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

# # Iris

# ### Introduction:
# 
# This exercise may seem a little bit strange, but keep doing it.
# 
# ### 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/iris/iris.data). 

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

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# ### Step 4. Create columns for the dataset

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# 1. sepal_length (in cm)
# 2. sepal_width (in cm)
# 3. petal_length (in cm)
# 4. petal_width (in cm)
# 5. class


# ### Step 5.  Is there any missing value in the dataframe?

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# ### Step 6.  Lets set the values of the rows 10 to 29 of the column 'petal_length' to NaN

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# ### Step 7. Good, now lets substitute the NaN values to 1.0

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# ### Step 8. Now let's delete the column class

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# ### Step 9.  Set the first 3 rows as NaN

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# ### Step 10.  Delete the rows that have NaN

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# ### Step 11. Reset the index so it begins with 0 again

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

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