gistfile1.txt

dataset = df[df['gender'] <= 1]
model = linear_model.LogisticRegression()

dataset_data = np.array(dataset[['loan', 'months']])
dataset_data = dataset_data.astype(float)
dataset_target = np.array(dataset[['gender']])
dataset_target = dataset_target.ravel()

model.fit(dataset_data,dataset_target)

dataset = df[df['gender'] == 2]
dataset_data = np.array(dataset[['loan', 'months']])

predicted_2 = model.predict(dataset_data)
df_gender = list(df.gender)

j = 0
for i in range(0,len(df_gender)-1):
    if df_gender[i] == 2:
        df_gender[i] = predicted_2[j]
        j += 1
df.gender = df_gender