diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb index 36a3e2bb7..dfe19a3d1 100644 --- a/02_activities/assignments/assignment_2.ipynb +++ b/02_activities/assignments/assignment_2.ipynb @@ -72,11 +72,139 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "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', '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', 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"0,1,2,2,2,3,6,6,6,7,6,3,11,12,13,15,15,10,14,11,11,8,6,12,10,5,12,7,7,11,5,8,5,2,5,5,2,0,2,1\n", + "\n", + "0,0,2,1,3,5,6,7,5,8,9,3,12,10,12,4,12,9,13,10,10,6,10,11,4,15,13,7,3,4,2,9,7,2,4,2,1,2,1,1\n", + "\n", + "0,0,1,2,4,1,5,5,2,3,4,8,8,12,5,15,9,17,7,19,14,18,12,17,14,4,13,13,8,11,5,6,6,2,3,5,2,1,1,1\n", + "\n", + "0,0,0,3,1,3,6,4,3,4,8,3,4,8,3,11,5,7,10,5,15,9,16,17,16,3,8,9,8,3,3,9,5,1,6,5,4,2,2,0\n", + "\n", + "0,1,2,2,2,5,5,1,4,6,3,6,5,9,6,7,4,7,16,7,16,13,9,16,12,6,7,9,10,3,6,4,5,4,6,3,4,3,2,1\n", + "\n", + "0,1,1,2,3,1,5,1,2,2,5,7,6,6,5,10,6,7,17,13,15,16,17,14,4,4,10,10,10,11,9,9,5,4,4,2,1,0,1,0\n", + "\n", + "0,1,0,3,2,4,1,1,5,9,10,7,12,10,9,15,12,13,13,6,19,9,10,6,13,5,13,6,7,2,5,5,2,1,1,1,1,3,0,1\n", + "\n", + "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", + "\n", + "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", + "\n", + "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", + "\n", + "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", + "\n", + "0,0,1,3,1,4,3,6,7,8,5,7,11,3,6,11,6,10,6,19,18,14,6,10,7,9,8,5,8,3,10,2,5,1,5,4,2,1,0,1\n", + "\n", + "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", + "\n", + "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", + "\n", + "0,0,2,3,4,5,4,6,2,9,7,4,9,10,8,11,16,12,15,17,19,10,18,13,15,11,8,4,7,11,6,7,6,5,1,3,1,0,0,0\n", + "\n", + "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", + "\n", + "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", + "\n", + "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", + "\n", + "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", + "\n", + "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", + "\n", + "0,0,0,2,4,4,5,3,3,3,10,4,4,4,14,11,15,13,10,14,11,17,9,11,11,7,10,12,10,10,10,8,7,5,2,2,4,1,2,1\n", + "\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", + "\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", + "\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", + "\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", + "\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", + "\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", + "\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", + "\n" + ] + } + ], "source": [ "all_paths = [\n", " \"../../05_src/data/assignment_2_data/inflammation_01.csv\",\n", @@ -94,9 +222,19 @@ "]\n", "\n", "with open(all_paths[0], 'r') as f:\n", + " \n", " # YOUR CODE HERE: Use the readline() or readlines() method to read the .csv file into a variable\n", + " print (f.readlines ())\n", + " \n", " \n", - " # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection" + "# I opened the file 01.csv into a variabe [as a list]\n", + " \n", + " \n", + " # 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 f:\n", + " for i in range (60):\n", + " print(f. readline())\n", + "# I opened each line for inspection using a for loop" ] }, { @@ -130,7 +268,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "metadata": { "id": "82-bk4CBB1w4" }, @@ -144,35 +282,159 @@ "\n", " # Implement the specific operation based on the 'operation' argument\n", " if operation == 'mean':\n", + " \n", " # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n", - "\n", + " summary_values = data.mean(ax)\n", + " \n", + " \n", " elif operation == 'max':\n", " # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n", + " summary_values = data.max(ax)\n", + "\n", "\n", " elif operation == 'min':\n", " # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n", - "\n", + " summary_values = data.min(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", "\n", - " return summary_values" + " return summary_values\n", + "# explanation: based on the structure you provided and the lectures I defined the variable \"summary_values\" as the outcome of using one of the methods \n", + "# (min, max, mean) on the array \"data\", while ax defined as 1 [row]" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "3TYo0-1SDLrd" - }, - "outputs": [], + "execution_count": 50, + "metadata": {}, + "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[0], 'min')\n", "print(len(data_min))" ] }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([5.45 , 5.425, 6.1 , 5.9 , 5.55 , 6.225, 5.975, 6.65 , 6.625,\n", + " 6.525, 6.775, 5.8 , 6.225, 5.75 , 5.225, 6.3 , 6.55 , 5.7 ,\n", + " 5.85 , 6.55 , 5.775, 5.825, 6.175, 6.1 , 5.8 , 6.425, 6.05 ,\n", + " 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 ,\n", + " 5.925, 7.225, 6.15 , 5.95 , 6.275, 5.7 , 6.1 , 6.825, 5.975,\n", + " 6.725, 5.7 , 6.25 , 6.4 , 7.05 , 5.9 ])" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "patient_summary (all_paths[0], 'mean')\n", + "# I tested my function here to see if it returns \"summary values\" as an array data type with 60 values and corroborated them against the file\n" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " 0., 0., 0., 0., 0., 0., 0., 0., 0.])" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "patient_summary (all_paths[0], 'min')" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([18., 18., 19., 17., 17., 18., 17., 20., 17., 18., 18., 18., 17.,\n", + " 16., 17., 18., 19., 19., 17., 19., 19., 16., 17., 15., 17., 17.,\n", + " 18., 17., 20., 17., 16., 19., 15., 15., 19., 17., 16., 17., 19.,\n", + " 16., 18., 19., 16., 19., 18., 16., 19., 15., 16., 18., 14., 20.,\n", + " 17., 15., 17., 16., 17., 19., 18., 18.])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "patient_summary (all_paths[0], 'max')" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "id": "3TYo0-1SDLrd" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[18., 18., 19., 17.],\n", + " [17., 18., 17., 20.],\n", + " [17., 18., 18., 18.],\n", + " [17., 16., 17., 18.],\n", + " [19., 19., 17., 19.],\n", + " [19., 16., 17., 15.],\n", + " [17., 17., 18., 17.],\n", + " [20., 17., 16., 19.],\n", + " [15., 15., 19., 17.],\n", + " [16., 17., 19., 16.],\n", + " [18., 19., 16., 19.],\n", + " [18., 16., 19., 15.],\n", + " [16., 18., 14., 20.],\n", + " [17., 15., 17., 16.],\n", + " [17., 19., 18., 18.]])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "patient_summary (all_paths[0], 'max').reshape (15,4)\n", + "# here I used an array data type's method [reshape] to organize the max matrix\n" + ] + }, { "cell_type": "markdown", "metadata": { @@ -228,7 +490,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": { "id": "_svDiRkdIwiT" }, @@ -251,7 +513,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 56, "metadata": { "id": "LEYPM5v4JT0i" }, @@ -260,22 +522,73 @@ "# Define your function `detect_problems` here\n", "\n", "def detect_problems(file_path):\n", + " \n", " #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n", - "\n", - " return" + " x = patient_summary (file_path, 'mean')\n", + " if check_zeros (x) == True:\n", + " return True\n", + " else:\n", + " return False\n", + " \n", + " # explanation: I defined x in the same way \"data_mean\" was defined above. Then, based on the explanation you provided on the check_zeros\n", + " # function which returns only boolean values, I defined the conditional." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 57, "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": 58, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True\n" + ] + } + ], + "source": [ + "print(detect_problems(all_paths[1]))\n", + "\n", + "## here I changed all the values in row 60 in \"_02.csv\" to 0, and then test this file to check my function" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n" + ] + } + ], + "source": [ + "print(detect_problems(all_paths[11]))" + ] + }, { "cell_type": "markdown", "metadata": { @@ -314,8 +627,9 @@ "provenance": [] }, "kernelspec": { - "display_name": "Python 3", - "name": "python3" + "display_name": "python-env (3.11)", + "language": "python", + "name": "python-env" }, "language_info": { "codemirror_mode": { @@ -327,7 +641,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.8" + "version": "3.11.13" } }, "nbformat": 4, diff --git a/05_src/data/assignment_2_data/inflammation_02.csv b/05_src/data/assignment_2_data/inflammation_02.csv index e30a9b275..dd01f4134 100644 --- a/05_src/data/assignment_2_data/inflammation_02.csv +++ b/05_src/data/assignment_2_data/inflammation_02.csv @@ -57,4 +57,4 @@ 0,1,0,2,2,1,6,2,2,2,9,5,9,12,5,12,10,13,9,4,17,14,5,10,12,3,13,4,9,8,8,6,7,4,4,5,4,0,2,0 0,0,2,0,4,3,5,5,6,9,4,5,4,3,10,3,7,11,12,10,19,16,17,14,16,9,12,5,10,11,6,7,7,3,3,1,1,0,2,0 0,0,0,3,3,1,5,7,7,7,6,8,7,6,10,14,6,12,5,15,20,18,14,17,14,11,13,10,9,5,5,5,5,7,1,5,3,2,2,0 -0,1,2,0,4,5,6,6,2,5,10,10,3,7,13,9,5,16,6,18,15,10,13,11,12,15,10,12,3,8,8,7,5,6,2,5,2,3,2,0 +0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0