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Commit 1acba39

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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"name": "Measure_of_Center.ipynb",
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"version": "0.3.2",
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"provenance": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "gmHVVuCdiHnl",
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"colab_type": "text"
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},
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"source": [
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"# Measure of Center\n",
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"\n",
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"---\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "Cs6hAcU2h5NT",
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"colab_type": "code",
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"colab": {}
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},
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"source": [
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"import numpy as np\n",
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"x=[2,4,6,7,20,10,22]\n",
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"y=np.array(x)"
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],
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"execution_count": 0,
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"outputs": []
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "v0B8j5IsiDL7",
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"colab_type": "text"
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},
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"source": [
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"# Mean:\n",
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"\n",
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"---\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "oYOWjwMviCLm",
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"colab_type": "code",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 34
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},
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"outputId": "1a7c27be-63e3-4423-cfad-da76e679bf10"
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},
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"source": [
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"print(\"Mean is : \",y.mean())"
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],
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"execution_count": 3,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Mean is : 10.142857142857142\n"
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],
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"name": "stdout"
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}
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "0IpYCciHiQKX",
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"colab_type": "text"
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},
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"source": [
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"# Median:\n",
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"\n",
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"---\n",
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"\n"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "ZRjbvMUoiM9U",
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"colab_type": "code",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 34
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},
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"outputId": "4ee89fc5-f940-4595-afd3-d95b90ac2663"
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},
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"source": [
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"print(\"Median is : \",np.median(y))"
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],
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"execution_count": 4,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Median is : 7.0\n"
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],
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"name": "stdout"
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}
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "Q3hBUZmEiYCh",
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"colab_type": "text"
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},
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"source": [
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"# Mode:\n",
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"\n",
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"---\n"
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]
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},
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{
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"cell_type": "code",
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"metadata": {
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"id": "k-wIC7j_iPdR",
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"colab_type": "code",
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"colab": {
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"base_uri": "https://localhost:8080/",
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"height": 34
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},
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"outputId": "1cb99ae2-a249-4b9a-ab13-f344cd7dc583"
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},
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"source": [
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"from statistics import mode\n",
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"print(\"Mode is:\",mode([1, 1, 2, 3, 3, 3, 3, 4]))"
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],
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"execution_count": 5,
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"outputs": [
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{
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"output_type": "stream",
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"text": [
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"Mode is: 3\n"
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],
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"name": "stdout"
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}
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]
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}
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]
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}
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import numpy as np
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x=[2,4,6,7,20,10,22]
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y=np.array(x)
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print("Mean is : ",y.mean())
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print("Median is : ",np.median(y))
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print("\n")
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print("Mean is : ",y.mean())
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print("\n")
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from statistics import mode
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print("Mode is:",mode([1, 1, 2, 3, 3, 3, 3, 4]))

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