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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 <h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc" style="margin-top
Step1:  The dataset above contains the ice cream sales, temperature, number of deaths by drowning and humidity level in a city during a timespan of 12 months.
Step2:  Identify strong (i.e., correleation coefficient > 0.9) and meaningful correlations among pairs of columns in this dataset. 
Append these pairs of correlated columns in the following form [column_x, column_y] to the variable below.
Step3:  Clue
Some of the correlations you found above may be spurious
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Python Code:
# Run the following to import necessary packages and import dataset. Do not use any additional plotting libraries.
import pandas as pd
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
datafile = "dataset/icecream.csv"
df = pd.read_csv(datafile)
df
Explanation: <h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc" style="margin-top: 1em;"><ul class="toc-item"><li><span><a href="#Ice-Cream" data-toc-modified-id="Ice-Cream-1">Ice Cream</a></span><ul class="toc-item"><li><ul class="toc-item"><li><span><a href="#Instructions-/-Notes:" data-toc-modified-id="Instructions-/-Notes:-1.0.1">Instructions / Notes:</a></span></li><li><span><a href="#The-dataset-above-contains-the-ice-cream-sales,-temperature,-number-of-deaths-by-drowning-and-humidity-level-in-a-city-during-a-timespan-of-12-months." data-toc-modified-id="The-dataset-above-contains-the-ice-cream-sales,-temperature,-number-of-deaths-by-drowning-and-humidity-level-in-a-city-during-a-timespan-of-12-months.-1.0.2">The dataset above contains the ice cream sales, temperature, number of deaths by drowning and humidity level in a city during a timespan of 12 months.</a></span></li></ul></li><li><span><a href="#Clue" data-toc-modified-id="Clue-1.1">Clue</a></span><ul class="toc-item"><li><span><a href="#Some-of-the-correlations-you-found-above-may-be-spurious:-https://en.wikipedia.org/wiki/Spurious_relationship----Only-include-meaningful-correlations-to-the-list!" data-toc-modified-id="Some-of-the-correlations-you-found-above-may-be-spurious:-https://en.wikipedia.org/wiki/Spurious_relationship----Only-include-meaningful-correlations-to-the-list!-1.1.1">Some of the correlations you found above may be spurious: <a href="https://en.wikipedia.org/wiki/Spurious_relationship" target="_blank">https://en.wikipedia.org/wiki/Spurious_relationship</a> -- Only include meaningful correlations to the list!</a></span></li></ul></li></ul></li></ul></div>
Ice Cream
Instructions / Notes:
Read these carefully
Read and execute each cell in order, without skipping forward
You may create new Jupyter notebook cells to use for e.g. testing, debugging, exploring, etc.- this is encouraged in fact!- just make sure that your final answer dataframes and answers use the set variables outlined below
Have fun!
End of explanation
# Here are the correlation coefficients between pairs of columns
corr = df.corr()
corr
abs_corr = np.abs(df.corr())
indices = corr.index
corr_pairs = []
for i, idx_i in enumerate(indices):
    for j, c in enumerate(abs_corr[idx_i]):
        if c > .9 and i < j:
            corr_pairs.append((idx_i, indices[j]))
corr_pairs
Explanation: The dataset above contains the ice cream sales, temperature, number of deaths by drowning and humidity level in a city during a timespan of 12 months.
End of explanation
correlations = []
correlations.append(['ice_cream_sales', 'temperature'])
# do not touch
correlations.sort()
print(correlations)
Explanation: Identify strong (i.e., correleation coefficient > 0.9) and meaningful correlations among pairs of columns in this dataset. 
Append these pairs of correlated columns in the following form [column_x, column_y] to the variable below.
End of explanation
# meaningful_correlation.append(['column_x', 'column_y'])
correlations_clue = []
# do not touch
correlations_clue.sort()
print(correlations_clue)
Explanation: Clue
Some of the correlations you found above may be spurious: https://en.wikipedia.org/wiki/Spurious_relationship -- Only include meaningful correlations to the list!
If this clue changes your answer, try again below. Otherwise, if you are confident in your answer above, leave the following untouched.
End of explanation
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