Python Programming

Class 8

Date and Time

Unix epoch

Is the number of seconds that have elapsed since January 1, 1970 in UTC.

>> date +%s
1517710580

Python Native

time(), datetime(), dateutil()

import time

# time.time() returns the number of seconds
# since the epoch, as seconds. 
print(time.time())

ts = time.time()

#Convert to a string that is human readable. 
import datetime 
st = datetime.datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M:%S')
print(st)


#date_time functions
print(datetime.datetime.now())
print(datetime.datetime.now().isoformat())
print(datetime.datetime.now().utcnow())

Python Native

time(), datetime(), dateutil()

"""
date_time objects
"""

#Build a datetime using datetime
import datetime 
datetime.datetime(year=2018, month=2, day=5,hour = 11,minute = 12,second = 40)

#Parse dates with dateutil from string formats
from dateutil import parser
date = parser.parse("2018-02-05 22:46:34")

Source:  Python Data Science Handbook: Essential Tools for Working with Data

NumPy’s datetime64

The datetime64 dtype encodes dates as 64-bit integers, and thus allows arrays of dates to be represented very compactly.

Source:  Python Data Science Handbook: Essential Tools for Working with Data

import numpy as np
date = np.array('2018-02-05', dtype=np.datetime64)
date

# vectorized operations
date + np.arange(7)

Pandas Timestamp object

Pandas  provides a Timestamp object NumPy-style vectorized operations directly on this same object.

Source:  Python Data Science Handbook: Essential Tools for Working with Data

import pandas as pd
date = pd.to_datetime("2018-02-03 22:46:34")
date

date.strftime('%A')
 
#We can do NumPy-style vectorized operations directly on this sameobject
date + pd.to_timedelta(np.arange(12), 'D')
    

Pandas Time Series: Indexing by Time

Source:  Python Data Science Handbook: Essential Tools for Working with Data

index = pd.DatetimeIndex(['2018-02-03', '2018-02-04','2018-02-05', '2018-02-06'])
data = pd.Series([100, 50, 150, 400], index=index)
data

The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text.

• Matplotlib is a multiplatform data visualization library built on NumPy arrays, and designed to work with the broader SciPy stack.  

• It was conceived by John Hunter in2002, originally as a patch to IPython for enabling interactive MATLAB-style plotting via gnu plot from the IPython command line.

• Plotting package of choice of the Space Telescope Science Institute (Hubble Telescope).

More information: http://pbpython.com/effective-matplotlib.html

import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 10, 100)
plt.plot(x, np.sin(x))
plt.plot(x, np.cos(x))
plt.show()

Bike example

Open Jupyter Notebook.

Challenge

See on Evernote

Resources

• Python Data Science Handbook: Essential Tools for Working with Data
• http://pbpython.com/effective-matplotlib.html
• https://matplotlib.org
• https://docs.python.org/2/library/datetime.html