2023-01-12 16:13:39 +02:00
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{
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"cells": [
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{
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"cell_type": "code",
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2023-01-12 21:45:54 +02:00
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"execution_count": 1,
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2023-01-12 20:25:12 +02:00
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"id": "41405f3d",
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2023-01-12 16:13:39 +02:00
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"metadata": {},
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"outputs": [],
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"source": [
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"from matplotlib import pyplot as plt\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "markdown",
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2023-01-12 20:25:12 +02:00
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"id": "dfc88764",
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"metadata": {},
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"source": [
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"## General conversions \n",
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"\n",
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"Conversions\n",
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"\n",
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"Sunflower Seeds, sunflower seed kernels, dried\n",
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"584kcal/100g\n",
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"https://fdc.nal.usda.gov/fdc-app.html#/food-details/170562/nutrients\n",
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"FDC ID: 170562\n",
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"USDA Unit LB/acre\n",
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" \n",
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"Potatoes, flesh and skin, raw\n",
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"https://fdc.nal.usda.gov/fdc-app.html#/food-details/170026/nutrients\n",
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"77kcal/100g\n",
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"FDC ID: 170026 \n",
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"USDA Unit CWT/acre\n",
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"1 CWT = 100lbs\n",
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" \n",
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"Wheat, hard red winter\n",
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"FDC ID: 168890\n",
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"327kcal/100g\n",
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"https://fdc.nal.usda.gov/fdc-app.html#/food-details/168890/nutrients\n",
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"USDA Unit BU/acre\n",
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"60lb / BU https://www.plainsgrains.org/wp-content/uploads/2018/10/2017-HRWW-Report__HiRes-FINAL.pdf\n",
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"\n",
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"Corn grain, yellow\n",
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"365kcal/100g\n",
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"https://fdc.nal.usda.gov/fdc-app.html#/food-details/170288/nutrients\n",
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"FDC ID: 170288 \n",
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"USDA Unit BU/acre\n",
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"Shelled, 56lbs/BU\n",
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"\n",
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"Soybeans, mature seeds, raw\n",
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"446kcal/100g\n",
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"https://fdc.nal.usda.gov/fdc-app.html#/food-details/174270/nutrients\n",
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"FDC ID: 174270 \n",
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"USDA Unit BU/acre\n",
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"60LB/BU https://soybeanresearchinfo.com/research-highlight/exploring-the-impact-of-genetics-on-soybean-test-weight\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "72029669",
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2023-01-12 16:13:39 +02:00
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"metadata": {},
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"source": [
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"## Corn"
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]
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},
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{
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"cell_type": "code",
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2023-01-12 21:45:54 +02:00
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"execution_count": 2,
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2023-01-12 20:25:12 +02:00
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"id": "116f0267",
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2023-01-12 16:13:39 +02:00
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"metadata": {},
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2023-01-12 21:45:54 +02:00
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([[ nan, 2022. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 172.3, nan],\n",
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" [ nan, 2021. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 176.7, nan],\n",
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" [ nan, 2020. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 171.4, nan]])"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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2023-01-12 16:13:39 +02:00
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"source": [
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"csv=np.genfromtxt ('./data/corn.csv',\n",
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" skip_header=1,\n",
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" delimiter=\",\")\n",
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"csv[0:3]\n",
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"#csv[0:3].astype(float)"
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]
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},
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{
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"cell_type": "code",
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2023-01-12 21:45:54 +02:00
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"execution_count": 3,
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2023-01-12 20:25:12 +02:00
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"id": "0db69a97",
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2023-01-12 16:13:39 +02:00
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"metadata": {},
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"outputs": [],
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"source": [
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"corn_year=csv[:,1]\n",
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2023-01-12 20:25:12 +02:00
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"corn_bu_per_acre=csv[:,-2]\n",
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"\n",
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"grams_per_lbs=453.592\n",
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"corn_lbs_per_bu=(56.0/1.0)\n",
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"corn_kcal_per_gram=(365/100)\n",
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"corn_kcal_per_acre = corn_bu_per_acre*corn_lbs_per_bu*grams_per_lbs*corn_kcal_per_gram"
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2023-01-12 16:13:39 +02:00
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]
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},
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{
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"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
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"execution_count": 4,
|
2023-01-12 20:25:12 +02:00
|
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"id": "eb375958",
|
2023-01-12 16:13:39 +02:00
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"metadata": {},
|
2023-01-12 21:45:54 +02:00
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"outputs": [
|
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{
|
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"data": {
|
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"text/plain": [
|
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"<matplotlib.legend.Legend at 0x2a58376dc70>"
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]
|
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},
|
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
|
2023-01-12 20:25:12 +02:00
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"source": [
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"plt.plot(corn_year,corn_bu_per_acre,\"o\",label=\"corn\")\n",
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"plt.xlabel(\"time (calendar year)\")\n",
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"plt.ylabel(\"Corn, bu/acre\")\n",
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"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
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"plt.legend()\n",
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"\n",
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"#plt.show()\n",
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|
|
"#plt.savefig(\"bear-quadratic.pdf\")"
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]
|
2023-01-12 16:13:39 +02:00
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},
|
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{
|
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"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
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|
"execution_count": 5,
|
2023-01-12 20:25:12 +02:00
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|
"id": "9c6ffb7f",
|
2023-01-12 16:13:39 +02:00
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"metadata": {},
|
2023-01-12 21:45:54 +02:00
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"outputs": [
|
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|
{
|
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"data": {
|
|
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|
|
"text/plain": [
|
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|
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|
"<matplotlib.legend.Legend at 0x2a584089a00>"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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2023-01-12 16:13:39 +02:00
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"source": [
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2023-01-12 20:25:12 +02:00
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"plt.plot(corn_year,corn_kcal_per_acre,\"o\",label=\"corn\")\n",
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2023-01-12 16:13:39 +02:00
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"plt.xlabel(\"time (calendar year)\")\n",
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2023-01-12 20:25:12 +02:00
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"plt.ylabel(\"kcal/acre\")\n",
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2023-01-12 16:13:39 +02:00
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"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
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"plt.legend()\n",
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"\n",
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"#plt.show()\n",
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"#plt.savefig(\"bear-quadratic.pdf\")"
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]
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},
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{
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"cell_type": "markdown",
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2023-01-12 20:25:12 +02:00
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"id": "fa891f0e",
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"metadata": {},
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"source": [
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"## Wheat"
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]
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},
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{
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"cell_type": "code",
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2023-01-12 21:45:54 +02:00
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"execution_count": 6,
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2023-01-12 20:25:12 +02:00
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"id": "263ea341",
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"metadata": {},
|
2023-01-12 21:45:54 +02:00
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"outputs": [
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{
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"data": {
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"text/plain": [
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|
|
|
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"array([[ nan, 2022. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 46.5, nan],\n",
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" [ nan, 2021. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 44.3, nan],\n",
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" [ nan, 2020. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 49.7, nan]])"
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]
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},
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|
"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
|
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|
|
],
|
2023-01-12 20:25:12 +02:00
|
|
|
"source": [
|
|
|
|
|
"csv=np.genfromtxt ('./data/wheat.csv',\n",
|
|
|
|
|
" skip_header=1,\n",
|
|
|
|
|
" delimiter=\",\")\n",
|
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|
|
"csv[0:3]\n",
|
|
|
|
|
"#csv[0:3].astype(float)"
|
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|
|
]
|
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|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 7,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "5aa38243",
|
|
|
|
|
"metadata": {},
|
|
|
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|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"wheat_year=csv[:,1]\n",
|
|
|
|
|
"wheat_bu_per_acre=csv[:,-2]\n",
|
|
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|
"\n",
|
|
|
|
|
"wheat_lbs_per_bu=60\n",
|
|
|
|
|
"#grams_per_lbs\n",
|
|
|
|
|
"wheat_kcal_per_gram=327.0/100.0\n",
|
|
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|
"\n",
|
|
|
|
|
"wheat_kcal_per_acre=wheat_bu_per_acre*wheat_lbs_per_bu*grams_per_lbs*wheat_kcal_per_gram"
|
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|
]
|
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|
|
},
|
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|
{
|
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|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 8,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "5dd77124",
|
|
|
|
|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
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|
"outputs": [
|
|
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|
|
{
|
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
|
2023-01-12 20:25:12 +02:00
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"source": [
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"plt.plot(corn_year,corn_bu_per_acre,\"o\",label=\"Corn (BU/ACRE)\")\n",
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"plt.plot(wheat_year,wheat_bu_per_acre,\"x\",label=\"Wheat (BU/ACRE)\")\n",
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"plt.xlabel(\"time (calendar year)\")\n",
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"plt.ylabel(\"Average per acre production\")\n",
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"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
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"plt.legend()\n",
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"plt.yscale(\"log\")\n",
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"#plt.show()\n",
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"#plt.savefig(\"bear-quadratic.pdf\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "89c8f489",
|
2023-01-12 16:13:39 +02:00
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"metadata": {},
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"source": [
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|
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"## Potatoes"
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|
]
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},
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{
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"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
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|
"execution_count": 9,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "c31828d0",
|
2023-01-12 16:13:39 +02:00
|
|
|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
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|
"outputs": [
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|
|
{
|
|
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|
"data": {
|
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|
"text/plain": [
|
|
|
|
|
"array([[ nan, 2022., nan, nan, nan, nan, nan, nan, nan,\n",
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|
" nan, nan, nan, nan, 0., nan, nan, nan, nan,\n",
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" 438., nan],\n",
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" [ nan, 2021., nan, nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, 0., nan, nan, nan, nan,\n",
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|
" 444., nan],\n",
|
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" [ nan, 2020., nan, nan, nan, nan, nan, nan, nan,\n",
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|
" nan, nan, nan, nan, 0., nan, nan, nan, nan,\n",
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" 461., nan]])"
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]
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},
|
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|
"execution_count": 9,
|
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"metadata": {},
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"output_type": "execute_result"
|
|
|
|
|
}
|
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|
|
],
|
2023-01-12 16:13:39 +02:00
|
|
|
"source": [
|
|
|
|
|
"csv=np.genfromtxt ('./data/potatoes.csv',\n",
|
|
|
|
|
" skip_header=1,\n",
|
|
|
|
|
" delimiter=\",\")\n",
|
|
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|
|
"csv[0:3]\n",
|
|
|
|
|
"#csv[0:3].astype(float)"
|
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|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 10,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "86091fed",
|
2023-01-12 16:13:39 +02:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"potatoes_year=csv[:,1]\n",
|
2023-01-12 20:25:12 +02:00
|
|
|
"potatoes_cwt_per_acre=csv[:,-2]\n",
|
|
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|
|
"\n",
|
|
|
|
|
"lbs_per_cwt=100\n",
|
|
|
|
|
"#grams_per_lbs\n",
|
|
|
|
|
"potatoes_kcal_per_gram=77.0/100.0\n",
|
|
|
|
|
"potatoes_kcal_per_acre=potatoes_cwt_per_acre*lbs_per_cwt*grams_per_lbs*potatoes_kcal_per_gram"
|
2023-01-12 16:13:39 +02:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 11,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "5ea8b2ac",
|
2023-01-12 16:13:39 +02:00
|
|
|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
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|
"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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2023-01-12 20:25:12 +02:00
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"source": [
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"plt.plot(corn_year,corn_bu_per_acre,\"o\",label=\"Corn (BU/ACRE)\")\n",
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"plt.plot(wheat_year,wheat_bu_per_acre,\"x\",label=\"Wheat (BU/ACRE)\")\n",
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"plt.plot(potatoes_year,potatoes_cwt_per_acre,\"+\",label=\"Potatoes (CWT / ACRE)\")\n",
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"plt.xlabel(\"time (calendar year)\")\n",
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"plt.ylabel(\"Average per acre production\")\n",
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"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
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"plt.legend()\n",
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"plt.yscale(\"log\")\n",
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"#plt.show()\n",
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"#plt.savefig(\"bear-quadratic.pdf\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0201b588",
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"metadata": {},
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"source": [
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"## Soybeans"
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]
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2023-01-12 16:13:39 +02:00
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},
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{
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"cell_type": "code",
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2023-01-12 21:45:54 +02:00
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"execution_count": 12,
|
2023-01-12 20:25:12 +02:00
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"id": "ce223c5b",
|
2023-01-12 16:13:39 +02:00
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"metadata": {},
|
2023-01-12 21:45:54 +02:00
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"outputs": [
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{
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|
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"data": {
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|
"text/plain": [
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|
|
|
|
"array([[ nan, 2022. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 50.2, nan],\n",
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" [ nan, 2021. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 51.7, nan],\n",
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" [ nan, 2020. , nan, nan, nan, nan, nan, nan,\n",
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" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 51. , nan]])"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
|
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|
|
],
|
2023-01-12 16:13:39 +02:00
|
|
|
"source": [
|
2023-01-12 20:25:12 +02:00
|
|
|
"csv=np.genfromtxt ('./data/soybeans.csv',\n",
|
|
|
|
|
" skip_header=1,\n",
|
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|
|
|
" delimiter=\",\")\n",
|
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|
"csv[0:3]\n",
|
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|
"#csv[0:3].astype(float)"
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|
]
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},
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|
{
|
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|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 13,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "12fe395c",
|
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|
"metadata": {},
|
|
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|
"outputs": [],
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|
|
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|
"source": [
|
|
|
|
|
"soybeans_year=csv[:,1]\n",
|
2023-01-12 21:45:54 +02:00
|
|
|
"soybeans_bu_per_acre=csv[:,-2]\n",
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|
"\n",
|
|
|
|
|
"soybeans_lbs_per_bu=60\n",
|
|
|
|
|
"#grams_per_lbs\n",
|
|
|
|
|
"soybeans_kcal_per_gram=446.0/100.0\n",
|
|
|
|
|
"soybeans_kcal_per_acre=soybeans_bu_per_acre*soybeans_lbs_per_bu*grams_per_lbs*soybeans_kcal_per_gram"
|
2023-01-12 20:25:12 +02:00
|
|
|
]
|
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|
},
|
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{
|
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|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
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|
"execution_count": 14,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "ae3f6ad4",
|
|
|
|
|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
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"outputs": [
|
|
|
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|
{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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2023-01-12 20:25:12 +02:00
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"source": [
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"plt.plot(corn_year,corn_bu_per_acre,\"o\",label=\"Corn (BU/ACRE)\")\n",
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"plt.plot(wheat_year,wheat_bu_per_acre,\"x\",label=\"Wheat (BU/ACRE)\")\n",
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"plt.plot(potatoes_year,potatoes_cwt_per_acre,\"+\",label=\"Potatoes (CWT / ACRE)\")\n",
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"plt.plot(soybeans_year,soybeans_bu_per_acre,\"*\",label=\"Soybeans (BU/ACRE)\")\n",
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2023-01-12 16:13:39 +02:00
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"plt.xlabel(\"time (calendar year)\")\n",
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2023-01-12 20:25:12 +02:00
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"plt.ylabel(\"Average per acre production\")\n",
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2023-01-12 16:13:39 +02:00
|
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"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
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"plt.legend()\n",
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2023-01-12 20:25:12 +02:00
|
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"plt.yscale(\"log\")\n",
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"#plt.show()\n",
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"#plt.savefig(\"bear-quadratic.pdf\")"
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]
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},
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{
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"cell_type": "markdown",
|
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"id": "c68984fa",
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"metadata": {},
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"source": [
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|
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"## Sugarbeets"
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|
]
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},
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{
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"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
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"execution_count": 15,
|
2023-01-12 20:25:12 +02:00
|
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|
"id": "6e74b0b8",
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"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
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|
"outputs": [
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|
|
|
{
|
|
|
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|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"array([[ nan, 2022. , nan, nan, nan, nan, nan, nan,\n",
|
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|
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|
" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
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" nan, nan, 29.1, nan],\n",
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" [ nan, 2021. , nan, nan, nan, nan, nan, nan,\n",
|
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|
" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
|
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|
" nan, nan, 33.2, nan],\n",
|
|
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|
|
" [ nan, 2020. , nan, nan, nan, nan, nan, nan,\n",
|
|
|
|
|
" nan, nan, nan, nan, nan, 0. , nan, nan,\n",
|
|
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|
" nan, nan, 29.4, nan]])"
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]
|
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},
|
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|
|
|
"execution_count": 15,
|
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|
"metadata": {},
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"output_type": "execute_result"
|
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}
|
|
|
|
|
],
|
2023-01-12 20:25:12 +02:00
|
|
|
"source": [
|
|
|
|
|
"csv=np.genfromtxt ('./data/sugarbeets.csv',\n",
|
|
|
|
|
" skip_header=1,\n",
|
|
|
|
|
" delimiter=\",\")\n",
|
|
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|
"csv[0:3]\n",
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|
|
"#csv[0:3].astype(float)"
|
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|
]
|
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|
},
|
|
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|
{
|
|
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|
|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 16,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "ab73b355",
|
|
|
|
|
"metadata": {},
|
|
|
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|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"sugarbeets_year=csv[:,1]\n",
|
|
|
|
|
"sugarbeets_tons_per_acre=csv[:,-2]"
|
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|
]
|
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},
|
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|
{
|
|
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|
|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 17,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "cbaa454a",
|
|
|
|
|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
|
|
"outputs": [
|
|
|
|
|
{
|
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|
"data": {
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|
"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
|
2023-01-12 20:25:12 +02:00
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"source": [
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"plt.plot(corn_year,corn_bu_per_acre,\"o\",label=\"Corn (BU/ACRE)\")\n",
|
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|
|
|
"plt.plot(wheat_year,wheat_bu_per_acre,\"x\",label=\"Wheat (BU/ACRE)\")\n",
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"plt.plot(potatoes_year,potatoes_cwt_per_acre,\"+\",label=\"Potatoes (CWT / ACRE)\")\n",
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"plt.plot(soybeans_year,soybeans_bu_per_acre,\"*\",label=\"Soybeans (BU/ACRE)\")\n",
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"plt.plot(sugarbeets_year,sugarbeets_tons_per_acre,\".\",label=\"Sugarbeets (TONS/ACRE)\")\n",
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"plt.xlabel(\"time (calendar year)\")\n",
|
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|
|
|
"plt.ylabel(\"Average per acre production\")\n",
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|
|
|
"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
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"plt.legend()\n",
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|
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"plt.yscale(\"log\")\n",
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"#plt.show()\n",
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|
|
"#plt.savefig(\"bear-quadratic.pdf\")"
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]
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},
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{
|
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|
"cell_type": "markdown",
|
|
|
|
|
"id": "884a7b05",
|
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"metadata": {},
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|
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|
"source": [
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|
|
|
"## Sunflowers"
|
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|
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|
]
|
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},
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{
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"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
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|
"execution_count": 18,
|
2023-01-12 20:25:12 +02:00
|
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|
"id": "846722a4",
|
|
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|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
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|
"outputs": [
|
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|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"array([[ nan, 2022., nan, nan, nan, nan, nan, nan, nan,\n",
|
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|
" nan, nan, nan, nan, 0., nan, nan, nan, nan,\n",
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" 1782., nan],\n",
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" [ nan, 2021., nan, nan, nan, nan, nan, nan, nan,\n",
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|
" nan, nan, nan, nan, 0., nan, nan, nan, nan,\n",
|
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|
" 1529., nan],\n",
|
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|
|
" [ nan, 2020., nan, nan, nan, nan, nan, nan, nan,\n",
|
|
|
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|
" nan, nan, nan, nan, 0., nan, nan, nan, nan,\n",
|
|
|
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" 1790., nan]])"
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]
|
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},
|
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|
"execution_count": 18,
|
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|
"metadata": {},
|
|
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"output_type": "execute_result"
|
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|
}
|
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|
|
|
],
|
2023-01-12 20:25:12 +02:00
|
|
|
"source": [
|
|
|
|
|
"csv=np.genfromtxt ('./data/sunflowers.csv',\n",
|
|
|
|
|
" skip_header=1,\n",
|
|
|
|
|
" delimiter=\",\")\n",
|
|
|
|
|
"csv[0:3]\n",
|
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|
|
|
"#csv[0:3].astype(float)"
|
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|
]
|
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|
},
|
|
|
|
|
{
|
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|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 19,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "c79d0d11",
|
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|
"metadata": {},
|
|
|
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|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"sunflowers_year=csv[:,1]\n",
|
2023-01-12 21:45:54 +02:00
|
|
|
"sunflowers_lbs_per_acre=csv[:,-2]\n",
|
|
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|
"\n",
|
|
|
|
|
"#grams_per_lbs\n",
|
|
|
|
|
"sunflowers_kcal_per_gram=584.0/100.0\n",
|
|
|
|
|
"sunflowers_kcal_per_acre=sunflowers_lbs_per_acre*grams_per_lbs*sunflowers_kcal_per_gram"
|
2023-01-12 20:25:12 +02:00
|
|
|
]
|
|
|
|
|
},
|
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|
{
|
|
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|
|
"cell_type": "code",
|
2023-01-12 21:45:54 +02:00
|
|
|
"execution_count": 20,
|
2023-01-12 20:25:12 +02:00
|
|
|
"id": "569111b9",
|
|
|
|
|
"metadata": {},
|
2023-01-12 21:45:54 +02:00
|
|
|
"outputs": [
|
|
|
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|
{
|
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|
"data": {
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|
|
"image/png": "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
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
2023-01-12 20:25:12 +02:00
|
|
|
"source": [
|
|
|
|
|
"plt.plot(corn_year,corn_bu_per_acre,\"o\",label=\"Corn (BU/ACRE)\")\n",
|
|
|
|
|
"plt.plot(wheat_year,wheat_bu_per_acre,\"x\",label=\"Wheat (BU/ACRE)\")\n",
|
|
|
|
|
"plt.plot(potatoes_year,potatoes_cwt_per_acre,\"+\",label=\"Potatoes (CWT / ACRE)\")\n",
|
|
|
|
|
"plt.plot(soybeans_year,soybeans_bu_per_acre,\"*\",label=\"Soybeans (BU/ACRE)\")\n",
|
|
|
|
|
"plt.plot(sugarbeets_year,sugarbeets_tons_per_acre,\".\",label=\"Sugarbeets (TONS/ACRE)\")\n",
|
|
|
|
|
"plt.plot(sunflowers_year,sunflowers_lbs_per_acre,\"d\",label=\"Sunflowers (LB/ACRE)\")\n",
|
|
|
|
|
"plt.xlabel(\"time (calendar year)\")\n",
|
|
|
|
|
"plt.ylabel(\"Average per acre production\")\n",
|
|
|
|
|
"plt.title(\"US Agriculture yields, NASS (USDA)\")\n",
|
|
|
|
|
"plt.legend()\n",
|
|
|
|
|
"plt.yscale(\"log\")\n",
|
2023-01-12 16:13:39 +02:00
|
|
|
"#plt.show()\n",
|
|
|
|
|
"#plt.savefig(\"bear-quadratic.pdf\")"
|
|
|
|
|
]
|
2023-01-12 20:25:12 +02:00
|
|
|
},
|
2023-01-12 21:45:54 +02:00
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"id": "5828e06b",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
|
|
|
|
"### All together, kcal/acre"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": null,
|
|
|
|
|
"id": "9d58d630",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": []
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 21,
|
|
|
|
|
"id": "7903705c",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"image/png": "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
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"<Figure size 640x480 with 1 Axes>"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "display_data"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plt.plot(corn_year,corn_kcal_per_acre,\"o\",label=\"Corn\")\n",
|
|
|
|
|
"plt.plot(wheat_year,wheat_kcal_per_acre,\"x\",label=\"Wheat\")\n",
|
|
|
|
|
"plt.plot(potatoes_year,potatoes_kcal_per_acre,\"+\",label=\"Potatoes\")\n",
|
|
|
|
|
"plt.plot(soybeans_year,soybeans_kcal_per_acre,\"*\",label=\"Soybeans\")\n",
|
|
|
|
|
"#plt.plot(sugarbeets_year,sugarbeets_kcal_per_acre,\".\",label=\"Sugarbeets\")\n",
|
|
|
|
|
"plt.plot(sunflowers_year,sunflowers_kcal_per_acre,\"d\",label=\"Sunflowers\")\n",
|
|
|
|
|
"plt.xlabel(\"time (calendar year)\")\n",
|
|
|
|
|
"plt.ylabel(\"kcal/acre production\")\n",
|
|
|
|
|
"plt.title(\"Average US Agriculture yields by year, NASS (USDA)\")\n",
|
|
|
|
|
"plt.legend()\n",
|
|
|
|
|
"plt.yscale(\"log\")\n",
|
|
|
|
|
"#plt.show()\n",
|
|
|
|
|
"#plt.savefig(\"bear-quadratic.pdf\")"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 25,
|
|
|
|
|
"id": "db78da0c",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"plt.plot(corn_year,corn_kcal_per_acre,\"o\",label=\"Corn\")\n",
|
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|
"plt.plot(wheat_year,wheat_kcal_per_acre,\"x\",label=\"Wheat\")\n",
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"plt.plot(potatoes_year,potatoes_kcal_per_acre,\"+\",label=\"Potatoes\")\n",
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"plt.plot(soybeans_year,soybeans_kcal_per_acre,\"*\",label=\"Soybeans\")\n",
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|
"#plt.plot(sugarbeets_year,sugarbeets_kcal_per_acre,\".\",label=\"Sugarbeets\")\n",
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"plt.plot(sunflowers_year,sunflowers_kcal_per_acre,\"d\",markerfacecolor=\"none\",label=\"Sunflowers\")\n",
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|
|
"plt.xlabel(\"time (calendar year)\")\n",
|
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|
|
|
"plt.ylabel(\"kcal/acre production\")\n",
|
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|
|
|
"plt.title(\"Average US Agriculture yields by year, NASS (USDA)\")\n",
|
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"plt.legend()\n",
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"plt.grid()\n",
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"#plt.yscale(\"log\")\n",
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"#plt.show()\n",
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"#plt.savefig(\"bear-quadratic.pdf\")"
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]
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},
|
2023-01-12 20:25:12 +02:00
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{
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|
"cell_type": "code",
|
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|
|
"execution_count": null,
|
2023-01-12 21:45:54 +02:00
|
|
|
"id": "26e9a397",
|
2023-01-12 20:25:12 +02:00
|
|
|
"metadata": {},
|
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"outputs": [],
|
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|
|
"source": []
|
2023-01-12 16:13:39 +02:00
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}
|
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|
|
],
|
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|
"metadata": {
|
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|
|
"kernelspec": {
|
|
|
|
|
"display_name": "Python 3 (ipykernel)",
|
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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": {
|
|
|
|
|
"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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|
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|
"name": "python",
|
|
|
|
|
"nbconvert_exporter": "python",
|
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|
"pygments_lexer": "ipython3",
|
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|
"version": "3.9.13"
|
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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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|
|
}
|
