Ramon J Romero y Vigil - 10 months ago 82

Python Question

Given a square pandas DataFrame of the following form:

`a b c`

a 1 .5 .3

b .5 1 .4

c .3 .4 1

How can I

`melt`

`Row Column Value`

a a 1

a b .5

a c .3

b b 1

b c .4

c c 1

#Note the combination a,b is only listed once. There is no b,a listing

I'm more interested in an idiomatic pandas solution, a custom indexer would be easy enough to write by hand... Thank you in advance for your consideration and response.

Answer Source

First I convert lower values of `df`

to `NaN`

by `where`

and `numpy.triu`

and then `stack`

, `reset_index`

and set column names:

```
import numpy as np
print df
a b c
a 1.0 0.5 0.3
b 0.5 1.0 0.4
c 0.3 0.4 1.0
print np.triu(np.ones(df.shape)).astype(np.bool)
[[ True True True]
[False True True]
[False False True]]
df = df.where(np.triu(np.ones(df.shape)).astype(np.bool))
print df
a b c
a 1 0.5 0.3
b NaN 1.0 0.4
c NaN NaN 1.0
df = df.stack().reset_index()
df.columns = ['Row','Column','Value']
print df
Row Column Value
0 a a 1.0
1 a b 0.5
2 a c 0.3
3 b b 1.0
4 b c 0.4
5 c c 1.0
```