8000 Assignment 2 re-submission by reearmed · Pull Request #211 · UofT-DSI/python · GitHub
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Assignment 2 re-submission #211

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147 changes: 117 additions & 30 deletions 02_activities/assignments/assignment_2.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -72,31 +72,100 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 9,
"metadata": {
"id": "n0m48JsS-nMC"
},
"outputs": [],
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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]
}
],
"source": [
"all_paths = [\n",
" \"python/05_src/data/assignment_2_data/inflammation_01.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_02.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_03.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_04.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_05.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_06.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_07.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_08.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_09.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_10.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_11.csv\",\n",
" \"python/05_src/data/assignment_2_data/inflammation_12.csv\"\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_01.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_02.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_03.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_04.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_05.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_06.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_07.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_08.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_09.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_10.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_11.csv\",\n",
" \"/Users/rehanahmed/python/05_src/data/assignment_2_data/inflammation_12.csv\"\n",
"]\n",
"\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",
" \n",
" # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection"
" lines = f.readlines()\n",
" # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n",
" for line in lines:\n",
" print(line.strip())"
]
},
{
Expand Down Expand Up @@ -130,27 +199,28 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 20,
"metadata": {
"id": "82-bk4CBB1w4"
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"\n",
"def patient_summary(file_path, operation):\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",
" summary_values = np.mean(data, axis=1)\n",
"\n",
" elif operation == 'max':\n",
" # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n",
" summary_values = np.max(data, axis=1)\n",
"\n",
" elif operation == 'min':\n",
" # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n",
" summary_values = np.min(data, axis=1)\n",
"\n",
" else:\n",
" # If the operation is not one of the expected values, raise an error\n",
Expand All @@ -161,11 +231,19 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 21,
"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 @@ -228,7 +306,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 27,
"metadata": {
"id": "_svDiRkdIwiT"
},
Expand All @@ -251,7 +329,7 @@
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 28,
"metadata": {
"id": "LEYPM5v4JT0i"
},
Expand All @@ -260,16 +338,24 @@
"# 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",
" mean_values = patient_summary(file_path, 'mean')\n",
"\n",
" return"
" return check_zeros(mean_values)"
]
},
{
"cell_type": "code",
"execution_count": null,
"execution_count": 29,
"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 +400,8 @@
"provenance": []
},
"kernelspec": {
"display_name": "Python 3",
"display_name": "dsi_participant",
"language": "python",
"name": "python3"
},
"language_info": {
Expand All @@ -327,7 +414,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
"version": "3.9.21"
}
},
"nbformat": 4,
Expand Down
0