Python 基于其他列的值比较值和颜色单元格
我正在从事一个项目,将最终值(在“金额”列中)与其他列中的值进行比较,以确定最终值是否超过预先确定的阈值。如果违反,则最终值将根据违反的阈值上色,如果未违反,则最终值将上色为绿色。样本:Python 基于其他列的值比较值和颜色单元格,python,pandas,formatting,styling,Python,Pandas,Formatting,Styling,我正在从事一个项目,将最终值(在“金额”列中)与其他列中的值进行比较,以确定最终值是否超过预先确定的阈值。如果违反,则最终值将根据违反的阈值上色,如果未违反,则最终值将上色为绿色。样本: df Product Components Amount Yellow Orange Red Bound A a1 61 50 55 60 Upper A
df
Product Components Amount Yellow Orange Red Bound
A a1 61 50 55 60 Upper
A a2 28 60 30 20 Lower
A a3 37 10 5 0 Lower
B b1 89 90 100 110 Upper
B b2 91 100 95 90 Lower
C c1 5 10 15 20 Upper
C c2 29 30 20 10 Lower
C c3 15 100 200 300 Upper
C c4 201 500 400 300 Lower
预期:
尝试使用以下代码:
def highlight(df):
r = 'red'
g = 'green'
o = 'orange'
y = 'yellow'
yellow_up = (df['Amount'] > df['Yellow']) & (df['Amount'] < df['Orange']) & (df['Amount'] < df['Red']) & (df['Bound']=='Upper')
orange_up = (df['Amount'] > df['Yellow']) & (df['Amount'] > df['Orange']) & (df['Amount'] < df['Red']) & (df['Bound']=='Upper')
red_up = (df['Amount'] > df['Yellow']) & (df['Amount'] > df['Orange']) & (df['Amount'] > df['Red']) & (df['Bound']=='Upper')
yellow_down = (df['Amount'] < df['Yellow']) & (df['Amount'] > df['Orange']) & (df['Amount'] > df['Red']) & (df['Bound']=='Lower')
orange_down = (df['Amount'] < df['Yellow']) & (df['Amount'] < df['Orange']) & (df['Amount'] > df['Red']) & (df['Bound']=='Lower')
red_down = (df['Amount'] < df['Yellow']) & (df['Amount'] < df['Orange']) & (df['Amount'] < df['Red']) & (df['Bound']=='Lower')
df1 = pd.DataFrame('background-color: ', index = df.index, columns = df.columns)
df1['Amount'] = np.where(yellow_up, 'background-color: {}'.format(y), 'background-color: {}'.format(g))
df1['Amount'] = np.where(orange_up, 'background-color: {}'.format(o), 'background-color: {}'.format(g))
df1['Amount'] = np.where(red_up, 'background-color: {}'.format(r), 'background-color: {}'.format(g))
df1['Amount'] = np.where(yellow_down, 'background-color: {}'.format(y), 'background-color: {}'.format(g))
df1['Amount'] = np.where(orange_down, 'background-color: {}'.format(y), 'background-color: {}'.format(g))
df1['Amount'] = np.where(red_down, 'background-color: {}'.format(y), 'background-color: {}'.format(g))
return df1
df.style.apply(highlight, axis = None)
def突出显示(df):
r=‘红色’
g=‘绿色’
o=‘橙色’
y=‘黄色’
黄色上移=(df['Amount']>df['yellow'])和(df['Amount']df['Yellow'])和(df['Amount']>df['orange'])和(df['Amount']df['Yellow'])和(df['Amount']>df['Orange'])和(df['Amount']>df['red'])和(df['Bound']='Upper')
黄色向下=(df['Amount']df['Orange'])和(df['Amount']>df['Red'])和(df['Bound']='Lower')
橙色向下=(df['Amount']df['Red'])和(df['Bound']='Lower')
红色向下=(df['Amount']
然而,这并不像预期的那样有效。提前感谢您的帮助 我会这样写函数:
def highlight(row):
color_map = {'Yellow':'yellow','Orange':'orange', 'Red':'red'}
name = row.name
thresh = df.loc[name, ['Yellow','Orange','Red']]
direction = -1 if df.at[name, 'Bound']=='Upper' else 1
value = row['Amount'] * direction
thresh = (thresh * direction).sort_values()
if (thresh > value).any():
color = color_map[(thresh > value).idxmax()]
else:
color = 'green'
return [f'background-color:{color}']
# apply
df.style.apply(highlight, subset=['Amount'], axis=1)
输出:
非常感谢您!这正是我要找的。问题,name=row.name,行是否应该是df['Amount']?我在试着理解你的逻辑。看了一段时间后,你之所以选择“row”作为函数的参数,是因为末尾的axis=1吗?@bomann是的,axis=1在这种情况下表示row。和
行。name
是该行的索引。