pandas 有条件地格式化粗体字段

Question

I have a pandas dataframe:

import pandas as pd
import numpy as np

df = pd.DataFrame({'foo':[1,2, 3, 4],
                   'bar':[[1,2,0.04], [1,2,0.04], [1,2,0.06], np.nan]})
display(df)

def stars(x, sign_level):
    if x is np.nan:
        return ''
    else:
        p_value = x[2]
        if p_value < sign_level:
            return '*'
        else:
            return ''

df['marker'] = df.bar.apply(stars, sign_level=0.05)
df

Instead of adding a column with a star in case the result is considered significant, is it possible to format the cell (like in an Excel sheet) as bold?

display DataFrame() values in bold font in one row only seems to be able to format a whole row - I would like to reformat only a specific cell

Conditionally format Python pandas cell

seems similar, though they only change the background, not format as bold.

edit

the code below can already change the background color - I just do not know how to format as bold.

def highlight_significant(x, sign_level):
    if x is np.nan:
        return ''
    else:
        if isinstance(x, list):
            p_value = x[2]
            color = 'lightgreen' if p_value < sign_level else ''
            if p_value < sign_level:
                return 'background-color: %s' % color
            else:
                return ''
        else:
            return ''

df.style.applymap(highlight_significant, sign_level=0.05)

Answer 1

This might help...

Set up a dataframe

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

create functional you can apply to add bold based on a condition of you define

def negative_bold(val):


    bold = 'bold' if val < 0 else ''


    return 'font-weight: %s' % bold

Apply the function to the style of the data frame

s = df.style.applymap(negative_bold)

Look at the dataframe, you should find all negative numbers are bold

I looked here https://mode.com/example-gallery/python_dataframe_styling/ and here https://pandas.pydata.org/pandas-docs/stable/user_guide/style.html

EDIT Adding to this answer...

Combining two styles

I have two functions, one to highlight yellow the number is negative and another make the number bold if negative

Negative_yellow

def negative_yellow(val):


    color = 'yellow' if val < 0 else ''


    return 'background-color:' + color  

Negative bold

def negative_bold(val):


    bold = 'bold' if val < 0 else ''


    return 'font-weight: %s' % bold

I apply the two the data frame like this

df.style.\
    applymap(negative_yellow).\
    applymap(negative_bold)

I imagine there are more elegant ways of doing this. Hope this helps:)