PyExcelerate | Accelerated Excel XLSX Writing Library for Python | Data Visualization library
kandi X-RAY | PyExcelerate Summary
kandi X-RAY | PyExcelerate Summary
PyExcelerate is a Python for writing Excel-compatible XLSX spreadsheet files, with an emphasis on speed.
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Top functions reviewed by kandi - BETA
- Returns the style of this cell
- Apply method to data
- Get an attribute from the worksheet
- Set row style
- Get row style
- Get XML data
- Get cell data
- Convert datetime to an Excel date
- Convert a coordinate to a string
- Write the Workbook to a ZIP file
- Render a template
- Get the XML representation of a column
- Return the data type of the given value
- Get the xml data
- Align styles
- Get row string for row
PyExcelerate Key Features
PyExcelerate Examples and Code Snippets
Lines of Code : 8License : Strong Copyleft (CC BY-SA 4.0)
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from pyexcelerate import Workbook
values = [df.columns] + list(df.values)
wb = Workbook()
wb.new_sheet('data_sheet_name', data=values)
wb.save('data.xlsx')
wb = Workbook()
ws = wb.new_sheet("sheet name")
style = Style(fill=Fill(background=Color(255,0,0,0)))
for row in range(1, len(rows) + 1, 2):
ws.set_row_style(row, style)
wb.save("output.xlsx")
df = DataFrame({'Name': ['a', 'b', 'c'], 'Age': ['one', 'two', 'three']})
data = [df.columns.tolist()] + df.values.tolist()
data = [[index] + row for index, row in zip(df.index, data)]
import timeit
from pyexcelerate import Workbook
def to_Excel(data, fileName):
start_time = timeit.default_timer()
wb = Workbook()
for key in data.keys():
ws = wb.new_sheet(key)
fdf = df[~df.sku.isin(delete_set)]
print(df)
sku product_group name
0 ABAAb00610-23.0 ABA1 Anti-Involucrin [SY5]
1 ABAAb00610-10.0 ABA1 Anti-Involucrin [SY5]
2 Community Discussions
Trending Discussions on PyExcelerate
QUESTION
I have the following table
I want to convert int into a matrix using python, to look something like below:
Can I get some direction as to where to start with this? I have used pandas to read two dataframes and merge them to create the initial table I have shown(one having two columns).
Code I am using is below is below:
...ANSWER
Answered 2019-Sep-02 at 01:40We can do
QUESTION
I am trying to compare value associated with the index to values associated with other index and come up with percentage match.
I have the below table :
...ANSWER
Answered 2019-Sep-03 at 04:35I show you the solution I have found:
I have named df to:
QUESTION
What I'm trying to do is delete several rows of an Excel-Files (with pandas) and then save the File without those rows to .xlsx (with pyexcelerate module).
I'm aware that I can remove rows of a data frame by dropping them (I already got that to work). But I have read in several posts that when there are many (in my case > 5000) rows that should be deleted it's much faster to just get the indexes of the "to delete" rows from the data frame and then slice the data frame (just as a SQL Except statement for example would do). Unfortunately I can't get it to work, even though I've tried several methods.
Here are my "source posts":
Slice Pandas dataframe by labels that are not in a list - Answer from User ASGM
How to drop a list of rows from Pandas dataframe? - Answer from User Dennis Golomazov
And here is a part of the function, that should delete the rows and save the created file:
...ANSWER
Answered 2017-Oct-02 at 14:37Use pd.Series.isin:
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