import python file into jupyter notebook - python-3.x

Question

I have a python file bucket.py. I'm trying to import it in to a jupyter notebook using the code below. I'm then trying to use one of the functions in it "exp1" to explore a dataframe. I'm getting the error below. Can someone please tell me how to import a file from a directory so I can use the functions in it, in my jupyter notebook?
code:
import importlib.util
spec = importlib.util.spec_from_file_location("module.name", '/Users/stuff/bucket/bucket.py')
foo = importlib.util.module_from_spec(spec)
foo.exp1(df)
error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-9-e1cc80f06e24> in <module>
----> 1 foo.exp1(harborsideoakland_df)
AttributeError: module 'module.name' has no attribute 'exp1'
bucket.py file:
# import libraries
import numpy as np
import pandas as pd
from time import time
import scipy.stats as stats
from IPython.display import display # Allows the use of display() for DataFrames
# # Pretty display for notebooks
# %matplotlib inline
###########################################
# Suppress matplotlib user warnings
# Necessary for newer version of matplotlib
import warnings
warnings.filterwarnings("ignore", category = UserWarning, module = "matplotlib")
#
# Display inline matplotlib plots with IPython
from IPython import get_ipython
get_ipython().run_line_magic('matplotlib', 'inline')
###########################################
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import warnings
warnings.filterwarnings('ignore')
import seaborn as sns
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score
from sklearn.preprocessing import MinMaxScaler
from sklearn.decomposition import PCA
### HELPER FUNCTIONS:
# Initial Exploration
def exp1(df):
with pd.option_context('display.max_rows', None, 'display.max_columns', None):
# shape of data
print('rows and columns: {}'.format(df.shape))
# head data
# display(df.head())
print('')
# data types and columns in data
print('data types and columns in data:')
print('')
#display(df.info())
print(df.info())
print('')
# unique values in each column
print('unique values in each column:')
#display(df.nunique())
print(df.nunique())
print('')
# percentage duplicates
print('percentage duplicates : {}'.format(1-(float(df.drop_duplicates().shape[0]))/df.shape[0]))
print('')
## Percentage of column with missing values
print('Percentage of column with missing values:')
print('')
missingdf=df.apply(lambda x: float(sum(x.isnull()))/len(x))
#display(missingdf.head(n=missingdf.shape[0]))
print(missingdf.head(n=missingdf.shape[0]))
print('')
print('Data snapshot:')
print('')
print(df[:5])

Answer 1

this worked:
import sys
sys.path.append(r'/Users/stuff/bucket/bucket')
import bucket as Lb