StyleFrame¶

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

Contents:

Installation and testing¶

$ pip install styleframe

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

from StyleFrame import tests

tests.run()

Getting Started¶

Basic Usage¶

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 used to export StyleFrame to Excel:

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

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)

Example with ‘real world’ data¶

Note

The data used in this example is the first 500 rows of of Kaggle’s “StackLite: Stack Overflow questions and tags” dataset available at https://www.kaggle.com/stackoverflow/stacklite

Note

These examples are focusing on StyleFrame’s styling abilities rather than on pandas data mingling abilities (and the subset of these abilities that is available with StyleFrame)

Setting up

import pandas as pd
from datetime import timedelta
from StyleFrame import StyleFrame, Styler, utils

df = pd.read_csv('data.csv', parse_dates=['CreationDate', 'ClosedDate', 'DeletionDate'])
sf = StyleFrame(df)

Using red background for Id column for rows with questions that were closed less than 5 minutes after creation

sf.apply_style_by_indexes(indexes_to_style=sf[sf['ClosedDate'] - sf['CreationDate'] < timedelta(minutes=5)],
                          styler_obj=Styler(bg_color=utils.colors.red),
                          cols_to_style=['Id'])

Changing the width of the date columns so their content fits nicely

sf.set_column_width(columns=['CreationDate', 'ClosedDate', 'DeletionDate'],
                    width=20)

Using color-scale conditional formatting for the questions’ scores, based on percentage

sf.add_color_scale_conditional_formatting(start_type=utils.conditional_formatting_types.percentile,
                                          start_value=0,
                                          start_color=utils.colors.red,
                                          end_type=utils.conditional_formatting_types.percentile,
                                          end_value=100,
                                          end_color=utils.colors.green,
                                          columns_range=['Score'])

Adding filters to the header row, freezing it and exporting to Excel

sf.to_excel('output.xlsx', columns_and_rows_to_freeze='A2', row_to_add_filters=0,
            best_fit=['OwnerUserId', 'AnswerCount']).save()

Entire code

import pandas as pd
from datetime import timedelta
from StyleFrame import StyleFrame, Styler, utils

# data.csv contains the first 500 rows of Kaggle's "StackLite: Stack Overflow questions and tags"
# dataset available at https://www.kaggle.com/stackoverflow/stacklite
df = pd.read_csv('data.csv', parse_dates=['CreationDate', 'ClosedDate', 'DeletionDate'])

sf = StyleFrame(df)

sf.apply_style_by_indexes(indexes_to_style=sf[sf['ClosedDate'] - sf['CreationDate'] < timedelta(minutes=5)],
                          styler_obj=Styler(bg_color=utils.colors.red),
                          cols_to_style=['Id'])

sf.set_column_width(columns=['CreationDate', 'ClosedDate', 'DeletionDate'],
                    width=20)

sf.add_color_scale_conditional_formatting(start_type=utils.conditional_formatting_types.percentile,
                                          start_value=0,
                                          start_color=utils.colors.red,
                                          end_type=utils.conditional_formatting_types.percentile,
                                          end_value=100,
                                          end_color=utils.colors.green,
                                          columns_range=['Score'])

sf.to_excel('output.xlsx', columns_and_rows_to_freeze='A2', row_to_add_filters=0,
            best_fit=['OwnerUserId', 'AnswerCount']).save()

API Documentation¶

utils module¶

This 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 Excel recognises it.

utils.number_formats¶

general = 'General'
general_integer = '0'
general_float = '0.00'
percent = '0.0%'
thousands_comma_sep = '#,##0'
date = 'DD/MM/YY'
time_24_hours = 'HH:MM'
time_24_hours_with_seconds = 'HH:MM:SS'
time_12_hours = 'h:MM AM/PM'
time_12_hours_with_seconds = 'h:MM:SS AM/PM'
date_time = 'DD/MM/YY HH:MM'
date_time_with_seconds = 'DD/MM/YY HH:MM:SS'

decimal_with_num_of_digits¶

arguments:

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'

utils.colors¶

white = op_colors.WHITE
blue = op_colors.BLUE
dark_blue = op_colors.DARKBLUE
yellow = op_colors.YELLOW
dark_yellow = op_colors.DARKYELLOW
green = op_colors.GREEN
dark_green = op_colors.DARKGREEN
black = op_colors.BLACK
red = op_colors.RED
dark_red = op_colors.DARKRED
purple = '800080'
grey = 'D3D3D3'

utils.fonts¶

aegean = 'Aegean'
aegyptus = 'Aegyptus'
aharoni = 'Aharoni CLM'
anaktoria = 'Anaktoria'
analecta = 'Analecta'
anatolian = 'Anatolian'
arial = 'Arial'
calibri = 'Calibri'
david = 'David CLM'
dejavu_sans = 'DejaVu Sans'
ellinia = 'Ellinia CLM'

utils.borders¶

dash_dot = 'dashDot'
dash_dot_dot = 'dashDotDot'
dashed = 'dashed'
dotted = 'dotted'
double = 'double'
hair = 'hair'
medium = 'medium'
medium_dash_dot = 'mediumDashDot'
medium_dash_dot_dot = 'mediumDashDotDot'
medium_dashed = 'mediumDashed'
slant_dash_dot = 'slantDashDot'
thick = 'thick'
thin = 'thin'

utils.horizontal_alignments¶

general = 'general'
left = 'left'
center = 'center'
right = 'right'
fill = 'fill'
justify = 'justify'
center_continuous = 'centerContinuous'
distributed = 'distributed'

utils.vertical_alignments¶

top = 'top'
center = 'center'
bottom = 'bottom'
justify = 'justify'
distributed = 'distributed'

utils.underline¶

single = 'single'
double = 'double'

utils.fill_pattern_types¶

solid = 'solid'
dark_down = 'darkDown'
dark_gray = 'darkGray'
dark_grid = 'darkGrid'
dark_horizontal = 'darkHorizontal'
dark_trellis = 'darkTrellis'
dark_up = 'darkUp'
dark_vertical = 'darkVertical'
gray0625 = 'gray0625'
gray125 = 'gray125'
light_down = 'lightDown'
light_gray = 'lightGray'
light_grid = 'lightGrid'
light_horizontal = 'lightHorizontal'
light_trellis = 'lightTrellis'
light_up = 'lightUp'
light_vertical = 'lightVertical'
medium_gray = 'mediumGray'

utils.conditional_formatting_types¶

num = 'num'
percent = 'percent'
max = 'max'
min = 'min'
formula = 'formula'
percentile = 'percentile'

styler module¶

This module contains classes that represent styles.

Styler Class¶

Used to represent a style.

Styler(bg_color=None, bold=False, font=utils.fonts.arial, font_size=12, font_color=None,
       number_format=utils.number_formats.general, protection=False, underline=None,
       border_type=utils.borders.thin, horizontal_alignment=utils.horizontal_alignments.center,
       vertical_alignment=utils.vertical_alignments.center, wrap_text=True, shrink_to_fit=True,
       fill_pattern_type=utils.fill_pattern_types.solid, indent=0, comment_author=None, comment_text=None)

horizontal_alignment:
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
border_type:	(str: one of utils.borders or any other border type Excel supports) The border type
	(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
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)

Methods¶

combine¶

A classmethod used to combine Styler Class 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)

arguments:

styles:	Arbitrary number of Styler objects

returns:

Styler Class object

to_openpyxl_style¶

arguments:	None
returns:	openpyxl style object.

style_frame module¶

StyleFrame Class¶

Represent a stylized dataframe

StyleFrame(obj, styler_obj=None)

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 Class) A Styler object. Will be used as the default style of all cells.

Methods¶

apply_style_by_indexes¶

arguments:

indexes_to_style:
	(list \| tuple \| int \| Container) The StyleFrame indexes to style. This usually passed as pandas selecting syntax. For example, `sf[sf['some_col'] = 20]`
styler_obj:	(Styler Class) Styler object that contains the style which will be applied to indexes in indexes_to_style
cols_to_style=None:
	(None \| str \| list \| tuple \| set) The column names to apply the provided style to. If `None` all columns will be styled.
height=None:	(None \| int \| float) If provided, height for rows whose indexes are in indexes_to_style.
complement_style=None:
	(None \| Styler Class) Styler object that contains the style which will be applied to indexes not in indexes_to_style
complement_height=None:
	(None \| int \| float) Height for rows whose indexes are not in indexes_to_style. If not provided then height will be used (if provided).
overwrite_default_style=True:
	(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

apply_column_style¶

arguments:

style_header=False:
cols_to_style:	(str \| list \| tuple \| set) The column names to style.
styler_obj:	(Styler Class) A Styler object.
	(bool) If True, the column(s) header will also be styled.
use_default_formats=True:
	(bool) If True, the default formats for date and times will be used.
width=None:	(None \| int \| float) If provided, the new width for the specified columns.
overwrite_default_style=True:
	(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

apply_headers_style¶

arguments:

styler_obj:	(Styler Class) A Styler object.

returns:

self

style_alternate_rows¶

arguments:

styles:	(list \| tuple \| set) List or tuple of Styler Class objects to be applied to rows in an alternating manner

returns:

self

rename¶

arguments:

columns=None:	(dict) A dictionary from old columns names to new columns names.
inplace=False:	(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

set_column_width¶

arguments:

columns:	(str \| list\| tuple) Column name(s).
width:	(int \| float) The new width for the specified columns.

returns:

self

set_column_width_dict¶

arguments:

col_width_dict:	(dict) A dictionary from column names to width.

returns:

self

set_row_height¶

arguments:

rows:	(int \| list \| tuple \| set) Row(s) index.
height:	(int \| float) The new height for the specified indexes.

returns:

self

set_row_height_dict¶

arguments:

row_height_dict:
	(dict) A dictionary from row indexes to height.

returns:

self

add_color_scale_conditional_formatting¶

arguments:

columns_range=None:
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:	(None \| str: one of utils.conditional_formatting_types or any other type Excel supports) The type for the middle bound
mid_value=None:	The threshold for the middle bound
mid_color=None:	(None \| str: one of utils.colors, hex string or color name ie ‘yellow’ Excel supports) The color for the middle bound
	(None \| list \| tuple) 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

read_excel¶

A classmethod used to create a StyleFrame object from an existing Excel.

Note

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

arguments:

read_style=False:
path:	(str) The path to the Excel file to read.
sheetname:	Deprecated since version 1.6: Use `sheet_name` instead.
sheet_name=0:	(str \| int) The sheet name to read. If an integer is provided then it be used as a zero-based sheet index. Default is 0.
	(bool) If True the sheet’s style will be loaded to the returned StyleFrame object.
use_openpyxl_styles=True:
	(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 Class objects. Defaults to True for backward compatibility.

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=False:
	(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

to_excel¶

Note

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

arguments:

excel_writer=’output.xlsx’:
	(str \| pandas.ExcelWriter) File path or existing ExcelWriter
sheet_name=’Sheet1’:
	(str) Name of sheet the StyleFrame will be exported to
allow_protection=False:
	(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=False:
	(bool) Makes the sheet right-to-left.
columns_to_hide=None:
	(None \| str \| list \| tuple \| set) Columns names to hide.
row_to_add_filters=None:
	(None \| int) Add filters to the given row index, starts from 0 (which will add filters to header row).
columns_and_rows_to_freeze=None:
	(None \| str) Column and row string to freeze. For example “C3” will freeze columns: A, B and rows: 1, 2.
best_fit=None:	(None \| str \| list \| tuple \| 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

returns:

self

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`	Path to the json file
`--json`	json string
`--output_path`	Path to the output xlsx file. If not provided defaults to `output.xlsx`

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.