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：
