本文介绍了使用Pandas突出显示不同颜色的多个单元格的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
假设我们有一个数据框,我想给不同的单元格涂上颜色:
- 单元格
['Arizona','company'](1st)
,['Texas','size'](1099)
为绿色。 - 单元格
['Florida','veterans'](26)
,['Maine','armored'](0)
为红色。
做这件事的好方法是什么?
raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'],
'company': ['1st', '1st', '2nd', '2nd', '1st', '1st', '2nd', '2nd','1st', '1st', '2nd', '2nd'],
'deaths': [523, 52, 25, 616, 43, 234, 523, 62, 62, 73, 37, 35],
'battles': [5, 42, 2, 2, 4, 7, 8, 3, 4, 7, 8, 9],
'size': [1045, 957, 1099, 1400, 1592, 1006, 987, 849, 973, 1005, 1099, 1523],
'veterans': [1, 5, 62, 26, 73, 37, 949, 48, 48, 435, 63, 345],
'readiness': [1, 2, 3, 3, 2, 1, 2, 3, 2, 1, 2, 3],
'armored': [1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1],
'deserters': [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],
'origin': ['Arizona', 'California', 'Texas', 'Florida', 'Maine', 'Iowa', 'Alaska', 'Washington', 'Oregon', 'Wyoming', 'Louisana', 'Georgia']}
df = pd.DataFrame(raw_data, columns = ['regiment', 'company', 'deaths', 'battles', 'size', 'veterans', 'readiness', 'armored', 'deserters', 'origin'])
df = df.set_index('origin')
df.head()
(http://chrisalbon.com/python/pandas_indexing_selecting.html)
推荐答案
可以将slicing in Style与参数subset
和函数Styler.applymap
一起使用以获得基本样式,请在jupyter notebook
中运行代码:
import pandas as pd
import numpy as np
def red(val):
color = 'red'
return 'background-color: %s' % color
def green(val):
color = 'green'
return 'background-color: %s' % color
raw_data = {'regiment': ['Nighthawks', 'Nighthawks', 'Nighthawks', 'Nighthawks', 'Dragoons', 'Dragoons', 'Dragoons', 'Dragoons', 'Scouts', 'Scouts', 'Scouts', 'Scouts'],
'company': ['1st', '1st', '2nd', '2nd', '1st', '1st', '2nd', '2nd','1st', '1st', '2nd', '2nd'],
'deaths': [523, 52, 25, 616, 43, 234, 523, 62, 62, 73, 37, 35],
'battles': [5, 42, 2, 2, 4, 7, 8, 3, 4, 7, 8, 9],
'size': [1045, 957, 1099, 1400, 1592, 1006, 987, 849, 973, 1005, 1099, 1523],
'veterans': [1, 5, 62, 26, 73, 37, 949, 48, 48, 435, 63, 345],
'readiness': [1, 2, 3, 3, 2, 1, 2, 3, 2, 1, 2, 3],
'armored': [1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1],
'deserters': [4, 24, 31, 2, 3, 4, 24, 31, 2, 3, 2, 3],
'origin': ['Arizona', 'California', 'Texas', 'Florida', 'Maine', 'Iowa', 'Alaska', 'Washington', 'Oregon', 'Wyoming', 'Louisana', 'Georgia']}
df = pd.DataFrame(raw_data, columns = ['regiment', 'company', 'deaths', 'battles', 'size', 'veterans', 'readiness', 'armored', 'deserters', 'origin'])
df = df.set_index('origin')
print (df)
df.style.applymap(green, subset=pd.IndexSlice['Arizona':'Texas', 'company': 'size'])
.applymap(red, subset=pd.IndexSlice['Florida':'Maine', 'veterans': 'armored'])
如果只需要更改DataFrame
中的一些值,您可以使用Styler.apply
WITHaxis=None
作为表式样式,该函数还必须返回具有相同索引和列标签的DataFrame
:
def create_colors(x):
#copy df to new - original data are not changed
df1 = x.copy()
#select all values to default value - no color
df1.loc[:,:] = 'background-color: '
#overwrite values with green and red color
df1.loc['Arizona', 'company'] = 'background-color: green'
df1.loc['Texas', 'size'] = 'background-color: green'
df1.loc['Florida', 'veterans'] = 'background-color: red'
df1.loc['Maine', 'armored'] = 'background-color: red'
#return color df
return df1
df.style.apply(create_colors, axis=None)
这篇关于使用Pandas突出显示不同颜色的多个单元格的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持编程学习网!
本站部分内容来源互联网,如果有图片或者内容侵犯您的权益请联系我们删除!