preprocessing error trying to use OneHot Encoder Python - python-2.7

Question

I'm trying to run the code below in virtual machine for a homework practice problem. I'm getting the error message below, and I'm trying to figure out if it's an issue with my code or the site. If anyone can point out if it's an error with my code an how to fix it I'd be grateful. If my code looks ok, then I'll let the course know they have a bug.
Code:
import numpy as np
import pandas as pd
# Load the dataset
X = pd.read_csv('titanic_data.csv')
# Limit to categorical data
X = X.select_dtypes(include=[object])
from sklearn.preprocessing import LabelEncoder
from sklearn.preprocessing import OneHotEncoder
# TODO: Create a LabelEncoder object, which will turn all labels present in
# in each feature to numbers.
# HINT: Use LabelEncoder()
df=pd.DataFrame(X)
le = preprocessing.labelEncoder()
# TODO: For each feature in X, apply the LabelEncoder's fit_transform
# function, which will first learn the labels for the feature (fit)
# and then change the labels to numbers (transform).
df2=df.apply(le.fit_transform)
#for feature in X:
# HINT: use fit_transform on X[feature] using the LabelEncoder() object
#X[feature] = label_encoder.fit_transform(X[feature])
# TODO: Create a OneHotEncoder object, which will create a feature for each
# label present in the data.
# HINT: Use OneHotEncoder()
ohe = preprocessing.OneHotEncoder()
# TODO: Apply the OneHotEncoder's fit_transform function to all of X, which will
# first learn of all the (now numerical) labels in the data (fit), and then
# change the data to one-hot encoded entries (transform).
# HINT: Use fit_transform on X using the OneHotEncoder() object
onehotlabels = enc.fit_transform(df2)
Error:
Traceback (most recent call last):
File "vm_main.py", line 33, in <module>
import main
File "/tmp/vmuser_zrkfroofmi/main.py", line 2, in <module>
import studentMain
File "/tmp/vmuser_zrkfroofmi/studentMain.py", line 3, in <module>
import OneHot
File "/tmp/vmuser_zrkfroofmi/OneHot.py", line 21, in <module>
le = preprocessing.labelEncoder()
NameError: name 'preprocessing' is not defined

Answer 1

Call OneHotEncoder without preprocessing before the name. So just do ohe = OneHotEncoder(). The problem is in your import, what you have in your script would work if you did from sklearn import preprocessing.

Answer 2

From the code, 'from sklearn.preprocessing import OneHotEncoder', user was trying to import OneHotEncoder from preprocessing without importing preprocessing first. Preprocessing is a package from sklearn and OneHotEncoder is a preprocessor. That caused the error. So import preprocessing and then try with OneHotEncoder