填充 nan 值

Question

I have a dataset that contains nan values. These values are dependent on another variable, and I am trying to clean the data using it. I write a code to replace the nan values but it doesn't work. The code is:

df.loc[(df["house"]=="rented") & (df["car"]=="yes")]["debt"].fillna(2, inplace=True)

Answer 1

https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.loc.html

Conditional that returns a boolean Series with column labels specified

df.loc[df['shield'] > 6, ['max_speed']]

            max_speed
sidewinder          7

Based on the documentation it should be converted to this:

df.loc['filter','selected column']

Give it a try like this:

df.loc[(df["house"]=="rented") & (df["car"]=="yes"), ["debt"]].fillna(2, inplace=True)

Answer 2

Switch df.loc to

for val in df.index:
    if (df["house"][val] == "rented") and (df["car"][val] == "yes"):
        df["debt"][val] = 2

If I understand you correctly, you do not want to just fill in the na values. Rather, you'd like to fill the na values only when house is rented and you have a car. To fill all na values at df index "debt"

df["debt"].fillna(2, inplace=True)

should be used rather then your second line of code.