pandas 样式功能突出显示特定列 [英] Pandas style function to highlight specific columns

问题描述

我一直在尝试编写一个用于熊猫风格的函数.我想突出显示我在参数中指定的列.这不是很优雅，但是，例如:

I have been trying to write a function to use with pandas style. I want to highlight columns that I specify in the arguments. This is not very elegant, but, for example:

data =  pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))

def highlight_cols(df, cols, colcolor = 'gray'):
    for col in cols:
        for dfcol in df.columns:
            if col == cols:
                color = colcolor
    return ['background-color: %s' % color]*df.shape[0]

然后致电:

data.style.apply(highlight_cols(cols=['B','C']))

我得到一个错误: (系列"对象没有属性列"")

I get an error: ("'Series' object has no attribute 'columns'")

我认为我从根本上不了解样式器如何调用和应用该函数.

I think I fundamentally don't quite understand how the styler calls and applies the function.

谢谢

推荐答案

我认为您可以使用

I think you can use Slicing in Styles for select columns B and C and then Styler.applymap for elementwise styles.

import pandas as pd
import numpy as np

data =  pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
#print (data)

def highlight_cols(s):
    color = 'grey'
    return 'background-color: %s' % color

data.style.applymap(highlight_cols, subset=pd.IndexSlice[:, ['B', 'C']])

如果要更多颜色或更灵活，请使用Styler.apply(func, axis=None)，该函数必须返回具有相同索引和列标签的DataFrame:

If you want more colors or be more flexible, use Styler.apply(func, axis=None), the function must return a DataFrame with the same index and column labels:

import pandas as pd
import numpy as np

data =  pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
#print (data)

def highlight_cols(x):
    #copy df to new - original data are not changed
    df = x.copy()
    #select all values to default value - red color
    df.loc[:,:] = 'background-color: red'
    #overwrite values grey color
    df[['B','C']] = 'background-color: grey'
    #return color df
    return df    

data.style.apply(highlight_cols, axis=None)

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