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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:
 <a href="https
Step1:  Dataset Exploration
For this project you will be given a dataset and an associated problem. Over the course of the day, you will explore the dataset and train the best model you can in order to solve the problem. At the end of the day, you will give a short presentation about your model and solution.
Deliverables
A copy of this Colab notebook containing your code and responses to the ethical considerations below.
At the end of the day, we will ask you and your group to stand in front of the class and give a brief presentation about what you have done. 
Team
Please enter your team members' names in the placeholders in this text area
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Python Code:
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
Explanation: <a href="https://colab.research.google.com/github/google/applied-machine-learning-intensive/blob/master/content/02_data/06_project_data_processing/colab.ipynb" target="_parent"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/></a>
Copyright 2019 Google LLC.
End of explanation
# Use as many text and code blocks as you need to create your solution.
# Make sure to take notes and add lots of code comments, so your instructor
# understands what you are doing!
print("Good luck!")
Explanation: Dataset Exploration
For this project you will be given a dataset and an associated problem. Over the course of the day, you will explore the dataset and train the best model you can in order to solve the problem. At the end of the day, you will give a short presentation about your model and solution.
Deliverables
A copy of this Colab notebook containing your code and responses to the ethical considerations below.
At the end of the day, we will ask you and your group to stand in front of the class and give a brief presentation about what you have done. 
Team
Please enter your team members' names in the placeholders in this text area:
Team Member Placeholder
Team Member Placeholder
Team Member Placeholder
Exercises
Exercise 1: Coding
Kaggle hosts a dataset containing US airline on-time statistics and delay data from the US Department of Transportation's Bureau of Transportation Statistics (BTS). In this project, we will use flight statistics data to gain insights into US airports' and airlines' flights in 2008.
You are free to use any toolkit we've covered in class to solve the problem (e.g. Pandas, Matplotlib, Seaborn).
Demonstrations of competency:
1. Get the data into a Python object.
1. Inspect the data for each column's data type and summary statistics.
1. Explore the data programmatically and visually.
1. Produce an answer and visualization, where applicable, for at least three questions from the list below, and discuss any relevant insights. Feel free to generate and answer some of your own questions. 
Which U.S. airport is the busiest airport? You can decide how you'd like to measure "business" (e.g., annually, monthly, daily).
Of the 2008 flights that are actually delayed, think about:
Which 10 U.S. airlines have the most delays?
Which 10 U.S. airlines have the longest average delay time?
Which 10 U.S. airports have the most delays?
Which 10 U.S. airports have the longest average delay time?
More analysis:
Are there patterns on how flight delays are distributed across different hours of the day?
How about across months or seasons? Can you think of any reasons for these seasonal delays?
If you look at average delay time or number of delays by airport, does the data show linearity? Does any subset of the data show linearity?
Add reason for delay to your delay analysis above.
Examine flight frequencies, delays, time of day or year, etc. for a specific airport, airline or origin-arrival airport pair.
Student Solution
End of explanation
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