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.
# 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.