pandas 如何在熊猫中同时突出显示一行和一列
声明：本页面是StackOverFlow热门问题的中英对照翻译，遵循CC BY-SA 4.0协议，如果您需要使用它，必须同样遵循CC BY-SA许可，注明原文地址和作者信息，同时你必须将它归于原作者（不是我）：StackOverFlow
原文地址: http://stackoverflow.com/questions/40335140/
Warning: these are provided under cc-by-sa 4.0 license. You are free to use/share it, But you must attribute it to the original authors (not me):
StackOverFlow
How to highlight both a row and a column at once in pandas
提问by maxymoo
I can highlight a column using the syntax
我可以使用语法突出显示一列
import pandas as pd
df = pd.DataFrame([[1,0],[0,1]])
df.style.apply(lambda x: ['background: lightblue' if x.name == 0 else '' for i in x])
Similarly I can highlight a row by passing axis=1:
同样，我可以通过传递突出显示一行axis=1：
df.style.apply(lambda x: ['background: lightgreen' if x.name == 0 else '' for i in x],
axis=1)
However I can't work out how to do both at once; the problem is that when I use applymap, I only get the values, not the names of the series that they come from.
但是我不知道如何同时做这件事；问题是，当我使用 时applymap，我只得到值，而不是它们来自的系列的名称。
采纳答案by Psidom
How about doing something like this? Enumerate the column and check the index while building up the style list:
做这样的事情怎么样？枚举列并在构建样式列表时检查索引：
df.style.apply(lambda x: ['background: lightblue' if x.name == 0 or i == 0 else ''
for i,_ in x.iteritems()])
Or if you have color preference:
或者，如果您有颜色偏好：
df.style.apply(lambda x: [('background: lightblue' if x.name == 0
else ('background: lightgreen' if i == 0 else ''))
for i,_ in x.iteritems()])
回答by Iman Mirzadeh
You can also chain your styles:
您还可以链接您的样式：
import pandas as pd
df = pd.DataFrame([[1,0],[0,1]])
df.style\
.apply(lambda x: ['background: lightblue' if x.name == 0 else '' for i in x])\
.apply(lambda x: ['background: lightgreen' if x.name == 0 else '' for i in x], axis=1)
