oj

Reading excel (but more than just cell values: Also colors

To install: pip install oj

Overview

The oj package provides advanced functionalities for reading Excel files using Python, focusing not only on cell values but also on extracting and manipulating cell styles, colors, and formats. It utilizes libraries such as pandas, numpy, and openpyxl to handle and process Excel files in a more detailed manner.

Features

• Loading Excel Sheets: Load specific sheets from Excel files with ease.
• Style Extraction: Extract styles from cells including fonts, fills, borders, and more.
• Data Manipulation: Functions to manipulate and filter data based on cell values and styles.
• Integration with Pandas: Seamlessly convert Excel data into pandas DataFrames with additional style information.

Installation

To install the package, use the following pip command:

pip install oj

Usage

Loading and Reading Excel Sheets

To load an Excel sheet and read data:

from oj import get_sheet_data

# Load a specific sheet from the Excel file
sheet = get_sheet_data('path_to_file.xlsx', 'Sheet1')

Extracting All Cell Styles

To extract styles from all cells in a given sheet:

from oj import extract_all_cell_styles

# Assuming 'sheet' is already loaded
styles_df = extract_all_cell_styles(sheet)
print(styles_df.head())

Appending Styles to DataFrame

To append style information to an existing DataFrame:

from oj import append_styles_to_dataframe

# Assuming 'sheet' is loaded and 'df' is a DataFrame with coordinates
styled_df = append_styles_to_dataframe(sheet, df)
print(styled_df)

Filtering DataFrame by Value and Style

To filter a DataFrame based on cell values and specific style properties:

from oj import filter_df_by_value_and_style

# Create a sample DataFrame
df = pd.DataFrame({
    'coordinate': ['A1', 'A2'],
    'value': ['Hello', 'World'],
    'font': ['Arial', 'Calibri'],
    'fill': ['Yellow', 'Blue']
})

# Filter by value and font style
filtered_df = filter_df_by_value_and_style(df, value='Hello', style_property='font', style_value='Arial')
print(filtered_df)

Documentation

Each function in the oj package is documented with docstrings, providing a clear description of its functionality, parameters, and usage examples. This ensures ease of use and understanding of the available methods.

Contributing

Contributions to the oj package are welcome. Please ensure that any pull requests or issues are clear and provide sufficient information for review.