{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Import Dependencies\n", "In this task, the libraries I used are:\n", "* Numpy\n", "* Pandas\n", "* Matplotlib" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# File\n", "For this task, I have snipped specific columns in the \"Optimization Plant\" and make another csv to be read." ] }, { "cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
| \n", " | GUDANG | \n", "BIAYA HANDLING @ CARTON | \n", "ONGKIR-BDG @ CARTON | \n", "ONGKIR-YOGYA @ CARTON | \n", "ONGKIR-MLG @ CARTON | \n", "ONGKIR-JKT @ CARTON | \n", "INDEX_MARGIN AA | \n", "INDEX_MARGIN BB | \n", "INDEX_MARGIN_CC | \n", "Capacity AA | \n", "Capacity BB | \n", "Capacity CC | \n", "
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | \n", "PLANT1 | \n", "1,000 | \n", "2,500 | \n", "1,500 | \n", "2,000 | \n", "2,000 | \n", "50,000 | \n", "45,000 | \n", "60,000 | \n", "15,000 | \n", "20,000 | \n", "12,000 | \n", "
| 1 | \n", "PLANT2 | \n", "1,100 | \n", "2,400 | \n", "1,000 | \n", "2,000 | \n", "2,500 | \n", "50,000 | \n", "50,000 | \n", "70,000 | \n", "22,000 | \n", "15,000 | \n", "15,000 | \n", "
| 2 | \n", "PLANT3 | \n", "1,200 | \n", "1,000 | \n", "3,000 | \n", "2,000 | \n", "3,000 | \n", "60,000 | \n", "45,000 | \n", "55,000 | \n", "20,000 | \n", "10,000 | \n", "27,000 | \n", "