Coloring Single Column of Pandas Dataframe.to_html()


Before this is marked as duplicate, I have tried the code from the following topics and none has worked for me thus far:

[<a href="https://stackoverflow.com/questions/44388149/colouring-one-column-of-pandas-dataframe" rel="nofollow">Colouring one column of pandas dataframe</a> ]

[<a href="https://stackoverflow.com/questions/43839112/format-the-color-of-a-cell-in-a-panda-dataframe-according-to-multiple-conditions" rel="nofollow">Format the color of a cell in a panda dataframe according to multiple conditions</a> ]

[<a href="https://stackoverflow.com/questions/42408246/how-to-color-selected-columns-in-python-dataframe" rel="nofollow">how to color selected columns in python dataframe?</a> ]

I have code that produces three pandas dataframe that looks like this:

RowName Orders Market StartTime StopTime Status good A 9 gold 10:00:00 10:09:45 . . . bad B 60 silver 07:54:43 08:02:12 RowName Orders Market StartTime StopTime Status good E 19 plat. 10:00:00 10:09:45 . . bad F 54 mercury 07:54:43 08:02:12 RowName Orders Market StartTime StopTime Status great D 3 alum. 10:00:00 10:09:45 . . ok C 70 bronze 07:54:43 08:02:12

where the Status column is set as the index of each frame

<strong>For each frame</strong>, I want to highlight the StartTime column with the value #D42A2A (aka red) regardless of what value is in a given cell.

How can this be done?



def column_style(col): if col.Name == 'StartTime': return pd.Series('bgcolor: #d42a2a', col.index)

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def col_color(data): color = 'red' if data != '' else 'black' return 'color: %s' %color frame.style.applymap(col_color, subset=['StartTime'])

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but this also fails.



I am using VI within a linux shell

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The entire script is being called by IE (internet explorer) so the output of the script is html

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I am using BS (beautifulsoup) to scrape data from a few sites and the aggregating the results onto one page {*after scraping the initial website and creating the required website (call it Page1), I tried to scrape Page1 in the same script and add in the html lines via the .attrs method, but this "fails", i.e. the webserver times out during the run}

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Let's try this:

import pandas as pd import numpy as np np.random.seed(24) df = pd.DataFrame({'A': np.linspace(1, 10, 10)}) df = pd.concat([df, pd.DataFrame(np.random.randn(10, 4), columns=list('BCDE'))], axis=1) df.iloc[0, 2] = np.nan def highlight_column(s, col): return ['background-color: #d42a2a' if s.name == col else '' for v in s.index] df.style.apply(highlight_column, col = 'B')


<a href="https://i.stack.imgur.com/ZtZ4J.jpg" rel="nofollow"><img alt="enter image description here" class="b-lazy" data-src="https://i.stack.imgur.com/ZtZ4J.jpg" data-original="https://i.stack.imgur.com/ZtZ4J.jpg" src="https://etrip.eimg.top/images/2019/05/07/timg.gif" /></a>


If anyone is using BeautifulSoup to parse a website and then using pandas to create a DataFrame that you may want to add styles to, you can do something like:

(before using this you have already; imported beautifulsoup, scraped your site and created your dataframe)

variable_name = beautifulsoup(dataframe_name.to_html())

list = []

`for table in variable_name.findAll('table'):` `for tbody in variable_name.findAll('table'):` `for td in variable_name.findAll('tbody'):` `list.append(td)`

list[td_index]['attribute_name'] = 'attribute_value'

This will add your all your table data to a list and you can select any element from that list and add/update a tag attribute

(if more efficient way please comment to help improve)


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