Saravanan666/pypi-org huggingface dataset:
Package: excel2txt
excel2txtConvert Excel files to delimited textSynopsisFor usage, runexcel2txt --help:usage: excel2txt [-h] [-o str] [-d str] [-D] [-n] [--version] FILE [FILE ...]

Convert Excel files to delimited text

positional arguments:
  FILE                  Input Excel file(s)

optional arguments:
  -h, --help            show this help message and exit
  -o str, --outdir str  Output directory (default:
                        /Users/kyclark/work/python/excel2txt-py)
  -d str, --delimiter str
                        Delimiter for output file (default: )
  -D, --mkdirs          Create separate directories for output files (default:
                        False)
  -n, --normalize       Normalize headers (default: False)
  --version             show program's version number and exitGiven one or more Excel files as positional parameters, the program
will create an output text file in the given output directory (which
defaults to the current working directory).For example:$ excel2txt tests/test1.xlsx
  1: tests/test1.xlsx
Done, see output in "/Users/kyclark/work/python/excel2txt-py".Now you should have a file called "test1__sheet1.txt" in the current directory.
You could use the "csvchk" program to see the structure of this file:$ csvchk test1__sheet1.txt
// ****** Record 1 ****** //
name          : Ed
rank          : Captain
serial_number : 12345If you are processing multiple files, you might find the "--mkdirs" option useful to put all the sheets from each workbook into a separate directories:$ ./excel2txt.py tests/*.xlsx --outdir out --mkdirs
  1: tests/test1.xlsx
  2: tests/test2.xlsx
Done, see output in "/Users/kyclark/work/python/excel2txt-py/out".In the "out" directory, there will be "test1" and "test2" directories:$ find out -type f
out/test1/test1__sheet1.txt
out/test2/test2__sheet1.txtYou can use the "--delimiter" option to change the output file delimiter.Column, file normalizationThe "--normalize" option will alter the headers of each output file to lowercase values and remove non-alphanumeric characters or the underscore.
This will also break "CamelCase" values into "snake_case."This same normalization will be used to create the output file names so as to avoid any possibility of creating output files with illegal or difficult characters.See alsocsvkit, csvchkAuthorKen Youens-Clarkkyclark@gmail.com
Package: excel2wisxml
# excel2wisxml, an excel to WMO XML conversion toolexcel2wisxml tool has been developed by Météo-France and allows the generation of large set of metadata WMO Core 1.3 profile issued from an excel document. The python package is under the free open source GFor any information, please contact:gisc_support@meteo.frOfficial documentation for excel2wis can be found in the [exce2wis github repository](https://github.com/OpenWIS/excel2wis):[User Manual](https://github.com/OpenWIS/excel2wis/blob/master/Excel2wisxml_manual.pdf“excel2wisxml User Manual”)[Developer Manual](https://github.com/OpenWIS/excel2wis/blob/master/excel2wisxml_developer_manual.md“excel2wisxml Developer Manual”)
Package: excel2x
excel2x转换 Config 配置工具 excel2xPython3库excel2x。只需要用工具生成自己项目的配置文件，就可以按照配置文件导Excel表了。现在支持csv、lua、json格式，后面后继续扩展xml等格式。支持生成数据格式Schema接口，现在支持Lua table、TypeScript interface，后面会支持Java Class和C# Class。安装pipinstallexcel2x使用方式查看帮助python3-mexcel2x-h# orexcel2x-cli-h创建项目配置python3-mexcel2x--configproject_path/config.json--nameproject_name--create# orexcel2x-cli--configproject_path/config.json--nameproject_name--create命令行转换 Excelpython3-mexcel2x--configproject_path/config.json# orexcel2x-cli--configproject_path/config.json在Python脚本中使用#!/usr/bin/env python3# -*- coding: utf-8 -*fromexcel2x.mainimportconvert_configif__name__=="__main__":# 项目配置路径proj_config_path="project_path/config.json"convert_config(proj_config_path)
Package: excel2xx
简介导出 Excel 到各种结构化数据或代码。除命令行接口外也提供了
Python API 便于做二次加工。繁介你总会需要一些由非技术人员提供的数据来充实你的产品内容，比如美术资源和游戏数值。美术资源好说，
规范好目录和文件名就万事大吉了，但数值咋放呢？必须要有一个他懂、你懂、程序也懂的数值载体。
Excel 作为一款数据处理工具，做游戏数值简直易如反掌。于是本项目应运而生，用来搬运 Excel 数据。p.s: 避免人工编辑 json, xml, 数据库之类的，那样太低效，很没人情味。特性支持类型约束基本类型:string, int, float, bool数组类型:文法：array<类型>例子：array<int>, array<float>, array<bool> 等等Map 类型:键值对数据, 就是 hash table文法：map<类型, 类型>例子：map<string, string>, map<string, int> 等等Object 类型:用于自定义字段名和字段类型文法：Object<字段1:类型, 字段2：类型, ...> 字段名和类型可自由定义多个例子：Object<id:int, name>  表示将{9527, “小明”}导出为{“id”:9527, "name":"小明"}ItemExpr(物品表达式)一种易于读写的 DSL, 用于描述游戏中的资源数值。文法: 类型-ID-数量.例子: coin-100 表示 100 金币.  weapon-1001-4 表示 4件ID为1001的武器。Ratio 类型： 表示数字比例例子： 1:100支持多种数据结构 e.g. list,dict, （tree 还有待探索）。支持导出到 json, msgpack.支持导出到任意代码(需要使用 mako 模板脚本)。运行依赖Python3.6+安装$ pip install excel2xx使用Excel 数据表Python API示例（推荐）读取 excel sheetfromexcel2xximportExcelexcel=Excel("abc.xlsx")# 获取第一个 sheetsheet=excel[0]forrowinsheet:print(row)# 根据 sheet 名获取sheet=excel["你好啊"]forrowinsheet:print(row)自定义 ItemExpr(游戏资源类型)fromexcel2xximportExcelfromexcel2xx.fieldsimportItemExpr# 注册一个只包含 count 字段的资源类型ItemExpr.register("coin",ItemExpr.OnlyCount)# 注册自定义的资源类型defparse_youritem(v:str)->dict:# parsing...returnblahblah...ItemExpr.register("your item",parse_youritem)excel=Excel("abc.xlsx")...CLI 示例（即将作废）$ excel2xx json example/test.xls    -o example/test.json
$ excel2xx msgpack example/test.xls -o example/test.msgpack
$ excel2xx mako example/test.xls    -o example/test.lua  --template example/test.lua.makoTODO支持导出到任意编程语言代码(用 mako 模板引擎).支持自定义数据检错过程，用于杜绝过于低级的数值错误.LICENSEDO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE
                    Version 2, December 2004

 Copyright (C) 2014-2023 cupen<xcupen@gmail.com>

 Everyone is permitted to copy and distribute verbatim or modified
 copies of this license document, and changing it is allowed as long
 as the name is changed.

            DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE
   TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION

  0. You just DO WHAT THE FUCK YOU WANT TO.
Package: excel-anonymizer
Excel AnonymizerA Python script that anonymizes an Excel file and synthesizes new data in its place.Convert your sheets with sensitive data into anonymized data.What is Excel AnonymizerExcel Anonymizer is a python script that helps to ensure sensitive data is properly managed and governed. It provides fast identification and anonymization for private entities in text such as credit card numbers, names, locations, phone numbers, email address, date/time, with more entities to come.Use caseData anonymization is crucial because it helps protect privacy and maintain confidentiality. If data is not anonymized, sensitive information such as names, addresses, contact numbers, or other identifiers linked to specific individuals could potentially be learned and misused. Hence, by obscuring or removing this personally identifiable information (PII), data can be used freely without compromising individuals’ privacy rights or breaching data protection laws and regulations.OverviewAnonymization consists of two steps:Identification: Identify all data fields that contain personally identifiable information (PII).Replacement: Replace all PIIs with pseudo values that do not reveal any personal information about the individual but can be used for reference.Excel Anonymizer uses Microsoft Presidio together with Faker framework for anonymization purposes.QuickstartInstall the requirementspip install presidio_analyzer
pip install presidio_anonymizer
python -m spacy download en_core_web_lgInstall the packagepip install excel-anonymizerNote: Spacy will install a Natural Language Processing package on the first run (587.7MB).Run the demoexcel-anonymizer ../../personal_information.xlsxThat's it!UsageTo use Excel Anonymizer with your Excel file, simply input the file.excel-anonymizer your_excel_file_here.xlsxAuthorSiddharth BhatiaLicense:MIT License
Package: excelasyn
python excel asynlibreria para armar excel con librerias asincronasFree software: MIT licenseDocumentation:https://excelasyn.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-03-09)First release on PyPI.
Package: excelbdd
Use Excel file as BDD feature file, get example data from excel files, support automation testsV1.4.9 changes:
columns are not selected after a blank header is present in bdd format.
behavior is removed, use excelbdd instead, as below.
old: from excelbdd.behavior import get_example_list
new: from excelbdd import excelbdd#pip install excelbdd
import pytest
from excelbdd import excelbdd
import FizzBuzz

excelBDDFile = "path of excel file" 
@pytest.mark.parametrize("HeaderName, Number1, Output1, Number2, Output2, Number3, Output3, Number4, Output4",
                        excelbdd.get_example_list(excelBDDFile,"FizzBuzz"))
def test_FizzBuzz(HeaderName, Number1, Output1, Number2, Output2, Number3, Output3, Number4, Output4):
    assert FizzBuzz.handle(Number1) == Output1
    assert FizzBuzz.handle(Number2) == Output2
    assert FizzBuzz.handle(Number3) == Output3
    assert FizzBuzz.handle(Number4) == Output4Get data from table in Excel, similar to get from csv filefrom excelbdd import excelbdd
@pytest.mark.parametrize("Header01, Header02, Header03, Header04, Header05, Header06, Header07, Header08",
                         excelbdd.get_example_table(excelBDDFile, "DataTable4"))
def test_get_example_tableB(Header01, Header02, Header03, Header04, Header05, Header06, Header07, Header08):
    print(Header01, Header02, Header03, Header04, Header05, Header06, Header07, Header08)
    # add test code here"Specification by testcase" is supported. the bdd excel files can be regarded as the test reports.
The test format in excel is detected automatically, only extra parameters(expected, test result) are needed to take into test method.Python unittest is also supported by ExcelBDD.import unittest
from excelbdd import excelbdd
from parameterized import parameterized

class ExcelBDDTest(unittest.TestCase):
    @parameterized.expand(excelbdd.get_example_list(excelBDDFile))
    def test_get_example_tableB(self, HeaderName, ParamName1, ParamName2, ParamName3, ParamName4):
        print(HeaderName, ParamName1, ParamName2, ParamName3, ParamName4)
        # add test code here
        self.assertEqual(ParamName1, "P1")
        self.assertEqual(ParamName3, None)more information atExcelBDD Python Guideline
Package: excelcleaner
excelcleanerWhat is it?A package that helps you clean and recover columns of Excel data converted from PDF files.Where to get itpip install excelcleanerDependenciesopenpyxlfor opening/saving Excel file in Python.tksheetfor displaying the content of the Excel file.ChangesVersion 0.0.18Added function-key featuresF1: delete rows or columnsF2: delete rows having a particular cellF3: combine rows or columnsF4: combine selected rowsF5: insert a cell to row and repeat the process to other rows in the same patternF7: delete a cell to row and repeat the process to other rows in the same patternF10: split a column to two columns with a particular stringAdded an option to save processes to a fileThe processes saved in the file can be executed to speed the process until wanted cleaning is completed.Clicking a row provides the rows having the same pattern of the cells in rowVersion 0.0.10Restoring just the data before the last action is extended to data of all actions since the first action.Changed function keys for actions.Screen displays the selected row where the next action is needed.Version 0.0.9A tiny bug of renaming a cleaned xlsx file was fixed.Version 0.0.7Added some help:When a column is all None, it will be deleted without any notice.Rows in a pattern that takes place at the least number of rows will be highlighted.The first row of the rows will be selected and is ready for next action. This selection is only a hint and should not be followed unless otherwise.Version 0.0.5Disabled some bindings that belong to tksheet package.Version 0.0.4importexcelcleanerasxlxlpath='(excel file name with extension)'xl.sheet(xlpath)A tksheet window will be opened with the contents of excel file.Here are recommending orders of actions to try:Remove unwanted rows (F1) firstRemove unwanted columns (F1) or combine columns (F3)Click a cell to insert (F5) or delete the cell (F7)If the same pattern or kind of selected rows/columns is found at other locations, the same action is repeated for the found rows/columns.Thus, it would better try one action at the topTo remove rows, click and drag the row names.To remove or combine columns, click and drag the column names.When rows or columns are to be combined, the cells of the same rows or columns are combined.After every action, the contents will be saved to a file that is the original name with a string "_cleaned".When a cell is inserted, all values to the right are moved to the right, and an empty cell is added at the end of all other unchanged rows.When a cell is deleted, all the values ​​on the right are moved to the left and the last column is empty.If one action is done by mistake, press comination key (control-z) to restore the the data before he last actionAfter each action is completed,the number of columns and rows and the number of patterns of rows will be displayedeither a few columns or muliple rows are highlighted, which are indicative of ok to be deleted.
Package: excelcsv
[![Build Status](https://travis-ci.org/unnonouno/excelcsv.svg?branch=master)](https://travis-ci.org/unnonouno/excelcsv)[![Coverage Status](https://coveralls.io/repos/github/unnonouno/excelcsv/badge.svg?branch=master)](https://coveralls.io/github/unnonouno/excelcsv?branch=master)# excelcsv## Requirements- Python 2.7, 3,4, 3.5## Installation```$ pip install excelcsv```## Usage```with excelcsv.read_excel_tsv(path) as reader:for row in reader:do_something(row)``````with excelcsv.write_excel_tsv(path) as writer:for row in rows:writer.writerow(row)```## LicenseMIT License.
Package: excel-csv-converter
Excel csv converterConvert each page from xlsx file to csv files, convert file csv to xlsx document, insert csv data in existing fileInstall$pipinstallexcel_csv_converterHow to use# import converterfromexcel_csv_converterimportconverter# CONVERT XLSX DOCUMENTS TO CSVsfile_xlsx="c:\\my_file.xlsx"folder_destination="c:\\my_folder"my_converter=converter.Xlsx_to_csv(file_xlsx,folder_destination)# INSERT CSV FILE IN XLSX DOCUMENTfile_csv="c:\\my_file.csv"file_xlsx_destination="c:\\my_file.xlsx"my_converter=converter.Csv_to_xlsx(file_csv,file_xlsx_destination)
Package: excel-db-connector
Excel Database ConnectorConnects Excel to a database connector to transfer information to and fro.Fyleis an expense management system.InstallationThis project requiresPython 3+.Download this project and use it (copy it in your project, etc).Install it frompip.$ pip install excel-db-connectorUsageThis connector is very easy to use.First you'll need to create a connection using the main class FyleSDK.importsqlite3fromexcel_db_connectorimportExcelConnectordbconn=sqlite3.connect('/tmp/temp.db')excel_connector=ExcelConnector(dbconn)After that you'll be able to extract data from excel and store it in the db# Create the tables to for all objectsexcel_connector.create_tables('/tmp/create_tables.sql')excel_connector.extract('excel.xlsx','table_name')ContributeTo contribute to this project follow the stepsFork and clone the repository.Runpip install -r requirements.txtSetup pylint precommit hookCreate a file.git/hooks/pre-commitCopy and paste the following lines in the file -#!/usr/bin/env bashgit-pylint-commit-hookRunchmod +x .git/hooks/pre-commitLicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: exceldrive2py
gsheets|PyPI version| |License| |Supported Python| |Format|gsheetsis a small wrapper around theGoogle Sheets API_ (v4)to provide
more convenient access toGoogle Sheets_from Python scripts.go togoogle console1.Create a Project in google cloud2.through Navigation menu Go ti API'S & Services and go to library3.search for google sheets api and enable it4.search for google drive api enable it and on the right side corner click on create credentials
select google drive api in which api you are using column and web server (eg node js tomcat) in  Where will you be calling the API from dropdown and tick on application data. and then no and press button5.fill any name in account and role select project and then editor and type json and submit. it will download the json file .6.open json file search client email go to google sheet you want to use and select share and give access to client email and send.LinksGitHub:https://github.com/afsarahmad786/Read-ExcelPyPI:https://afsarahmad786.github.io/Read-Excel/InstallationThis package runs under Python 2.7, and 3.6+, use pip_ to install:.. code:: bash$ pip install read-excelThis will also install google-api-python-client_ and its dependencies, notably
httplib2_ and oauth2client_, as required dependencies.QuickstartLog into theGoogle Developers Console_ with the Google account whose
spreadsheets you want to access. Create (or select) a project and enable theDrive APIandSheets API(underGoogle Apps APIs).Go to theCredentialsfor your project and createNew credentials>OAuth client ID> of typeOther. In the list of yourOAuth 2.0 client
IDsclickDownload JSONfor the Client ID you just created. Save the
file asclient_secrets.jsonin your home directory (user directory).import the library and load the data by passing the filename and json file downloaded from console it will return a dataframe and print top 5 rows of your data:.. code:: python>>> import read-excel as rf

>>> dataframe = rf.load_data(filename_of_your_sheet,json_path)For plotting the data you have to pass the dataframe you just loaded and pass the name X axis  columns name and Y axis column name it will plot the data for you:.. code:: pythonfor plotting
>>> plot_data(dataframe,"x-axis-column","y-axis-column")...
Package: excel-exporter
django-excel-exportA Django library for exporting data in xlsx, xls, docx format.Live DemoUser: adminPassword: adminDemo Source CodeHow to install$pipinstallexcel-exporterHow to useExport is achieved by subclassing ExportAdmin, which implements export as an admin action.# app/admin.pyfromexcel_exporter.adminimportExportAdminclassPersonAdmin(ExportAdmin):list_display=('name','address',...)export_fields=('name','address',...)What you getYou can define custom export action and add it to export_actions list:# app/admin.pyfromexcel_exporter.adminimportExportAdminfromexcel_exporter.actionimportDocxclassPersonExportDocx(Docx):desc='persons to docx'tpl='persons.docx'queryset_name='ps'defget_payloads(self,queryset,list_display):payload=super().get_payloads(queryset,list_display)payload['test']='A Big Company'payload['logo']='staticfiles/1.jpg'returnpayloadclassPersonaAdmin(ExportAdmin):list_display=('name','address',...)export_actions=[PersonExportDocx,...]What you getSeeadmin.pyinDemo Source Code.
Package: excelextractor
ExcelExtractorExcelExtractor handles maschine readable data for excel documentsExcelExtrator handles excel worksheet with an headline and data under it.
It can read/write from those data and presents them in an maschine readable format in python
Needed file Structure in Excel:|    A    |    B    |    C    | ....
+---------+---------+---------+-------
| ... 
+---------+---------+---------+-------
| Header1 | Header2 | Header3 | ...
+---------+---------+---------+-------
| Content | Content | Content | ...
+---------+---------+---------+-------
| ...RequirementsPython >= 3.6openpyxlInstallationInstall with pippip install excelextractorDocumentationhttps://dcfsec.github.io/excelextractor/VersioningWe useSemVerfor versioning. For the versions available, see thetags on this repository.AuthorsdcfSec-Initial workSee also the list ofcontributorswho participated in this project.LicenseThis project is licensed under the Apache 2.0 License - see theLICENSEfile for detailsToDoTestsDocumentation
Package: excel-fast-load
excel_fast_loadLoad XLSX/XLSM files into pandas dataframes faster than pandas.read_excelauthor:FelixKlingNOTE: Science for Change just packages this code to use it because we find it useful for Citizen Science projects!This code is provided as is, with no license and no warranties, as it was shared by Felix:https://stackoverflow.com/a/62277641Usagefrom excel_fast_load import excel_fast_load
dataframe = excel_fast_load('path/to/excelfile.xlsx')Optional parameters after pathsheet_name: str. Name of the sheet to read. If none, the first (not the active!) sheet is read. The default is None.header: bool. Whether to use the first line as column headers. The default is True.index_col: bool. Whether to use the first column as index. The default is False.skiprows: list of int. The row numbers to skip ([0, 1] skips the first two rows). The default is [].skipcolumns: list of int. The column numbers to skip ([0, 1] skips the first two columns). The default is [].RaisesTypeErrorIf the file is no .xlsx or .xlsm file.FileNotFoundErrorIf the sheet name is not found.ReturnsPandas.DataFrame. The input file as DataFrame.
Package: excel-formulas-calculator
Excel-formulas-calculatorExcel-formulas-calculator (EFC) is a high-level Py23 library that allows you to calculate Excel formulas on any OS.Openpyxl interfacefromopenpyxlimportload_workbookfromefc.interfaces.iopenpyxlimportOpenpyxlInterfacewb=load_workbook('test.xlsx')interface=OpenpyxlInterface(wb=wb,use_cache=True)# e.g. A1 stores formula '=1 + 2', then result = 3result=interface.calc_cell('A1','Worksheet1')# EFC does not change the source documentprint(wb['Worksheet1']['A1'].value)# prints '=1 + 2'# If you need to replace a formula in a workbook with a value,# you need to do thiswb['Worksheet1']['A1'].value=interface.calc_cell('A1','Worksheet1')print(wb['Worksheet1']['A1'].value)# prints '3'# The EFC does not track changes to values in the workbook.# If the use_cache=True option is used, the calculated formulas# are not recalculated again when they are accessed.# e.g. A2 = 2, A3 = 1, A4 = A2 + A3print(interface.calc_cell('A4','Worksheet1'))# prints '3'wb['Worksheet1']['A2'].value=1234print(interface.calc_cell('A4','Worksheet1'))# prints '3'# If you have made changes to the workbook, then you need to reset# the cache to get up-to-date resultsinterface.clear_cache()print(interface.calc_cell('A4','Worksheet1'))# prints '1235'# You can disable caching of results,# but then when you run a large number of related formulas,# the calculation speed will decrease significantlyCustom interfaceInherit from efc.interface.BaseExcelInterface in your excel file class and implement abstract methods. This class will be used to get data from excel file using any library you want.Use calc_cell to calculate cell's formula.FunctionalityArithmetic:-, +, *, /, ^, ()Comparison:<>, >, >=, <, <=, =String concatenation:&Functions:ABS, AND, AVERAGE, AVERAGEIFS, COLUMN, CONCATENATE, COUNT, COUNTA, COUNTIF, COUNTIFS, COUNTBLANK,  FLOOR, IF, IFS, IFERROR, INDEX, ISBLANK, ISERROR, HLOOKUP, LARGE, LEN, LEFT, LOWER, MATCH, MAX, MID, MIN, MOD, NOT, OFFSET, OR, RIGHT, ROUND, ROUNDDOWN, ROW, SEARCH, SMALL, SUBSTITUTE, SUM, SUMIF, SUMIFS, TRIM, VLOOKUP, YEARFRAC,  UNIQUE, UPPERAll variations of the spelling of the cell and range addresses (linked docs will be skipped)Formula cell offset - this can be useful when calculating shared formulas
Package: excel-framework
A framework for creating excel files declaratively.openpyxlis a different library that is often used for creating excel files. However, it only provides very rudementary controls forcing you to access, style and fill every cell individually in an imperative manner. This can get unwieldy and difficult to maintain very quickly which is the problem solved by this package.excel-framworkbuilds on top ofopenpyxlproviding you with a large set of ui components that you can compose into new ones to create excel files in an easy, readable and maintainable way.The archictecture ofexcel-framworkwas inspired by the cross platform ui development frameworkflutter.QuickstartAn excel file with one cell containing hello world in bold:ExcelFile("hello.xlsx",sheets=[ExcelSheet("first sheet",child=Styler(child=ExcelCell("Hello World!"),style=Style(text_style=TextStyle(bold=True))))]).create()