Set value for particular cell in pandas DataFrame using index
I've created a pandas DataFrame
df=DataFrame(index=['A','B','C'], columns=['x','y'])
and got this
x y
A NaN NaN
B NaN NaN
C NaN NaN
Then I want to assign value to particular cell, for example for row 'C' and column 'x'. I've expected to get such result:
x y
A NaN NaN
B NaN NaN
C 10 NaN
with this code:
df.xs('C')['x']=10
but contents of df haven't changed. It's again only Nan's in dataframe.
Any suggestions?
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
Update: The .set_value method is going to be deprecated. .iat/.at are good replacements, unfortunately pandas provides little documentation
The fastest way to do this is using set_value. This method is ~100 times faster than .ix method. For example:
df.set_value('C', 'x', 10)
You can also use a conditional lookup using .loc as seen here:
df.loc[df[<some_column_name>] == <condition>, <another_column_name>] = <value_to_add>
where <some_column_name is the column you want to check the <condition> variable against and <another_column_name> is the column you want to add to (can be a new column or one that already exists). <value_to_add> is the value you want to add to that column/row.
This example doesn't work precisely with the question at hand, but it might be useful for someone wants to add a specific value based on a condition.
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