Bài 15: Làm việu với dữ liệu Text (p2) – Python Panda

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22/02/2022 Training 83 viewed

Nội dung

1 split(pattern)
2 cat(sep=pattern)
3 get_dummies()
4 contains ()
5 replace(a,b)
6 repeat(value)
7 count(pattern)
8 startswith(pattern)
9 endswith(pattern)
10 find(pattern)
11 findall(pattern)
12 swapcase()
13 islower()
14 isupper()
15 isnumeric()

split(pattern)

import pandas as pd
import numpy as np
s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])
print s
print ("Split Pattern:")
print s.str.split(' ')

Kết quả :

0            Tom
1   William Rick
2           John
3        Alber@t
dtype: object

Split Pattern:
0   [Tom, , , , , , , , , , ]
1   [, , , , , William, Rick]
2   [John]
3   [Alber@t]
dtype: object

cat(sep=pattern)

import pandas as pd
import numpy as np

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print s.str.cat(sep='_')

Kết quả :

Tom _ William Rick_John_Alber@t

get_dummies()

import pandas as pd
import numpy as np

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print s.str.get_dummies()

Kết quả :

William Rick   Alber@t   John   Tom
0             0         0      0     1
1             1         0      0     0
2             0         0      1     0
3             0         1      0     0

contains ()

import pandas as pd

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print s.str.contains(' ')

Kết quả :

0   True
1   True
2   False
3   False
dtype: bool

replace(a,b)

import pandas as pd
s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])
print s
print ("After replacing @ with $:")
print s.str.replace('@','$')

Kết quả :

0   Tom
1   William Rick
2   John
3   Alber@t
dtype: object

After replacing @ with $:
0   Tom
1   William Rick
2   John
3   Alber$t
dtype: object

repeat(value)

import pandas as pd

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print s.str.repeat(2)

Kết quả :

0   Tom            Tom
1   William Rick   William Rick
2                  JohnJohn
3                  Alber@tAlber@t
dtype: object

count(pattern)

import pandas as pd
 
s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print ("The number of 'm's in each string:")
print s.str.count('m')

Kết quả :

The number of 'm's in each string:
0    1
1    1
2    0
3    0

startswith(pattern)

import pandas as pd

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print ("Strings that start with 'T':")
print s.str. startswith ('T')

Kết quả :

0  True
1  False
2  False
3  False
dtype: bool

endswith(pattern)

import pandas as pd
s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])
print ("Strings that end with 't':")
print s.str.endswith('t')

Kết quả :

Strings that end with 't':
0  False
1  False
2  False
3  True
dtype: bool

find(pattern)

import pandas as pd

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print s.str.find('e')

Kết quả :

0  -1
1  -1
2  -1
3   3
dtype: int64

“-1” cho biết rằng phần tử không có pattern như vậy.

findall(pattern)

import pandas as pd

s = pd.Series(['Tom ', ' William Rick', 'John', 'Alber@t'])

print s.str.findall('e')

Kết quả :

0 []
1 []
2 []
3 [e]
dtype: object

Danh sách rỗng ([]) có nghĩa không có sẵn pattern trong phần tử.

swapcase()

import pandas as pd

s = pd.Series(['Tom', 'William Rick', 'John', 'Alber@t'])
print s.str.swapcase()

Kết quả :

0  tOM
1  wILLIAM rICK
2  jOHN
3  aLBER@T
dtype: object

islower()

import pandas as pd

s = pd.Series(['Tom', 'William Rick', 'John', 'Alber@t'])
print s.str.islower()

Kết quả :

0  False
1  False
2  False
3  False
dtype: bool

isupper()

import pandas as pd

s = pd.Series(['Tom', 'William Rick', 'John', 'Alber@t'])

print s.str.isupper()

Kết quả :

0  False
1  False
2  False
3  False
dtype: bool

isnumeric()

import pandas as pd

s = pd.Series(['Tom', 'William Rick', 'John', 'Alber@t'])

print s.str.isnumeric()

Kết quả :

0  False
1  False
2  False
3  False
dtype: bool

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