I'm trying to understand how can I convert a lambda function to a normal one. I have this lambda function that it supposed to fill the null values of each column with the mode
def fill_nn(data):
df= data.apply(lambda column: column.fillna(column.mode()[0]))
return df
I tried this:
def fill_nn(df):
for column in df:
if df[column].isnull().any():
return df[column].fillna(df[column].mode()[0])
Hi 👋 Hope you are doing well!
If I understood your question correctly then the best possible way will be similar to this:
import pandas as pd
def fill_missing_values(series: pd.Series) -> pd.Series:
"""Fill missing values in series/column."""
value_to_use = series.mode()[0]
return series.fillna(value=value_to_use)
df = pd.DataFrame(
{
"A": [1, 2, 3, 4, 5],
"B": [None, 2, 3, 4, None],
"C": [None, None, 3, 4, None],
}
)
df = df.apply(fill_missing_values) # type: ignore
print(df)
# A B C
# 0 1 2.0 3.0
# 1 2 2.0 3.0
# 2 3 3.0 3.0
# 3 4 4.0 4.0
# 4 5 2.0 3.0
but personally, I would still use the lambda
as it requires less code and is easier to handle (especially for such a small task).