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Python Program to Implement Quality Control Assignment Solution.


Instructions

Objective
Write a python assignment program to implement quality control.

Requirements and Specifications

program to implement quality control in python

Source Code

import pandas as pd

import matplotlib.pyplot as plt

import numpy as np

# Define function to display main menu and ask for option

def menu():

while True:

try :

print("Please choose from the following options:")

print("\t1 - Load data from a file")

print("\t2 - View data")

print("\t3 - Clean data")

print("\t4 - Analyse data")

print("\t5 - Visualise data")

print("\t6 - Save data to a file")

print("\t7 - Quit")

option = int(input())

if option >= 1 and option <= 7:

return option

else:

print("Please enter a valid option.")

except:

print("Please enter a valid menu option")

# Define a function to display the menu for the 'Clean Data' option

def cleandata_menu():

while True:

try :

print("Cleaning data:")

print("\t1 - Drop rows with missing values")

print("\t2 - Fill missing values")

print("\t3 - Drop duplicate rows")

print("\t4 - Drop column")

print("\t5 - Rename column")

print("\t6 - Finish cleaning")

option = int(input())

if option >= 1 and option <= 6:

return option

else:

print("Please enter a valid option.")

except:

print("Please enter a valid menu option")

# Define a function to get an integer from user. The integer must be between [lb, ub]

def get_int(message, lb, ub):

"""

Requests an integer input 'n' such that lb <= n <= ub

"""

while True:

try :

option = int(input(message))

if option >= lb and option <= ub:

return option

else:

print(f"Please enter a value between {lb} and {ub}.")

except:

print("Please enter a valid integer.")

# Main code

current_data = None # Variable to store the current loaded data

running = True

while running:

option = menu()

if option == 1:

# Ask for file name

file_name = input("Enter file name: ")

try:

data = pd.read_csv(file_name)

current_data = data

print(f" File {file_name} correctly loaded!")

# Ask if s/he wants to set a column name as index

while True:

col_name = input("Enter column name to be set as index: ")

if len(col_name) > 0:

if col_name in current_data.columns:

current_data = current_data.set_index(col_name)

current_data = current_data.drop(columns=[col_name])

break

else:

print("Sorry, the data does not contain a column with that name.")

else:

break

except:

print("File does not exist or could not be loaded.")

elif option == 2:

# Print

if current_data:

print(current_data)

else:

print("No data loaded.")

elif option == 3:

if current_data:

while True:

opt = cleandata_menu()

if opt == 1: # drop rows with missing values

# Ask for threshold

treshold = get_int("Enter the treshold for dropping rows: ", 1, np.inf)

current_data = current_data[current_data.isnull().sum(axis = 1) < treshold]

elif opt == 2: # fill missing values

replacement = get_int("Enter the replacement value", -np.inf, np.inf)

current_data.fillna(replacement)

elif opt == 3: # Drop duplicate rows

# Get current amount of rowas

n_current = len(current_data)

current_data.drop_duplicates()

n_new = len(current_data)

print(f"{n_current-n_new} rows dropped.")

elif opt == 4: # drop dolumn

# Ask name of column

print("Which column do you want to drop? (leave blank for none)")

for c in current_data.columns:

print(f"\t{c}")

column = input()

if len(column) > 0:

if column in current_data.columns:

current_data = current_data.drop(columns = [column])

print(f"{column} dropped.")

else:

print("Invalid selection!")

else:

print("No column dropped.")

elif opt == 5: # Rename column

print("Which column do you want to rename? (leave blank for none)")

for c in current_data.columns:

print(f"\t{c}")

column = input()

if len(column) > 0:

if column in current_data.columns:

# Ask for new name

new_column = input("Enter the new name: ")

current_data.rename(columns={column:new_column})

print(f"{column} renamed to {new_column}.")

else:

print("Invalid selection!")

else:

print("No column renamed.")

elif opt == 6: # finish cleaning

break

print(current_data)

else:

print("No data loaded.")

elif option == 4: # Analyse data

if current_data:

for c in current_data.columns:

print(c)

print('-'*len(c))

print("{:<15s}:{:>5d}".format("number of values (n)", current_data[c].count()))

print("{:<15s}:{:>5.2f}".format("minimum", current_data[c].min()))

print("{:<15s}:{:>5.2f}".format("maximum", current_data[c].max()))

print("{:<15s}:{:>5.2f}".format("mean", current_data[c].mean()))

print("{:<15s}:{:>5.2f}".format("median", current_data[c].median()))

print("{:<15s}:{:>5.2f}".format("standard deviation", current_data[c].std()))

print("{:<15s}:{:>5.2f}".format("std. err. of mean", current_data[c].sem()))

# Display correlation table

print(current_data.corr())

else:

print("No data loaded.")

elif option == 5: # Visualize

if current_data:

while True:

# Ask for plot type

print("Please choose from the following kinds: line, bar, box")

plot_type = input()

if plot_type.lower() in ['line', 'bar', 'box']:

print("Do you want subplots? (y/n)")

yn = input()

if yn.lower() in ['y', 'n']:

plot_title = input("Please enter the title for the plot (leave blank for no title)\n")

x_label = input("Please enter the x-axis label (leave blank for no label).\n")

y_label = input("Please enter the y-axis label (leave balnk for no label).\n")

if yn == 'y': # subplots

n_columns = len(current_data.columns)

if plot_type != 'box':

fig, axes = plt.subplots(nrows = n_columns, ncols = 1)

for i, c in enumerate(current_data.columns):

if plot_type == 'line':

current_data.plot(y=c, use_index = True, ax = axes[i])

elif plot_type == 'bar':

current_data.plot.bar(y=c, use_index = True, ax = axes[i])

axes[i].set_title(plot_title)

axes[i].set_xlabel(x_label)

axes[i].set_ylabel(y_label)

plt.show()

break

else:

plt.figure()

current_data.boxplot()

plt.title(plot_title)

plt.xlabel(x_label)

plt.ylabel(y_label)

plt.show()

break

else:

n_columns = len(current_data.columns)

if plot_type != 'box':

for i, c in enumerate(current_data.columns):

plt.figure()

current_data.plot(y=c, use_index = True)

plt.title(plot_title)

plt.xlabel(x_label)

plt.ylabel(y_label)

plt.show()

break

else:

plt.figure()

current_data.boxplot()

plt.title(plot_title)

plt.xlabel(x_label)

plt.ylabel(y_label)

plt.show()

break

else:

print("Invalid selection!")

else:

print("Invalid selection!")

else:

print("No data loaded.")

elif option == 6: #Save to a file

if current_data:

file_name = input("Enter the filename, including extension: ")

try:

current_data.to_csv(file_name,sep=',')

except:

print(f"Data could not be saved to {file_name}")

else:

print("No data loaded.")

elif option == 7:

running = False

print("Goodbye")