How can i use .fillna with specific values?

Question

df["load_weight"] = df.loc[(df["dropoff_site"] == "HORNSBY BEND") & (df[‘load_type’] == "BRUSH")].fillna(1000, inplace=True)

i want to change the NaN value in "load_weight" column, but only for the rows that contain "HORNSBY BEND" and "BRUSH", but above code gave me "none" to the whole "load_weight" column, what did i do wrong?

Asked By: Huesca Rashad

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Answer 1

I would use a mask for boolean indexing:

m = (df["dropoff_site"] == "HORNSBY BEND") & (df['load_type'] == "BRUSH")
df.loc[m, "load_weight"] = df.loc[m, 'load_weight'].fillna(1000)

NB. you can’t keep inplace=True when you assign the output. This is what was causing your data to be replaced with None as methods called with inplace=True return nothing.

Alternative with only boolean indexing:

m1 = (df["dropoff_site"] == "HORNSBY BEND") & (df['load_type'] == "BRUSH")
m2 = df['load_weight'].isna()
df.loc[m1&m2, "load_weight"] = 1000

Answered By: mozway

Answer 2

Instead of fillna, you can directly use df.loc to do the required imputation

df.loc[((df['dropoff_site']=='HORNSBY BEND')&(df['load_type']=='BRUSH')
&(df['load_weight'].isnull())),'load_weight'] = 1000

Answered By: mahak

How can i use .fillna with specific values?

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