From 1bbcee0bba2f387d47f9e3bcc31ed15910aaf49d Mon Sep 17 00:00:00 2001 From: mrf Date: Tue, 2 Sep 2025 21:40:43 -0300 Subject: [PATCH] assignment2 new - updating --- 02_activities/assignments/assignment_2.ipynb | 167 +++++++++++++++++-- 1 file changed, 150 insertions(+), 17 deletions(-) diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb index fd02cc6cc..45ab902f6 100644 --- a/02_activities/assignments/assignment_2.ipynb +++ b/02_activities/assignments/assignment_2.ipynb @@ -72,13 +72,81 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "metadata": { "id": "n0m48JsS-nMC" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "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", + "0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1\n", + 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\"python/05_src/data/assignment_2_data/inflammation_03.csv\",\n", @@ -91,12 +159,34 @@ " \"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", + "#]\n", + "\"\"\"\n", + "# # Absolute path to the inflammation data file \n", + "#r means raw string i.e Treat this string exactly as it's written, don't interpret any escape characters.\n", + "all_paths = [ \n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_01.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_02.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_03.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_04.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_05.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_06.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_07.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_08.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_09.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_10.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\python\\05_src\\data\\assignment_2_data\\inflammation_11.csv\",\n", + " r\"C:\\Users\\mrfst\\DSI7-Task\\python\\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" + " # Read all lines from the file\n", + " lines = f.readlines()\n", + " # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n", + " # Iterate through each line and print it\n", + " for row in lines:\n", + " #print(row)\n", + " print(row.strip()) # strip() removes any extra whitespace or newline characters\n", + " " ] }, { @@ -145,12 +235,18 @@ " # 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", + " # Calculate the mean (average) number of flare-ups for each patient\n", + " summary_values = np.mean(data, axis=1) # axis=1 means calculate along rows (patients)\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 = 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", + " # 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", @@ -165,14 +261,33 @@ "metadata": { "id": "3TYo0-1SDLrd" }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Length of data_min: 60\n", + "First few values: [0. 0. 0. 0. 0. 0.]\n" + ] + } + ], "source": [ + "#\n", "# 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", + "print(f\"Length of data_min: {len(data_min)}\")\n", + "print(f\"First few values: {data_min[:6]}\") # show first few values to verify" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", "metadata": { @@ -228,7 +343,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "metadata": { "id": "_svDiRkdIwiT" }, @@ -251,29 +366,46 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "metadata": { "id": "LEYPM5v4JT0i" }, "outputs": [], "source": [ "# Define your function `detect_problems` here\n", + "#Detects if any patients have a mean inflammation score of 0\n", + "# Returns: bool: True if any patients have mean score of 0 (data issue), otherwise False\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" + " # Use patient_summary() to get the means\n", + " mean_scores = patient_summary(file_path, 'mean')\n", + " # Use check_zeros() to check for zeros in the means\n", + " zeros_found = check_zeros(mean_scores) # \n", + " return zeros_found\n", + " " ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + "False\n" + ] + } + ], "source": [ "# Test out your code here\n", "# Your output for the first file should be False\n", - "print(detect_problems(all_paths[0]))" + "#return bool: True if any patients have mean score of 0 (data issue), otherwise :false\n", + "print(detect_problems(all_paths[0]))\n", + "print(detect_problems(all_paths[1]))" ] }, { @@ -314,7 +446,8 @@ "provenance": [] }, "kernelspec": { - "display_name": "Python 3", + "display_name": "dsi_participant", + "language": "python", "name": "python3" }, "language_info": { @@ -327,7 +460,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.19" } }, "nbformat": 4,