Pandas Series - iat[] property

The Pandas iat[] property is used to access a single value for a row/column pair by integer position.

Exceptions

Raises IndexError if integer position is out of bounds.

Example: Indexing element of a DataFrame

In the example below, a DataFrame df is created. The iat[] is used to get and set the elements of this DataFrame.

import pandas as pd
import numpy as np

df = pd.DataFrame({
  "Salary": [25, 24, 30, 28],
  "Bonus": [10, 8, 9, np.nan],
  "Others": [5, 4, 7, 5]},
  index= ["2015", "2016", "2017", "2018"]
)

print("The DataFrame is:")
print(df)

#getting value at specified location
print("\ndf.iat[1, 1] returns:")
print(df.iat[1, 1])

#setting value at specified location
df.iat[0, 0] = 100

#after modification
print("\nThe DataFrame is:")
print(df)

The output of the above code will be:

The DataFrame is:
      Salary  Bonus  Others
2015      25   10.0       5
2016      24    8.0       4
2017      30    9.0       7
2018      28    NaN       5

df.iat[1, 1] returns:
8.0

The DataFrame is:
      Salary  Bonus  Others
2015     100   10.0       5
2016      24    8.0       4
2017      30    9.0       7
2018      28    NaN       5

Example: Indexing element of a Series

The iat[] can be used to get the elements of a Series as well. Consider the example below:

import pandas as pd
import numpy as np

df = pd.DataFrame({
  "Salary": [25, 24, 30, 28],
  "Bonus": [10, 8, 9, np.nan],
  "Others": [5, 4, 7, 5]},
  index= ["2015", "2016", "2017", "2018"]
)

print("The DataFrame is:")
print(df)

#getting value of second element of the given series
print("\ndf.iloc[1].iat[1] returns:")
print(df.iloc[1].iat[1])

The output of the above code will be:

The DataFrame is:
      Salary  Bonus  Others
2015      25   10.0       5
2016      24    8.0       4
2017      30    9.0       7
2018      28    NaN       5

df.iloc[1].iat[1] returns:
8.0

❮ Pandas Series - Functions