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
2
votes
1 answer
How do I further melt horizontal values into vertical values?
I have a dataframe which has horizontal identifiers (yes and no) and values, and I want to melt it into vertical values into each yes. Here is a snippet of my dataframe:
option Region Store Name option1 option2 …
Aeternis
- 23
- 3
2
votes
1 answer
How can I combine 2 levels index into one in pandas?
I am trying to extract only the relevant information from a dataframe. My data looks like
import pandas as pd
import numpy as np
df = pd.DataFrame({'ID': {0: 'id1', 1: 'id1', 2: 'id1'},
'EM': {0: 'met1', 1: 'met2', 2: 'met3'},
…
Amilovsky
- 397
- 6
- 15
2
votes
4 answers
Make a wide dataframe long and add columns according to another column's name
I need to use some names of the columns as part of the df. While keeping the first 3 columns identical, I need to create some other columns based on the content of the row.
Here I have some transactions from some customers:
cust_id cust_first …
AnaMil
- 23
- 3
2
votes
3 answers
I am trying to Stack, Melt, grouby or reshape a Pandas DataFrame
I am trying to reshape the dataframe below (imported from a .csv), keeping the Easting, Northing and Node Name value together on the same row, but having everything 'stacked' in 4 columns. So I want data in columns V0e, V0n and Vd on top of data in…
WillH
- 281
- 2
- 13
2
votes
3 answers
How do I melt a pandas with custom nam
I have a table like this
device_type
version
pool
testMean
testP50
testP90
testP99
testStd
WidgetMean
WidgetP50
WidgetP90
WidgetP99
WidgetStd
PNB0Q7
8108162
123
124
136
140.8
141.88
21.35
2.2
0
6.4
9.64
3.92
I want it to be transformed…
Aditya
- 818
- 1
- 10
- 21
2
votes
3 answers
Grouping several dataframe columns based on another columns values
I have this dataframe:
refid col2 price1 factor1 price2 factor2 price3 factor3
0 1 a 200 1 180 3 150 10
1 2 b 500 1 450 3 400 10
2 3 c 700 …
imatiasmb
- 113
- 7
2
votes
1 answer
Melt on pandas dataframes with multi-level
I have a data table that looks like this:
Original Table
Importing this into pandas using df = pd.read_excel('H:/test/test.xlsx', header=[0,1,2]) gives this dataframe:
Day Cats Dogs
Unnamed:…
jski212002
- 83
- 1
- 7
2
votes
1 answer
How to transform pandas df containing boolean columns into a heatmap compatible table?
I have a table something like this:
A
B
C
1
1
1
1
2
0
1
1
3
0
0
1
Where each cell is containing whether the row is connected to the specified column.
I want to transform this into a table like…
David Utassy
- 23
- 3
2
votes
4 answers
How to unpivot dataset in Python
I have a dataset which I need to unpivot into multiple rows into columns.
Eg:
ID Currency Val1 Val2 Month
101 INR 57007037.32 1292025.24 2021-03
101 INR 49171143.9 1303785.98 2021-02
101 INR 54039073.81 1469727.23 …
Rummy
- 51
- 8
1
vote
3 answers
How can I transform a DataFrame using pivot and melt in Python Pandas?
I have a DataFrame
date price num_floors house
1 2023-01-01 94.30076 3 A
2 2023-01-01 95.58771 2 B
3 2023-01-02 102.78559 1 C
4 2023-01-03 93.29053 3 D
and I…
jonas Chen
- 11
- 2
1
vote
1 answer
Unpivot yahoo finance multiple ticker download
I am trying to unpivot a yahoo finance download.
import yfinance as yf
import pandas as pd
from datetime import date
today = date.today()
data = yf.download("AAPL WMT", start="2023-05-01", end=today).round(2)
Running this script I…
Stix
- 39
- 6
1
vote
2 answers
Data Preparation Advanced Pandas Melt Multiple Column Sets. Merge some Columns to make them one
I have a dataset like:
Mileage
Operator 1
16 Seater
29-seater
Operator 2
16-seater.1
29-seater.1
80
BusRus
£199
£299
Wheels
£190
£290
I want it in the following format to build a price prediction model with Operator and Seats as…
Arronjeet Kooner
- 23
- 5
1
vote
1 answer
Turn the column names of a pandas df into a single column feature (with many nans)
pd.DataFrame({'apple': [np.nan, 'Bad', 'Good'], 'banana': [np.nan, np.nan, np.nan], 'orange': ['Good', np.nan, np.nan]})
Right now, I have a pd dataframe in the format similar to below:
apple banana orange
0 NaN NaN Good
1 Bad …
sharkbirth
- 17
- 4
1
vote
4 answers
Melt four (or more) dataframe columns into two rows
I am trying to convert a dataframe of structure:
ID ID2 ID3 R_u L_u R_sd L_sd
1 F G1 x y z t
2 M G2 x y z t
into
ID ID2 ID3 Side u sd
1 F G1 R x z
1 F G1 L y t
2 M G2 R x z
2 M G2 L y t
I…
SAM
- 55
- 1
- 7
1
vote
1 answer
regex column selection inside pd.melt function
I have a very wide df with about 100 columns, within which there are several 'XYZ_rating' columns that I want to pivot longer.
df = pd.DataFrame({
'id': [1, 1, 1, 2, 2, 2, 3, 3, 3],
'first_rating': [1, 2, 3, 1, 2, 3, 1, 2, 3],
…
prayner
- 393
- 1
- 10