pandas.DataFrame.T property is used to transpose index and columns of the data frame. The property T is somehow related to method transpose(). The main function of this property is to create a reflection of the data frame overs the main diagonal by making rows as columns and vice versa.
Syntax: DataFrame.T
Parameters:
copy: If True, the underlying data is copied, otherwise (default).
*args, **kwargs: Additional keywordsReturns: The Transposed data frame
Example 1:
Sometimes we need to transpose the data frame in order to study it more accurately. In this situation pandas.DataFrame.T property plays an important role.
Python3
# Importing pandas moduleimport pandas as pd # Creating a dictionarydit = {'August': [10, 25, 34, 4.85, 71.2, 1.1], 'September': [4.8, 54, 68, 9.25, 58, 0.9], 'October': [78, 5.8, 8.52, 12, 1.6, 11], 'November': [100, 5.8, 50, 8.9, 77, 10]} # Converting it to data framedf = pd.DataFrame(data=dit) # Original DataFramedf |
Output:
Transposing the data frame.
Python3
# Transposing the data frame # using dataframe.T propertydf_trans = df.T print("Transposed Data frame :")df_trans |
Output:
In the above example, we transpose the data frame ‘df’ having numeric values/content.
Example 2:
Python3
# Import pandas libraryimport pandas as pd # initialize list of listsdata = [['Harvey.', 10.5, 45.25, 95.2], ['Carson', 15.2, 54.85, 50.8], ['juli', 14.9, 87.21, 60.4], ['Ricky', 20.3, 45.23, 99.5], ['Gregory', 21.1, 77.25, 90.9], ['Jessie', 16.4, 95.21, 10.85]] # Create the pandas DataFramedf = pd.DataFrame(data, columns=['Name', 'Age', 'Percentage', 'Accuracy'], index=['a', 'b', 'c', 'd', 'e', 'f']) # print dataframe.df |
Output:
Transposing the dataframe.
Python3
# Transposing the data frame # using dataframe.T propertydf_trans = df.T print("Transposed Data frame :")df_trans |
Output:
In the above example, we transpose the data frame ‘df’ having mixed up data type.
