labs for session02 through session06 and lightening talk files

students/JohnRudolph/session4/sherlock_small.txt

@@ -0,0 +1,16 @@
+One night--it was on the twentieth of March, 1888--I was
+returning from a journey to a patient (for I had now returned to
+civil practice), when my way led me through Baker Street. As I
+passed the well-remembered door, which must always be associated
+in my mind with my wooing, and with the dark incidents of the
+Study in Scarlet, I was seized with a keen desire to see Holmes
+again, and to know how he was employing his extraordinary powers.
+His rooms were brilliantly lit, and, even as I looked up, I saw
+his tall, spare figure pass twice in a dark silhouette against
+the blind. He was pacing the room swiftly, eagerly, with his head
+sunk upon his chest and his hands clasped behind him. To me, who
+knew his every mood and habit, his attitude and manner told their
+own story. He was at work again. He had risen out of his
+drug-created dreams and was hot upon the scent of some new
+problem. I rang the bell and was shown up to the chamber which
+had formerly been in part my own.

students/susanRees/LighteningTalkFiles/lighteningTalk.py

@@ -0,0 +1,69 @@
+####################
+## import modules ##
+####################
+
+# the program opens the workbook by importing the openpyxl module and calling
+# the openpyxl.load_workbook() function.
+import openpyxl as op
+wb = openpyxl.load_workbook('surveyData.xlsx')
+
+def get_age_groups(my_sheet, my_column):
+    # calls the get_sheet_by_name function to get the worksheet object
+    sheet = wb.get_sheet_by_name(my_sheet)
+    # Use the cell() sheet method with row and column keyword arguments
+    # to pull values from all cells in one column.  puts them into a tuple.
+    rawAgeData = sheet.columns[my_column]
+    for cellObj in sheet.columns[my_column]:
+        print(cellObj.value)
+    # puts them in order
+    ageDataOrdered = [sorted(rawAgeData)]
+    # Using a for loop?  counts the total number of entries, creates dictionary
+    # with unique entries (age) as keys, and the number of times each entry
+    # appears as value?
+    ageGroups = {}
+    for items in ageDataOrdered:
+        if items == items:
+            ageGroups = {counts(items)}
+            # remove duplicate items?? use itertools
+        else:
+            ageGroups = {counts(items)}
+    # in new dictionary? iterates through dict values and divides by total
+    # number of entries to provide the percentage (new value) of the whole that
+    # each unique entry group (keys) represents
+    # sorts entries (keys) by percentage (value) to see the order of importance
+    for keys, values in (ageGroups.items()):
+        numAges = len(keys)
+        percentAge = int(values/numAges)
+        finalNums = {percentAge}
+        sorted(finalNums, percentAge)
+
+# starts program
+if __name__ == '__main__':
+    my_script.main()
+
+my_sheet = 'path to excel sheet'
+
+# Displays them in a pie (lol) chart or bar graph of some sort?
+# example from automate the borimg stuff below.
+# import openpyxl
+# wb = openpyxl.Workbook()
+# sheet = wb.get_active_sheet()
+# for i in range(1, 11):         # create some data in column A
+#     sheet['A' + str(i)] = i
+
+# refObj = openpyxl.charts.Reference(sheet, (1, 1), (10, 1))
+
+# seriesObj = openpyxl.charts.Series(refObj, title='First series')
+
+# chartObj = openpyxl.charts.PieChart()   # can also use BarChart
+# chartObj.append(seriesObj)
+# chartObj.drawing.top = 50       # set the position
+# chartObj.drawing.left = 100
+# chartObj.drawing.width = 300    # set the size
+# chartObj.drawing.height = 200
+
+# sheet.add_chart(chartObj)
+# wb.save('sampleChart.xlsx')
+
+# convert this program to require user input (which column do you want?) or to
+# run on all columns automatically?

students/susanRees/LighteningTalkFiles/lighteningTalkPandas.py

@@ -0,0 +1,42 @@
+# Imports pandas
+# reads the spreadsheet
+# pops the "Age" column out
+# uses .value_counts to group ages together and
+# sorts them in ascending order according to frequency of occurance
+
+import pandas as pd
+df = pd.read_excel("surveyData.xlsx")
+ages = df.pop("Age")
+print(ages.value_counts(normalize=True, sort=True, ascending=False, bins=None, dropna=True))
+
+
+# pandas.series.value_counts
+# series.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True)
+
+#   Returns object containing counts of unique values.
+
+#   The resulting object will be in descending order so that the first
+#   element is the most frequently-occurring element. Excludes NA values
+#   by default.
+
+#       Parameters:
+
+#       normalize : boolean, default False
+#           If True then the object returned will contain the relative
+#           frequencies of the unique values.
+
+#       sort : boolean, default True
+#           Sort by values
+
+#       ascending : boolean, default False
+#           Sort in ascending order
+
+#       bins : integer, optional
+#           Rather than count values, group them into half-open bins, a
+#           convenience for pd.cut, only works with numeric data
+
+#       dropna : boolean, default True
+#           Don’t include counts of NaN.
+
+#       Returns:
+#           counts : Series

students/susanRees/session02/PrintGrid.py

@@ -21,23 +21,38 @@ def print_column():
     print_column()
     print_row()
 
-
 print_grid(10)
 
 
 def second_grid(x, y):
-    n = (y-1)
-    for n in range(0, n):
-        def print_rows():
+    n = (x + 1)
+    m = (n - 1)
+    for m in range(0, m):
+        def print_row():
             print('+', end=' '),
             print('-' * y, end=' '),
-        print_rows()
-        print('+')
-        def print_columns():
+        def print_rows():
+            n = (x + 1)
+            m = (n - 1)
+            for m in range (0, m):
+                print_row()
+        def print_column():
             print('|', end=' '),
             print(' ' * y, end=' '),
-        print_columns()
-        print('|')
+        def print_columns():
+            n = (x + 1)
+            m = (n - 1)
+            for m in range (0, m):
+                print_column()
+        print_rows()
+        print('+')
+        def print_mult_columns():
+            n = (y + 1)
+            m = (n - 1)
+            for m in range (0, m):
+                print_columns()
+                print('|')
+        print_mult_columns()
     print_rows()
     print('+')
-second_grid(3, 4)
+second_grid(4, 10)

students/susanRees/session03/Lists.py

@@ -95,16 +95,16 @@
 
 
 # Make a copy of the original list
-backwards_fruits = fruits[0:-1]
+backwards_fruits = fruits[:]
 
 # reverse the letters in each fruit in the copy.
-# for bwards in backwards_fruits:
-
-# print(backwards_fruits)
+for item in backwards_fruits[:]:
+    bward_item = item[::-1]
+    backwards_fruits.append(bward_item)
 
 # Delete the last item of the original list.
-# fruits.pop(-1)
+fruits.pop(-1)
 
 # Display the original list and the copy.
-# print(fruits)
-# print(backwards_fruits)
+print(fruits)
+print(backwards_fruits)

students/susanRees/session04/DictionaryLab.py

@@ -1,51 +1,72 @@
 # Create a dictionary containing “name”, “city”, and “cake”
 # for “Chris” from “Seattle” who likes “Chocolate”.
-dict = {'name': "Chris", 'city': "Seattle", 'cake': "Chocolate"}
+stuff = {'name': "Chris", 'city': "Seattle", 'cake': "Chocolate"}
 
 # Display the dictionary.
-print(dict)
+print(stuff)
 
 # Delete the entry for “cake”.
-dict.pop('cake')
+stuff.pop('cake')
 
 # Display the dictionary.
-print(dict)
+print(stuff)
 
 # Add an entry for “fruit” with “Mango” and display the dictionary.
-dict.update({'fruit': "Mango"})
+stuff.update({'fruit': "Mango"})
 
-print(dict)
+print(stuff)
 
 # Display the dictionary keys.
-print(dict.keys())
+print(stuff.keys())
 
 
 # Display the dictionary values.
-print(dict.values())
+print(stuff.values())
 
 # Display whether or not “cake” is a key in the dictionary (i.e. False) (now).
-print("True" if 'cake' in dict else "False")
+print("True" if 'cake' in stuff else "False")
 
 # Display whether or not “Mango” is a value in the dictionary (i.e. True).
-print("True" if "Mango" in dict.values() else "False")
+print("True" if "Mango" in stuff.values() else "False")
 
 # Using the dictionary from item 1:
 # Make a dictionary using same keys but with the number of ‘t’s in each value.
-# Not sure I understand the assingment...
+stuff = {'name': "Chris".count("t"), 'city': "Seattle".count("t"), 'cake': "Chocolate".count("t")}
+print(stuff)
 
 # Create sets s2, s3 and s4 containing numbers from 0-20, divisible 2, 3 and 4.
-s2 = set([1:20])
-s3 = set([1:20])
-s4 = set([1:20])
+s2 = set([x for x in range(0, 20) if x % 2 == 0])
+s3 = set([x for x in range(0, 20) if x % 3 == 0])
+s4 = set([x for x in range(0, 20) if x % 4 == 0])
 
 # Display the sets.
+print(s2)
+print(s3)
+print(s4)
 
 # Display if s3 is a subset of s2 (False)
+if s3.issubset(s2):
+    print(True)
+else:
+    print(False)
 
 # and if s4 is a subset of s2 (True).
+if s4.issubset(s2):
+    print(True)
+else:
+    print(False)
 
-# Create a set with the letters in ‘Python’ and add ‘i’ to the set.
+# Create a set with the letters in ‘Python’
+python = set(["p", "y", "t", "h", "o", "n"])
+
+#add ‘i’ to the set.
+python.update(["i"])
+print(python)
 
 # Create a frozenset with the letters in ‘marathon’
+marathon = frozenset(["m", "a", "r", "a", "t", "h", "o", "n"])
+print(marathon)
 
-# display the union and intersection of the two sets.
+# display the union and intersection of the two sets.
+print(marathon.union(python))
+print(marathon.intersection(python))

students/susanRees/session05/comprehensions.py

@@ -0,0 +1,36 @@
+feast = ['lambs', 'sloths', 'orangutans', 'breakfast cereals', 'fruit bats']
+comprehension = [delicacy.capitalize() for delicacy in feast]
+print(comprehension[0])
+print(comprehension[2])
+
+comp = [delicacy for delicacy in feast if len(delicacy) > 6]
+print(len(feast))
+print(len(comp))
+
+list_of_tuples = [(1, 'lumberjack'), (2, 'inquisition'), (4, 'spam')]
+comprehension = [skit * number for number, skit in list_of_tuples]
+print(comprehension[0])
+print(len(comprehension[2]))
+
+eggs = ['poached egg', 'fried egg']
+meats = ['lite spam', 'ham spam', 'fried spam']
+comprehension = ['{0} and {1}'.format(egg, meat) for egg in eggs for meat in meats]
+print(len(comprehension))
+print(comprehension[0])
+
+comprehension = {x for x in 'aabbbcccc'}
+print(comprehension)
+
+dict_of_weapons = {'first': 'fear', 'second': 'surprise', 'third':'ruthless efficiency', 'forth':'fanatical devotion', 'fifth': None}
+dict_comprehension = {k.upper(): weapon for k, weapon in dict_of_weapons.iteritems() if weapon}
+print('first' in dict_comprehension)
+print('FIRST' in dict_comprehension)
+print(len(dict_of_weapons))
+print(len(dict_comprehension))
+
+#count_evens([2, 1, 2, 3, 4]) == 3
+#count_evens([2, 2, 0]) == 3
+#count_evens([1, 3, 5]) == 0
+
+#def count_evens(nums):
+#   one_line_comprehension_here

students/susanRees/session05/exceptions.py

@@ -0,0 +1,12 @@
+# Create a wrapper function, safe_input()
+# returns None rather rather than raising the exceptions EOFError or KeyboardInterrupt
+# when user enters ^C for Keyboard Interrupt, or ^D (^Z on Windows) for End Of File.
+
+def safe_input():
+    try:
+        input("Type something here")
+    except (EOFError, KeyboardInterrupt):
+        return None
+    else:
+        print("Thanks.")
+safe_input()