6.15. DataFrame Drop

pd.cut()

6.15.1. SetUp

>>> import pandas as pd
>>>
>>> df = pd.DataFrame([
...     {'firstname': 'Alice', 'lastname': 'Apricot', 'age': 30},
...     {'firstname': 'Bob', 'lastname': 'Blackthorn', 'age': 31},
...     {'firstname': 'Carol', 'lastname': 'Corn', 'age': 32},
...     {'firstname': 'Dave', 'lastname': 'Durian', 'age': 33},
...     {'firstname': 'Eve', 'lastname': 'Elderberry', 'age': 34},
...     {'firstname': 'Mallory', 'lastname': 'Melon', 'age': 15},
... ])
>>>
>>> df
  firstname    lastname  age
0     Alice     Apricot   30
1       Bob  Blackthorn   31
2     Carol        Corn   32
3      Dave      Durian   33
4       Eve  Elderberry   34
5   Mallory       Melon   15

6.15.2. Drop Columns

>>> df
  firstname    lastname  age
0     Alice     Apricot   30
1       Bob  Blackthorn   31
2     Carol        Corn   32
3      Dave      Durian   33
4       Eve  Elderberry   34
5   Mallory       Melon   15
>>>
>>>
>>> df.drop(columns='age')
  firstname    lastname
0     Alice     Apricot
1       Bob  Blackthorn
2     Carol        Corn
3      Dave      Durian
4       Eve  Elderberry
5   Mallory       Melon
>>>
>>>
>>> df.drop(columns=['firstname','lastname'])
   age
0   30
1   31
2   32
3   33
4   34
5   15

6.15.3. Drop Rows

>>> df
  firstname    lastname  age
0     Alice     Apricot   30
1       Bob  Blackthorn   31
2     Carol        Corn   32
3      Dave      Durian   33
4       Eve  Elderberry   34
5   Mallory       Melon   15
>>>
>>> df.drop(index=[1, 3, 5])
  firstname    lastname  age
0     Alice     Apricot   30
2     Carol        Corn   32
4       Eve  Elderberry   34

6.15.4. Drop Duplicates

>>> df.drop_duplicates(subset=['firstname'])
  firstname    lastname  age
   Alice     Apricot   30
     Bob  Blackthorn   31
   Carol        Corn   32
    Dave      Durian   33
     Eve  Elderberry   34
 Mallory       Melon   15

>>> df.drop_duplicates(subset=['firstname'], keep='last')
  firstname    lastname  age
   Alice     Apricot   30
     Bob  Blackthorn   31
   Carol        Corn   32
    Dave      Durian   33
     Eve  Elderberry   34
 Mallory       Melon   15