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219 changes: 194 additions & 25 deletions 02_assignments/assignment_2.ipynb
Original file line number Diff line number Diff line change
Expand Up @@ -90,16 +90,156 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 33,
"metadata": {
"id": "n0m48JsS-nMC"
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"outputs": [],
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{
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"\n",
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"\n",
"It have 60 lines in the file ../05_data/assignment_2_data/inflammation_01.csv\n"
]
}
],
"source": [
"with open(all_paths[0], 'r') as f:\n",
" # YOUR CODE HERE: Use the readline() method to read the .csv file into 'contents'\n",
"\n",
" # Initialize the line count, assume not known yet for general purpose\n",
" lines = 0\n",
" \n",
" # YOUR CODE HERE: Iterate through 'contents' using a for loop and print each row for inspection"
" # Iterate using a while loop and print each row for inspection\n",
" while True:\n",
" # Use the readline() method to read the .csv file into linebuf\n",
" linebuf = f.readline()\n",
" if len(linebuf) > 0: # To check if it has the content in the line, or EOF\n",
" print (linebuf)\n",
" lines += 1\n",
" else:\n",
" print (\"It have \" + str(lines) + \" lines in the file \" + all_paths[0])\n",
" break\n",
" "
]
},
{
Expand Down Expand Up @@ -133,7 +273,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 39,
"metadata": {
"id": "82-bk4CBB1w4"
},
Expand All @@ -143,33 +283,52 @@
"\n",
"def patient_summary(file_path, operation):\n",
" # load the data from the file\n",
" data = np.loadtxt(fname=file_path, delimiter=',')\n",
" ax = 1 # this specifies that the operation should be done for each row (patient)\n",
"\n",
" data = np.loadtxt(fname = file_path, delimiter = ',')\n",
" \n",
" # implement the specific operation based on the 'operation' argument\n",
" # axis = 1 to specify that the operation should be done for each row (patient)\n",
" if operation == 'mean':\n",
" # YOUR CODE HERE: calculate the mean (average) number of flare-ups for each patient\n",
" # calculate the mean (average) number of flare-ups for each patient\n",
" summary_values = data.mean(axis = 1)\n",
"\n",
" elif operation == 'max':\n",
" # YOUR CODE HERE: calculate the maximum number of flare-ups experienced by each patient\n",
" # calculate the maximum number of flare-ups experienced by each patient\n",
" summary_values = data.max(axis = 1)\n",
"\n",
" elif operation == 'min':\n",
" # YOUR CODE HERE: calculate the minimum number of flare-ups experienced by each patient\n",
" # calculate the minimum number of flare-ups experienced by each patient\n",
" summary_values = data.min(axis = 1)\n",
"\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",
"\n",
" return summary_values"
" #print (summary_values)\n",
" return summary_values\n",
"\n",
"\n",
"#print (len(patient_summary(all_paths[0], \"mean\")))\n",
"#print (len(patient_summary(all_paths[0], \"max\")))\n",
"#print (len(patient_summary(all_paths[0], \"min\")))\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 35,
"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",
Expand Down Expand Up @@ -232,7 +391,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 36,
"metadata": {
"id": "_svDiRkdIwiT"
},
Expand All @@ -255,25 +414,35 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 37,
"metadata": {
"id": "LEYPM5v4JT0i"
},
"outputs": [],
"source": [
"# Define your function `detect_problems` here\n",
"\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"
"# identifies any irregularities in the patient data\n",
"# specifically focusing on detecting patients with a mean inflammation score of 0.\n",
"def detect_problems(file_path): \n",
" \n",
" #Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
" result = patient_summary(file_path, 'mean')\n",
"\n",
" return check_zeros(result)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 38,
"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 True\n",
Expand Down Expand Up @@ -331,7 +500,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.9.15"
}
},
"nbformat": 4,
Expand Down