122 lines
2.6 KiB
Plaintext
122 lines
2.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "49839009",
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"metadata": {},
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"source": [
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"# Import dependencies"
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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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"id": "bb8a880c",
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"metadata": {},
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"outputs": [],
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"source": [
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"#!/usr/bin/env python3\n",
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"import pandas as pd\n",
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"from scipy.optimize import linear_sum_assignment\n",
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"import prettytable as pt"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8f2e14e2",
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"metadata": {},
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"source": [
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"# Read data\n",
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"Read the CSV file where I stored Google Form responses. The matrix has been\n",
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"transposed (rows = projects, columns = people) and the Borda count matrix score\n",
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"was evaluated subtracting 1 to poll responses (a score of 0 corresponds to the\n",
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"most desirable assignation)."
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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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"id": "cf13fa73",
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"metadata": {},
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"outputs": [],
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"source": [
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"df = pd.read_csv(\"form_responses.csv\", index_col=0)\n",
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"cost = df.values"
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]
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},
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{
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"cell_type": "markdown",
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"id": "391fd82c",
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"metadata": {},
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"source": [
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"# Solve the assignment problem using scipy"
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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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"id": "7efa127e",
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"metadata": {},
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"outputs": [],
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"source": [
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"row_ind, col_ind = linear_sum_assignment(cost)\n",
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"assignment = pd.DataFrame({\n",
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" \"Project\": df.index[row_ind],\n",
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" \"Assignee\": df.columns[col_ind],\n",
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" \"Cost\": cost[row_ind, col_ind],\n",
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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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"id": "b5e6f5a2",
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"metadata": {},
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"source": [
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"# Show results"
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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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"id": "d4563429",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(\"These are the best assignments:\")\n",
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"assignment[[\"Assignee\", \"Cost\", \"Project\"]].reset_index(drop=True)"
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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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"id": "ac221b1f",
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"metadata": {},
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"outputs": [],
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"source": [
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"print(f\"The total cost of these assignments was {assignment['Cost'].sum()}\")"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "pytorch",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.13.9"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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