# Python pandas: fill a dataframe row by row

###### Posted By: Anonymous

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 ?

## Solution

`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
```

###### Answered By: Anonymous

Disclaimer: This content is shared under creative common license cc-by-sa 3.0. It is generated from StackExchange Website Network.