I\'ve created a Pandas DataFrame
df = DataFrame(index=[\'A\',\'B\',\'C\'], columns=[\'x\',\'y\'])
and got this
x y A NaN
RukTech's answer, df.set_value('C', 'x', 10)
, is far and away faster than the options I've suggested below. However, it has been slated for deprecation.
Going forward, the recommended method is .iat/.at.
Why df.xs('C')['x']=10
does not work:
df.xs('C')
by default, returns a new dataframe with a copy of the data, so
df.xs('C')['x']=10
modifies this new dataframe only.
df['x']
returns a view of the df
dataframe, so
df['x']['C'] = 10
modifies df
itself.
Warning: It is sometimes difficult to predict if an operation returns a copy or a view. For this reason the docs recommend avoiding assignments with "chained indexing".
So the recommended alternative is
df.at['C', 'x'] = 10
which does modify df
.
In [18]: %timeit df.set_value('C', 'x', 10)
100000 loops, best of 3: 2.9 µs per loop
In [20]: %timeit df['x']['C'] = 10
100000 loops, best of 3: 6.31 µs per loop
In [81]: %timeit df.at['C', 'x'] = 10
100000 loops, best of 3: 9.2 µs per loop