{ "cells": [ { "cell_type": "markdown", "id": "1327e560", "metadata": {}, "source": [ "(lecture06:selecting-rows)=\n", "# Selecting dataframe rows that satisfy a boolean expression\n", "\n", "We are now going to put to use what we learned about Python boolean expressions to extract rows from a dataframe that satisfy certain criteria.\n", "\n", "## Extract rows that satisfy single boolean expression\n", "\n", "Let's do this by example.\n", "Let's load again the `temperature_raw.xlsx` dataset we played with in {ref}`lecture05:models-are-functions`." ] }, { "cell_type": "code", "execution_count": 1, "id": "47846435", "metadata": { "tags": [ "hide-input" ] }, "outputs": [ { "data": { "text/html": [ "
\n", " | household | \n", "date | \n", "score | \n", "t_out | \n", "t_unit | \n", "hvac | \n", "
---|---|---|---|---|---|---|
0 | \n", "a1 | \n", "2018-01-07 | \n", "100.0 | \n", "4.283373 | \n", "66.693229 | \n", "246.473231 | \n", "
1 | \n", "a10 | \n", "2018-01-07 | \n", "100.0 | \n", "4.283373 | \n", "66.356134 | \n", "5.492116 | \n", "
2 | \n", "a11 | \n", "2018-01-07 | \n", "58.0 | \n", "4.283373 | \n", "71.549132 | \n", "402.094327 | \n", "
3 | \n", "a12 | \n", "2018-01-07 | \n", "64.0 | \n", "4.283373 | \n", "73.429514 | \n", "211.692244 | \n", "
4 | \n", "a13 | \n", "2018-01-07 | \n", "100.0 | \n", "4.283373 | \n", "63.923937 | \n", "0.850536 | \n", "