CODEWITHSUNDEEP
pythonpandas
Petr Petrov
Petr Petrov

Reputation: 4442

Pandas: fillna every columns with some value

I have dataframe and there are NaN values:

col1   col2    col3
234    NaN     1
NaN    NaN     18
9      2       NaN

I have list with values [12, 15, 3] and I need to fill this columns:

Desire output

col1   col2   col3
234    15     1
12     15     18
9      2      3

I can do it with 

for (col, mean) in zip(df.columns, means):
    df[col].fillna(mean, inplace=True)

But is any way to do it without loop?

Upvotes: 1

Views: 946

Answers (3)

JohnE
JohnE

Reputation: 30424

Yet another approach:

df.fillna( pd.Series( [12, 15, 3], index=df.columns ) )

It looks like you may want the mean of each column (?), in which case you could just do:

df.fillna( df.mean() )      # df.mean() returns a series

In any event, the key to this answer and the others is just to give some sort of labelled output to fillna. Here I'm using a series whereas the other answers use dictionaries. Either approach is fine, of course, just depends on which is more convenient for you.

Upvotes: 4

alex314159
alex314159

Reputation: 3247

You can convert your list to a dictionary and give fillna a dictionary as an argument:

 df.fillna({'col1': 12,'col2': 15, 'col3':3}, inplace=True)

Upvotes: 2

BENY
BENY

Reputation: 323266

Build a dict of those , then fillna

l1= [12, 15, 3]

df.fillna(dict(zip(df.columns,l1)))
Out[120]: 
    col1  col2  col3
0  234.0  15.0   1.0
1   12.0  15.0  18.0
2    9.0   2.0   3.0

Upvotes: 4

Related Questions