Excel Report Generator

Overview

The ExcelReportGenerator class is designed to create standardized Excel reports from Python. It utilizes the openpyxl library to generate Excel workbooks with multiple sheets, each containing formatted table versions of Pandas DataFrames.

• This package was originally designed to be tightly integrated with SQL queries. If you want, you can use the sql-report-template repo to simply write SQL queries; ExcelReportGenerator will handle the report generation for you.
• ExcelReportGenerator does not rely on SQL in any way. You may use it as a standalone tool for turning Pandas DataFrames into Excel reports.

Installation

# OPTIONAL, but recommended: Make a new virtual environment, if you don't already have one
conda create -n my_new_environment
# Install the package from GitHub
# Change the version number after the "@" symbol to get different versions
pip install git+https://github.com/GSU-Analytics/[email protected]

Usage

Initialization

Create an instance of the ExcelReportGenerator class by providing the results dictionary and introduction text.

from excel_report_generator import ExcelReportGenerator

results = {
    "Sheet1": {
        "First Table Name": df1,
        "Second, Different Table Name": df2
    },
    "Sheet2": {
        "Another table name!": df3
    }
}

intro_text = [
    "This report contains the results of an analysis I conducted.",
    "Each sheet represents a different collection of results."
]

report_generator = ExcelReportGenerator(results, intro_text)

Generating the Workbook

Call the generate_workbook method to create the Excel workbook and save it to the specified path.

output_path = "path/to/save/report.xlsx"
report_generator.generate_workbook(output_path)

Class Methods

__init__(self, results, intro_text)

Initializes the Excel report generator.

• results (dict): A dictionary where each key is a sheet name and each value is a dictionary mapping table names to DataFrames.
• intro_text (list of str): A list of text lines to be added to the introduction sheet.

create_introduction_sheet(self)

Creates the Introduction worksheet and populates it with the intro text.

append_df_as_table(self, ws, df, table_title, start_row)

Appends a Pandas DataFrame to a worksheet as a formatted table.

• ws (Worksheet): The worksheet object.
• df (DataFrame): The Pandas DataFrame to add.
• table_title (str): Title to display above the table.
• start_row (int): The starting row number in the worksheet.

Returns:

• int: The row number after the inserted table.

create_results_sheets(self)

Creates a separate worksheet for each SQL file (based on the file name) and populates it with all tables derived from that file’s queries.

generate_workbook(self, output_path)

Creates the workbook with the Introduction and all results sheets and saves it.

• output_path (str): The file path where the workbook will be saved.

Example

from excel_report_maker import ExcelReportGenerator
import pandas as pd

# Sample data
df1 = pd.DataFrame({
    "Column1": [1, 2, 3],
    "Column2": [4, 5, 6]
})

df2 = pd.DataFrame({
    "Column1": [7, 8, 9],
    "Column2": [10, 11, 12]
})

results = {
    "Sheet1": {
        "Query1": df1,
        "Query2": df2
    }
}

intro_text = [
    "This report contains the results of various tables.",
    "Each sheet represents a different grouping of tables."
]

# Create the report generator
report_generator = ExcelReportGenerator(results, intro_text)

# Generate the workbook
output_path = "report.xlsx"
report_generator.generate_workbook(output_path)