【Python数据分析】pandas去重和替换

1.去重复:duplicated

import pandas as pd

s = pd.Series([1,1,1,1,2,2,2,3,3,4,4,5,6])

# 通过duplicated判断是否重复
print(s.duplicated())

# 通过布尔判断，得到不重复的值
print(s[s.duplicated() == False])

# 移除重复drop_duplicates
s_re = s.drop_duplicates()
print(s_re)

# Dataframe中使用duplicated
df = pd.DataFrame({'key1':['a','a','b','a','b'],
                  'key2':['a','a','c',5,'c']
                  })
print('------------df----------------')
print(df)
print('-----------df.duplicated()-----------------') # 第2行与第1行重复了，所以为True,第5行与第3行重复，所以为True
print(df.duplicated())

print('-----------df[\'key1\'].duplicated()-----------------')
print(df['key1'].duplicated())

输出结果：

2.替换:replace

import pandas as pd
import numpy as np
s = pd.Series(list('aseaasasx'))
print(s.replace('a', np.nan)) # 替换a为np.nan
print(s.replace(['a','s'], np.nan)) # a替换为s,然后再将s替换为np.nan
print(s.replace({'a':'@@@','s':'***'})) # 一次性替换为多个值

输出结果：