diff --git a/02_activities/assignments/assignment_1.ipynb b/02_activities/assignments/assignment_1.ipynb index 156d0408e..8aad59f7f 100644 --- a/02_activities/assignments/assignment_1.ipynb +++ b/02_activities/assignments/assignment_1.ipynb @@ -56,16 +56,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 8, + "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", + " a_list = sorted(word_a.lower())\n", + " b_list = sorted(word_b.lower())\n", + " return a_list == b_list\n", "\n", "# Run your code to check using the words below:\n", - "anagram_checker(\"Silent\", \"listen\")" + "anagram_checker(\"Silent\", \"listen\")\n" ] }, { @@ -73,15 +87,44 @@ "execution_count": null, "metadata": {}, "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "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\")" ] @@ -99,20 +142,49 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "def anagram_checker(word_a, word_b, is_case_sensitive):\n", " # Modify your existing code here\n", - "\n", + " if not is_case_sensitive:\n", + " a_list = sorted(word_a.lower())\n", + " b_list = sorted(word_b.lower())\n", + " return a_list == b_list \n", + " \n", + " else:\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" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "False" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "anagram_checker(\"Silent\", \"Listen\", True) # False" ] @@ -130,7 +202,7 @@ ], "metadata": { "kernelspec": { - "display_name": "new-learner", + "display_name": "dsi_participant", "language": "python", "name": "python3" }, @@ -144,7 +216,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.19" } }, "nbformat": 4, diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb index fd02cc6cc..18922154f 100644 --- a/02_activities/assignments/assignment_2.ipynb +++ b/02_activities/assignments/assignment_2.ipynb @@ -76,27 +76,106 @@ "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", + "\n", + "['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", + "['0', '1', '1', '3', '3', '2', '6', '2', '5', '9', '5', '7', '4', '5', '4', '15', '5', '11', '9', '10', '19', '14', '12', '17', '7', '12', '11', '7', '4', '2', '10', '5', '4', '2', '2', '3', '2', '2', '1', '1']\n", + "['0', '0', '2', '0', '4', '2', '2', '1', '6', '7', '10', '7', '9', '13', '8', '8', '15', '10', '10', '7', '17', '4', '4', '7', '6', '15', '6', '4', '9', '11', '3', '5', '6', '3', '3', '4', '2', '3', '2', '1']\n", + "['0', '1', '1', '3', '3', '1', '3', '5', '2', '4', '4', '7', '6', '5', '3', '10', '8', '10', '6', '17', '9', '14', '9', '7', '13', '9', '12', '6', '7', '7', '9', '6', '3', '2', '2', '4', '2', '0', '1', '1']\n", + "['0', '0', '1', '2', '2', '4', '2', '1', '6', '4', '7', '6', '6', '9', '9', '15', '4', '16', '18', '12', '12', '5', '18', '9', '5', '3', '10', '3', '12', '7', '8', '4', '7', '3', '5', '4', '4', '3', '2', '1']\n", + "['0', '0', '2', '2', '4', '2', '2', '5', '5', '8', '6', '5', '11', '9', '4', '13', '5', '12', '10', '6', '9', '17', '15', '8', '9', '3', '13', '7', '8', '2', '8', '8', '4', '2', '3', '5', '4', '1', '1', '1']\n", + "['0', '0', '1', '2', '3', '1', '2', '3', '5', '3', '7', '8', '8', '5', '10', '9', '15', '11', '18', '19', '20', '8', '5', '13', '15', '10', '6', '10', '6', '7', '4', '9', '3', '5', '2', '5', '3', '2', '2', '1']\n", + "['0', '0', '0', '3', '1', '5', '6', '5', '5', '8', '2', '4', '11', '12', '10', '11', '9', '10', '17', '11', '6', '16', '12', '6', '8', '14', '6', '13', '10', '11', '4', '6', '4', '7', '6', '3', '2', '1', '0', '0']\n", + "['0', '1', '1', '2', '1', '3', '5', '3', '5', '8', '6', '8', '12', '5', '13', '6', '13', '8', '16', '8', '18', '15', '16', '14', '12', '7', '3', '8', '9', '11', '2', '5', '4', '5', '1', '4', '1', '2', '0', '0']\n", + "['0', '1', '0', '0', '4', '3', '3', '5', '5', '4', '5', '8', '7', '10', '13', '3', '7', '13', '15', '18', '8', '15', '15', '16', '11', '14', '12', '4', '10', '10', '4', '3', '4', '5', '5', '3', '3', '2', '2', '1']\n", + "['0', '1', '0', '0', '3', '4', '2', '7', '8', '5', '2', '8', '11', '5', '5', '8', '14', '11', '6', '11', '9', 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'2', '2', '4', '1', '2', '1']\n", + "['0', '0', '2', '1', '1', '4', '4', '7', '2', '9', '4', '10', '12', '7', '6', '6', '11', '12', '9', '15', '15', '6', '6', '13', '5', '12', '9', '6', '4', '7', '7', '6', '5', '4', '1', '4', '2', '2', '2', '1']\n", + "['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", + "['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", + "['0', '1', '1', '2', '2', '5', '1', '7', '4', '2', '5', '5', '4', '6', '6', '4', '16', '11', '14', '16', '14', '14', '8', '17', '4', '14', '13', '7', '6', '3', '7', '7', '5', '6', '3', '4', '2', '2', '1', '1']\n", + "['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", + "['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", + "['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" + ] + } + ], "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import csv\n", + "\n", "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", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_01.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_02.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_03.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_04.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_05.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_06.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_07.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_08.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_09.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_10.csv\",\n", + " \"C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_11.csv\",\n", + " \"C:/Users/NEWPC/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", + " read_line = f.readline() # read just the nex line\n", + " print(read_line)\n", " \n", - " # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection" + " # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n", + "with open(all_paths[0], 'r') as p:\n", + " read_all = csv.reader(p)\n", + " for row in read_all: # we are going to loop each row so that we can have all the elements lsited in trhe csv format like data set\n", + " print(row)" ] }, { @@ -130,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 58, "metadata": { "id": "82-bk4CBB1w4" }, @@ -145,13 +224,13 @@ " # 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", - "\n", + " summary_values = np.mean(data, axis = ax)\n", " elif operation == 'max':\n", " # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n", - "\n", + " summary_values = np.max(data, axis = ax)\n", " elif operation == 'min':\n", " # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n", - "\n", + " summary_values = np.min(data, axis = ax)\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", @@ -161,18 +240,54 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 90, "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", - "data_min = patient_summary(all_paths[0], 'min')\n", + "data_min = patient_summary(all_paths[7], 'min')\n", "print(len(data_min))" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(60,)\n" + ] + }, + { + "data": { + "text/plain": [ + "numpy.ndarray" + ] + }, + "execution_count": 91, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(data_min.shape) # provide the shape of the data\n", + "type(data_min) # this is a numpy array" + ] + }, { "cell_type": "markdown", "metadata": { @@ -228,7 +343,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 66, "metadata": { "id": "_svDiRkdIwiT" }, @@ -261,19 +376,55 @@ "\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" + " \n", + " mean_values = patient_summary(file_path, 'mean') # we assign just the means values to mean_values\n", + " True_equal_0_or_False = check_zeros(mean_values) # we are checking to see if there is any zero mean value: True/False, from above function check_zeros(x)\n", + " return True_equal_0_or_False\n", + " " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_01.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_02.csv\n", + " we have a problem detected in : C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_03.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_04.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_05.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_06.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_07.csv\n", + " we have a problem detected in : C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_08.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_09.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_10.csv\n", + " we have a problem detected in : C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_11.csv\n", + " No problem in: C:/Users/NEWPC/DSI/python/05_src/data/assignment_2_data/inflammation_12.csv\n" + ] + } + ], "source": [ "# Test out your code here\n", "# Your output for the first file should be False\n", - "print(detect_problems(all_paths[0]))" + "print(detect_problems(all_paths[9]))\n", + "\n", + "# we can loop and display list of paths with problem or not:\n", + "\n", + "for path in all_paths:\n", + " if detect_problems(path):\n", + " print(f\" we have a problem detected in : {path}\")\n", + " else:\n", + " print(f\" No problem in: {path}\")\n", + " \n", + "\n", + "\n", + "\n", + "\n" ] }, { @@ -314,7 +465,8 @@ "provenance": [] }, "kernelspec": { - "display_name": "Python 3", + "display_name": "dsi_participant", + "language": "python", "name": "python3" }, "language_info": { @@ -327,7 +479,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.9.19" } }, "nbformat": 4,