pandas DataFrame 列的条件格式基于列 header 字符串

Question

如果单元格大于依赖于列 header 的值，我想突出显示它们。

我要'read'列header，如果在字典中（CEPA_FW）则返回相应的值。然后，如果该列中的任何单元格大于此值，它们将填充为深橙色。我的努力在下面，但我收到错误（ValueError：长度不匹配：预期轴有 1 个元素，新值有 4 个元素）。

df=pd.DataFrame(({'As':['0.001', 0, '0.001','0.06'], 'Zn': ['6','4','6','8'], 'Pb': ['0.006','0','0.005','0.005'], 'Yt': [1,0,0.002,6]}))
cols=df.columns

CEPA_FW=  {'Ag':0.05,'As' :0.05 ,'Ba':1.0,'B':1.0,'Cd' :0.01 ,'Cr' :0.05 ,'Co':0.001,'Cu' :1.0 ,'K':5.0,'Pb' :0.005 ,'Hg' :0.0002 ,'Mn':0.5,'Ni' :1.0 ,'Se':0.01,'Sn':0.5,'SO4':400.0,'Zn' :5.0}



def fill_exceedances(val):
    for header in cols:
        if header in CEPA_FW:
            for c in df[header]:
                fill = 'darkorange' if c> CEPA_FW[header] else ''
                return ['backgroundcolor: %s' % fill]

df.style.apply(fill_exceedances, axis = 1).to_excel('styled.xlsx', engine='openpyxl')

Answer 1

使用自定义函数创建 DataFrame 按条件填充样式：

def fill_exceedances(x):
    color = 'orange'
    #get columns which are in keys of dict
    c = x.columns.intersection(CEPA_FW.keys())
    #filter columns and rename by dict
    df2 = x[c].rename(columns=CEPA_FW)
    #create boolean mask only for matched columns and compare
    mask = df2.astype(float).values > df2.columns[None,:].values
    #new DataFrame filled by no color
    df1 = pd.DataFrame('', index=x.index, columns=c)
    #set color by mask and add missing non matched columns names by reindex
    df1 = (df1.where(mask, 'background-color: {}'.format(color))
              .reindex(columns=x.columns, fill_value=''))

    return df1

df.style.apply(fill_exceedances, axis=None).to_excel('styled.xlsx', engine='openpyxl')

pandas DataFrame 列的条件格式基于列 header 字符串

Conditional formatting of pandas DataFrame columns based on column header string

python

conditional-formatting

pandas