{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "pending-friday", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "id": "trained-massachusetts", "metadata": {}, "outputs": [], "source": [ "dataset = pd.read_csv('./diet.csv')" ] }, { "cell_type": "code", "execution_count": 3, "id": "waiting-treatment", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Month | \n", "diet | \n", "
---|---|---|
0 | \n", "2013-01 | \n", "100 | \n", "
1 | \n", "2013-02 | \n", "93 | \n", "
2 | \n", "2013-03 | \n", "92 | \n", "
3 | \n", "2013-04 | \n", "95 | \n", "
4 | \n", "2013-05 | \n", "90 | \n", "
... | \n", "... | \n", "... | \n", "
116 | \n", "2022-09 | \n", "46 | \n", "
117 | \n", "2022-10 | \n", "45 | \n", "
118 | \n", "2022-11 | \n", "42 | \n", "
119 | \n", "2022-12 | \n", "39 | \n", "
120 | \n", "2023-01 | \n", "52 | \n", "
121 rows × 2 columns
\n", "