Python Pandas 样式功能突出显示特定列
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Pandas style function to highlight specific columns
提问by Maria Petrova
I have been trying to write a function to use with pandas style. I want to highlight columns that I specify in the arguments. This is not very elegant, but, for example:
我一直在尝试编写一个用于熊猫风格的函数。我想突出显示我在参数中指定的列。这不是很优雅，但是，例如：
data = pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
def highlight_cols(df, cols, colcolor = 'gray'):
for col in cols:
for dfcol in df.columns:
if col == cols:
color = colcolor
return ['background-color: %s' % color]*df.shape[0]
then call with:
然后调用：
data.style.apply(highlight_cols(cols=['B','C']))
I get an error: ("'Series' object has no attribute 'columns'")
我收到一个错误：（“'Series' 对象没有属性 'columns'”）
I think I fundamentally don't quite understand how the styler calls and applies the function.
我想我从根本上不太了解样式器如何调用和应用该函数。
Thanks,
谢谢，
回答by jezrael
I think you can use Slicing in Stylesfor select columns Band Cand then Styler.applymapfor elementwise styles.
我想你可以使用在切片Styles的选择列B，并C再Styler.applymap为按元素的风格。
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
#print (data)
def highlight_cols(s):
color = 'grey'
return 'background-color: %s' % color
data.style.applymap(highlight_cols, subset=pd.IndexSlice[:, ['B', 'C']])
If you want more colors or be more flexible, use Styler.apply(func, axis=None), the function must return a DataFramewith the same index and column labels:
如果您想要更多颜色或更灵活，请使用Styler.apply(func, axis=None)，该函数必须返回DataFrame具有相同索引和列标签的 a：
import pandas as pd
import numpy as np
data = pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
#print (data)
def highlight_cols(x):
#copy df to new - original data are not changed
df = x.copy()
#select all values to default value - red color
df.loc[:,:] = 'background-color: red'
#overwrite values grey color
df[['B','C']] = 'background-color: grey'
#return color df
return df
data.style.apply(highlight_cols, axis=None)
回答by MaxU
You can do it bit more dynamically:
您可以更动态地执行此操作：
data = pd.DataFrame(np.random.randn(5, 3), columns=list('ABC'))
# dictionary of column colors
coldict = {'A':'grey', 'C':'yellow'}
def highlight_cols(s, coldict):
if s.name in coldict.keys():
return ['background-color: {}'.format(coldict[s.name])] * len(s)
return [''] * len(s)
data.style.apply(highlight_cols, coldict=coldict)
