python 对数据常用的几种去重方式

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,:]

人生苦短，我用python！