在 pandas 数据框 python 中匹配列并突出显示结果

Question

我想在 pandas 数据框中找到两列之间的匹配项并突出显示两列的结果，所以我做了以下代码：

df=pd.DataFrame({'Name':['Zea mays','Zea mays subsp. mexicana','Zea mays subsp. parviglumis'],'ID':[1,2,3],'type':[1.1,1.2,1.3],
                 'Name.1':['Zea mays subsp. huehuetenangensis','Zea mays subsp. mays','Zea mays'],'ID.1':[1,2,3],'type.1':[1.1,1.2,1.3],
                 'Name.2':['Zea nicaraguensis','Zea luxurians','Zea perennis'],'ID.2':[1,2,3],'type.2':[1.1,1.2,1.3],
                 'Name.3':['Capsicum annuum','Capsicum frutescens','Capsicum chinense'],'ID.3':[1,2,3],'type.3':[1.1,1.2,1.3]})

def in_statements(s):
    color = 'yellow'
    if np.where(str(s.iloc[4]) == str(s.iloc[8])):
        color = 'yellow'
    else:
        color = 'black'
    return 'background-color: %s' % color
df.style.applymap(in_statements)

但是，它给了我这个错误：“（“'str' 对象没有属性 'iloc'”，'occurred at index Samples'）”

这是输入的例子：

它应该是这样的：

有人能指出我正确的方向吗？谢谢

Answer 1

如果要突出显示 Name 列中的重复值，请使用 Styler.apply with mask creted by DataFrame.filter for columns with Name, reshaped by DataFrame.stack, get duplicates by Series.duplicated and reshaped back by Series.unstack:

df=pd.DataFrame({'Name':['Dog','Dog.1','Dog.3'],'ID':[1,2,3],'type':[1.1,1.2,1.3],
                 'Name.1':['Dog','cat','Dog.3'],'ID.1':[1,2,3],'type.1':[1.1,1.2,1.3],
                 'Name.2':['cat','cat.12','Dog.1'],'ID.2':[1,2,3],'type.2':[1.1,1.2,1.3],
                 'Name.3':['cat.7','cat.13','Dog.3'],'ID.3':[1,2,3],'type.3':[1.1,1.2,1.3]})

print (df)
    Name  ID  type Name.1  ID.1  type.1  Name.2  ID.2  type.2  Name.3  ID.3  \
0    Dog   1   1.1    Dog     1     1.1     cat     1     1.1   cat.7     1   
1  Dog.1   2   1.2    cat     2     1.2  cat.12     2     1.2  cat.13     2   
2  Dog.3   3   1.3  Dog.3     3     1.3   Dog.1     3     1.3   Dog.3     3   

   type.3  
0     1.1  
1     1.2  
2     1.3  

def color(x):
    c1 = 'background-color: yellow'
    c = '' 
    #compare columns
    names = x.filter(like='Name')
    mask = names.stack().duplicated(keep=False).unstack()
    #DataFrame with same index and columns names as original filled empty strings
    df1 =  pd.DataFrame(c, index=x.index, columns=x.columns)
    #modify values of df1 column by boolean mask
    df1 = names.mask(mask, c1).reindex(df1.columns, axis=1, fill_value='')
    return df1


df.style.apply(color, axis=None).to_excel('df.xlsx', engine='openpyxl', index=False)

在 pandas 数据框 python 中匹配列并突出显示结果

Match columns and Highlight results in pandas dataframe python

python

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pandas