Analyzing Tides

This sea level data spans 2011-2015 for Mornington Island, Australia.

Thanks to UCF undergraduates Lissa Galguera, for finding the, and Hunter Tanchin, for starting the development of this notebook.



In [1]:

    
# The first pieces of code we need to start with are called 'imports'

import numpy as np
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt

# These imports contain programming instructions (called 'modules') to read data, plot data, etc.
# You can think of imports like tool boxes. Each tool box contains a different set of tools (modules) to use.

Importing the Data



In [2]:

    
# We need to read some data. Let's use our tool ".read_csv" located in the "pd" import.
data = pd.read_csv("https://github.com/adamlamee/CODINGinK12-data/raw/master/tides.csv", names = ["rawData"])

data['height'] = data.rawData.str[13:].astype(float)
data['rawTime'] = data.rawData.str[:12]
dates = pd.to_datetime(data.rawTime.tolist(), format='%d%m%Y%H%M')
tides = pd.Series(data.iloc[:,1].tolist(), dates)



In [3]:

    
# displays the first several entries of the data set
tides.head(5)









    Out[3]:





2011-01-01 00:00:00    2.560
2011-01-01 00:10:00    2.539
2011-01-01 00:20:00    2.494
2011-01-01 00:30:00    2.460
2011-01-01 00:40:00    2.411
dtype: float64

Plotting the data



In [4]:

    
# plots the entire data set
tides.plot(title="Sea level height (m)")









    Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fb21e255ba8>



In [5]:

    
# plots just one month in the data set
tides['June 2014'].plot(title="Sea level height (m)")









    Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fb216ff5518>



In [6]:

    
# or just one day
tides['June 1 2014'].plot(title="Sea level height (m)")









    Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fb21ba2f240>



In [7]:

    
# plots a range of times in the data set
tides['Jan 22 2012':'July 28 2012'].plot(title="Sea level height (m)")









    Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x7fb21ba21f28>

Ideas for analyses

How can you identify a high tide on the graph? How many high tides happened in September 2015?
What patterns do you see in the data?
Are there daily, monthly, or yearly patterns? Why do you think so?
How can neap tides be identified in a graph?
What do you think happened in June 2011?
This data comes from Australia. How might it be different from data taken in Florida?



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