Difference between transpose() and .T in Pandas

I have a sample of data:

d = {'name': ['Alice', 'Bob'], 'score': [9.5, 8], 'kids': [1, 2]} 

I want to display simple statistics of the dataset in pandas using describe() method.

df = pd.DataFrame(data=d) print(df.describe().transpose()) 

Output 1:

Is there any difference between the two workflows when I am ending up with the same result?

df = pd.DataFrame(data=d) print(df.describe().T) 

Output 2:

References:

• Pandas | API documentation | pandas.DataFrame.transpose

1 Answer

There is no difference. As mentioned in the T attribute documentation, T is simply an accessor for the transpose() method. Indeed a quick look in the pandas DataFrame source code shows that the entire implementation of T is nothing more than:

T = property(transpose)