由于Python的去重方式比较多，本人在项目中总结了几种常用方法，欢迎补充。
一、对列表去重
1.用循环查找的方式
li = [1,2,3,3,4,2,3,4,5,6,1]
news_li = []
for i in li:
if i not in news_li:
news_li.append(i)
print (news_li)
2.用集合的特性set()
li1 = [1,4,3,3,4,2,3,4,5,6,1]
new_li1 = list(set(li1))
3.使用itertools模块的grouby方法
import itertools
li2 = [1,4,3,3,4,2,3,4,5,6,1]
li2.sort() # 排序
it = itertools.groupby(li2)
for k, g in it:
print (k)
4.运用while循环遍历的方式
def quchong(lb):
for x in lb:
while lb.count(x)>1:
del lb[lb.index(x)]
return lb
li3 = [1,4,3,3,4,2,3,4,5,6,1]
quchong(li3)
5.使用keys()方式
li4 = [1,0,3,7,7,5]
formatli = list({}.fromkeys(li4).keys())
print (formatli)
二、对数据框去重
1.用unique()对单属性列去重
import pandas as pd
data = {'id':['A','B','C','C','C','A','B','C','A'],'age':[18,20,14,10,50,14,65,14,98]}
data = pd.DataFrame(data)
data.id.unique()
#或者
import numpy as np
np.unique(data.id)
2.用frame.drop_duplicates()对单属性列去重
data.drop_duplicates(['id'])
3.用frame.drop_duplicates()对多属性列去重
data.drop_duplicates(['id','age'])
4.用frame.duplicated()对多属性列去重
isduplicated = data.duplicated(['id','age'],keep='first')
data.loc[~isduplicated,:]
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