XlsxWriter | A Python module for creating Excel XLSX files | Data Visualization library
kandi X-RAY | XlsxWriter Summary
kandi X-RAY | XlsxWriter Summary
A Python module for creating Excel XLSX files.
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Top functions reviewed by kandi - BETA
- Compute conditional format
- Returns the workbook
- Return the index number for a format
- Return simple table data
- Add a table to the table
- Convert a table function to a worksheet formula
- Writes a blank cell to the worksheet
- Write to a cell
- Protect the worksheet
- Set the header
- Inserts a chart into the worksheet
- Set row
- Substitute a column
- Writes the legend element
- Set footer
- Validate data
- Add sparkline
- Add a series to an Excel chart
- Set the column width
- Write the plotArea element
- Set up the up and down bars
- Defines a defined name
- Merge a range of cells
- Add a chart
- Prepare drawing
- Protect sheet
XlsxWriter Key Features
XlsxWriter Examples and Code Snippets
Lines of Code : 22License : Strong Copyleft (CC BY-SA 4.0)
Copyimport pandas as pd
import linecache
import xlsxwriter as xlsw
import os
import glob
directory=('test')
os.chdir(directory)
files=glob.glob('*.txt')
final_list = []
for filename in files:
name = linecache.getline(filename,5)
id = linecdf = pd.read_excel('sample_file.xlsx')
#test all rows if previous row is only NaNs
m1 = df.shift(fill_value=0).isna().all(axis=1)
#test all rows if no NaNs
m2 = df.notna().all(axis=1)
#chain together and filter all next rows after first mdf # you already have it
df_excel = pd.read_excel('Aged Data.xlsx', sheet_name='Sheet1')
pd.concat([df, df_excel], axis=0).to_excel('output.xlsx')
with pd.ExcelWriter('output.xlsx') as xlsx:
df1.to_excel(xlsx, sheet_name='Sheet 1')
df2.to_excel(xlsx, sheet_name='Sheet 1', startrow=len(df1) + 2)
cell1="A"+str(cellone)
cell1=f"A{cellone}"
pyinstaller --onefile main.py
if getattr(sys, 'frozen', False):
application_path = os.path.dirname(sys.executable)
elif __file__:
application_path = os.path.dirname(__file__)
python is /opt/anaconda3/bin/python
python is /usr/local/bin/python
python is /usr/bin/python
import xlsxwriter
workbook = xlsxwriter.Workbook('test.xlsx')
worksheet = workbook.add_worksheet()
worksheet.write_dynamic_array_formula(0, 0, 0, 0, '=SUM(IF($F$5:$F$130=$F$4,I$5:I$130))')
workbook.close()
import xlsxwriter
workbook = xlsxwriter.Workbook('panes.xlsx')
worksheet = workbook.add_worksheet()
side_format = workbook.add_format({'bold': True,
'fg_color': '#D7E4BC',
@app.callback(
Output("download_xlsx", "data"),
Input("btn_download_xlsx", "n_clicks"), State("df", "data")
)
def download_xlsx(n_clicks, json_df):
df = pd.read_json(json_df)
if os.path.exists("export.xlsx"):
os.remove(Community Discussions
Trending Discussions on XlsxWriter
QUESTION
I wrote a script that reads this .xlsx file, then creates a column that is the sum of the three other columns, and saves everything into a new file:
...ANSWER
Answered 2022-Mar-24 at 22:46How might I create a formula in pandas without using such tools?
Pandas uses xlsxwriter (or openpyxl) to create xlsx file so you are already using them.
You can add formulas, instead of a static sum, like this:
QUESTION
ANSWER
Answered 2022-Mar-08 at 21:54Possible solution is following:
QUESTION
UPDATE: Fixed. Sheet protected, selected column is possible to unhide.
Is it possible to lock all visible cells (protection from editing), but still allow the users to unhide certain columns?
I would like to export a pandas dataframe via pd.excel_writer().
worksheet.protect() doesn't allow for any arguments? I apply column-wise formatting and tried 'lock': False on the hidden columns, but that didn't work.
...ANSWER
Answered 2022-Jan-31 at 12:24You just need to set protect() to turn on worksheet protection but turn on the exceptions that you want. In this case turning on "Format Columns" should get you what you want:
QUESTION
I'm trying to write a dataframe along with the axis name to an excel file.
...ANSWER
Answered 2022-Jan-19 at 08:03You can pass df.columns.name to parameter index_label:
QUESTION
i using VSCode as my IDE for development odoo and for now run using Start > Debugging ( F5)
While running at web browser localhost:8069 ( default ) then appear Internal Server Error and in terminal VSCode there are errors :
...ANSWER
Answered 2021-Dec-27 at 17:01After trying for a few days and just found out that pip and python in the project are not pointing to .venv but to anaconda due to an update. when error
no module stdnum
actually there is a problem with pip so make sure your pip path with which pip or which python
- to solve .venv that doesn't work by deleting the .venv folder, create venv in python, and install all requirements again
QUESTION
I have few dataframes in an excel sheet with 2 rows of spaces between them and now I want to give title or description to those dfs. How is it possible?
Used this function for multiple dfs
...ANSWER
Answered 2021-Dec-20 at 15:57You can wrap your description in a Series and write it the same way as the dataframe:
QUESTION
I'll preface this with the fact that I am new to Python and coding in general. I can successfully separate my data based on unique values in a certain column, but as the for loop iterates I also want to create a plot. For some reason, python is creating the separate Excel sheets but is completely ignoring the plot. Any advice/pointing out what I'm doing wrong would be greatly appreciated.
...ANSWER
Answered 2021-Dec-08 at 08:51The main issue is that the program is overwriting the xlsx file created by xlsxwriter.Workbook() with one of same name created by df1.to_excel().
See the XlsxWriter docs on Working with Python Pandas and XlsxWriter for the correct way to use Pandas and XlsxWriter together.
Fixing that issue the program should work. Here is an updated version:
QUESTION
It has been a few days since I rebuilt my project but when I was testing some things this morning I wanted to update my Werkzeug package due to an issue I was having with its Multidict class, I rebuilt and started getting this error:
...ANSWER
Answered 2021-Oct-07 at 02:19If you have a look for the base image, you could see it just be updated 27hours ago.
QUESTION
This seems relatively straight forward, but I have yet to find a duplicate that answers my question, or a method with the needed functionality.
I have an Excel spreadsheet where each column that contains data has a unique header. I would like to use pandas to get the letter key of the column by passing this header string into a function.
For example, if I pass "Output Parameters" to the function, I would like to return "M":
The closest thing that I have found is the xlsxwriter.utility.xl_col_to_name(index) method outlined in the second answer in Convert spreadsheet number to column letter
This is very similar to what I am trying to do, however the column numbers within my sheets will not remain constant (unlike the headers, which will). This being said, a method that can return the column number based on the header would also work, as I would then be able to apply the above.
Does pandas or xlsxwriter have a method that can handle the above case?
ANSWER
Answered 2021-Sep-29 at 08:20You can try:
QUESTION
I am currently trying to export my data frame into a csv. The basis of the code is to run a list of tickers through yahoo_fin and get options data. The code works, and I retrieve info for every ticker, however, when I assign the stocks a data frame to export into csv form, the csv only opens with the last item on the list. Example:
...ANSWER
Answered 2021-Sep-24 at 18:06The df.to_csv is in your for loop so it writes a CSV file at every iteration. However, the name of the CSV file is always the same, so it overwrites the previous file at every iteration.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install XlsxWriter
You can use XlsxWriter like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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