Having a data set as below.Here I need to group the subset in column and fill the missing values using mode method.
Need to group the value 'Tom' from name and fill the missing value in value using mode.
Name Value
0 Tom 20.0
1 Tom 20.0
2 Tom NaN
3 nick 19.0
4 nick 18.0
5 krish 15.0
6 nick 15.0
7 nick 20.0
8 jack NaN
9 Tom 23.0
10 Tom NaN
I tried the code below:
data['value']= data.loc[data["Name"]=='Tom'].fillna(data['value'].mode()[0], inplace=True)
Didn't get the output as expected. What if i need to compare more than one value?
To replace on specific conditions you could use np.where() to evaluate the condition, when it is met, replace it with the mode, otherwise retain the column's original value. Kindly try:
data['Value'] = np.where(data['Name'] =='Tom',data['Value'].fillna(data['Value'].mode()[0]),data['Value'])
This returns:
Name Value
0 Tom 20.0
1 Tom 20.0
2 Tom 20.0
3 nick 19.0
4 nick 18.0
5 krish 15.0
6 nick 15.0
7 nick 20.0
8 jack NaN
9 Tom 23.0
10 Tom 20.0