Use this tag for questions related to the pandas.melt or pandas.DataFrame.melt. Be sure to also include the [pandas] tag.
Melt can be used to unpivot a DataFrame from wide to long format.
Useful Canonical:
The documentation:
Questions tagged [pandas-melt]
102 questions
1
vote
0 answers
Transpose multiple columns into rows, but convert the transposed columns into one column
With this dataframe:
+--------+---------+------+----------+
| metric | control | test | duration |
+--------+---------+------+----------+
| logins | 4 | 2 | short |
+--------+---------+------+----------+
I want to transpose the control…
bbk611
- 321
- 2
- 10
1
vote
2 answers
Transpose Pandas Dataframe Python
I have this following dataframe:
Status Percentage Value Name Tahun
0 X 66.666667 4.0 A 2021
1 Y 33.333333 2.0 A 2021
2 Z 0.000000 0.0 A 2021
0 X 25.000000 2.0 A …
ohai
- 183
- 10
1
vote
1 answer
Add label-column to DataFrame
I have two DataFrames for example
df1:
0 1 2 3
a 1 2 3 4
b 10 20 30 40
c 100 200 300 400
------------------
df2:
0
0 x
1 y
2 z
Now I want to combine both like:
df_new:
value label
0 1 x
1 …
olzalk
- 15
- 3
1
vote
0 answers
Pandas pivot any columns to rows
Does anyone have any idea how to do this in Pandas?
I have this data frame:
Uf IBGE CNES 2020 2021
ES 320120 2547678 2747 2916
ES 320120 2485656 1817 2071
ES 320120 3125416 2965 3156
And I need it to look like this:
Uf …
TiagoAssun
- 11
- 2
1
vote
1 answer
How do I reshape my panda data frame using pivot?
So I have the following code as an exercise and I am trying to melt and unmelt the table using pivot. These are what I have so far:
sp500data=yf.Tickers('MMM ABT ...ZTS).history(group_by='ticker',period = '2y')
melted =…
user4808494
1
vote
1 answer
How to "Unpivot" multiple columns using melt() function
I need some help to solve this problem. I have a panda dataframe that has 101 unique columns[Column A to Column CW)]. I need to unpivot them into row-based output.
Original Data frame;
HSP CAT AMK COL OPK ROI GIO DOL …
adey27
- 439
- 3
- 19
1
vote
1 answer
Rearrange Pandas Dataframe using Pandas.Melt to take multiple columns at once?
I have a pandas Dataframe set out as follows. There are in fact 192 X,Y,Z triplet columns, this is just the first three.
shot V0e V0n V0d S0_Pe S0_Pn S0_Pd S0_Se S0_Sn S0_Sd
0 1001 457950.4 …
WillH
- 281
- 2
- 13
1
vote
1 answer
InvalidIndexError with melt function Pandas
I have the following dataframe and when I apply melt function:
numerics = ['int16', 'int32', 'int64', 'float16', 'float32', 'float64']
df_rm_features_melted = df_rm_features.melt(
id_vars=['id', 'date'],
…
gunel
- 161
- 13
1
vote
1 answer
Pivot data in pandas using melt and unstack
Given the following data:
data = pd.DataFrame(
{
"A": ["a", "a", "b", "b"],
"B": ["x", "y", "p", "q"],
"C": ["one", "two", "one", "two"],
}
)
which looks as:
A B C
0 a x one
1 a y two
2 b p one
3 b …
baxx
- 3,956
- 6
- 37
- 75
1
vote
1 answer
Melt column groupings in Pandas
I have a dataframe that looks like this:
df1 = pd.DataFrame([('company1',15,20,40,33,5, 9, 81, 34, 7), ('company2', 5,7,10,20,31, 14,18,37,42)],
columns=['company','legs - dog', 'head - dog', 'tail - dog','legs - cat', 'head - cat',…
Han
- 63
- 3
1
vote
2 answers
Melt/unpivot a dataset with multiple groups of values
I'm trying to convert a dataframe in Python, and I am stuck because I don't know exactly how to phrase what I want to do (which makes searching for it difficult). It seems like I need a combination of unstack and pivot. I can explain it with an…
KJ_
- 336
- 1
- 3
- 11
1
vote
1 answer
how to convert pandas dataframe to columns in python
I have a dataset given below:
weekid A B C D E F
1 10 20 30 40 0 50
2 70 100 0 0 80 0
I am trying to convert given first dataset into another format without including…
user3104352
- 1,100
- 1
- 16
- 34
0
votes
1 answer
How do I melt and/or pivot my pandas dataframe in way that forces x-axis titles to become index? (see description for visual)
Say I have a df that looks like this:
Store Name | 8/7 | 8/14 | 8/21 | 8/28 | more dates...
---------------------------------------------
Store 1 | 2.3 | 4.5 | 6.4 | 6.5 | Value..
Store 2 | 5.6 | 6.4 | 5.4 | 4.3 | Value..
Store 3 |…
Benjamin Parsons
- 35
- 7
0
votes
1 answer
Using stack, melt, pivot and other operators together to convert a messy dataframe to an organized one
I'm fairly new to Pandas and often find myself stuck in situations that I have no solution to them rather than asking for help. I have read so many tutorials and checked many Stackoverflow topics but none of them asnwered mine since it is very…
mahb
- 39
- 6
0
votes
1 answer
Reshape pandas data frame from long to wide having string/text responses
I have a survey dataset, a part of which I need to expand as columns having textual responses to rating questions asked. The dataset is large, what is the best way of doing this?
import pandas as pd
pd.DataFrame({'S.No': {0: 63.0,
1: nan,
2:…
Ayan
- 145
- 2
- 16