or float) – Height for rows whose indexes are not in indexes_to_style. If not provided then height will be used (if provided).

New in version 1.6.

Parameters:

overwrite_default_style (bool) – If True, the default style (the style used when initializing StyleFrame) will be overwritten. If False then the default style and the provided style wil be combined using Styler.combine() method.

Returns:

self

Return type:

StyleFrame

classmethod read_excel(path: str, sheet_name: str | int = 0, read_style: bool = False, use_openpyxl_styles: bool = False, read_comments: bool = False, **kwargs) → StyleFrame[source]#

Creates a StyleFrame object from an existing Excel.

Note

read_excel() also accepts all arguments that pandas.read_excel() accepts as kwargs.

Parameters:

  • path (str) – The path to the Excel file to read.

  • sheet_name (str or int) – The sheet name to read. If an integer is provided then it be used as a zero-based sheet index. Default is 0.

  • read_style (bool) – If True the sheet’s style will be loaded to the returned StyleFrame object.

  • use_openpyxl_styles (bool) –

    If True (and read_style is also True) then the styles in the returned StyleFrame object will be Openpyxl’s style objects. If False, the styles will be Styler objects.

    Note

    Using use_openpyxl_styles=False is useful if you are going to filter columns or rows by style, for example:

    sf = sf[[col for col in sf.columns if col.style.font == utils.fonts.arial]]

  • read_comments (bool) – If True (and read_style is also True) cells’ comments will be loaded to the returned StyleFrame object. Note that reading comments without reading styles is currently not supported.

Returns:

StyleFrame object

Return type:

StyleFrame

classmethod read_excel_as_template(path: str, df: DataFrame, use_df_boundaries: bool = False, **kwargs) → StyleFrame[source]#

New in version 3.0.1.

Create a StyleFrame object from an excel template with data of the given DataFrame.

Note

read_excel_as_template() also accepts all arguments that read_excel() accepts as kwargs except for read_style which must be True.

Parameters:

  • path (str) – The path to the Excel file to read.

  • df (pandas.DataFrame) – The data to apply to the given template.

  • use_df_boundaries (bool) – If True the template will be cut according to the boundaries of the given DataFrame.

Returns:

StyleFrame object

Return type:

StyleFrame

rename(columns=None, inplace=False)[source]#

Renames the underlying dataframe’s columns

Parameters:

  • columns (dict) – A dictionary from old columns names to new columns names.

  • inplace (bool) – If False, a new StyleFrame object will be returned. If True, renames the columns inplace.

Returns:

self if inplace is True, new StyleFrame object is False

Return type:

StyleFrame

set_column_width(columns: str | List[str] | Tuple[str] | List[int] | Tuple[int], width: int | float) → StyleFrame[source]#

Set the width of the given columns

Parameters:
Returns:

self

Return type:

StyleFrame

set_column_width_dict(col_width_dict: Dict[str, int | float]) → StyleFrame[source]#
Parameters:

col_width_dict (dict[str, int or float]) – A dictionary from column names to width.

Returns:

self

Return type:

StyleFrame

set_row_height(rows: int | List[int] | Tuple[int] | Set[int], height: int | float) → StyleFrame[source]#

Set the height of the given rows

Parameters:
Returns:

self

Return type:

StyleFrame

set_row_height_dict(row_height_dict: Dict[int, int | float]) → StyleFrame[source]#
Parameters:

row_height_dict (dict[int, int or float]) – A dictionary from row indexes to height.

Returns:

self

Return type:

StyleFrame

style_alternate_rows(styles: List[Styler] | Tuple[Styler], **kwargs) → StyleFrame[source]#

New in version 1.2.

Applies the provided styles to rows in an alternating manner.

Note

style_alternate_rows() also accepts all arguments that apply_style_by_indexes() accepts as kwargs.

Parameters:

styles (list[Styler] or tuple[Styler]) – List or tuple of Styler objects to be applied to rows in an alternating manner

Returns:

self

Return type:

StyleFrame

to_excel(excel_writer: str | ExcelWriter | Path = 'output.xlsx', sheet_name: str = 'Sheet1', allow_protection: bool = False, right_to_left: bool = False, columns_to_hide: None | str | list | tuple | set = None, row_to_add_filters: int | None = None, columns_and_rows_to_freeze: str | None = None, best_fit: None | str | list | tuple | set = None, index: bool = False, **kwargs) → ExcelWriter[source]#

Saves the dataframe to excel and applies the styles.

Note

to_excel() also accepts all arguments that pandas.DataFrame.to_excel() accepts as kwargs.

Parameters:

  • excel_writer (str or pandas.ExcelWriter or pathlib.Path) – File path or existing ExcelWriter

  • sheet_name (str) – Name of sheet the StyleFrame will be exported to

  • allow_protection (bool) – Allow to protect the cells that specified as protected. If used protection=True in a Styler object this must be set to True.

  • right_to_left (bool) – Makes the sheet right-to-left.

  • columns_to_hide (None or str or list or tuple or set) – Columns names to hide.

  • row_to_add_filters (None or int) – Add filters to the given row index, starts from 0 (which will add filters to header row).

  • columns_and_rows_to_freeze (None or str) – Column and row string to freeze. For example “C3” will freeze columns: A, B and rows: 1, 2.

New in version 1.4.

Parameters:

best_fit (None or str or list or tuple or set) –

single column, list, set or tuple of columns names to attempt to best fit the width for.

Note

best_fit will attempt to calculate the correct column-width based on the longest value in each provided column. However this isn’t guaranteed to work for all fonts (works best with monospaced fonts). The formula used to calculate a column’s width is equivalent to

(len(longest_value_in_column) + A_FACTOR) * P_FACTOR

The default values for A_FACTOR and P_FACTOR are 13 and 1.3 respectively, and can be modified before calling StyleFrame.to_excel by directly modifying StyleFrame.A_FACTOR and StyleFrame.P_FACTOR

New in version 4.2.

Parameters:

index (bool) – Write row names.

Return type:

pandas.ExcelWriter

styler#

class Styler(bg_color: str | None = None, bold: bool = False, font: str = 'Arial', font_size: int | float = 12.0, font_color: str | None = None, number_format: str = 'General', protection: bool = False, underline: str | None = None, border_type: str | Set[str] | Dict[str, str] = 'thin', horizontal_alignment: str = 'center', vertical_alignment: str = 'center', wrap_text: bool = True, shrink_to_fit: bool = True, fill_pattern_type: str = 'solid', indent: int | float = 0.0, comment_author: str | None = None, comment_text: str | None = None, text_rotation: int = 0, date_format: str = 'DD/MM/YY', time_format: str = 'HH:MM', date_time_format: str = 'DD/MM/YY HH:MM', strikethrough: bool = False, italic: bool = False)[source]#

Used to represent a style

Parameters:

  • bg_color (str: one of utils.colors, hex string or color name ie ‘yellow’ Excel supports) – The background color

  • bold (bool) – If True, a bold typeface is used

  • font (str: one of utils.fonts or other font name Excel supports) – The font to use

  • font_size (int) – The font size

  • font_color (str: one of utils.colors, hex string or color name ie ‘yellow’ Excel supports) – The font color

  • number_format (str: one of utils.number_formats or any other format Excel supports) – The format of the cell’s value

  • protection (bool) – If True, the cell/column will be write-protected

  • underline (str: one of utils.underline or any other underline Excel supports) – The underline type

Changed in version 4.2.

Parameters:

border_type (str or set[str] or dict[str, str]) –

  • If provided a string (one of utils.borders or any other border type Excel supports): all borders will be set to that type.

  • If provided a set of strings (utils.border_locations or any other border location Excel supports): each provided border will be set to the default border type.

  • If provided a dict (from location, one of utils.border_locations or any other border location Excel supports) to border type (one of utils.borders or any other border type Excel supports): each provided border will be set to the provided border type.

New in version 1.2.

Parameters:

  • horizontal_alignment (str: one of utils.horizontal_alignments or any other horizontal alignment Excel supports) – Text’s horizontal alignment

  • vertical_alignment (str: one of utils.vertical_alignments or any other vertical alignment Excel supports) – Text’s vertical alignment

New in version 1.3.

Parameters:

  • wrap_text (bool) –

  • shrink_to_fit (bool) –

  • fill_pattern_type (str: one of utils.fill_pattern_types or any other fill pattern type Excel supports) – Cells’s fill pattern type

  • indent (int) –

  • comment_author (str) –

  • comment_text (str) –

  • text_rotation (int) – Integer in the range 0 - 180

New in version 4.0.

Parameters:

Note

For any of date_format, time_format and date_time_format to take effect, the value being styled must be an actual date/time/datetime object.

New in version 4.1.

Parameters:

  • strikethrough (bool) –

  • italic (bool) –

classmethod combine(*styles: Styler)[source]#

New in version 1.6.

Used to combine Styler objects. The right-most object has precedence. For example:

Styler.combine(Styler(bg_color='yellow', font_size=24), Styler(bg_color='blue'))

will return

Styler(bg_color='blue', font_size=24)
Parameters:

styles (list or tuple or set) – Iterable of Styler objects

Returns:

self

Return type:

Styler

utils#

The utils module contains the most widely used values for styling elements such as colors and border types for convenience. It is possible to directly use a value that is not present in the utils module as long as the spreadsheet software recognises it.

class number_formats[source]#
Variables:

  • general (str) – ‘General’

  • general_integer (str) – ‘0’

  • general_float (str) – ‘0.00’

  • percent (str) – ‘0.0%’

  • thousands_comma_sep (str) – ‘#,##0’

  • date (str) – ‘DD/MM/YY’

  • time_24_hours (str) – ‘HH:MM’

  • time_24_hours_with_seconds (str) – ‘HH:MM:SS’

  • time_12_hours (str) – ‘h:MM AM/PM’

  • time_12_hours_with_seconds (str) – ‘h:MM:SS AM/PM’

  • date_time (str) – ‘DD/MM/YY HH:MM’

  • date_time_with_seconds (str) – ‘DD/MM/YY HH:MM:SS’

static decimal_with_num_of_digits(num_of_digits: int) → str[source]#

New in version 1.6.

Parameters:

num_of_digits (int) – Number of digits after the decimal point

Returns:

A format string that represents a floating point number with the provided number of digits after the decimal point.

For example, utils.number_formats.decimal_with_num_of_digits(2) will return '0.00'

Return type:

str

class colors[source]#
Variables:

  • white (str) – ‘00FFFFFF’

  • blue (str) – ‘000000FF’

  • dark_blue (str) – ‘00000080’

  • yellow (str) – ‘00FFFF00’

  • dark_yellow (str) – ‘00808000’

  • green (str) – ‘0000FF00’

  • dark_green (str) – ‘00008000’

  • black (str) – ‘00000000’

  • red (str) – ‘00FF0000’

  • dark_red (str) – ‘00800000’

  • purple (str) – ‘800080’

  • grey (str) – ‘D3D3D3’

class fonts[source]#

New in version 1.1.

Variables:

  • aegean (str) – ‘Aegean’

  • aegyptus (str) – ‘Aegyptus’

  • aharoni (str) – ‘Aharoni CLM’

  • anaktoria (str) – ‘Anaktoria’

  • analecta (str) – ‘Analecta’

  • anatolian (str) – ‘Anatolian’

  • arial (str) – ‘Arial’

  • calibri (str) – ‘Calibri’

  • david (str) – ‘David CLM’

  • dejavu_sans (str) – ‘DejaVu Sans’

  • ellinia (str) – ‘Ellinia CLM’

class borders[source]#
Variables:

  • dash_dot (str) – ‘dashDot’

  • dash_dot_dot (str) – ‘dashDotDot’

  • dashed (str) – ‘dashed’

  • default_grid (str) – ‘default_grid’

  • dotted (str) – ‘dotted’

  • double (str) – ‘double’

  • hair (str) – ‘hair’

  • medium (str) – ‘medium’

  • medium_dash_dot (str) – ‘mediumDashDot’

  • medium_dash_dot_dot (str) – ‘mediumDashDotDot’

  • medium_dashed (str) – ‘mediumDashed’

  • slant_dash_dot (str) – ‘slantDashDot’

  • thick (str) – ‘thick’

  • thin (str) – ‘thin’

class border_locations[source]#

New in version 4.2.

Variables:

  • top (str) – ‘top’

  • bottom (str) – ‘bottom’

  • left (str) – ‘left’

  • right (str) – ‘right’

class horizontal_alignments[source]#
Variables:

  • general (str) – ‘general’

  • left (str) – ‘left’

  • center (str) – ‘center’

  • right (str) – ‘right’

  • fill (str) – ‘fill’

  • justify (str) – ‘justify’

  • center_continuous (str) – ‘centerContinuous’

  • distributed (str) – ‘distributed’

class vertical_alignments[source]#
Variables:

  • top (str) – ‘top’

  • center (str) – ‘center’

  • bottom (str) – ‘bottom’

  • justify (str) – ‘justify’

  • distributed (str) – ‘distributed’

class underline[source]#
Variables:

  • single (str) – ‘single’

  • double (str) – ‘double’

class fill_pattern_types[source]#

New in version 1.2.

Variables:

  • solid (str) – ‘solid’

  • dark_down (str) – ‘darkDown’

  • dark_gray (str) – ‘darkGray’

  • dark_grid (str) – ‘darkGrid’

  • dark_horizontal (str) – ‘darkHorizontal’

  • dark_trellis (str) – ‘darkTrellis’

  • dark_up (str) – ‘darkUp’

  • dark_vertical (str) – ‘darkVertical’

  • gray0625 (str) – ‘gray0625’

  • gray125 (str) – ‘gray125’

  • light_down (str) – ‘lightDown’

  • light_gray (str) – ‘lightGray’

  • light_grid (str) – ‘lightGrid’

  • light_horizontal (str) – ‘lightHorizontal’

  • light_trellis (str) – ‘lightTrellis’

  • light_up (str) – ‘lightUp’

  • light_vertical (str) – ‘lightVertical’

  • medium_gray (str) – ‘mediumGray’

class conditional_formatting_types[source]#
Variables:

  • num (str) – ‘num’

  • percent (str) – ‘percent’

  • max (str) – ‘max’

  • min (str) – ‘min’

  • formula (str) – ‘formula’

  • percentile (str) – ‘percentile’

Commandline Interface#

General Information#

Starting with version 1.1 styleframe offers a commandline interface that lets you create an xlsx file from a json file.

Usage#

Flag

Explanation

-v

Displays the installed versions of styleframe and its dependencies

--json_path/--json-path

Path to the json file

--json

The json string which defines the Excel file, see example below

--output_path/--output-path

Path to the output xlsx file. If not provided defaults to output.xlsx

--test

Execute the tests

Usage Examples#

$ styleframe --json_path data.json --output_path data.xlsx

$ styleframe --json "[{\"sheet_name\": \"sheet_1\", \"columns\": [{\"col_name\": \"col_a\", \"cells\": [{\"value\": 1}]}]}]"

Note

You may need to use different syntax to pass a JSON string depending on your OS and terminal application.

JSON Format#

The input JSON should be thought of as an hierarchy of predefined entities, some of which correspond to a Python class used by StyleFrame. The top-most level should be a list of sheet entities (see below).

The provided JSON is validated against the following schema:

{
    "$schema": "http://json-schema.org/draft-04/schema#",
    "title": "sheets",
    "definitions": {
        "Sheet": {
            "$id": "#sheet",
            "title": "sheet",
            "type": "object",
            "properties": {
                "sheet_name": {
                    "type": "string"
                },
                "columns": {
                    "type": "array",
                    "items": {
                        "$ref": "#/definitions/Column"
                    },
                    "minItems": 1
                },
                "row_heights": {
                    "type": "object"
                },
                "extra_features": {
                    "type": "object"
                },
                "default_styles": {
                    "type": "object",
                    "properties": {
                        "headers": {
                            "$ref": "#/definitions/Style"
                        },
                        "cells": {
                            "$ref": "#/definitions/Style"
                        }
                    },
                    "additionalProperties": false
                }
            },
            "required": [
                "sheet_name",
                "columns"
            ]
        },
        "Column": {
            "$id": "#column",
            "title": "column",
            "type": "object",
            "properties": {
                "col_name": {
                    "type": "string"
                },
                "style": {
                    "$ref": "#/definitions/Style"
                },
                "width": {
                    "type": "number"
                },
                "cells": {
                    "type": "array",
                    "items": {
                        "$ref": "#/definitions/Cell"
                    }
                }
            },
            "required": [
                "col_name",
                "cells"
            ]
        },
        "Cell": {
            "$id": "#cell",
            "title": "cell",
            "type": "object",
            "properties": {
                "value": {},
                "style": {
                    "$ref": "#/definitions/Style"
                }
            },
            "required": [
                "value"
            ],
            "additionalProperties": false
        },
        "Style": {
            "$id": "#style",
            "title": "style",
            "type": "object",
            "properties": {
                "bg_color": {
                    "type": "string"
                },
                "bold": {
                    "type": "boolean"
                },
                "font": {
                    "type": "string"
                },
                "font_size": {
                    "type": "number"
                },
                "font_color": {
                    "type": "string"
                },
                "number_format": {
                    "type": "string"
                },
                "protection": {
                    "type": "boolean"
                },
                "underline": {
                    "type": "string"
                },
                "border_type": {
                    "type": "string"
                },
                "horizontal_alignment": {
                    "type": "string"
                },
                "vertical_alignment": {
                    "type": "string"
                },
                "wrap_text": {
                    "type": "boolean"
                },
                "shrink_to_fit": {
                    "type": "boolean"
                },
                "fill_pattern_type": {
                    "type": "string"
                },
                "indent": {
                    "type": "number"
                }
            },
            "additionalProperties": false
        }
    },
    "type": "array",
    "items": {
        "$ref": "#/definitions/Sheet"
    },
    "minItems": 1
}

An example JSON:

[
  {
    "sheet_name": "Sheet1",
    "default_styles": {
      "headers": {
        "font_size": 17,
        "bg_color": "yellow"
      },
      "cells": {
        "bg_color": "red"
      }
    },
    "columns": [
      {
        "col_name": "col_a",
        "style": {"bg_color": "blue", "font_color": "yellow"},
        "width": 30,
        "cells": [
          {
            "value": 1
          },
          {
            "value": 2,
            "style": {
              "bold": true,
              "font": "Arial",
              "font_size": 30,
              "font_color": "green",
              "border_type": "double"
            }
          }
        ]
      },
      {
        "col_name": "col_b",
        "cells": [
          {
            "value": 3
          },
          {
            "value": 4,
            "style": {
              "bold": true,
              "font": "Arial",
              "font_size": 16
            }
          }
        ]
      }
    ],
    "row_heights": {
      "3": 40
    },
    "extra_features": {
      "row_to_add_filters": 0,
      "columns_and_rows_to_freeze": "A7",
      "startrow": 5
    }
  }
]

style#

Corresponds to Styler class.

This entity uses the arguments of Styler.__init__() as keys. Any missing keys in the JSON will be given the same default values.

"style": {"bg_color": "yellow", "bold": true}

cell#

This entity represents a single cell in the sheet.

Required keys:

"value" - The cell’s value.

Optional keys:

"style" - The style entity for this cell. If not provided, the style provided to the coloumn entity will be used. If that was not provided as well, the default Styler.__init__() values will be used.

{"value": 42, "style": {"border": "double"}}

column#

This entity represents a column in the sheet.

Required keys:

"col_name" - The column name.

"cells" - A list of cell entities.

Optional keys:

"style" - A style used for the entire column. If not provided the default Styler.__init__() values will be used.

"width" - The column’s width. If not provided Excel’s default column width will be used.

sheet#

This entity represents the entire sheet.

Required keys:

"sheet_name" - The sheet’s name.

"columns" - A list of column entities.

Optional keys:

"default_styles" - A JSON object with items as keys and style entities as values. Currently supported items: headers and cells.

"default_styles": {"headers": {"bg_color": "blue"}}

"row_heights" - A JSON object with rows indexes as keys and heights as value.

"extra_features" - A JSON that contains the same arguments as the to_excel method, such as "row_to_add_filters", "columns_and_rows_to_freeze", "columns_to_hide", "right_to_left" and "allow_protection". You can also use other arguments that Pandas’ "to_excel" accepts.