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AhmedmouiAhmedmoui
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‎Week_1_data_structures/.OTTER_LOG‎

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‎Week_1_data_structures/Lab_1_data_analysis.ipynb‎

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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 10,
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"metadata": {
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"deletable": false,
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"editable": false
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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": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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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": 15,
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"metadata": {
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"tags": [
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"otter_answer_cell"
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]
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},
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"outputs": [],
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"<>:3: SyntaxWarning: invalid escape sequence '\\S'\n",
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"<>:3: SyntaxWarning: invalid escape sequence '\\S'\n",
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"C:\\Users\\HunterJi\\AppData\\Local\\Temp\\ipykernel_30872\\2403592241.py:3: SyntaxWarning: invalid escape sequence '\\S'\n",
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" clap_data = np.loadtxt(\"Data\\S01C01.csv\", dtype=\"float\", delimiter=\",\")\n"
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]
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}
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],
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"source": [
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"\n",
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"# TODO - put the code to load the data \n",
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"# Make sure you save it into the variable name given - clap_data - or the autograder won't work.\n",
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"clap_data = ..."
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"clap_data = np.loadtxt(\"Data\\S01C01.csv\", dtype=\"float\", delimiter=\",\")"
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]
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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": 16,
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"metadata": {
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"tags": [
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"otter_answer_cell"
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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": 21,
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"metadata": {
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"tags": [
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"otter_answer_cell"
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]
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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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"Number of time steps: 101\n"
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]
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}
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],
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"source": [
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"# TODO\n",
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"# - set the n_time_steps variable. Do NOT just put in a number - use the variable clap_data to calculate this.\n",
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"# - change the print line to print out the number of time steps\n",
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"n_time_steps = ...\n",
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"print(f\"Number of time steps: {}\")"
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"n_time_steps = np.shape(clap_data)[0]\n",
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"print(f\"Number of time steps: {n_time_steps}\")"
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]
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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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"tags": [
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"otter_answer_cell"
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]
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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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"Third column: [11.92438773 12.83811787 12.74563683 18.88675076 15.89095011]\n",
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"How many numbers are above 0.5? 5\n",
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"Sum of array as double 5.0 and integer 5\n"
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]
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}
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],
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"source": [
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"# EXAMPLE CODE\n",
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"# Remember you want all of the rows - that's what the : is for\n",
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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": 25,
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"metadata": {
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"tags": [
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"otter_answer_cell"
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]
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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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"Number of datapoints with positive z: 53\n",
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"Number of datapoints with negative z: 48\n"
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]
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}
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],
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"source": [
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"# TODO - set the variables n_pos_z and n_neg_z and print them out. Do NOT just put in a number - use the variable\n",
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"# clap_data.\n",
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"\n",
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"\n",
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"n_pos_z = ...\n",
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"print(f\"Number of datapoints with positive z: {}\")\n",
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"n_pos_z = np.count_nonzero(clap_data[:,3] > 0) \n",
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"print(f\"Number of datapoints with positive z: {n_pos_z}\")\n",
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"\n",
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"n_neg_z = ...\n",
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"print(f\"Number of datapoints with negative z: {}\")"
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"n_neg_z = np.count_nonzero(clap_data[:,3] < 0) \n",
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"print(f\"Number of datapoints with negative z: {n_neg_z}\")"
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]
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},
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{
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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": "3.11.7"
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"version": "3.12.7"
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},
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"otter": {
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"OK_FORMAT": true,

‎Week_1_data_structures/a_tutorial_numpy.ipynb‎

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"source": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"execution_count": 2,
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"metadata": {},
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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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"Size of csv data (660, 13)\n",
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"Element in first row, first column: -0.766481911\n",
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"Element in first row, second column: 5.317314204\n",
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"Element in second row, first column: -2.597236044\n",
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"Element in last row, last column: 269.9840088\n",
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"Element in third row, last column: 299.9920044\n"
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]
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}
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],
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"source": [
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"# This creates a variable file_name that is a string. You could just put the string into loadtext\n",
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"# instead of creating a variable, but using a variable means you can ask what the filename is later - for example,\n",
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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": "3.9.6"
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"version": "3.12.7"
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}
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},
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"nbformat": 4,

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