Category: Python

we have a data science project I need a perfect project and perfect analysis but

we have a data science project I need a perfect project and perfect analysis but to be at student level and I want a Word document or a video to explain each part of the code to understand what you do also If I have questions I will ask, also divide the project to be for 2 student equivalently

Required
1. In this assignment, you are to write codes that generate a unique pa

Required
1. In this assignment, you are to write codes that generate a unique password for different websites.
2. The rules are as follows:
Assume the website url address is “http://www.google.com”,
Rule 1: Write codes to remove “http://www.” as this part is same across any websites.
Rule 2: For the same reason, write codes to remove “.com”. At this point, what you are left with is the unique website name (usually the name of a company, “google”, in our example)
Rule 3: Create a variable and write codes to extract the first three characters of the website name. In our example, the first three characters are “goo.”
Rule 4: Create a variable and write codes to count the number of characters of the website name. In our example, the number of characters is 6 (g, o, o, g, l, e).
Rule 5. Create a variable and write codes to count the number of letter “e” in the unique website name. In our example, we only have one instance of “e” in “google”.
Rule 6. Create a variable and write codes to concatenate the outputs of Rule 3, Rule 4, Rule 5, and also add “!” at the end.
Rule 7. After creating the variable containing the unique password, print the following statement: “The unique password for website url address is: unique password!”In case of “http://www.google.com,” the output statement would look like as the follows: “The unique password for http://www.google.com is: goo61!”
If the url address is “http://www.youtube.com,” the output statement would look like as the follows: “The unique password for http://www.youtube.com is: you71!”
3. Once you write codes, copy and paste them onto MS word doc. Do NOT screenshot the codes.
Suggestions
1. Begin by creating a variable (url)
url = “http://www.google.com”
2. Then, write codes to satisfy the rules. For example, you are to write codes to remove “http://www” to satisfy Rule 1.
3. Make sure that you write codes in detail so that anyone without Python background can run your codes by copying and pasting onto Visual Studio Codes. For example, if a package is required to run your code, you are to include the codes that import necessary packages. If directions/instructions are required when running your codes, include the directions/instructions hashed out.

###Python basic operations
##Check Python version
import sys
print(‘Python: {}’.

###Python basic operations
##Check Python version
import sys
print(‘Python: {}’.format(sys.version))
###############################################################################
##1 Arithmetic
# Python as a calculator
# Addition and subtraction
4+4
print(4+4 +5)
# Space does not matter
print(5 – 5)
# Multiplication and division
print(3 * 5)
print(10 / 2)
# Exponentiation
print(4 ** 2)
# Modulo
print(18 % 7)
#More complicated math functions do not exist in Python base package
sin(30) #NameError: name ‘sin’ is not defined
import math
math.sin(30)
dir(math) # all available functions in “math”
###############################################################################
##2 Python variables, types and operators
#Python has five standard data types:
#-Numbers
#-String
#-List
#-Tuple
#-Dictionary
#In Python, a variable allows you to refer to a value with a name.
#Python is case sensitive
#To create a variable use “=”, like this example:
print (“John is 20 years old” )
print (“He doesn’t like being 20 years old” )
age = ’20’
print (“John is “+ age +” years old,” )
print (“He doesn’t like being ” + age+ ” years old” )
weight = 60
height = 1.7
bmi = weight/height**2
bmi
#You can now use the name of this variable, weight, instead of the actual value,
60.
#Remember, = in Python means assignment, it doesn’t test equality!
#To check the type of a variable:
type(bmi) # bmi is a float
x=3 # x is an integer
y=’I love Python’ # y is a string
z=True # z is a boolean
type(x)
type(y)
type(z)
#Different types have different operation rules, for example,
2+3
True + False
True – False
False-True
#and, or, not operators
True and False
True or False
not (True and False)
3>4
3==4
3==3.0
3!=3
‘ab’+’cd’
‘ab ‘+’cd’
a+a #name ‘a’ is not defined
#local and global variable
x=10
def myfun(x):
y=x**2
x=4
return y
myfun(x)
myfun(5)
myfun(2)
x
###############################################################################
##3. Data structures: list, array, dictionary and dataframe
##3.1. Lists are a simple container of items, much like arrays in many languages.
#They can change size at any time, can contain items of different types.
list_family_member = [‘Mom’, ‘Dad’, ‘Son’, ‘Daughter’]; list_family_member
list_family_height1 = [‘Mom’, 1.65, ‘Dad’, 1.85, ‘Son’, 1.79, ‘Daughter’, 1.52]
print(list_family_height1)
#Check the type of a list
type(list_family_height1)
##index pointer: zero based indexing and backward indexing
list_family_height1[0]
list_family_height1[7]
list_family_height1[-1]
list_family_height1[-8]
#list slicing
list_family_height1[2:4] #the ending index “4” is not included
list_family_height1[:4]
list_family_height1[4:]
##You saw that a Python list can contain practically anything; it can even contain
other lists!
x = [[“a”, “b”, “c”],
[“d”, “e”, “f”],
[“g”, “h”, “i”]]
x
#To subset a list of lists, you can use the same technique as before: square
brackets.
x[2]
x[2][0]
#x[2] results in a list, that you can subset again by adding additional square
brackets.
x[2][:2]
#Replace/delete/extend list elements
x = [“a”, “b”, “c”, “d”]
x[1] = “r”; x
x[2:] = [“s”, “t”]
x
del(x[1]);x #del() is associated with an index
x.remove(‘s’); x #remove() is associated with an element
y = x + [“e”, “f”]; y
y.append(“z”);y
y.clear();y #clear() to empty a list
#Exercise #1
#The areas of the different parts of your house are stored in separate variables,
#as shown below:
# area variables (in square meters)
hall = 11.25
kit = 18.0
liv = 20.0
bed = 10.75
bath = 9.50
#a. Create a list of lists “areas” such that each sub-list contains the name of
each room as a string
#More specifically, use the strings “hallway”, “kitchen”, “livingroom”, “bedroom”
and “bathroom” for
#the appropriate locations and then its corresponding area.
#b. Sum of the areas of kitchen and bedroom and name it “eat_sleep_area”
#c. Use two different ways of slicing to create a new list, “downstairs”, that
contains the first 3 sub-lists of areas.
#d. Do a similar thing to create a new variable, upstairs, that contains the last 2
sub-lists of areas.
#e. You did a miscalculation when determining the area of the bathroom;
#it’s 10.50 square meters instead of 9.50. Can you make the changes?
#Make the areas list more trendy! Change “livingroom” to “chillzone”.
#f. Use the + operator to paste the list [“poolhouse”, 24.5] to the end
#of the areas list. Store the resulting list as areas_1.
#g. Further extend areas_1 by adding data on your garage. Add the string
#”garage” and float 15.45. Name the resulting list areas_2
#h. remove the “poolhouse” and its corresponding float from the areas list.
#List summary
#Powerful
#Collection of values
#Hold different types
#Change, add, remove
#Question: Can we perform mathematical operations over lists?
height = [1.73, 1.68, 1.71, 1.89, 1.79]
height
#Out: [1.73, 1.68, 1.71, 1.89, 1.79]
weight = [65.4, 59.2, 63.6, 88.4, 68.7]
weight
#Out: [65.4, 59.2, 63.6, 88.4, 68.7]
weight / height ** 2
#TypeError: unsupported operand type(s) for **: ‘list’ and ‘float’
###############################################################################
##3.2 We’ll need other data structures such as array (can be created using array()
#from “numpy” module)
#if we want to perform mathematical operation over the data,
#array operation offers element-wise calculations
###############################################################################
###Pyhton package installation
#list all the modules installed in your system
help(“modules”)
#check if a module ‘numpy’ is installed
help(‘numpy’) # documentation will be found if previously installed
help(‘pulp’) #no documentation can be found if not installed
import sys
‘numpy’ in sys.modules
#To install a package, use “!pip install” or “!conda install”
pip install pulp
help(‘pulp’) #shows the documentation for the module
#If the installation doesn’t work for you, try the following excerpts
#import pip
#pip.main([“install”, “pulp”])
#If not try
#sudo pip install pulp
? numpy # object is not found if not imported even it is installed
import numpy
array([1, 2, 3])
# NameError: name ‘array’ is not defined
numpy.array([1, 2, 3])
#Alternatively,
import numpy as np
np.array([1, 2, 3])
#We can also import a function from a module
from numpy import array
array([1, 2, 3])
#or
from numpy import * #very inadvisable practice-function member may be mixed up
array([1, 2, 3])
#output: array([1, 2, 3])
##Exercise #2
#Import the ‘math’ package so you can access the constant pi with math.pi.
#Calculate the circumference of the circle and store it in C, C=2pir
#Calculate the area of the circle and store it in A,A=pir^2
#Print out the results as
#Circumference: C
#Area: A
# Selectively only import pi from the math package
#you can always make your import more selective.
###############################################################################
np_height = np.array(height)
np_height
#Out: array([ 1.73, 1.68, 1.71, 1.89, 1.79])
np_weight = np.array(weight)
np_weight
type(np_weight)
#Out: array([ 65.4, 59.2, 63.6, 88.4, 68.7])
bmi = np_weight / np_height ** 2
bmi
#array([ 21.852, 20.975, 21.75 , 24.747, 21.441])
65.4/1.73**2
#NumPy remarks: it contains only one type!
np.array([1.0, “is”, True])
#array([‘1.0’, ‘is’, ‘True’],
# dtype=’ 23
#Out: array([False, False, False, True, False], dtype=bool)
bmi[bmi > 23]
#Out: array([ 24.747])
##Exercise #3
# a. Create list baseball_height that contains data of the baseball players’ height
in inches
baseball_height = [74, 69, 71, 73, 76, 79, 75, 81]
#Use np.array() to create a numpy array from baseball_height. Name this array
np_baseball_height.
#Print out the type of np_baseball_height to check that you got it right.
#convert the units to meters by Multiplying np_baseball_height with 0.0254.
#Store the new values in a new array, np_baseball_height_m.
#Print out np_baseball_height_m and check if the output makes sense.
# b. Create list baseball_weight that contains data of the baseball players’ weight
in pounds
baseball_weight = [174, 210, 181, 193, 230, 200, 185, 190]
#Create a numpy array from the baseball_weight list. Name this array
np_baseball_weight.
#Multiply by 0.453592 to go from pounds to kilograms. Store the resulting numpy
array as np_baseball_weight_kg.
#Use np_baseball_height_m and np_baseball_weight_kg to calculate the BMI of each
player.
#Print out bmi
#c. Create a boolean numpy array: the element of the array should be True if the
corresponding
#baseball player’s BMI is below 21. You can use the < operator for this. Name the array light. #Print the array light. # Print out a numpy array with the BMIs of all baseball players whose BMI is below` 21. #Use light inside square brackets to do a selection on the bmi array. ##2D NumPy Arrays #Type of NumPy Arrays type(np_height) #Out: numpy.ndarray type(np_weight) #Out: numpy.ndarray #ndarray = N-dimensional array np_2d = np.array([[1.73, 1.68, 1.71, 1.89, 1.79], [65.4, 59.2, 63.6, 88.4, 68.7]]) np_2d #Out:array([[ 1.73, 1.68, 1.71, 1.89, 1.79], # [ 65.4 , 59.2 , 63.6 , 88.4 , 68.7 ]]) np_2d.shape #(2, 5); 2 rows, 5 columns np.array([[1.73, 1.68, 1.71, 1.89, 1.79], [65.4, 59.2, 63.6, 88.4, "68.7"]]) #array([['1.73', '1.68', '1.71', '1.89', '1.79'], # ['65.4', '59.2', '63.6', '88.4', '68.7']], # dtype='v>1.5}
dict_doubleCond
# Dictionary has other Replace/delete/extend operations that are similar to list
Dict_family_height1[‘Mom’] = 1.60;Dict_family_height1
# Delete a single element
del Dict_family_height1[‘Mom’];Dict_family_height1
# Delete all elements in the dictionary
Dict_family_height1.clear();Dict_family_height1
#Exercise #5
#In a supply chain system, there were 7 customers, namely “customer1”,
“customer2″…”customer7″
#and their corresponding demands are 20,35,60,70,42,80,15
StrDemand =”customer”
DemandKeys=[]
for i in range(1,8):
DemandKeys.append(StrDemand+str(i))
DemandKeys
DemandValues=[20,35,60,70,42,80,15]
#a. Creates a dictionary “demand” to store the demand information and use the name
of the customers
#as the keys. First create two lists for keys and values respectively and then make
dictionary from them.
#b. What is the demand of customer7?
#c. The demand of each customer is increased by 20% in the next season. Create the
new dictionary “newdemand”.
#d. Find out the customers who have demand between 21 and 50.
###############################################################################
#3.4 Data frame is a 2-D labeled data structure with columns of potentially
different type (like an excel sheet).
#DataFrame makes data manipulation easy, from selecting or replacing columns and
indices to reshaping data
## Create a dataframe – a function from Pandas module
#Create a dataFrame with 3 months of sales information for 3 companies
account Jan Feb Mar
0 Jones LLC 150 200 140
1 Alpha Co 200 210 215
2 Blue Inc 50 90 95
#3.4.1 The “default” manner to create a DataFrame from python is to use a list of
dictionaries.
#In this case each dictionary key is used for the column headings. A default index
will be
#created automatically:
help(“pandas”)
? pandas
import pandas
import pandas as pd
sales = [{‘account’: ‘Jones LLC’, ‘Jan’: 150, ‘Feb’: 200, ‘Mar’: 140},
{‘account’: ‘Alpha Co’, ‘Jan’: 200, ‘Feb’: 210, ‘Mar’: 215},
{‘account’: ‘Blue Inc’, ‘Jan’: 50, ‘Feb’: 90, ‘Mar’: 95 }]
sales
type(sales)
df = pd.DataFrame(sales)
df
type()
#3.4.2 Alternatively, use from_dict()
sales = {‘account’: [‘Jones LLC’, ‘Alpha Co’, ‘Blue Inc’],
‘Jan’: [150, 200, 50],
‘Feb’: [200, 210, 90],
‘Mar’: [140, 215, 95]}
df = pd.DataFrame.from_dict(sales)
df
sales
#3.4.3 Use lists to create dataframe
#This is a row oriented approach using pandas from_records().
#This approach is similar to the dictionary approach but you need to explicitly
#call out the column labels.
sales = [(‘Jones LLC’, 150, 200, 50),
(‘Alpha Co’, 200, 210, 90),
(‘Blue Inc’, 140, 215, 95)]
labels = [‘account’, ‘Jan’, ‘Feb’, ‘Mar’]
df = pd.DataFrame.from_records(sales, columns=labels)
df
### Exercise 6
#Create the following datafame in two ways (using dictionary and list)
one two three four
a 1.0 1 10.0 11.0
b 2.0 2 20.0 22.0
c 3.0 3 30.0 33.0
#a. From dictionary
#b. From list
##############################################################################
##4. Functions
#Next we learn how to define (create) functions and how to use them.
# In order to define a function, we need to use a reserved word “def”
#A function also has a body, which is indented
#In order for a function to run, it must be called into action.
#Otherwise, a function will not run by itself
#Function hello1 below requires no argument.
#To run it, you need just to call it by typing its name in the program body
#This function returns nothing back
def hello1():
print (“hello world inside the function”)
return
hello1() ##To run it, you need just to call it
#Function hello2 requires one argument.
#Upon calling this function, you have to pass it an argument
def hello2(x):
print (x)
return
hello2()#TypeError: hello2() missing 1 required positional argument: ‘x’
hello2(‘I love Python’)
x=56
hello2(x)
#Function hello3 below requires no argument.
#To run it, you need just to call it by typing its name in the program body
#This function returns content of x
def hello3():
x = “hello world passed to script”
return(x)
hello3()
#Function hello4 below requires no argument.
#To run it, you need just to call it by typing its name in the program body
#This function returns nothing
#Notice that there is no call of this function in the program body
def hello4():
x= “hello world will not be printed as I am not called in the program body”
#this is just an assignment and will not return anything if x is not called
return
hello4()
#Define funtions to do calculation
def sumProblem(x, y):
sum = x + y
print(sum)
sumProblem(2, 3)
def main():
a = int(input(“Enter an integer: “))
b = int(input(“Enter another integer: “))
print( sumProblem(a, b))
main()
#Excercises 7
#Create the following 2 functions.
#a. Write a function “function1”:It takes three argument, all strings. The function
returns the concatenated three arguments.
#test the function with the three strings: I, love, Python. The expected results is
“l love Python”
#b. Write a function “function2”: It takes 3 arguments, three numbers. The function
returns the Max of three arguments.
#test the function with numnbers 2, 3 and 4. Hint: you can first define a funtion
that returns the max of two arguments
#and then define the funtion that returns the max of the three aguments. Use “if”
syntax for condtion
###############################################################################
##5. Loop
#The excerpts bellow helps you to master loop functions
#We create two sets of numbers, and symbols (which is also strings)
list_num = [1, 2, 3, 4, 5]
list_str = [“@”, “#”, “$”, “%”, “&”]
for number in list_num:
print (‘Number_FOR: ‘, number)
#newlist=[]
#for i in list_num:
# i=1+i
# newlist.append(i)
#newlist
#Use for loop to extract data from dictionary
Dict_family_height1= {‘Mom’: 1.65, ‘Dad’: 1.85, ‘Son’: 1.79, ‘Daughter’: 1.52}
Dict_family_height1[‘Mom’]
for i in Dict_family_height1: #i refers to the keys
print(i)
for i in Dict_family_height1: #i refers to the keys
print(Dict_family_height1[i])
num=0
while (num < 5): print ('Number_while: ', list_num[num]) num = num +1 # we get the length of the list_str from the set itself #range(a, b): a, a+1, a+2, ..., b-1 range(len(list_str)) for index in range(len(list_str)): print ('Current String_FOR: ', list_str[index]) #or for data in list_str: print ('Current String_FOR: ', data) #Since we know the number of elements in the set, the above loop could be also written like this: SP=0 while (SP < 5): print ('Current String_while: ', list_str[SP]) SP = SP +1 # we can also build lists using loop, first start with an empty one elements = [] # then use the range function to do 0 to 5 counts for i in range(0, 6): print ("Adding %d to the list." % i) #%d is a space holder for numbers # append is a function that lists understand elements.append(i) elements #Now, we create one nested loop, i.e., a loop inside another loop for vertical in range(1, 6): print (vertical) for horizontal in ['a','b','c']: print (horizontal) # Exercise 8 #a. Write a function "function3": use loop function to sum all the numbers in a list. #The contents of the list should be user specified #Hint: use "+=" operator #Sample List : [4, 2, 7, 1, 3] #Expected Output : 17 #b. Write a function "function4": use loop function to print the even numbers from a given list. #Hint: even number means n % 2 == 0 #Sample List : [4, 10, 13, 14, 50, 61, 70, 87, 90] #Expected Result : [4, 10, 14, 50, 70, 90] # The "+=" and *=" operators bmi bmi+=bmi #"+=" if number, add the right hand side to the left hand side bmi*=2 #"*=" if number, multiply the right hand side to the left hand side #"+=" and *=" are useful in looping

Required
1. In this assignment, you are to write codes that generate a unique pa

Required
1. In this assignment, you are to write codes that generate a unique password for different websites.
2. The rules are as follows:
Assume the website url address is “http://www.google.com”,
Rule 1: Write codes to remove “http://www.” as this part is same across any websites.
Rule 2: For the same reason, write codes to remove “.com”. At this point, what you are left with is the unique website name (usually the name of a company, “google”, in our example)
Rule 3: Create a variable and write codes to extract the first three characters of the website name. In our example, the first three characters are “goo.”
Rule 4: Create a variable and write codes to count the number of characters of the website name. In our example, the number of characters is 6 (g, o, o, g, l, e).
Rule 5. Create a variable and write codes to count the number of letter “e” in the unique website name. In our example, we only have one instance of “e” in “google”.
Rule 6. Create a variable and write codes to concatenate the outputs of Rule 3, Rule 4, Rule 5, and also add “!” at the end.
Rule 7. After creating the variable containing the unique password, print the following statement: “The unique password for website url address is: unique password!”In case of “http://www.google.com,” the output statement would look like as the follows: “The unique password for http://www.google.com is: goo61!”
If the url address is “http://www.youtube.com,” the output statement would look like as the follows: “The unique password for http://www.youtube.com is: you71!”
3. Once you write codes, copy and paste them onto MS word doc. Do NOT screenshot the codes.
Suggestions
1. Begin by creating a variable (url)
url = “http://www.google.com”
2. Then, write codes to satisfy the rules. For example, you are to write codes to remove “http://www” to satisfy Rule 1.
3. Make sure that you write codes in detail so that anyone without Python background can run your codes by copying and pasting onto Visual Studio Codes. For example, if a package is required to run your code, you are to include the codes that import necessary packages. If directions/instructions are required when running your codes, include the directions/instructions hashed out.

Fish hatcheries grow baby fish and release them into streams. The fish then swim

Fish hatcheries grow baby fish and release them into streams. The fish then swim down the streams, sometimes as far as the oceans. The State of Oregon has historically spent tens of millions of dollars operating fish hatcheries, especially to support salmon spawning. These funds not only pay for raising and releasing baby fish; they also pay for monitoring of fish populations as the fish eventually return to spawn their own natural babies in dozens of streams, rivers and other waterways throughout the state.
All those monitoring stations produce data that scientists then need to analyze. That’s where you come in. In this assignment, you will use the third-party OpenPyXL library to calculate some statistics based on Excel spreadsheets. You will read from file (CLO2), use lists (CLO4), do computations (CLO1) and, of course, use a 3rd-party library (CLO6).
To illustrate, a typical spreadsheet might look a bit like the following:
Monitoring point:WILLAMETTE FALLS (downstream)Notes
WillametteTeam5/135/145/155/165/175/18
CHINOOK ADULTA37240023216218192Fish were sampled and sent to OSU on 5/14 and 5/17
CHINOOK JACKA572928(data missing)226
TOTAL STEELHEADB544752484158
Monitoring point:WILLAMETTE FALLS (upstream)data was not gathered on all dates
WillametteTeam5/135/145/155/165/18
CHINOOK ADULTA36538121915581
CHINOOK JACKA471227130
TOTAL STEELHEADB3944514038
You will need to grab data out of the spreadsheet and compute some statistics.s
What you must do
Use your text editor to create a .py file containing a Python program with a function called analyze(filename, query) that accepts two parameters. The first parameter, filename, will indicate the name of an XLSX file. The second parameter, query, will give the name of a fish type (such as ‘CHINOOK ADULT’). Your function should do the following:
Open the file
Iterate the rows and find those whose first column matches the query
Having found the rows that match, retrieve all numbers from all columns within those rows
Return a tuple containing the (minimum, average, maximum) of these values.
For example, calling analyze(filename, ‘CHINOOK JACK’) on the sample spreadsheet shown above would identify the following values: [57, 29, 28, 22, 6, 47, 12, 27, 13, 0]. The minimum of these is 0, the maximum is 57, and the average is 24.1. Thus, the function would return (0, 24.1, 57).
Please note that the sample spreadsheet above is just an example. The real spreadsheet passed in might have more columns, fewer columns, more rows, fewer rows, more fish names, or fewer fish names. There might be missing values as illustrated above. There might be unusual columns inserted into unpredictable places (such as the “Team” column above). Just find the rows based on the leftmost column, then scan horizontally to retrieve all of the cells in those rows that look like floating-point numbers. Finally, compute and return the requested statistics.

This assignment assesses your skills and knowledge on constructing code to manip

This assignment assesses your skills and knowledge on constructing code to manipulate the content of a dictionary.
In this unit, we have explored the fundamental concepts of Iterations and Strings in Python. Before you proceed with this assignment, please review the reading material listed below:
Think Python: How to think like a computer scientist : Chapter 11 – Dictionaries
Python Beginner Tutorial 8 – For loop, Lists, and Dictionaries
Please ensure that you review all examples presented in the Chapter before you work on this assignment. In a program, a dictionary contains lists of students and their courses. The teacher is interested to have a dictionary that has the courses as key and the students enrolled in each course as values. Each key has three different values.
To address this requirement, write a function to invert the dictionary and implement a solution that satisfies the teacher’s need. In particular, the function will need to turn each of the list items into separate keys in the inverted dictionary. Also provide a technical explanation for the code and its output in minimum 200 words.
Sample input:
{
‘Stud1: [‘CS1101’, ‘CS2402’, ‘CS2001’],
‘Stud2: [‘CS2402’,’CS2001’,’CS1102’]
}
Inverted Output:
{
‘CS1101’: [‘Stud1’],
‘CS2402’:[‘Stud1’,’Stud2’],
‘CS2001’: [‘Stud1’,’Stud2’]
‘CS 1102’[‘Stud2’]
}
Programming Instructions: Print the original dictionary as well as the inverted dictionary.
Include your the Python program and the output in your submission.
The code and its output must be explained technically. The explanation can be provided before or after the code, or in the form of comments within the code.
Submission Instructions:Submit the solution in a word document.
Make sure your submission is double-spaced, using Times New Roman, 12-point font, with 1” margins.
Use sources to support your arguments. Add a reference list at the end of the submission. For assistance with APA formatting, view the Learning Resource Center: Academic Writing.
Your submission should be clearly written, concise, and well organized, and free of spelling and grammar errors. Read the grading rubric to understand on how your work will be evaluated.
References: Downey, A. (2015). Think Python: How to think like a computer scientist (2nd ed.). Green Tea Press.
kjdElectronics. (2017, August 5). Python beginner tutorial 8 – For loop, lists, and dictionaries [Video]. YouTube. https://youtu.be/bE6mSBNp4YU
Raj, A. (2022, March 3). Reverse a dictionary in Python. PythonForBeginners.
Python Dictionaries. (n.d.). W3schools.

Fish hatcheries grow baby fish and release them into streams. The fish then swim

Fish hatcheries grow baby fish and release them into streams. The fish then swim down the streams, sometimes as far as the oceans. The State of Oregon has historically spent tens of millions of dollars operating fish hatcheries, especially to support salmon spawning. These funds not only pay for raising and releasing baby fish; they also pay for monitoring of fish populations as the fish eventually return to spawn their own natural babies in dozens of streams, rivers and other waterways throughout the state.
All those monitoring stations produce data that scientists then need to analyze. That’s where you come in. In this assignment, you will use the third-party OpenPyXL library to calculate some statistics based on Excel spreadsheets. You will read from file (CLO2), use lists (CLO4), do computations (CLO1) and, of course, use a 3rd-party library (CLO6).
To illustrate, a typical spreadsheet might look a bit like the following:
Monitoring point:WILLAMETTE FALLS (downstream)Notes
WillametteTeam5/135/145/155/165/175/18
CHINOOK ADULTA37240023216218192Fish were sampled and sent to OSU on 5/14 and 5/17
CHINOOK JACKA572928(data missing)226
TOTAL STEELHEADB544752484158
Monitoring point:WILLAMETTE FALLS (upstream)data was not gathered on all dates
WillametteTeam5/135/145/155/165/18
CHINOOK ADULTA36538121915581
CHINOOK JACKA471227130
TOTAL STEELHEADB3944514038
You will need to grab data out of the spreadsheet and compute some statistics
Use your text editor to create a .py file containing a Python program with a function called analyze(filename, query) that accepts two parameters. The first parameter, filename, will indicate the name of an XLSX file. The second parameter, query, will give the name of a fish type (such as ‘CHINOOK ADULT’). Your function should do the following:
Open the file
Iterate the rows and find those whose first column matches the query
Having found the rows that match, retrieve all numbers from all columns within those rows
Return a tuple containing the (minimum, average, maximum) of these values.
For example, calling analyze(filename, ‘CHINOOK JACK’) on the sample spreadsheet shown above would identify the following values: [57, 29, 28, 22, 6, 47, 12, 27, 13, 0]. The minimum of these is 0, the maximum is 57, and the average is 24.1. Thus, the function would return (0, 24.1, 57).
Please note that the sample spreadsheet above is just an example. The real spreadsheet passed in might have more columns, fewer columns, more rows, fewer rows, more fish names, or fewer fish names. There might be missing values as illustrated above. There might be unusual columns inserted into unpredictable places (such as the “Team” column above). Just find the rows based on the leftmost column, then scan horizontally to retrieve all of the cells in those rows that look like floating-point numbers. Finally, compute and return the requested statistics.

Jana Center:
to know more about Jana Center, please visit their website https://

Jana Center:
to know more about Jana Center, please visit their website https://jana-sa.org/
Attached is sample paper, and dataset for further analysis (analysis shall be through python)
for the project objectives and the questions, below is one recommendation, you can as analyst change and adjust as needed.
Project objectives:
To identify and analyze the patterns and factors influencing loan disbursement and repayment among individuals in different regions of Saudi Arabia. This analysis aims to understand how demographic and socio-economic variables such as age, nationality, marital status, academic qualification, family income, number of dependents, and the sector of the loan influence the loan amount disbursed, the repayment rate, and the timing of loan disbursement.
Specific Questions to Address:
What are the demographic and socio-economic characteristics of individuals who apply for and receive loans in different regions of Saudi Arabia?
How does the loan disbursement amount vary across different sectors (e.g., cooking, salon businesses, makeup services) and demographic groups?
What factors contribute to a 100% repayment rate, and how can these insights inform strategies to improve loan repayment rates across all sectors?
Is there a relationship between the loan period, the amount disbursed, and the repayment rate?
How do external factors, such as the time of year or economic conditions, impact loan disbursement and repayment patterns?
PROJECT GENERAL GUIDELINES:
Singles-spaced.
1.5-2 pages max excluding references
Font size 11.
Two columns page setup.
References should be listed in an acceptable format (for example APA style).
Use headings and sub-headings styles.
Organizes the report in a logical and coherent manner.
Demonstrates effective communication skills with clear and concise writing.
Uses appropriate visualizations and diagrams to support the analysis.
Presents the technical details in a way that is understandable to a non-technical audience.
Provides appropriate citations and references to support claims and findings
Section1: Introduction & Problem Identification (2 pages)
Clearly defines the business problem or question to be addressed.
Describes the relevance and significance of the problem in the business context.
Provides a clear objective or goal for the project.
Identifies the target audience or stakeholders for the analysis.
Demonstrates a clear understanding of the data required to address the problem.
Section2: Background/Review of the Literature (2 pages)
Conducts a comprehensive review of relevant literature, theories, and frameworks related to the problem. (minimum 14)
Identifies and explains the key concepts and variables related to the problem.
Shows an understanding of existing research or similar projects in the field.
Analyzes and presents any existing data sources or datasets relevant to the problem.
Section3: Methodology (2 pages)
Clearly defines the methodology or approach used to address the problem.
Explains the rationale behind the chosen methodology (e.g., descriptive analytics, predictive analytics, prescriptive analytics).
Describes the data collection process and data preprocessing techniques used.
Discusses any assumptions or limitations of the chosen methodology.
Section4: Analysis and Findings
Performs appropriate data exploration and preprocessing techniques to gain insights from and prepare the data for analysis.
Applies relevant statistical or machine learning techniques to analyze the data.
Presents the analysis results in a clear and structured manner (e.g., data visualizations, summary statistics).
Provides a thorough interpretation and explanation of the analysis findings.
Evaluates the accuracy and reliability of the analysis results.
Section5: Discussion and Insights (2 pages)
Interprets the analysis results in the context of the business problem.
Identifies and discusses any patterns, trends, or relationships discovered.
Provides meaningful insights and recommendations based on the analysis findings using business language.
Relates the insights to the original problem statement and project objectives.
Considers any ethical, legal, or social implications of the analysis findings.
Section6: References
Accurately cites all the sources used in the project, following a consistent citation style (i.e., APA style).
Provides in-text citations where appropriate to support claims and findings.

Hello, please the material that is used for BUS 202. do not copy paste from chat

Hello, please the material that is used for BUS 202. do not copy paste from chat gtp or anywhere. It will be checked. for the extra credit assignment, use number besides 1,2,3. please look at the name on top of the screenshot for the right assignment. let me know if you are having hard time looking at the pictures.

Use the terms “equivalent” and “identical” to distinguish between objects and va

Use the terms “equivalent” and “identical” to distinguish between objects and values. Illustrate the difference further using your own examples with Python lists and the “is” operator.
Using your own Python list examples, explain how objects, references, and aliasing relate to one another.
Finally, create your own example of a function that modifies a list passed in as an argument. Hence, describe what your function does in terms of arguments, parameters, objects, and references.
Create your own unique examples for this assignment. Do not copy them from the textbook or any other source.
The code and its output must be explained technically whenever asked. The explanation can be provided before or after the code, or in the form of code comments within the code. For any descriptive type question, Your answer must be at least 150 words.
End your discussion post with one question related to programming fundamentals learned in this unit from which your colleagues can formulate a response or generate further discussion. Remember to post your initial response as early as possible, preferably by Sunday evening, to allow time for you and your classmates to have a discussion.
When you use information from a learning resource, such as a textbook, be sure to credit your source and include the URL. Continue to practice using APA format for citations and references.