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Jesscode-analystJesscode-analyst
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assignment 2 python completed
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‎02_activities/assignments/assignment_2.ipynb‎

Lines changed: 119 additions & 29 deletions
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 22,
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"metadata": {
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"id": "n0m48JsS-nMC"
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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104+
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108+
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109+
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118+
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119+
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120+
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122+
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123+
"0,1,1,3,1,1,5,5,3,7,2,2,3,12,4,6,8,15,16,16,15,4,14,5,13,10,7,10,6,3,2,3,6,3,3,5,4,3,2,1\n",
124+
"0,0,0,2,2,1,3,4,5,5,6,5,5,12,13,5,7,5,11,15,18,7,9,10,14,12,11,9,10,3,2,9,6,2,2,5,3,0,0,1\n",
125+
"0,0,1,3,3,1,2,1,8,9,2,8,10,3,8,6,10,13,11,17,19,6,4,11,6,12,7,5,5,4,4,8,2,6,6,4,2,2,0,0\n",
126+
"0,1,1,3,4,5,2,1,3,7,9,6,10,5,8,15,11,12,15,6,12,16,6,4,14,3,12,9,6,11,5,8,5,5,6,1,2,1,2,0\n",
127+
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128+
"0,1,1,3,3,4,4,6,3,4,9,9,7,6,8,15,12,15,6,11,6,18,5,14,15,12,9,8,3,6,10,6,8,7,2,5,4,3,1,1\n",
129+
"0,1,2,2,4,3,1,4,8,9,5,10,10,3,4,6,7,11,16,6,14,9,11,10,10,7,10,8,8,4,5,8,4,4,5,2,4,1,1,0\n",
130+
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131+
"0,1,1,3,1,4,6,2,8,2,10,3,11,9,13,15,5,15,6,10,10,5,14,15,12,7,4,5,11,4,6,9,5,6,1,1,2,1,2,1\n",
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"0,0,1,3,2,5,1,2,7,6,6,3,12,9,4,14,4,6,12,9,12,7,11,7,16,8,13,6,7,6,10,7,6,3,1,5,4,3,0,0\n",
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"0,0,1,2,3,4,5,7,5,4,10,5,12,12,5,4,7,9,18,16,16,10,15,15,10,4,3,7,5,9,4,6,2,4,1,4,2,2,2,1\n",
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"0,1,2,1,1,3,5,3,6,3,10,10,11,10,13,10,13,6,6,14,5,4,5,5,9,4,12,7,7,4,7,9,3,3,6,3,4,1,2,0\n",
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"0,1,2,2,3,5,2,4,5,6,8,3,5,4,3,15,15,12,16,7,20,15,12,8,9,6,12,5,8,3,8,5,4,1,3,2,1,3,1,0\n",
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"0,1,2,1,1,4,5,4,4,5,9,7,10,3,13,13,8,9,17,16,16,15,12,13,5,12,10,9,11,9,4,5,5,2,2,5,1,0,0,1\n",
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"0,0,1,3,2,3,6,4,5,7,2,4,11,11,3,8,8,16,5,13,16,5,8,8,6,9,10,10,9,3,3,5,3,5,4,5,3,3,0,1\n",
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"0,1,1,1,4,1,6,4,6,3,6,5,6,4,14,13,13,9,12,19,9,10,15,10,9,10,10,7,5,6,8,6,6,4,3,5,2,1,1,1\n",
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"0,0,0,1,4,5,6,3,8,7,9,10,8,6,5,12,15,5,10,5,8,13,18,17,14,9,13,4,10,11,10,8,8,6,5,5,2,0,2,0\n",
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"0,0,1,0,3,2,5,4,8,2,9,3,3,10,12,9,14,11,13,8,6,18,11,9,13,11,8,5,5,2,8,5,3,5,4,1,3,1,1,0\n"
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]
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}
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],
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"source": [
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"all_paths = [\n",
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" \"python/05_src/data/assignment_2_data/inflammation_01.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_02.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_03.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_04.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_05.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_06.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_07.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_08.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_09.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_10.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_11.csv\",\n",
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" \"python/05_src/data/assignment_2_data/inflammation_12.csv\"\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_01.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_02.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_03.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_04.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_05.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_06.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_07.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_08.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_09.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_10.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_11.csv\",\n",
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" \"C:/users/jsphy/python/05_src/data/assignment_2_data/inflammation_12.csv\"\n",
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"]\n",
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"\n",
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"with open(all_paths[0], 'r') as f:\n",
97164
" # YOUR CODE HERE: Use the readline() or readlines() method to read the .csv file into a variable\n",
98-
" \n",
99-
" # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection"
165+
" lines = f.readlines()\n",
166+
" # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n",
167+
"for line in lines:\n",
168+
" print(line.strip()) \n"
100169
]
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},
102171
{
@@ -130,7 +199,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 23,
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"metadata": {
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"id": "82-bk4CBB1w4"
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},
@@ -145,13 +214,13 @@
145214
" # Implement the specific operation based on the 'operation' argument\n",
146215
" if operation == 'mean':\n",
147216
" # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n",
148-
"\n",
217+
" summary_values = data.mean(axis=ax) \n",
149218
" elif operation == 'max':\n",
150219
" # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n",
151-
"\n",
220+
" summary_values = data.max(axis=ax) \n",
152221
" elif operation == 'min':\n",
153222
" # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n",
154-
"\n",
223+
" summary_values = data.min(axis=ax)\n",
155224
" else:\n",
156225
" # If the operation is not one of the expected values, raise an error\n",
157226
" raise ValueError(\"Invalid operation. Please choose 'mean', 'max', or 'min'.\")\n",
@@ -161,11 +230,19 @@
161230
},
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{
163232
"cell_type": "code",
164-
"execution_count": null,
233+
"execution_count": 24,
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"metadata": {
166235
"id": "3TYo0-1SDLrd"
167236
},
168-
"outputs": [],
237+
"outputs": [
238+
{
239+
"name": "stdout",
240+
"output_type": "stream",
241+
"text": [
242+
"60\n"
243+
]
244+
}
245+
],
169246
"source": [
170247
"# Test it out on the data file we read in and make sure the size is what we expect i.e., 60\n",
171248
"# Your output for the first file should be 60\n",
@@ -228,7 +305,7 @@
228305
},
229306
{
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"cell_type": "code",
231-
"execution_count": null,
308+
"execution_count": 25,
232309
"metadata": {
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"id": "_svDiRkdIwiT"
234311
},
@@ -261,18 +338,30 @@
261338
"\n",
262339
"def detect_problems(file_path):\n",
263340
" #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
264-
"\n",
265-
" return"
341+
" # mean inflammation scores for all patients\n",
342+
" mean_inflammations = patient_summary(file_path, 'mean')\n",
343+
" #Check if any mean score is zero\n",
344+
" problem_exists = check_zeros(mean_inflammations)\n",
345+
" return problem_exists"
266346
]
267347
},
268348
{
269349
"cell_type": "code",
270-
"execution_count": null,
350+
"execution_count": 27,
271351
"metadata": {},
272-
"outputs": [],
352+
"outputs": [
353+
{
354+
"name": "stdout",
355+
"output_type": "stream",
356+
"text": [
357+
"False\n"
358+
]
359+
}
360+
],
273361
"source": [
274362
"# Test out your code here\n",
275363
"# Your output for the first file should be False\n",
364+
"\n",
276365
"print(detect_problems(all_paths[0]))"
277366
]
278367
},
@@ -314,7 +403,8 @@
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"provenance": []
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},
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"kernelspec": {
317-
"display_name": "Python 3",
406+
"display_name": "dsi_participant",
407+
"language": "python",
318408
"name": "python3"
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},
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"language_info": {
@@ -327,7 +417,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.8"
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"version": "3.9.19"
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}
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},
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"nbformat": 4,

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