6.7. DataFrame At

• .at[row, col] - Indexing by label

• .iat[row, col] - Indexing by position

• Access a single value for a row/column pair by integer position

• Use iat if you need to get or set a single value in a DataFrame

Pandas Select Cell:

6.7.1. 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},
... ], index=['a', 'b', 'c'])

>>> df
  firstname    lastname  age
a     Alice     Apricot   30
b       Bob  Blackthorn   31
c     Carol        Corn   32

6.7.2. .iat[]

• DataFrame.iat[row, col] - Indexing by position

• Does not support fancy indexing

• Start included

• Stop excluded

>>> df.iat[0,0]
'Alice'
>>>
>>> df.iat[0,1]
'Apricot'

>>> df.iat[1,0]
'Bob'
>>>
>>> df.iat[1,1]
'Blackthorn'

6.7.3. .at[]

• DataFrame.at[row, col] - Indexing by label

• Supports fancy indexing

• Start included

• Stop included

>>> df.at['a', 'firstname']
'Alice'
>>>
>>> df.at['a', 'lastname']
'Apricot'

>>> df.at['b', 'firstname']
'Bob'
>>>
>>> df.at['b', 'lastname']
'Blackthorn'

6.7.4. Assignments