#!/usr/bin/env python
# coding: utf-8

# # Wine

# ### Introduction:
# 
# This exercise is a adaptation from the UCI Wine dataset.
# The only pupose is to practice deleting data with pandas.
# 
# ### Step 1. Import the necessary libraries

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# ### Step 2. Import the dataset from this [address](https://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data). 

# ### Step 3. Assign it to a variable called wine

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# ### Step 4. Delete the first, fourth, seventh, nineth, eleventh, thirteenth and fourteenth columns

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# ### Step 5. Assign the columns as below:
# 
# The attributes are (donated by Riccardo Leardi, riclea '@' anchem.unige.it):  
# 1) alcohol  
# 2) malic_acid  
# 3) alcalinity_of_ash  
# 4) magnesium  
# 5) flavanoids  
# 6) proanthocyanins  
# 7) hue 

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# ### Step 6. Set the values of the first 3 rows from alcohol as NaN

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# ### Step 7. Now set the value of the rows 3 and 4 of magnesium as NaN

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# ### Step 8. Fill the value of NaN with the number 10 in alcohol and 100 in magnesium

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# ### Step 9. Count the number of missing values

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# ### Step 10.  Create an array of 10 random numbers up until 10

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# ### Step 11.  Use random numbers you generated as an index and assign NaN value to each of cell.

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# ### Step 12.  How many missing values do we have?

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# ### Step 13. Delete the rows that contain missing values

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# ### Step 14. Print only the non-null values in alcohol

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# ### Step 15.  Reset the index, so it starts with 0 again

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# ### BONUS: Create your own question and answer it.

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