From 7691d81767a4fc439af31484a1564b69b9ba12e2 Mon Sep 17 00:00:00 2001 From: greg-antono Date: Sun, 16 Feb 2025 09:46:31 -0500 Subject: [PATCH 1/2] Code added to assignment --- 02_activities/assignments/assignment_1.ipynb | 85 ++++++++++++++++---- 1 file changed, 71 insertions(+), 14 deletions(-) diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb index 712158a61..d7897d6f9 100644 --- a/02_activities/assignments/assignment_1.ipynb +++ b/02_activities/assignments/assignment_1.ipynb @@ -56,13 +56,24 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# For testing purposes, we will write our code in the function\n", "def anagram_checker(word_a, word_b):\n", - " # Your code here\n", + " return sorted(word_a.lower()) == sorted(word_b.lower()) #convert to lowercase so as to by-pass case-sensitivity\n", "\n", "# Run your code to check using the words below:\n", "anagram_checker(\"Silent\", \"listen\")" @@ -70,18 +81,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"Silent\", \"Night\")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"night\", \"Thing\")" ] @@ -97,12 +130,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def anagram_checker(word_a, word_b, is_case_sensitive):\n", - " # Modify your existing code here\n", + " if not is_case_sensitive: # e.g. when case sensitivity is False, convert all to lowercase to compare\n", + " word_a, word_b = word_a.lower(), word_b.lower() # otherwise, take letters from the string as-is, sort and compare\n", + " return sorted(word_a) == sorted(word_b)\n", "\n", "# Run your code to check using the words below:\n", "anagram_checker(\"Silent\", \"listen\", False) # True" @@ -110,9 +156,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"Silent\", \"Listen\", True) # False" ] @@ -130,7 +187,7 @@ ], "metadata": { "kernelspec": { - "display_name": "new-learner", + "display_name": "dsi_participant", "language": "python", "name": "python3" }, @@ -144,7 +201,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.21" } }, "nbformat": 4, From f20f783e470b7aa315b72eb12125faf70126976a Mon Sep 17 00:00:00 2001 From: greg-antono Date: Sun, 2 Mar 2025 18:20:48 -0500 Subject: [PATCH 2/2] Code added to Assignment 2 --- 02_activities/assignments/assignment_2.ipynb | 258 ++++++++++++++++--- 1 file changed, 227 insertions(+), 31 deletions(-) diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb index b4a53186c..0604db82a 100644 --- a/02_activities/assignments/assignment_2.ipynb +++ b/02_activities/assignments/assignment_2.ipynb @@ -72,31 +72,160 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "id": 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\"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/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_01.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_02.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_03.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_04.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_05.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_06.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_07.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_08.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_09.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_10.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/python/05_src/data/assignment_2_data/inflammation_11.csv\",\n", + " \"/Users/gregantono/Desktop/DSI/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", + " inflammadata = f.readlines() # 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" + " # Iterate through the variable using a for loop and print each row for inspection\n", + "for row in inflammadata: # Prints all the rows; tested with inflammadata[:5] to start\n", + " print(row)\n" ] }, { @@ -130,7 +259,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": { "id": "82-bk4CBB1w4" }, @@ -144,13 +273,13 @@ "\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=ax) #Calculate the mean (average) number of flare-ups for each patient\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=ax) # Calculate the maximum number of flare-ups experienced by each patient\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=ax) # Calculate the minimum number of flare-ups experienced by each patient\n", "\n", " else:\n", " # If the operation is not one of the expected values, raise an error\n", @@ -161,11 +290,19 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "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", @@ -173,6 +310,30 @@ "print(len(data_min))" ] }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[5.45 5.425 6.1 5.9 5.55 6.225 5.975 6.65 6.625 6.525 6.775 5.8\n", + " 6.225 5.75 5.225 6.3 6.55 5.7 5.85 6.55 5.775 5.825 6.175 6.1\n", + " 5.8 6.425 6.05 6.025 6.175 6.55 6.175 6.35 6.725 6.125 7.075 5.725\n", + " 5.925 6.15 6.075 5.75 5.975 5.725 6.3 5.9 6.75 5.925 7.225 6.15\n", + " 5.95 6.275 5.7 6.1 6.825 5.975 6.725 5.7 6.25 6.4 7.05 5.9 ]\n", + "Total number of participants: 60\n" + ] + } + ], + "source": [ + "data_mean = patient_summary(all_paths[0], 'mean') # just checking with the means\n", + "print(data_mean)\n", + "print(\"Total number of participants:\", len(data_mean))" + ] + }, { "cell_type": "markdown", "metadata": { @@ -228,7 +389,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": { "id": "_svDiRkdIwiT" }, @@ -251,7 +412,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": { "id": "LEYPM5v4JT0i" }, @@ -260,22 +421,56 @@ "# 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" + " # Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n", + " patient_means = patient_summary(file_path, 'mean')\n", + "# check for means = zero\n", + " return check_zeros(patient_means)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "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", "print(detect_problems(all_paths[0]))" ] }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[4. 4.225 3.9 3.7 4.075 3.95 4.55 3.45 3.975 4.525 4.425 4.225\n", + " 3.85 4.925 4.5 3.225 4.4 4.275 4.5 4.125 4.7 5.9 3.975 4.\n", + " 5.275 4.075 4.475 3.7 3.775 3.7 3.925 4.525 4.125 4.025 4.1 4.675\n", + " 5.025 4.9 4.7 4.75 3.975 5.325 3.925 4.4 4.35 4.65 4.1 4.\n", + " 4.4 4.575 3.9 4.65 3.725 4. 4. 5.2 4.325 3.575 4.075 0. ]\n", + "True\n" + ] + } + ], + "source": [ + "# Checking with a different file with a different result: file 3's last patient should be flagged.\n", + "\n", + "print(patient_summary(all_paths[2], 'mean'))\n", + "print(detect_problems(all_paths[2])) \n" + ] + }, { "cell_type": "markdown", "metadata": { @@ -314,7 +509,8 @@ "provenance": [] }, "kernelspec": { - "display_name": "Python 3", + "display_name": "dsi_participant", + "language": "python", "name": "python3" }, "language_info": { @@ -327,7 +523,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.21" } }, "nbformat": 4,