{ "cells": [ { "cell_type": "markdown", "id": "worldwide-blood", "metadata": {}, "source": [ "# Introduction" ] }, { "cell_type": "markdown", "id": "understanding-numbers", "metadata": {}, "source": [ "STEM has increasingly become an important sector in the United States as demand for careers outweighs the number of students graduating with a degree in a STEM-related field. While demand increases, there is also a trend present with demographics entering STEM degree programs, with men making up the majority of applicants and graduates with only a small margin of women doing the same.s..*" ] }, { "cell_type": "markdown", "id": "greater-circular", "metadata": {}, "source": [ "## Overarching Question: What factors account for women taking a career in STEM?" ] }, { "cell_type": "markdown", "id": "appreciated-testimony", "metadata": {}, "source": [ "Diversity is one of the most important factors in innovation. Rooms of \"yes men\" that think similarly to one another will only limit the capabilities of future technological breakthroughs. There needs to be a variety of methods developed to get women into STEM degree programs and careers, but in order for these methods to be effective, specific data needs to be taken into account. \n", "\n", "This study will explore trends regarding women in STEM programs and careers, how they got to this point, and what can be done to increase numbers." ] }, { "cell_type": "markdown", "id": "permanent-pollution", "metadata": {}, "source": [ "# Data" ] }, { "cell_type": "code", "execution_count": 1, "id": "technical-evans", "metadata": {}, "outputs": [], "source": [ "#Include any import statements you will need\n", "import pandas as pd\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 7, "id": "overhead-sigma", "metadata": {}, "outputs": [], "source": [ "### 💻 FILL IN YOUR DATASET FILE NAME BELOW 💻 ###\n", "\n", "file_name = \"women-stem.csv\"\n", "dataset_path = \"data/\" + file_name\n", "\n", "df = pd.read_csv(dataset_path)" ] }, { "cell_type": "code", "execution_count": 8, "id": "heated-blade", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | Rank | \n", "Major_code | \n", "Major | \n", "Major_category | \n", "Total | \n", "Men | \n", "Women | \n", "ShareWomen | \n", "Median | \n", "
---|---|---|---|---|---|---|---|---|---|
0 | \n", "1 | \n", "2419 | \n", "PETROLEUM ENGINEERING | \n", "Engineering | \n", "2339 | \n", "2057 | \n", "282 | \n", "0.120564 | \n", "110000 | \n", "
1 | \n", "2 | \n", "2416 | \n", "MINING AND MINERAL ENGINEERING | \n", "Engineering | \n", "756 | \n", "679 | \n", "77 | \n", "0.101852 | \n", "75000 | \n", "
2 | \n", "3 | \n", "2415 | \n", "METALLURGICAL ENGINEERING | \n", "Engineering | \n", "856 | \n", "725 | \n", "131 | \n", "0.153037 | \n", "73000 | \n", "
3 | \n", "4 | \n", "2417 | \n", "NAVAL ARCHITECTURE AND MARINE ENGINEERING | \n", "Engineering | \n", "1258 | \n", "1123 | \n", "135 | \n", "0.107313 | \n", "70000 | \n", "
4 | \n", "5 | \n", "2418 | \n", "NUCLEAR ENGINEERING | \n", "Engineering | \n", "2573 | \n", "2200 | \n", "373 | \n", "0.144967 | \n", "65000 | \n", "