{ "cells": [ { "cell_type": "markdown", "id": "ddb0915a-4364-499f-8224-8af96e00cdf2", "metadata": {}, "source": [ "#### Advanced" ] }, { "cell_type": "code", "execution_count": 2, "id": "4f677ea5-7e64-4db2-8d25-c39eec1b1989", "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 3, "id": "38eeb7f7-ba40-41da-a029-35a4b5350878", "metadata": {}, "outputs": [], "source": [ "df = pd.read_csv('https://www.w3schools.com/python/pandas/data.csv')" ] }, { "cell_type": "code", "execution_count": 4, "id": "ff6a7d3f-d18f-43e8-a03e-257489439289", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Duration | \n", "Pulse | \n", "Maxpulse | \n", "Calories | \n", "
---|---|---|---|---|
0 | \n", "60 | \n", "110 | \n", "130 | \n", "409.1 | \n", "
1 | \n", "60 | \n", "117 | \n", "145 | \n", "479.0 | \n", "
2 | \n", "60 | \n", "103 | \n", "135 | \n", "340.0 | \n", "
3 | \n", "45 | \n", "109 | \n", "175 | \n", "282.4 | \n", "
4 | \n", "45 | \n", "117 | \n", "148 | \n", "406.0 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
164 | \n", "60 | \n", "105 | \n", "140 | \n", "290.8 | \n", "
165 | \n", "60 | \n", "110 | \n", "145 | \n", "300.0 | \n", "
166 | \n", "60 | \n", "115 | \n", "145 | \n", "310.2 | \n", "
167 | \n", "75 | \n", "120 | \n", "150 | \n", "320.4 | \n", "
168 | \n", "75 | \n", "125 | \n", "150 | \n", "330.4 | \n", "
169 rows × 4 columns
\n", "\n", " | Duration | \n", "Pulse | \n", "Maxpulse | \n", "Calories | \n", "
---|---|---|---|---|
Duration | \n", "1.000000 | \n", "-0.155408 | \n", "0.009403 | \n", "0.922717 | \n", "
Pulse | \n", "-0.155408 | \n", "1.000000 | \n", "0.786535 | \n", "0.025121 | \n", "
Maxpulse | \n", "0.009403 | \n", "0.786535 | \n", "1.000000 | \n", "0.203813 | \n", "
Calories | \n", "0.922717 | \n", "0.025121 | \n", "0.203813 | \n", "1.000000 | \n", "