Pandas eval with multi-index dataframes

Question

Consider a multi-index dataframe df:

A       bar                flux          
B       one     three       six     three
x  0.627915  0.507184  0.690787  1.166318
y  0.927342  0.788232  1.776677 -0.512259
z  1.000000  1.000000  1.000000  0.000000

I would like to use eval to substract ('bar', 'one') from ('flux', six'). Does the eval syntax support this type of index?

Answer 1

You can do this without using eval by using the equivalent standard Python notation:

df['bar']['one'] - df['flux']['six']`

Take a look at this reference. Below is an example for you, based off the object in your question:

from pandas import DataFrame, MultiIndex

# Create the object
columns = [
    ('bar', 'one'),
    ('bar', 'three'),
    ('flux', 'six'),
    ('flux', 'three')
]
data    = [
    [0.627915, 0.507184, 0.690787, 1.166318],
    [0.927342, 0.788232, 1.776677, -0.512259],
    [1.000000, 1.000000, 1.000000, 0.000000]
]
index   = MultiIndex.from_tuples(columns, names=['A', 'B'])
df      = DataFrame(data, index=['x', 'y', 'z'], columns=index)

# Calculate the difference
sub = df['bar']['one'] - df['flux']['six']
print sub

# Assign that difference to a new column in the object
df['new', 'col'] = sub
print df

The corresponding result is:

A       bar                flux                 new
B       one     three       six     three       col
x  0.627915  0.507184  0.690787  1.166318 -0.062872
y  0.927342  0.788232  1.776677 -0.512259 -0.849335
z  1.000000  1.000000  1.000000  0.000000  0.000000