Pyhton科学计算工具Pandas（八）—— 数据的去重及替换

Pyhton科学计算工具Pandas（七）—— 数据的去重及替换

去重 .duplicated()

# 去重 .duplicated()

s = pd.Series([1,1,1,1,2,2,2,3,4,5,5,5,5])
print(s.duplicated(keep='first'))
print(s[s.duplicated() == False])
print('-----')
# 判断是否重复
# 通过布尔判断，得到不重复的值

s_re = s.drop_duplicates()
print(s_re)
print('-----')
# drop.duplicates移除重复
# inplace参数：是否替换原值，默认False

df = pd.DataFrame({'key1':['a','a',3,4,5],
                  'key2':['a','a','b','b','c']})
print(df.duplicated())      #判断行是否重复
print(df['key2'].duplicated())    #当指定某列时，等同于Series去重
# Dataframe中使用duplicated

0     False
1      True
2      True
3      True
4     False
5      True
6      True
7     False
8     False
9     False
10     True
11     True
12     True
dtype: bool
0    1
4    2
7    3
8    4
9    5
dtype: int64
-----
0    1
4    2
7    3
8    4
9    5
dtype: int64
-----
0    False
1     True
2    False
3    False
4    False
dtype: bool
0    False
1     True
2    False
3     True
4    False
Name: key2, dtype: bool

替换 .replace()

# 替换 .replace

s = pd.Series(list('ascaazsd'))
print(s.replace('a', np.nan))
print(s.replace(['a','s'] ,np.nan))
print(s.replace({'a':'hello world!','s':123}))
# 可一次性替换一个值或多个值
# 可传入列表或字典

0    NaN
1      s
2      c
3    NaN
4    NaN
5      z
6      s
7      d
dtype: object
0    NaN
1    NaN
2      c
3    NaN
4    NaN
5      z
6    NaN
7      d
dtype: object
0    hello world!
1             123
2               c
3    hello world!
4    hello world!
5               z
6             123
7               d
dtype: object