xApple xApple - 1 month ago 7
Python Question

Python pandas: fill a dataframe row by row

The simple task of adding a row to a

pandas.DataFrame
object seems to be hard to accomplish. There are 3 stackoverflow questions relating to this, none of which give a working answer.

Here is what I'm trying to do. I have a DataFrame of which I already know the shape as well as the names of the rows and columns.

>>> df = pandas.DataFrame(columns=['a','b','c','d'], index=['x','y','z'])
>>> df
a b c d
x NaN NaN NaN NaN
y NaN NaN NaN NaN
z NaN NaN NaN NaN


Now, I have a function to compute the values of the rows iteratively. How can I fill in one of the rows with either a dictionary or a
pandas.Series
? Here are various attempts that have failed:

>>> y = {'a':1, 'b':5, 'c':2, 'd':3}
>>> df['y'] = y
AssertionError: Length of values does not match length of index


Apparently it tried to add a column instead of a row.

>>> y = {'a':1, 'b':5, 'c':2, 'd':3}
>>> df.join(y)
AttributeError: 'builtin_function_or_method' object has no attribute 'is_unique'


Very uninformative error message.

>>> y = {'a':1, 'b':5, 'c':2, 'd':3}
>>> df.set_value(index='y', value=y)
TypeError: set_value() takes exactly 4 arguments (3 given)


Apparently that is only for setting individual values in the dataframe.

>>> y = {'a':1, 'b':5, 'c':2, 'd':3}
>>> df.append(y)
Exception: Can only append a Series if ignore_index=True


Well, I don't want to ignore the index, otherwise here is the result:

>>> df.append(y, ignore_index=True)
a b c d
0 NaN NaN NaN NaN
1 NaN NaN NaN NaN
2 NaN NaN NaN NaN
3 1 5 2 3


It did align the column names with the values, but lost the row labels.

>>> y = {'a':1, 'b':5, 'c':2, 'd':3}
>>> df.ix['y'] = y
>>> df
a b \
x NaN NaN
y {'a': 1, 'c': 2, 'b': 5, 'd': 3} {'a': 1, 'c': 2, 'b': 5, 'd': 3}
z NaN NaN

c d
x NaN NaN
y {'a': 1, 'c': 2, 'b': 5, 'd': 3} {'a': 1, 'c': 2, 'b': 5, 'd': 3}
z NaN NaN


That also failed miserably.

So how do you do it ?

Answer

df['y'] will set a column

since you want to set a row, use .loc

Note that .ix is equivalent here, yours failed because you tried to assign a dictionary to each element of the row y probably not what you want; converting to a Series tells pandas that you want to align the input (for example you then don't have to to specify all of the elements)

In [7]: df = pandas.DataFrame(columns=['a','b','c','d'], index=['x','y','z'])

In [8]: df.loc['y'] = pandas.Series({'a':1, 'b':5, 'c':2, 'd':3})

In [9]: df
Out[9]: 
     a    b    c    d
x  NaN  NaN  NaN  NaN
y    1    5    2    3
z  NaN  NaN  NaN  NaN