Can fillna take in a function or just the given methods?

Question

Can fillna take in a function? Or just the methods ‘backfill’, ‘bfill’, ect ?

http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.html

If the dataframe does not have any initial data for example, the backfill method would be useless isn't it? viceversa ffill in case no data at end of dataframe.

That would be some of the reasons why I would like to use a proper method like extrapolations

Answer 1

fillna is intended to take either a value to fill with, or use one of the methods *{‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}*

From the docs you referenced

value : scalar, dict, Series, or DataFrame

Value to use to fill holes (e.g. 0), alternately a dict/Series/DataFrame of values specifying which value to use for each index (for a Series) or column (for a DataFrame). (values not in the dict/Series/DataFrame will not be filled). This value cannot be a list.

Answer

fillna does not take a function as a valid input for the value parameter. However, if you have a function that can produce a series or dataframe, then you can pass what ever inputs you need into the function and pass the results to fillna

---

examples

the value parameter can take scalars, dictionaries, series, or dataframes. Here are some examples of what that looks like

Consider the dataframe df

df = pd.DataFrame([
        [1, None, 2, None],
        [None, 3, None, 4],
        [5, 6, None, None],
        [None, None, 7, 8]
    ], list('ABCD'), list('WXYZ'))

print(df)

     W    X    Y    Z
A  1.0  NaN  2.0  NaN
B  NaN  3.0  NaN  4.0
C  5.0  6.0  NaN  NaN
D  NaN  NaN  7.0  8.0

fill with scalar

df.fillna(9)

     W    X    Y    Z
A  1.0  9.0  2.0  9.0
B  9.0  3.0  9.0  4.0
C  5.0  6.0  9.0  9.0
D  9.0  9.0  7.0  8.0

fill with dictionary

filler = dict(W=-9, X=-10, Y=-11, Z=-12)
df.fillna(filler)

     W     X     Y     Z
A  1.0 -10.0   2.0 -12.0
B -9.0   3.0 -11.0   4.0
C  5.0   6.0 -11.0 -12.0
D -9.0 -10.0   7.0   8.0

fill with series

filler = pd.Series(dict(W=-9, X=-10, Y=-11, Z=-12))
df.fillna(filler)

     W     X     Y     Z
A  1.0 -10.0   2.0 -12.0
B -9.0   3.0 -11.0   4.0
C  5.0   6.0 -11.0 -12.0
D -9.0 -10.0   7.0   8.0

fill with dataframe

filler = pd.DataFrame(-np.arange(df.size).reshape(df.shape), df.index, df.columns)
print(filler)

    W   X   Y   Z
A   0  -1  -2  -3
B  -4  -5  -6  -7
C  -8  -9 -10 -11
D -12 -13 -14 -15

df.fillna(filler)

     W     X     Y     Z
A  1.0 -10.0   2.0 -12.0
B -9.0   3.0 -11.0   4.0
C  5.0   6.0 -11.0 -12.0
D -9.0 -10.0   7.0   8.0

fill with along index, you need to transpose
df.fillna(filler, axis=1) generates a NotImplementedError

filler = dict(A=-9, B=-10, C=-11, D=-12)
print(df.T.fillna(filler).T)

      W     X     Y     Z
A   1.0  -9.0   2.0  -9.0
B -10.0   3.0 -10.0   4.0
C   5.0   6.0 -11.0 -11.0
D -12.0 -12.0   7.0   8.0

Answer 2

Short answer:

No, fillna cannot take a function but only the methods.

Less Short answer:

There is a df.interpolate function that allows you to fillna using different interpolation technique.

Long answer:

You can refer to the answer here, where someone has outlined a way to use scipy to extrapolate data. Unfortunately there isn't a native pandas function to accomplish this ):