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May 15, 2021 10:38
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| { | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Import Packages" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 3, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "import statistics\n", | |
| "import numpy as np" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Sample Data" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 4, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [ | |
| "data = [1,2,4,5,6,76,8,45]" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Using Formula without Python Packages\n", | |
| "\n", | |
| "If number of elements = odd -------> n/2\n", | |
| "\n", | |
| "If number of elements = even ------> (n+1)/2\n", | |
| "\n", | |
| "We can't use the (n+1)/2 exactly in coding. Because finding the position using float values gets error.\n", | |
| "So, I am slightly changing the formula for Even.\n", | |
| "\n", | |
| "m1 = (n/2)th position\n", | |
| "\n", | |
| "m2 = ((n/2) - 1) th position\n", | |
| "\n", | |
| "Median = (m1 + m2)/2\n", | |
| "\n" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 34, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "Sorted Data: [1, 2, 4, 5, 6, 8, 45, 76]\n", | |
| "Position of the data: 4 and 3\n", | |
| "Values in the Position: 6 and 5\n", | |
| "Median: 5.5\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "sorted_data_median = sorted(data)\n", | |
| "\n", | |
| "print(\"Sorted Data:\", sorted_data_median)\n", | |
| "\n", | |
| "m1 = int(len(sorted_data_median)/ 2)\n", | |
| "m2 = int((m1 - 1))\n", | |
| "\n", | |
| "print(f\"Position of the data: {m1} and {m2}\")\n", | |
| "print(f\"Values in the Position: {sorted_data_median[m1]} and {sorted_data_median[m2]}\")\n", | |
| "\n", | |
| "median = (sorted_data_median[m1] + sorted_data_median[m2])/2\n", | |
| "\n", | |
| "print(\"Median:\", median)" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Using numpy package" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 10, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "5.5\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print(np.median(data))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "markdown", | |
| "metadata": {}, | |
| "source": [ | |
| "### Using Statistics package" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": 9, | |
| "metadata": {}, | |
| "outputs": [ | |
| { | |
| "name": "stdout", | |
| "output_type": "stream", | |
| "text": [ | |
| "5.5\n" | |
| ] | |
| } | |
| ], | |
| "source": [ | |
| "print(statistics.median(data))" | |
| ] | |
| }, | |
| { | |
| "cell_type": "code", | |
| "execution_count": null, | |
| "metadata": {}, | |
| "outputs": [], | |
| "source": [] | |
| } | |
| ], | |
| "metadata": { | |
| "kernelspec": { | |
| "display_name": "Python 3", | |
| "language": "python", | |
| "name": "python3" | |
| }, | |
| "language_info": { | |
| "codemirror_mode": { | |
| "name": "ipython", | |
| "version": 3 | |
| }, | |
| "file_extension": ".py", | |
| "mimetype": "text/x-python", | |
| "name": "python", | |
| "nbconvert_exporter": "python", | |
| "pygments_lexer": "ipython3", | |
| "version": "3.7.4" | |
| } | |
| }, | |
| "nbformat": 4, | |
| "nbformat_minor": 4 | |
| } |
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median notebook file