我的数据框如下:
Week Item Buyer 11 12 13
0 clothes buyerID1 2 3 4
1 food buyerID2 2 1 1
2 water buyerID 7 5 1
11、12、13是星期。我试图有条件地为最后一列的行涂上颜色,以描述每周购买的物品的变化。我在这里使用another answer的改编版本,但是遇到了IndexingError: Too many indexers
错误。
下面是我的修改代码:
def highlight3(x):
#if increase
c1 = 'background-color: green'
#if decrease
c2 = 'background-color: red'
c3 = ''
#last row greater than value in second to last row
m1 = x.iloc[:, -1] > x.iloc[:, -2]
#last row lesser than value in second to last row
m2 = x.iloc[:, -1] < x.iloc[:, -2]
out = np.select([m1, m2], [c1, c2], default=c3)
return pd.DataFrame(out, index=x.index, columns=x.columns)
然后使用以下命令将其应用于我的df:df.apply(highlight3, axis=None)
答案 0 :(得分:1)
这是一个解决方案:
data = """Week Item Buyer 11 12 13
0 clothes buyerID1 2 3 4
1 food buyerID2 2 1 1
2 water buyerID 7 5 1 """
df = pd.read_csv(StringIO(data), sep="\s+")
green = 'background-color: green'
red = 'background-color: red'
def style_last_week(x):
s = pd.Series([""] * x.size)
if x[-1] > x[-2]:
s[x.size -1 ] = green
if x[-2] > x[-1]:
s[x.size -1 ] = red
return s
df.style.apply(style_last_week, axis=1)
结果是: