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Community Data Science Workshops (Fall 2014)/Day 1 lecture: Difference between revisions
Community Data Science Workshops (Fall 2014)/Day 1 lecture (view source)
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{{CDSW Moved}}
Welcome to the Saturday lecture section of the Community Data Science Workshop! For about 2 hours, we'll work through an introduction to the Python programming language via both a lecture and hand-on exercises.
At the beginning of the lecture, we'll give a [[Day 1 pre-lecture|short pre-lecture talk to motivate the sessions]].
== Resources ==
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** e.g., <code>"i" in "team"</code>
** e.g., "i" not in "team"</code>
* <tt>if</tt>/<tt>elif</tt>/<tt>else</tt> ('''move to external file''')
** if, something that evaluates to a boolean, and then colon
** e.g., <code>if "mako" in "makoshark"</code>
** e.g., adding else example: <code>if brother_age > sister_age</code>
** e.g., tempreature range
** e.g., adding elif: fix the bug in the previous program if they were the same age
** indent with spaces (we use 4 spaces!)
* functions
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=== Lists ===
* purpose
** Stores things ''in order''
** making a list called my list: <code>my_list = ["a", "b", "c"]</code>
** comma separated elements. in python they can be a mix of any kind of types
** <code>type(my_list)</code>
* <tt>len()</tt> review
* accessing elements
** indexing starts from the front and we ''start counting at 0'' (now you understand all the zeros we've been using
** we go from the end with negative numbers
** what happens if we try to move outside of the range? ('''error!'')
* adding elements
** using the the <code>my_list.append()</code> function
** the <code>.append()</code> function is a special kind of function that lists know about
* changing elements
** replacing elements like <code>my_list[0] = "foo"</code>
* finding elements in list
** e.g., <code>"z" in my_list</code>
* slicing lists
** the colon inside the [] is the ''slicing syntax''
** e.g., <code>my_list[0:2]</code> is 0th up to, but not including, the 2nd
** e.g., <code>my_list[2:]</code>
** e.g., <code>my_list[:2]</code>
** e.g., <code>my_list[:]</code>
* strings are like lists
** we can slice lists
** len()
*** <code>len("")</code> length of the empty string
* many other interesting functions for lists
** e.g., <code>min()</code> and <code>max()</code>
** e.g., create a list of names and sort it <code>names.sort()</code>
=== loops and more flow control ===
* <tt>for</tt> loops
** e.g., <code>for name in names: print name</code>
** e.g., <code>for name in names: print 'hello ' + name</code>
** Super powerful because it can do something many many times. Data science is about doing tedious things very quickly. For is the workhorse that makes this possible.
** Look and see name is after we're done looping.
** ''Move to editor.''
* <tt>if</tt> statements inside <tt>for</tt> loops
** e.g., <code>if name[0] in "AEIOU"</code> then print "starts with a vowel"
** show we can test things outside the loop to show how the comparisons are working
** add an else statement to capture words that start with a consonant
** append to a list within a for loop
** create a counter within a for loop (keep track)
** build up a sentence
* nested <tt>for</tt> loops
* <tt>range()</tt>
* <tt>while</tt> loops
* infinite loops
* <tt>if</tt> statements inside <tt>while</tt> loops
* <tt>break</tt>
* <tt>raw_input()</tt>
=== dictionaries ===
* purpose
* initialization
* accessing elements
* adding elements
* changing elements
* <tt>keys()</tt> and <tt>values()</tt>
=== modules ===
* purpose
* builtins
* imports
* <tt>import random</tt>
* <tt>random.randint</tt>
* <tt>random.choice</tt>
=== walk through state_capitals.py ===
Where state_capitals.py from http://mako.cc/teaching/2014/cdsw/state_capitals.py is the grand finale and synthesis of lecture material.
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