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
MDAnalysis is a Python library to analyze molecular dynamics simulations.

MDAnalysis Repository README [*] MDAnalysis is a Python library for the analysis of computer simulations of many-body systems at the molecular scale,

MDAnalysis 933 Dec 28, 2022
An Integrated Experimental Platform for time series data anomaly detection.

Curve Sorry to tell contributors and users. We decided to archive the project temporarily due to the employee work plan of collaborators. There are no

Baidu 486 Dec 21, 2022
An experimental project I'm undertaking for the sole purpose of increasing my Python knowledge

5ePy is an experimental project I'm undertaking for the sole purpose of increasing my Python knowledge. #Goals Goal: Create a working, albeit lightwei

Hayden Covington 1 Nov 24, 2021
Python beta calculator that retrieves stock and market data and provides linear regressions.

Stock and Index Beta Calculator Python script that calculates the beta (β) of a stock against the chosen index. The script retrieves the data and resa

sammuhrai 4 Jul 29, 2022
Mining the Stack Overflow Developer Survey

Mining the Stack Overflow Developer Survey A prototype data mining application to compare the accuracy of decision tree and random forest regression m

1 Nov 16, 2021
OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase working capital.

Overview OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase

Tom 3 Feb 12, 2022
A stock analysis app with streamlit

StockAnalysisApp A stock analysis app with streamlit. You select the ticker of the stock and the app makes a series of analysis by using the price cha

Antonio Catalano 50 Nov 27, 2022
PyTorch implementation for NCL (Neighborhood-enrighed Contrastive Learning)

NCL (Neighborhood-enrighed Contrastive Learning) This is the official PyTorch implementation for the paper: Zihan Lin*, Changxin Tian*, Yupeng Hou* Wa

RUCAIBox 73 Jan 03, 2023
Analyze the Gravitational wave data stored at LIGO/VIRGO observatories

Gravitational-Wave-Analysis This project showcases how to analyze the Gravitational wave data stored at LIGO/VIRGO observatories, using Python program

1 Jan 23, 2022
Titanic data analysis for python

Titanic-data-analysis This Repo is an analysis on Titanic_mod.csv This csv file contains some assumed data of the Titanic ship after sinking This full

Hardik Bhanot 1 Dec 26, 2021
A script to "SHUA" H1-2 map of Mercenaries mode of Hearthstone

lushi_script Introduction This script is to "SHUA" H1-2 map of Mercenaries mode of Hearthstone Installation Make sure you installed python=3.6. To in

210 Jan 02, 2023
A DSL for data-driven computational pipelines

"Dataflow variables are spectacularly expressive in concurrent programming" Henri E. Bal , Jennifer G. Steiner , Andrew S. Tanenbaum Quick overview Ne

1.9k Jan 03, 2023
Modular analysis tools for neurophysiology data

Neuroanalysis Modular and interactive tools for analysis of neurophysiology data, with emphasis on patch-clamp electrophysiology. Functions for runnin

Allen Institute 5 Dec 22, 2021
A python package which can be pip installed to perform statistics and visualize binomial and gaussian distributions of the dataset

GBiStat package A python package to assist programmers with data analysis. This package could be used to plot : Binomial Distribution of the dataset p

Rishikesh S 4 Oct 17, 2022
Example Of Splunk Search Query With Python And Splunk Python SDK

SSQAuto (Splunk Search Query Automation) Example Of Splunk Search Query With Python And Splunk Python SDK installation: ➜ ~ git clone https://github.c

AmirHoseinTangsiriNET 1 Nov 14, 2021
Demonstrate a Dataflow pipeline that saves data from an API into BigQuery table

Overview dataflow-mvp provides a basic example pipeline that pulls data from an API and writes it to a BigQuery table using GCP's Dataflow (i.e., Apac

Chris Carbonell 1 Dec 03, 2021
Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown.

Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown

915 Dec 26, 2022
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊

Thomas 2 May 26, 2022
fds is a tool for Data Scientists made by DAGsHub to version control data and code at once.

Fast Data Science, AKA fds, is a CLI for Data Scientists to version control data and code at once, by conveniently wrapping git and dvc

DAGsHub 359 Dec 22, 2022
Flenser is a simple, minimal, automated exploratory data analysis tool.

Flenser Have you ever been handed a dataset you've never seen before? Flenser is a simple, minimal, automated exploratory data analysis tool. It runs

John McCambridge 79 Sep 20, 2022