Useful tool for inserting DataFrames into the Excel sheet.

Overview

PyCellFrame

Insert Pandas DataFrames into the Excel sheet with a bunch of conditions

Install

pip install pycellframe

Usage

Examples

Let's suppose that we have an Excel file named "numbers.xlsx" with the sheet named "Dictionary" in which we would like to insert the pandas.DataFrame.

Import pandas and create an example DataFrame (which will be inserted into the Excel sheet):

import pandas as pd


ex = {
    'Num': [1, 2, 3, 4],
    'AfterFirstBlankCol': 'AfterFirstBlank',
    'Descr': ['One', 'Two', 'Three', 'Four'],
    'AfterSecondBlankCol': 'AfterSecondBlank.',
    'Squared': [1, 4, 9, 16],
    'Binary:': ['1', '10', '11', '100']
}

df = pd.DataFrame(ex)
  • Import openpyxl.load_workbook and open numbers.xlsx - Our Excel workbook;
  • Get - Dictionary our desired sheet:
from openpyxl import load_workbook


workbook = load_workbook('numbers.xlsx')
worksheet = workbook['Dictionary']

Functions

1. incell_style(cell_src, cell_dst)
  • Let's say, we have a cell in Excel Dictionary sheet that we would like to copy the style from, and it is O3;
  • Let O4 be our destination cell:

NOTE: If we wanted to copy that style to more than one cell, we would simply use the loop depending on the locations of the destination cells.

from pycellframe import incell_style


incell_style(cell_src=worksheet['O3'], cell_dst=worksheet['O4'])
2. sheet_to_sheet(filename_sheetname_src, filename_sheetname_dst, calculated)
  • Let's say that we have two Excel files, and we need specific sheet from one file to be completely copied to another file's specific sheet;
  • filename_sheetname_src is the parameter for one file -> sheet the data to be copied from (tuple(['FILENAME_SRC', 'SHEETNAME_SRC']));
  • worksheet_dst is the parameter for the destination Worksheet the data to be copied to (openpyxl.worksheet.worksheet.Worksheet);
  • Let's assume that we have file_src.xlsx as src file and for worksheet_src we can use its CopyThisSheet sheet.
  • We can use output.xlsx -> CopyToThisSheet sheet as the destination worksheet, for which we already declared the Workbook object above.

NOTE: We are assuming that we need all the formulas (where available) from the source sheet, not calculated data, so we set calculated parameter to False

from pycellframe import sheet_to_sheet


worksheet_to = workbook['CopyToThisSheet']

sheet_to_sheet(filename_sheetname_src=('file_src.xlsx', 'CopyThisSheet'),
               worksheet_dst=worksheet_to,
               calculated=False)
3. incell_frame(worksheet, dataframe, col_range, row_range, num_str_cols, skip_cols, headers)
  • From our package pycellframe import function incell_frame;
  • Insert ex - DataFrame into our sheet twice - with and without conditions:
from pycellframe import incell_frame


# 1 - Simple insertion
incell_frame(worksheet=worksheet, dataframe=df)

# 2 - Insertion with some conditions
incell_frame(worksheet=worksheet,
             dataframe=df,
             col_range=(3, 0),
             row_range=(6, 8),
             num_str_cols=['I'],
             skip_cols=['D', 'F'],
             headers=True)

In the first insertion, we did not give our function any arguments, which means the DataFrame ex will be inserted into the Dictionary sheet in the area A1:F4 (without the headers).

However, with the second insertion we define some conditions:

  • col_range=(3, 0) - This means that insertion will be started at the Excel column with the index 3 (column C) and will not be stopped until the very end, since we gave 0 as the second element of the tuple

  • row_range=(6, 8) - Only in between these rows (in Excel) will the DataFrame data be inserted, which means that only the first row (since the headers is set to True) from ex will be inserted into the sheet

  • num_str_cols=['F'] - Another condition here is to not convert Binary column values to int. If we count, this column will be inserted in the Excel column F, so we tell the function to leave the values in it as string

  • skip_cols=['D', 'F'] - D and F columns in Excel will be skipped and since our worksheet was blank in the beginning, these columns will be blank (that is why I named the columns in the DataFrame related names)

  • headers=True - This time, the DataFrame columns will be inserted, too, so the overall insertion area would be C6:J8

For really detailed description of the parameters, please see:
  1. incell_frame.__docs__
  2. sheet_to_sheet.__docs__
  3. incell_style.__docs__
  • Finally, let's save our changes to a new Excel file:
workbook.save('output.xlsx')

Full Code

import pandas as pd
from openpyxl import load_workbook
from pycellframe import incell_style, \
                        incell_frame, \
                        sheet_to_sheet


ex = {
    'Num': [1, 2, 3, 4],
    'AfterFirstBlankCol': 'AfterFirstBlank',
    'Descr': ['One', 'Two', 'Three', 'Four'],
    'AfterSecondBlankCol': 'AfterSecondBlank.',
    'Squared': [1, 4, 9, 16],
    'Binary:': ['1', '10', '11', '100']
}

df = pd.DataFrame(ex)

workbook = load_workbook('numbers.xlsx')
worksheet = workbook['Dictionary']


# Copy the cell style
incell_style(cell_src=worksheet['O3'], cell_dst=worksheet['O4'])


# Copy the entire sheet
worksheet_to = workbook['CopyToThisSheet']

sheet_to_sheet(filename_sheetname_src=('file_src.xlsx', 'CopyThisSheet'),
               worksheet_dst=worksheet_to,
               calculated=False)


# Insert DataFrame into the sheet

## 1 - Simple insertion
incell_frame(worksheet=worksheet, dataframe=df)

## 2 - Insertion with some conditions
incell_frame(worksheet=worksheet,
             dataframe=df,
             col_range=(3, 0),
             row_range=(6, 8),
             num_str_cols=['I'],
             skip_cols=['D', 'F'],
             headers=True)

workbook.save('output.xlsx')
Owner
Luka Sosiashvili
Luka Sosiashvili
collect training and calibration data for gaze tracking

Collect Training and Calibration Data for Gaze Tracking This tool allows collecting gaze data necessary for personal calibration or training of eye-tr

Pascal 5 Dec 17, 2022
Provide a market analysis (R)

market-study Provide a market analysis (R) - FRENCH Produisez une étude de marché Prérequis Pour effectuer ce projet, vous devrez maîtriser la manipul

1 Feb 13, 2022
Template for a Dataflow Flex Template in Python

Dataflow Flex Template in Python This repository contains a template for a Dataflow Flex Template written in Python that can easily be used to build D

STOIX 5 Apr 28, 2022
SNV calling pipeline developed explicitly to process individual or trio vcf files obtained from Illumina based pipeline (grch37/grch38).

SNV Pipeline SNV calling pipeline developed explicitly to process individual or trio vcf files obtained from Illumina based pipeline (grch37/grch38).

East Genomics 1 Nov 02, 2021
An Indexer that works out-of-the-box when you have less than 100K stored Documents

U100KIndexer An Indexer that works out-of-the-box when you have less than 100K stored Documents. U100K means under 100K. At 100K stored Documents with

Jina AI 7 Mar 15, 2022
The Dash Enterprise App Gallery "Oil & Gas Wells" example

This app is based on the Dash Enterprise App Gallery "Oil & Gas Wells" example. For more information and more apps see: Dash App Gallery See the Dash

Austin Caudill 1 Nov 08, 2021
Statistical Analysis 📈 focused on statistical analysis and exploration used on various data sets for personal and professional projects.

Statistical Analysis 📈 This repository focuses on statistical analysis and the exploration used on various data sets for personal and professional pr

Andy Pham 1 Sep 03, 2022
Intercepting proxy + analysis toolkit for Second Life compatible virtual worlds

Hippolyzer Hippolyzer is a revival of Linden Lab's PyOGP library targeting modern Python 3, with a focus on debugging issues in Second Life-compatible

Salad Dais 6 Sep 01, 2022
A crude Hy handle on Pandas library

Quickstart Hyenas is a curde Hy handle written on top of Pandas API to allow for more elegant access to data-scientist's powerhouse that is Pandas. In

Peter Výboch 4 Sep 05, 2022
AWS Glue ETL Code Samples

AWS Glue ETL Code Samples This repository has samples that demonstrate various aspects of the new AWS Glue service, as well as various AWS Glue utilit

AWS Samples 1.2k Jan 03, 2023
A distributed block-based data storage and compute engine

Nebula is an extremely-fast end-to-end interactive big data analytics solution. Nebula is designed as a high-performance columnar data storage and tabular OLAP engine.

Columns AI 131 Dec 26, 2022
Python package for analyzing behavioral data for Brain Observatory: Visual Behavior

Allen Institute Visual Behavior Analysis package This repository contains code for analyzing behavioral data from the Allen Brain Observatory: Visual

Allen Institute 16 Nov 04, 2022
Python tools for querying and manipulating BIDS datasets.

PyBIDS is a Python library to centralize interactions with datasets conforming BIDS (Brain Imaging Data Structure) format.

Brain Imaging Data Structure 180 Dec 18, 2022
A real data analysis and modeling project - restaurant inspections

A real data analysis and modeling project - restaurant inspections Jafar Pourbemany 9/27/2021 This project represents data analysis and modeling of re

Jafar Pourbemany 2 Aug 21, 2022
Open source platform for Data Science Management automation

Hydrosphere examples This repo contains demo scenarios and pre-trained models to show Hydrosphere capabilities. Data and artifacts management Some mod

hydrosphere.io 6 Aug 10, 2021
pyETT: Python library for Eleven VR Table Tennis data

pyETT: Python library for Eleven VR Table Tennis data Documentation Documentation for pyETT is located at https://pyett.readthedocs.io/. Installation

Tharsis Souza 5 Nov 19, 2022
Building house price data pipelines with Apache Beam and Spark on GCP

This project contains the process from building a web crawler to extract the raw data of house price to create ETL pipelines using Google Could Platform services.

1 Nov 22, 2021
CPSPEC is an astrophysical data reduction software for timing

CPSPEC manual Introduction CPSPEC is an astrophysical data reduction software for timing. Various timing properties, such as power spectra and cross s

Tenyo Kawamura 1 Oct 20, 2021
Python script for transferring data between three drives in two separate stages

Waterlock Waterlock is a Python script meant for incrementally transferring data between three folder locations in two separate stages. It performs ha

David Swanlund 13 Nov 10, 2021
Full ELT process on GCP environment.

Rent Houses Germany - GCP Pipeline Project: The goal of the project is to extract data about house rentals in Germany, store, process and analyze it u

Felipe Demenech Vasconcelos 2 Jan 20, 2022