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Assignment 2 #355

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6e20875
assignment-1
Osaheni-Lawani Mar 16, 2026
d965abe
assignment-2
Osaheni-Lawani Mar 22, 2026
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144 changes: 127 additions & 17 deletions 02_activities/assignments/assignment_1.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -56,36 +56,95 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"# For testing purposes, we will write our code in the function\n",
"# Answers/Solution to Part 1\n",
"# Function to check if two words are anagrams\n",
"def anagram_checker(word_a, word_b):\n",
" # Your code here\n",
"\n",
"# Run your code to check using the words below:\n",
"# Convert both words to lowercase\n",
" word_a = word_a.lower()\n",
" word_b = word_b.lower()\n",
"\n",
"# Compare sorted letters\n",
" if sorted(word_a) == sorted(word_b):\n",
" return True\n",
" else:\n",
" return False"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Check if Silent and listen are anagrams\n",
"anagram_checker(\"Silent\", \"listen\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 9,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Check if Silent and Night are anagrams\n",
"anagram_checker(\"Silent\", \"Night\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 10,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Check if night and Thing are anagrams\n",
"anagram_checker(\"night\", \"Thing\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
Expand All @@ -97,32 +156,83 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"# Answers/Solutions to Part 2 \n",
"# Modify existing code\n",
"# Check if two words are anagrams with case sensitivity option\n",
"def anagram_checker(word_a, word_b, is_case_sensitive):\n",
" # Modify your existing code here\n",
"\n",
"# Run your code to check using the words below:\n",
" if not is_case_sensitive:\n",
" word_a = word_a.lower()\n",
" word_b = word_b.lower()\n",
"\n",
" return sorted(word_a) == sorted(word_b)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Run your code to check using the words \"Silent\", \"listen\"\n",
"# Add boolean option False and check to see if they are anagrams of each other\n",
"anagram_checker(\"Silent\", \"listen\", False) # True"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 13,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Add boolean option True and check to see if they are anagrams of each other\n",
"anagram_checker(\"Silent\", \"listen\", True) # False"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 14,
"metadata": {},
"outputs": [],
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Add boolean option True and check to see if they are anagrams of each other\n",
"anagram_checker(\"Silent\", \"Listen\", True) # False"
]
},
Expand All @@ -139,7 +249,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "new-learner",
"display_name": "python-env",
"language": "python",
"name": "python3"
},
Expand All @@ -153,7 +263,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.11.14"
}
},
"nbformat": 4,
Expand Down
82 changes: 59 additions & 23 deletions 02_activities/assignments/assignment_2.ipynb
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -95,8 +95,15 @@
"\n",
"with open(all_paths[0], 'r') as f:\n",
" # YOUR CODE HERE: Use the readline() or readlines() method to read the .csv file into a variable\n",
" # Open the first file inflammation_01.csv\n",
" with open(r'/Users/osahenilawani/DSI_projects/python/05_src/data/assignment_2_data/inflammation_01.csv', 'r') as f: \n",
" lines = f.readlines() # Read all lines in the dataset from the file (inflammation_01.csv)\n",
" print(f.readlines()) # Print all lines in the dataset from the file (inflammation_01.csv)\n",
" \n",
" # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection"
" # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n",
"\n",
"for line in lines: # Loop through each line (observations for each patient) in the dataset and print it\n",
" print(line.strip())"
]
},
{
Expand Down Expand Up @@ -130,10 +137,8 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "82-bk4CBB1w4"
},
"execution_count": 133,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
Expand All @@ -144,21 +149,30 @@
"\n",
" # Implement the specific operation based on the 'operation' argument\n",
" if operation == 'mean':\n",
" # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n",
" # YOUR CODE HERE: \n",
" patient_summary = np.mean(data, axis=ax) # Calculate mean (average) flare-ups for each patient in the dataset\n",
"\n",
" elif operation == 'max':\n",
" # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n",
" # YOUR CODE HERE: \n",
" patient_summary = np.max(data, axis=ax) # Calculate the maximum number of flare-ups experienced by each patient in the dataset\n",
"\n",
" elif operation == 'min':\n",
" # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n",
"\n",
" # YOUR CODE HERE: \n",
" patient_summary = np.min(data, axis=ax) # Calculate the minimum number of flare-ups experienced by each patient in the dataset\n",
" else:\n",
" # If the operation is not one of the expected values, raise an error\n",
" raise ValueError(\"Invalid operation. Please choose 'mean', 'max', or 'min'.\")\n",
" raise ValueError(\"Invalid operation. Please choose 'mean', 'max', or 'min'.\") #flags an error if the mean, max or min is not specified in the operation\n",
"\n",
" return summary_values"
" return patient_summary"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
Expand All @@ -169,7 +183,7 @@
"source": [
"# Test it out on the data file we read in and make sure the size is what we expect i.e., 60\n",
"# Your output for the first file should be 60\n",
"data_min = patient_summary(all_paths[0], 'min')\n",
"data_min = patient_summary(r'/Users/osahenilawani/DSI_projects/python/05_src/data/assignment_2_data/inflammation_01.csv', 'min')\n",
"print(len(data_min))"
]
},
Expand Down Expand Up @@ -228,7 +242,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 114,
"metadata": {
"id": "_svDiRkdIwiT"
},
Expand All @@ -251,18 +265,38 @@
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "LEYPM5v4JT0i"
},
"execution_count": 115,
"metadata": {},
"outputs": [],
"source": [
"# Define your function `detect_problems` here\n",
"# Run this cell so you can use this helper function\n",
"\n",
"def check_zeros(x):\n",
" '''\n",
" Given an array, x, check whether any values in x equal 0.\n",
" Return True if any values found, else returns False.\n",
" '''\n",
" # np.where() checks every value in x against the condition (x == 0) and returns a tuple of indices where it was True (i.e. x was 0)\n",
" flag = np.where(x == 0)[0]\n",
"\n",
" # Checks if there are any objects in flag (i.e. not empty)\n",
" # If not empty, it found at least one zero so flag is True, and vice-versa.\n",
" return len(flag) > 0"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [],
"source": [
"# Define your function `detect_problems` here\n",
"def detect_problems(file_path):\n",
" #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
"\n",
" return"
" # Get mean inflammation values for each patient\n",
" means = patient_summary(r'/Users/osahenilawani/DSI_projects/python/05_src/data/assignment_2_data/inflammation_01.csv', 'mean')\n",
" has_problem = check_zeros(means) # Check if any mean values are zero\n",
" return has_problem"
]
},
{
Expand All @@ -273,7 +307,8 @@
"source": [
"# Test out your code here\n",
"# Your output for the first file should be False\n",
"print(detect_problems(all_paths[0]))"
"print(detect_problems(r'/Users/osahenilawani/DSI_projects/python/05_src/data/assignment_2_data/inflammation_01.csv')) \n",
"# prints output to detetect if any mean values are zero "
]
},
{
Expand Down Expand Up @@ -314,7 +349,8 @@
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"display_name": "python-env",
"language": "python",
"name": "python3"
},
"language_info": {
Expand All @@ -327,7 +363,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.11.14"
}
},
"nbformat": 4,
Expand Down