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submitting assignment 2 #2

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e6b7039
submitting assignment 2
dianayangs Oct 24, 2025
f8fd390
addressing issues
dianayangs Oct 29, 2025
2705293
addressing second comments
dianayangs Oct 29, 2025
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171 changes: 154 additions & 17 deletions 02_activities/assignments/assignment_2.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -72,11 +72,77 @@
},
{
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"execution_count": null,
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"metadata": {
"id": "n0m48JsS-nMC"
},
"outputs": [],
"outputs": [
{
"name": "stdout",
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]
}
],
"source": [
"all_paths = [\n",
" \"../../05_src/data/assignment_2_data/inflammation_01.csv\",\n",
Expand All @@ -93,10 +159,49 @@
" \"../../05_src/data/assignment_2_data/inflammation_12.csv\"\n",
"]\n",
"\n",
"import csv\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",
" first = f.readline()\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",
" contents = csv.reader(f)\n",
" for row in contents:\n",
" print(row)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0\\n'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"first"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"inflammation data csv: each represents a visit with your 60 patients\n",
"60 rows = 60 patients\n",
"columns = visits, number represents the # of flareups that patient had on that day\n",
"\n",
"part 1: can use read.line or read.lines to read the csv file then create a loop to print each row for inspection\n",
"all_paths[0] = corresponds to the all_paths file at index 0 (we only want to inspect the rows for the first csv file)\n",
"\n",
"part 2: create a fxn to provide summary stats for each patient. For each summary stat: we would print 60 values that represent the mean for each of the patients\n"
]
},
{
Expand Down Expand Up @@ -130,26 +235,29 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 4,
"metadata": {
"id": "82-bk4CBB1w4"
},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"def patient_summary(file_path, operation):\n",
"def patient_summary(file_path, operation): #the string is the summary stat\n",
" data = np.loadtxt(fname=file_path, delimiter=',') # Load the data from the file\n",
" ax = 1 # This specifies that the operation should be done for each row (patient)\n",
"\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",
" if operation == 'mean': #you will output a single array with 60 values\n",
" summary_values = np.mean(data,axis=ax)\n",
"\n",
" # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n",
" elif operation == 'max':\n",
" summary_values = np.max(data,axis=ax)\n",
" # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n",
"\n",
" elif operation == 'min':\n",
" summary_values = np.min(data,axis=ax)\n",
" # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n",
"\n",
" else:\n",
Expand All @@ -161,16 +269,26 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 5,
"metadata": {
"id": "3TYo0-1SDLrd"
},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"60\n"
]
}
],
"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",
"print(len(data_min))"
"print(len(data_min))\n",
"\n",
"#looking for length of 60 if you did it correctly"
]
},
{
Expand Down Expand Up @@ -226,9 +344,16 @@
"When using `check_zeros(x)` in conjunction with your `patient_summary()` function in the `detect_problems()` function, you'll be checking whether any patient in your dataset has an average (mean) inflammation score of 0."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"part 3: we want to flag irregularities in the data. they've given us a helper function that will check for 0s. you provide an array and it will return TRUE = if 0s are found, FALSE = otherwise.\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 9,
"metadata": {
"id": "_svDiRkdIwiT"
},
Expand All @@ -251,7 +376,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 10,
"metadata": {
"id": "LEYPM5v4JT0i"
},
Expand All @@ -260,16 +385,27 @@
"# Define your function `detect_problems` here\n",
"\n",
"def detect_problems(file_path):\n",
" '''first will find the mean and store in x, then will use check_zeros on mean to find zeros. if TRUE = return TRUE'''\n",
" x = patient_summary(file_path, 'mean')\n",
" answer = check_zeros(x)\n",
" #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
"\n",
" return"
" return answer"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 11,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"False\n"
]
}
],
"source": [
"# Test out your code here\n",
"# Your output for the first file should be False\n",
Expand Down Expand Up @@ -314,7 +450,8 @@
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"display_name": "python-env",
"language": "python",
"name": "python3"
},
"language_info": {
Expand All @@ -327,7 +464,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.11.13"
}
},
"nbformat": 4,
Expand Down