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Write a program in Python to transpose the index and columns in a given DataFrame
Input −
Assume you have a DataFrame, and the result for transpose of index and columns are,
Transposed DataFrame is 0 1 0 1 4 1 2 5 2 3 6
Solution 1
Define a DataFrame
Set nested list comprehension to iterate each element in the two-dimensional list data and store it in result.
result = [[data[i][j] for i in range(len(data))] for j in range(len(data[0]))
Convert the result to DataFrame,
df2 = pd.DataFrame(result)
Example
Let us see the complete implementation to get a better understanding −
import pandas as pd
data = [[1,2,3],[4,5,6]]
df = pd.DataFrame(data)
print("Original DataFrame is\n", df)
result = [[data[i][j] for i in range(len(data))] for j in range(len(data[0]))]
df2 = pd.DataFrame(result)
print("Transposed DataFrame is\n", df2)Output
Original DataFrame is 0 1 2 0 1 2 3 1 4 5 6 Transposed DataFrame is 0 1 0 1 4 1 2 5 2 3 6
Solution 2
Define a DataFrame
Apply transpose method either df.T or df.transpose() to the DataFrame.
df.transpose() # or df.T
Example
Let us see the complete implementation to get a better understanding −
import pandas as pd
data = [[1,2,3],[4,5,6]]
df = pd.DataFrame(data)
print("Original DataFrame is\n", df)
print("Transposed DataFrame is\n", df.transpose())Output
Original DataFrame is 0 1 2 0 1 2 3 1 4 5 6 Transposed DataFrame is 0 1 0 1 4 1 2 5 2 3 6
Solution 3
Define a DataFrame
Zip method returns an iterator of tuples. Apply to unzip to the two-dimensional list using * and zip it. It is defined below,
result = zip(*data)
Convert the result to DataFrame,
df2 = pd.DataFrame(result)
Example
Let us see the complete implementation to get a better understanding −
import pandas as pd
data = [[1,2,3],[4,5,6]]
df = pd.DataFrame(data)
print("Original DataFrame is\n", df)
result = zip(*data)
df2 = pd.DataFrame(result)
print("Transposed DataFrame is\n", df2)Output
Original DataFrame is 0 1 2 0 1 2 3 1 4 5 6 Transposed DataFrame is 0 1 0 1 4 1 2 5 2 3 6
Updated on: 24-Feb-2021
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