2017 Answer – pandas 0.20: .ix is deprecated. Use .loc

See the deprecation in the docs

.loc uses label based indexing to select both rows and columns. The labels being the values of the index or the columns. Slicing with .loc includes the last element.

Let’s assume we have a DataFrame with the following columns:
foo, bar, quz, ant, cat, sat, dat.

# selects all rows and all columns beginning at 'foo' up to and including 'sat'
df.loc[:, 'foo':'sat']
# foo bar quz ant cat sat

.loc accepts the same slice notation that Python lists do for both row and columns. Slice notation being start:stop:step

# slice from 'foo' to 'cat' by every 2nd column
df.loc[:, 'foo':'cat':2]
# foo quz cat

# slice from the beginning to 'bar'
df.loc[:, :'bar']
# foo bar

# slice from 'quz' to the end by 3
df.loc[:, 'quz'::3]
# quz sat

# attempt from 'sat' to 'bar'
df.loc[:, 'sat':'bar']
# no columns returned

# slice from 'sat' to 'bar'
df.loc[:, 'sat':'bar':-1]
sat cat ant quz bar

# slice notation is syntatic sugar for the slice function
# slice from 'quz' to the end by 2 with slice function
df.loc[:, slice('quz',None, 2)]
# quz cat dat

# select specific columns with a list
# select columns foo, bar and dat
df.loc[:, ['foo','bar','dat']]
# foo bar dat

You can slice by rows and columns. For instance, if you have 5 rows with labels v, w, x, y, z

# slice from 'w' to 'y' and 'foo' to 'ant' by 3
df.loc['w':'y', 'foo':'ant':3]
#    foo ant
# w
# x
# y