[Python] How do I melt a pandas dataframe?

Discussão em 'Python' iniciado por Stack, Junho 21, 2025.

  1. Stack

    Stack Membro Participativo

    On the pandas tag, I often see users asking questions about melting dataframes, but existing questions* are often too specific or lacking explanation to be broadly useful. I am going to attempt a canonical Q&A (self-answer) on this topic. I am is going to clarify:


    1. What is melt?


    2. How do I use melt?


    3. When do I use melt?
    Dataset


    I will have all my answers on this dataset of random grades for random people with random ages (easier to explain for the answers :D):

    import pandas as pd

    df = pd.DataFrame({
    'Name': ['Bob', 'John', 'Foo', 'Bar', 'Alex', 'Tom'],
    'Math': ['A+', 'B', 'A', 'F', 'D', 'C'],
    'English': ['C', 'B', 'B', 'A+', 'F', 'A'],
    'Age': [13, 16, 16, 15, 15, 13]})


    >>> df
    Name Math English Age
    0 Bob A+ C 13
    1 John B B 16
    2 Foo A B 16
    3 Bar F A+ 15
    4 Alex D F 15
    5 Tom C A 13

    Problems

    Problem 1


    How do I melt a dataframe so that the original dataframe becomes the following?

    Name Age Subject Grade
    0 Bob 13 English C
    1 John 16 English B
    2 Foo 16 English B
    3 Bar 15 English A+
    4 Alex 17 English F
    5 Tom 12 English A
    6 Bob 13 Math A+
    7 John 16 Math B
    8 Foo 16 Math A
    9 Bar 15 Math F
    10 Alex 17 Math D
    11 Tom 12 Math C


    I want to transpose this so that one column would be each subject and the other columns would be the repeated names of the students and their age and score.

    Problem 2


    Similar to Problem 1, but I want to make the Subject column only have Math; in other words, I want to filter out the English column:

    Name Age Subject Grades
    0 Bob 13 Math A+
    1 John 16 Math B
    2 Foo 16 Math A
    3 Bar 15 Math F
    4 Alex 15 Math D
    5 Tom 13 Math C

    Problem 3


    How would I group the melt and order the students by their scores?

    value Name Subjects
    0 A Foo, Tom Math, English
    1 A+ Bob, Bar Math, English
    2 B John, John, Foo Math, English, English
    3 C Tom, Bob Math, English
    4 D Alex Math
    5 F Bar, Alex Math, English


    I need it to be ordered and the names separated by comma and also the Subjects separated by comma in the same order respectively.

    Problem 4


    How would I unmelt a melted dataframe? Let's say I already melted this dataframe:

    df = df.melt(id_vars=['Name', 'Age'], var_name='Subject', value_name='Grades')


    To become:

    Name Age Subject Grades
    0 Bob 13 Math A+
    1 John 16 Math B
    2 Foo 16 Math A
    3 Bar 15 Math F
    4 Alex 15 Math D
    5 Tom 13 Math C
    6 Bob 13 English C
    7 John 16 English B
    8 Foo 16 English B
    9 Bar 15 English A+
    10 Alex 15 English F
    11 Tom 13 English A


    Then how would I translate this back to the original dataframe?

    Problem 5


    How would I group by the names of the students and separate the subjects and grades by comma?

    Name Subject Grades
    0 Alex Math, English D, F
    1 Bar Math, English F, A+
    2 Bob Math, English A+, C
    3 Foo Math, English A, B
    4 John Math, English B, B
    5 Tom Math, English C, A

    Problem 6


    How would I completely melt my dataframe - all columns as values?

    Column Value
    0 Name Bob
    1 Name John
    2 Name Foo
    3 Name Bar
    4 Name Alex
    5 Name Tom
    6 Math A+
    7 Math B
    8 Math A
    9 Math F
    10 Math D
    11 Math C
    12 English C
    13 English B
    14 English B
    15 English A+
    16 English F
    17 English A
    18 Age 13
    19 Age 16
    20 Age 16
    21 Age 15
    22 Age 15
    23 Age 13


    * Some existing questions


    Continue reading...
    Stack, Junho 21, 2025
    #1

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