import pandas as pd
data = pd.read_csv('E:\\training.csv')
array3 = data['Diabetes medicine years'].replace(np.Nan,-1)
length = array3.shape[0]
print(length)
arr3 = [];
for i in range(length):
    if array3[i] != -1:
#         print(i)
        arr3.append(array[i])

print(arr3)
trimmed = st.trim_mean(arr3,.05)
mask=(data['Diabetes']=='Yes') & ((data['Diabetes medicine years'=='NA']) |(data['Diabetes medicine years'=='No']|(data['Diabetes medicine years'=='VALID']))
data.loc[mask,'Diabetes medicine years']=pd.to_numeric(data['Diabetes medicine years'],errors='coerce').fillna(trimmed)
data.to_csv(r'E:\\data.csv')