pandas.DataFrame.T() function in Python
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 keywords Returns: 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.
# Importing pandas module
import pandas as pd
# Creating a dictionary
dit = {'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 frame
df = pd.DataFrame(data=dit)
# Original DataFrame
df
Output:
Transposing the data frame.
# Transposing the data frame
# using dataframe.T property
df_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:
# Import pandas library
import pandas as pd
# initialize list of lists
data = [['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 DataFrame
df = pd.DataFrame(data, columns=['Name', 'Age', 'Percentage', 'Accuracy'],
index=['a', 'b', 'c', 'd', 'e', 'f'])
# print dataframe.
df
Output:
Transposing the dataframe.
# Transposing the data frame
# using dataframe.T property
df_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.
