How can I manage units in pandas data?

Question

I\'m trying to figure out if there is a good way to manage units in my pandas data. For example, I have a DataFrame that looks like this:

Answer 1

There isn't any great way to do this right now, see github issue here for some discussion.

As a quick hack, could do something like this, maintaining a separate dict with the units.

In [3]: units = {}

In [5]: newcols = []
   ...: for col in df:
   ...:     name, unit = col.split(' ')
   ...:     units[name] = unit
   ...:     newcols.append(name)

In [6]: df.columns = newcols

In [7]: df
Out[7]:
   length  width  thickness
0     1.2    3.4        5.6
1     7.8    9.0        1.2
2     3.4    5.6        7.8

In [8]: units['length']
Out[8]: '(m)'

Answer 2

As I was searching for this, too. Here is what pint and the (experimental) pint_pandas is capable of today:

import pandas as pd
import pint
import pint_pandas

ureg = pint.UnitRegistry()
ureg.Unit.default_format = "~P"
pint_pandas.PintType.ureg.default_format = "~P"

df = pd.DataFrame({
    "length": pd.Series([1.2, 7.8, 3.4], dtype="pint[m]"),
    "width": pd.Series([3.4, 9.0, 5.6], dtype="pint[m]"),
    "thickness": pd.Series([5.6, 1.2, 7.8], dtype="pint[cm]"),
})

print(df.pint.dequantify())

     length width thickness
unit      m     m        cm
0       1.2   3.4       5.6
1       7.8   9.0       1.2
2       3.4   5.6       7.8

df['width'] = df['width'].pint.to("inch")

print(df.pint.dequantify())

     length       width thickness
unit      m          in        cm
0       1.2  133.858268       5.6
1       7.8  354.330709       1.2
2       3.4  220.472441       7.8