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lab_pokemon/lab_pokemon.ipynb
ilmabura dc1b4f2f5c completed pokemon lab 
I've taken many data analytics classes in undergrad. I't been a while since i've done it. I'm unsure about what I would like
to do my project on. If I can find a dataset on mathematics scores and problem solving mindsets, I would probably like to explore that.
It may also be interesting to analyze living standards and pays across the world.
2025-10-20 20:49:47 -04:00

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{
"cells": [
{
"cell_type": "markdown",
"id": "90041b00-672b-4bd4-a8e8-0cab3f0548af",
"metadata": {},
"source": [
"# Lab 04: Data Science Tools\n",
"\n",
"## 0. Jupyter Notebooks\n",
"\n",
"Welcome to your first Jupyter notebook! Notebooks are made up of cells. Some cells contain text (like this one) and others contain Python code.\n",
"\n",
"Each cell can be in two different modes: editing or running. To edit a cell, double-click on it. When you're done editing, press **shift+Enter** to run it. You can use [Markdown](https://www.markdownguide.org/cheat-sheet/) to add basic formatting to the text. Before you go on, try editing the text in this cell."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "5923b0d7-c0e0-48fa-b765-4aa6002c2d4f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"112"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Other cells are code cells, containing Python code. (This is a comment, of course!)\n",
"# Try running this cell (again, shift+Enter). You'll see the result of the final statement \n",
"# printed below the cell. \n",
"# Then try changing the Python code and re-run it.\n",
"\n",
"2*56\n"
]
},
{
"cell_type": "markdown",
"id": "257ef44f-8f53-4136-9d0d-23a811ec53e9",
"metadata": {},
"source": [
"### 0.1 Cells share state\n",
"\n",
"Even though code cells run one at a time, anything that happens in a cell (like declaring a variable or running a function) affects the whole notebook. Try running these two cells a few times, in different orders. What happens when you run *Cell B* over and over?"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "0e2a2927-f6d1-4b13-97ae-ff97416723e9",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"10"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Cell A\n",
"x = 10\n",
"x"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "69dd7908-b213-4d0f-8016-e46a4a491961",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"20"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Cell B\n",
"x = x * 2\n",
"x"
]
},
{
"cell_type": "markdown",
"id": "adc581ac-db13-40a8-bcfc-bf5d6e5472c5",
"metadata": {},
"source": [
"### 0.2 Saving your work\n",
"\n",
"When you finish working on a notebook, save your work using the icon in the menu bar above. Your notebook is stored in the file `lab_pokemon.ipynb` in the lab directory. You can commit your changes to `ipynb` files just like any other file. Once you finish with Jupyter, you can stop the server by pressing **Control + C** in the Terminal. \n",
"\n",
"*If you're doing this lab on a cloud-based platform like Binder, then you can't save your work. So don't close the tab!*"
]
},
{
"cell_type": "markdown",
"id": "c9c4aec2-949d-4a2e-b736-f5182b1f9ff7",
"metadata": {},
"source": [
"---\n",
"\n",
"## 1. Pandas\n",
"\n",
"Pandas is probably the most important Python library for data science. Pandas provides an object called a **DataFrame**, which is basically a table with rows and columns. Most of the time, you will load data into Pandas using a `.csv` file. CSV files can be exported from Excel or Google Sheets, and are a common format for public data sets. \n",
"\n",
"In this lab, we'll be working with two data sets: The first contains Pokémon characteristics and the second comes from a wide-scale survey conducted by the US Centers for Disease Control ([details](https://www.cdc.gov/brfss/annual_data/annual_2020.html)). We will demonstrate techniques with Pokémon; your job is to replicate these tasks with the CDC dataset. \n",
"\n",
"**Note:** Pandas has *extensive* capabilities, and there's no way we could possibly present them all here. If you have a clearly-formed idea of what you want to do with tabular data, there's a way to do it. This lab introduces *some* of what Pandas can do, but expect to spend time reading the documentation and Stack Overflow when you start working on new tasks. \n",
"\n",
"### 1.0 Getting started\n",
"\n",
"First, we'll import pandas (using the conventional variable name `pd`) and load the two datasets. *Run these cells and every code cell you encounter in this notebook.*"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "ba09a0f8-27d9-456f-aeff-3980e3362d5b",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a29d508a-2d9a-4d62-9ff6-7a0ecfd5eba4",
"metadata": {},
"outputs": [],
"source": [
"pokemon = pd.read_csv(\"pokemon.csv\")\n",
"people = pd.read_csv(\"brfss_2020.csv\")"
]
},
{
"cell_type": "markdown",
"id": "d4e0b811-b8bf-4e9a-a934-3aad8f0520bb",
"metadata": {},
"source": [
"### 1.1 A first look\n",
"\n",
"#### Demo\n",
"\n",
"Let's start by learning the *shape* of the data. How many columns are there? How many rows? What kinds of data are included?"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "579d8dda-ca39-48b1-8819-b17651029729",
"metadata": {},
"outputs": [
{
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" <td>DiancieMega Diancie</td>\n",
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" <td>80</td>\n",
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" <td>80</td>\n",
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" <td>70</td>\n",
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" </tr>\n",
" </tbody>\n",
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"<p>800 rows × 12 columns</p>\n",
"</div>"
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"text/plain": [
" name type subtype total hp attack defense \\\n",
"0 Bulbasaur Grass Poison 318 45 49 49 \n",
"1 Ivysaur Grass Poison 405 60 62 63 \n",
"2 Venusaur Grass Poison 525 80 82 83 \n",
"3 VenusaurMega Venusaur Grass Poison 625 80 100 123 \n",
"4 Charmander Fire NaN 309 39 52 43 \n",
".. ... ... ... ... .. ... ... \n",
"795 Diancie Rock Fairy 600 50 100 150 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 110 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 60 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"799 Volcanion Fire Water 600 80 110 120 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"0 65 65 45 1 False \n",
"1 80 80 60 1 False \n",
"2 100 100 80 1 False \n",
"3 122 120 80 1 False \n",
"4 60 50 65 1 False \n",
".. ... ... ... ... ... \n",
"795 100 150 50 6 True \n",
"796 160 110 110 6 True \n",
"797 150 130 70 6 True \n",
"798 170 130 80 6 True \n",
"799 130 90 70 6 True \n",
"\n",
"[800 rows x 12 columns]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"pokemon"
]
},
{
"cell_type": "markdown",
"id": "ee8b0718-56f9-4fc8-bd35-fa0ccb445179",
"metadata": {},
"source": [
"OK, 800 Pokémon, with 12 columns for each. And you can see all the columns. Not all the data is shown in this preview, of course. If there were more columns than could be displayed, you could see them all by typing `pokemon.columns`. \n",
"\n",
"#### Your turn\n",
"\n",
"Now do the same for your data set, `people`."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "c9e5e4ec-b197-450c-ae2d-318006fa0a2f",
"metadata": {},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>age</th>\n",
" <th>sex</th>\n",
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" <td>8</td>\n",
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" <td>35</td>\n",
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" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
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" <td>6</td>\n",
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" <td>35</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.75</td>\n",
" <td>86.18</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>166425 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"0 55 female 5 2 other 1.55 83.01 \n",
"1 65 female 8 1 heterosexual 1.65 78.02 \n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"3 55 male 8 4 heterosexual 1.83 81.65 \n",
"4 55 female 8 4 heterosexual 1.80 76.66 \n",
"... ... ... ... ... ... ... ... \n",
"166420 45 female 8 3 heterosexual 1.63 86.18 \n",
"166421 25 male 7 2 heterosexual 1.78 86.18 \n",
"166422 25 female 1 2 heterosexual 1.91 45.36 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"166424 35 male 7 2 heterosexual 1.75 86.18 \n",
"\n",
" health no_doctor exercise sleep \n",
"0 2 True True 7 \n",
"1 3 False False 8 \n",
"2 4 True True 7 \n",
"3 5 False True 8 \n",
"4 4 False True 8 \n",
"... ... ... ... ... \n",
"166420 1 False False 6 \n",
"166421 4 False True 6 \n",
"166422 1 False False 8 \n",
"166423 4 True True 6 \n",
"166424 3 False False 8 \n",
"\n",
"[166425 rows x 11 columns]"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people"
]
},
{
"cell_type": "markdown",
"id": "7fab76ef-d453-4568-a916-4d4c29535a42",
"metadata": {},
"source": [
"### 1.2 Descriptive Statistics\n",
"\n",
"#### Demo\n",
"\n",
"Let's get a sense of the data contained in some of the columns. For categorical data like `generation`, it makes sense to look at value counts--showing us how many of each category there are. You can use the optional keyword `normalize=True` to see percentage of total instead of frequencies. "
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "9afca362-9edc-423c-981b-dc42107d5de0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"generation\n",
"1 166\n",
"5 165\n",
"3 160\n",
"4 121\n",
"2 106\n",
"6 82\n",
"Name: count, dtype: int64"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.generation.value_counts()"
]
},
{
"cell_type": "markdown",
"id": "a9b98eee-bdc2-4c63-bab2-ee82e2466d0f",
"metadata": {},
"source": [
"For numeric data, we could start by looking at the mean value. We can select multiple columns and get all the column means at once."
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "5fe580d0-5939-4152-9f8c-4c32d35a4479",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"hp 69.25875\n",
"attack 79.00125\n",
"defense 73.84250\n",
"speed 68.27750\n",
"dtype: float64"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon[[\"hp\", \"attack\", \"defense\", \"speed\"]].mean()"
]
},
{
"cell_type": "markdown",
"id": "0d8e6e78-fcfc-4c38-a418-545fe4216a44",
"metadata": {},
"source": [
"We can also compute the mean of boolean data. In this case, True will map to 1 and False will map to 0. So the mean value equals the percentage of data which is True. "
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "dc69ef53-70cd-4ae0-80e7-c9c8e28de76f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(0.08125)"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.legendary.mean()"
]
},
{
"cell_type": "markdown",
"id": "69333e87-8df2-4b46-9005-2b8c9df3a7b4",
"metadata": {},
"source": [
"Just over 8% of Pokemon are legendary."
]
},
{
"cell_type": "markdown",
"id": "f563d97d-d9d3-4f2d-a46a-5d5dfc6382de",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.2.0.** In this survey, people are grouped into age bands of 18-24, 25-34, 35-44, 45-54, 55-64, and 65+, with the lower bound reported. What percentage of people are in each age band? (When we talk about \"people\" in this lab, we're referring to the people who responded to the survey, not the whole US population.)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "8fbcc766-8399-4f93-a6c8-e0607250a72a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"age\n",
"65 0.336326\n",
"55 0.206369\n",
"45 0.157669\n",
"35 0.135527\n",
"25 0.108866\n",
"18 0.055244\n",
"Name: proportion, dtype: float64"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people.age.value_counts(normalize=True)"
]
},
{
"cell_type": "markdown",
"id": "38006e7b-4771-4c29-86a8-19d04a50fc25",
"metadata": {},
"source": [
"**1.2.1.** What are the mean height and weight of people in this survey?"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "b7f910c8-3d40-49ae-b270-678734c04100",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"height 1.705082\n",
"weight 83.053588\n",
"dtype: float64"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people[[\"height\", \"weight\"]].mean()"
]
},
{
"cell_type": "markdown",
"id": "f74634bb-8664-46e4-b371-6f45cbb7c8ef",
"metadata": {},
"source": [
"**1.2.2.** The `exercise` column indicates whether a person has done any physical activity or exercise in the last 30 days, outside of work. What percentage of people have done exercise?"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "f3891188-a85f-4089-8388-d4d81c7438ad",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(0.7858014120474688)"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people.exercise.mean()"
]
},
{
"cell_type": "markdown",
"id": "f6082e65-321c-4ee0-9457-74f9bb1b0363",
"metadata": {},
"source": [
"### 1.3 Filtering\n",
"\n",
"Sometimes we're just interested in a selection of the data set. The way to do this is to create a boolean series, and then use this to select which rows you want to include. Vocabulary note: A dataframe is two-dimensional, with rows and columns. A series (a single row or a single column) is one-dimensional. \n",
"\n",
"#### Demo\n",
"`pokemon.legendary` is already boolean, so we can use this to select just the legendary pokémon. "
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "12c0c6c9-c07b-4183-82f6-5e346c74aac9",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
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" <th>hp</th>\n",
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" <th>158</th>\n",
" <td>Moltres</td>\n",
" <td>Fire</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>100</td>\n",
" <td>90</td>\n",
" <td>125</td>\n",
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" <tr>\n",
" <th>162</th>\n",
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" <td>Psychic</td>\n",
" <td>NaN</td>\n",
" <td>680</td>\n",
" <td>106</td>\n",
" <td>110</td>\n",
" <td>90</td>\n",
" <td>154</td>\n",
" <td>90</td>\n",
" <td>130</td>\n",
" <td>1</td>\n",
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" <tr>\n",
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" <td>MewtwoMega Mewtwo X</td>\n",
" <td>Psychic</td>\n",
" <td>Fighting</td>\n",
" <td>780</td>\n",
" <td>106</td>\n",
" <td>190</td>\n",
" <td>100</td>\n",
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" <tr>\n",
" <th>795</th>\n",
" <td>Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>600</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>100</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>796</th>\n",
" <td>DiancieMega Diancie</td>\n",
" <td>Rock</td>\n",
" <td>Fairy</td>\n",
" <td>700</td>\n",
" <td>50</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>160</td>\n",
" <td>110</td>\n",
" <td>110</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>797</th>\n",
" <td>HoopaHoopa Confined</td>\n",
" <td>Psychic</td>\n",
" <td>Ghost</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>60</td>\n",
" <td>150</td>\n",
" <td>130</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>798</th>\n",
" <td>HoopaHoopa Unbound</td>\n",
" <td>Psychic</td>\n",
" <td>Dark</td>\n",
" <td>680</td>\n",
" <td>80</td>\n",
" <td>160</td>\n",
" <td>60</td>\n",
" <td>170</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>799</th>\n",
" <td>Volcanion</td>\n",
" <td>Fire</td>\n",
" <td>Water</td>\n",
" <td>600</td>\n",
" <td>80</td>\n",
" <td>110</td>\n",
" <td>120</td>\n",
" <td>130</td>\n",
" <td>90</td>\n",
" <td>70</td>\n",
" <td>6</td>\n",
" <td>True</td>\n",
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" </tbody>\n",
"</table>\n",
"<p>65 rows × 12 columns</p>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"157 Zapdos Electric Flying 580 90 90 85 \n",
"158 Moltres Fire Flying 580 90 100 90 \n",
"162 Mewtwo Psychic NaN 680 106 110 90 \n",
"163 MewtwoMega Mewtwo X Psychic Fighting 780 106 190 100 \n",
".. ... ... ... ... ... ... ... \n",
"795 Diancie Rock Fairy 600 50 100 150 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 110 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 60 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"799 Volcanion Fire Water 600 80 110 120 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"156 95 125 85 1 True \n",
"157 125 90 100 1 True \n",
"158 125 85 90 1 True \n",
"162 154 90 130 1 True \n",
"163 154 100 130 1 True \n",
".. ... ... ... ... ... \n",
"795 100 150 50 6 True \n",
"796 160 110 110 6 True \n",
"797 150 130 70 6 True \n",
"798 170 130 80 6 True \n",
"799 130 90 70 6 True \n",
"\n",
"[65 rows x 12 columns]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary = pokemon[pokemon.legendary]\n",
"legendary"
]
},
{
"cell_type": "markdown",
"id": "b4ad804a-f5f0-441f-bb83-51f360c1c154",
"metadata": {},
"source": [
"Let's get all the ice pokémon. We can create a boolean series from another series..."
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "5d089acf-7b76-4f91-8803-42a4a9a11e3e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 False\n",
"1 False\n",
"2 False\n",
"3 False\n",
"4 False\n",
" ... \n",
"795 False\n",
"796 False\n",
"797 False\n",
"798 False\n",
"799 False\n",
"Name: type, Length: 800, dtype: bool"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.type == \"Ice\""
]
},
{
"cell_type": "markdown",
"id": "a5ea9e89-f466-48de-9133-346c99f4a6c1",
"metadata": {},
"source": [
"And then use this series to select just the ice pokémon. "
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "510fa0fc-2b38-4725-9bbf-ec57d62792be",
"metadata": {},
"outputs": [
{
"data": {
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" <tr>\n",
" <th>239</th>\n",
" <td>Piloswine</td>\n",
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" <td>100</td>\n",
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" <th>243</th>\n",
" <td>Delibird</td>\n",
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" <td>330</td>\n",
" <td>45</td>\n",
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" <td>45</td>\n",
" <td>65</td>\n",
" <td>45</td>\n",
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" <tr>\n",
" <th>257</th>\n",
" <td>Smoochum</td>\n",
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" <td>305</td>\n",
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" <td>15</td>\n",
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" <tr>\n",
" <th>395</th>\n",
" <td>Snorunt</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>300</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>480</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>3</td>\n",
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" </tr>\n",
" <tr>\n",
" <th>397</th>\n",
" <td>GlalieMega Glalie</td>\n",
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" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>398</th>\n",
" <td>Spheal</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>290</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>50</td>\n",
" <td>55</td>\n",
" <td>50</td>\n",
" <td>25</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>399</th>\n",
" <td>Sealeo</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>410</td>\n",
" <td>90</td>\n",
" <td>60</td>\n",
" <td>70</td>\n",
" <td>75</td>\n",
" <td>70</td>\n",
" <td>45</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>400</th>\n",
" <td>Walrein</td>\n",
" <td>Ice</td>\n",
" <td>Water</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>90</td>\n",
" <td>95</td>\n",
" <td>90</td>\n",
" <td>65</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>415</th>\n",
" <td>Regice</td>\n",
" <td>Ice</td>\n",
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" <td>580</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>100</td>\n",
" <td>100</td>\n",
" <td>200</td>\n",
" <td>50</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
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" <tr>\n",
" <th>522</th>\n",
" <td>Glaceon</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>525</td>\n",
" <td>65</td>\n",
" <td>60</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>95</td>\n",
" <td>65</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>524</th>\n",
" <td>Mamoswine</td>\n",
" <td>Ice</td>\n",
" <td>Ground</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>60</td>\n",
" <td>80</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>530</th>\n",
" <td>Froslass</td>\n",
" <td>Ice</td>\n",
" <td>Ghost</td>\n",
" <td>480</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>110</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>643</th>\n",
" <td>Vanillite</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>305</td>\n",
" <td>36</td>\n",
" <td>50</td>\n",
" <td>50</td>\n",
" <td>65</td>\n",
" <td>60</td>\n",
" <td>44</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>644</th>\n",
" <td>Vanillish</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>395</td>\n",
" <td>51</td>\n",
" <td>65</td>\n",
" <td>65</td>\n",
" <td>80</td>\n",
" <td>75</td>\n",
" <td>59</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>645</th>\n",
" <td>Vanilluxe</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>535</td>\n",
" <td>71</td>\n",
" <td>95</td>\n",
" <td>85</td>\n",
" <td>110</td>\n",
" <td>95</td>\n",
" <td>79</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>674</th>\n",
" <td>Cubchoo</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>305</td>\n",
" <td>55</td>\n",
" <td>70</td>\n",
" <td>40</td>\n",
" <td>60</td>\n",
" <td>40</td>\n",
" <td>40</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>675</th>\n",
" <td>Beartic</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>95</td>\n",
" <td>110</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>50</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>676</th>\n",
" <td>Cryogonal</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>30</td>\n",
" <td>95</td>\n",
" <td>135</td>\n",
" <td>105</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>788</th>\n",
" <td>Bergmite</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>304</td>\n",
" <td>55</td>\n",
" <td>69</td>\n",
" <td>85</td>\n",
" <td>32</td>\n",
" <td>35</td>\n",
" <td>28</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>789</th>\n",
" <td>Avalugg</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>514</td>\n",
" <td>95</td>\n",
" <td>117</td>\n",
" <td>184</td>\n",
" <td>44</td>\n",
" <td>46</td>\n",
" <td>28</td>\n",
" <td>6</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"133 Jynx Ice Psychic 455 65 50 35 \n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"238 Swinub Ice Ground 250 50 50 40 \n",
"239 Piloswine Ice Ground 450 100 100 80 \n",
"243 Delibird Ice Flying 330 45 55 45 \n",
"257 Smoochum Ice Psychic 305 45 30 15 \n",
"395 Snorunt Ice NaN 300 50 50 50 \n",
"396 Glalie Ice NaN 480 80 80 80 \n",
"397 GlalieMega Glalie Ice NaN 580 80 120 80 \n",
"398 Spheal Ice Water 290 70 40 50 \n",
"399 Sealeo Ice Water 410 90 60 70 \n",
"400 Walrein Ice Water 530 110 80 90 \n",
"415 Regice Ice NaN 580 80 50 100 \n",
"522 Glaceon Ice NaN 525 65 60 110 \n",
"524 Mamoswine Ice Ground 530 110 130 80 \n",
"530 Froslass Ice Ghost 480 70 80 70 \n",
"643 Vanillite Ice NaN 305 36 50 50 \n",
"644 Vanillish Ice NaN 395 51 65 65 \n",
"645 Vanilluxe Ice NaN 535 71 95 85 \n",
"674 Cubchoo Ice NaN 305 55 70 40 \n",
"675 Beartic Ice NaN 485 95 110 80 \n",
"676 Cryogonal Ice NaN 485 70 50 30 \n",
"788 Bergmite Ice NaN 304 55 69 85 \n",
"789 Avalugg Ice NaN 514 95 117 184 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"133 115 95 95 1 False \n",
"156 95 125 85 1 True \n",
"238 30 30 50 2 False \n",
"239 60 60 50 2 False \n",
"243 65 45 75 2 False \n",
"257 85 65 65 2 False \n",
"395 50 50 50 3 False \n",
"396 80 80 80 3 False \n",
"397 120 80 100 3 False \n",
"398 55 50 25 3 False \n",
"399 75 70 45 3 False \n",
"400 95 90 65 3 False \n",
"415 100 200 50 3 True \n",
"522 130 95 65 4 False \n",
"524 70 60 80 4 False \n",
"530 80 70 110 4 False \n",
"643 65 60 44 5 False \n",
"644 80 75 59 5 False \n",
"645 110 95 79 5 False \n",
"674 60 40 40 5 False \n",
"675 70 80 50 5 False \n",
"676 95 135 105 5 False \n",
"788 32 35 28 6 False \n",
"789 44 46 28 6 False "
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ice = pokemon[pokemon.type == \"Ice\"]\n",
"ice"
]
},
{
"cell_type": "markdown",
"id": "0af5f534-0bec-4577-beee-29b350102265",
"metadata": {},
"source": [
"Let's get the high-speed ice pokémon. You can join conditions together using the `&` (and) and `|` (or) operators. `~` means \"not\", so `pokemon[~(pokemon.type == \"Ice\")]` would select all the non-ice pokémon. Due to order of operations, each condition needs to be wrapped in parentheses."
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "05d4c5c2-c6b4-4795-9799-c884b15445a1",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>name</th>\n",
" <th>type</th>\n",
" <th>subtype</th>\n",
" <th>total</th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" <th>special_attack</th>\n",
" <th>special_defense</th>\n",
" <th>speed</th>\n",
" <th>generation</th>\n",
" <th>legendary</th>\n",
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" <tr>\n",
" <th>133</th>\n",
" <td>Jynx</td>\n",
" <td>Ice</td>\n",
" <td>Psychic</td>\n",
" <td>455</td>\n",
" <td>65</td>\n",
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" <td>115</td>\n",
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" <td>1</td>\n",
" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>156</th>\n",
" <td>Articuno</td>\n",
" <td>Ice</td>\n",
" <td>Flying</td>\n",
" <td>580</td>\n",
" <td>90</td>\n",
" <td>85</td>\n",
" <td>100</td>\n",
" <td>95</td>\n",
" <td>125</td>\n",
" <td>85</td>\n",
" <td>1</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>396</th>\n",
" <td>Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>480</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
" <td>80</td>\n",
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" <td>False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>397</th>\n",
" <td>GlalieMega Glalie</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>580</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>120</td>\n",
" <td>80</td>\n",
" <td>100</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
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" <tr>\n",
" <th>524</th>\n",
" <td>Mamoswine</td>\n",
" <td>Ice</td>\n",
" <td>Ground</td>\n",
" <td>530</td>\n",
" <td>110</td>\n",
" <td>130</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
" <td>60</td>\n",
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" <tr>\n",
" <th>530</th>\n",
" <td>Froslass</td>\n",
" <td>Ice</td>\n",
" <td>Ghost</td>\n",
" <td>480</td>\n",
" <td>70</td>\n",
" <td>80</td>\n",
" <td>70</td>\n",
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" <td>110</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
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" <th>676</th>\n",
" <td>Cryogonal</td>\n",
" <td>Ice</td>\n",
" <td>NaN</td>\n",
" <td>485</td>\n",
" <td>70</td>\n",
" <td>50</td>\n",
" <td>30</td>\n",
" <td>95</td>\n",
" <td>135</td>\n",
" <td>105</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"133 Jynx Ice Psychic 455 65 50 35 \n",
"156 Articuno Ice Flying 580 90 85 100 \n",
"396 Glalie Ice NaN 480 80 80 80 \n",
"397 GlalieMega Glalie Ice NaN 580 80 120 80 \n",
"524 Mamoswine Ice Ground 530 110 130 80 \n",
"530 Froslass Ice Ghost 480 70 80 70 \n",
"676 Cryogonal Ice NaN 485 70 50 30 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"133 115 95 95 1 False \n",
"156 95 125 85 1 True \n",
"396 80 80 80 3 False \n",
"397 120 80 100 3 False \n",
"524 70 60 80 4 False \n",
"530 80 70 110 4 False \n",
"676 95 135 105 5 False "
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"high_speed_ice = pokemon[(pokemon.type == \"Ice\") & (pokemon.speed >= 80)]\n",
"high_speed_ice"
]
},
{
"cell_type": "markdown",
"id": "c84dc7ce-24f2-4ac7-92d7-99ed331488e0",
"metadata": {},
"source": [
"You could get the pokémon who are fire or ice by selecting `pokemon[(pokemon.type == \"Fire\") | (pokemon.type == \"Ice\")]`."
]
},
{
"cell_type": "markdown",
"id": "1f0e9625-b194-450d-b003-b88798cc2f45",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.3.0.** `no_doctor` indicates whether there was a time in the last year when the person needed to see a doctor, but could not afford to do so. Create a dataframe containing only these people. "
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "198cb0c6-3f43-43c2-9eee-3939c12ea537",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>sex</th>\n",
" <th>income</th>\n",
" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
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" <th>no_doctor</th>\n",
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" <th>sleep</th>\n",
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" <td>5</td>\n",
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" <td>True</td>\n",
" <td>7</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
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" <td>heterosexual</td>\n",
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" <th>24</th>\n",
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" <td>10</td>\n",
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" <tr>\n",
" <th>66</th>\n",
" <td>45</td>\n",
" <td>female</td>\n",
" <td>6</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.57</td>\n",
" <td>72.57</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
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" <td>18</td>\n",
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" <td>5</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.68</td>\n",
" <td>68.04</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
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" <tr>\n",
" <th>166409</th>\n",
" <td>25</td>\n",
" <td>male</td>\n",
" <td>6</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.57</td>\n",
" <td>58.51</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166414</th>\n",
" <td>55</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>3</td>\n",
" <td>heterosexual</td>\n",
" <td>1.63</td>\n",
" <td>88.45</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166416</th>\n",
" <td>65</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.50</td>\n",
" <td>55.34</td>\n",
" <td>3</td>\n",
" <td>True</td>\n",
" <td>False</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>13784 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"0 55 female 5 2 other 1.55 83.01 \n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"24 35 male 8 3 heterosexual 1.73 94.35 \n",
"50 35 female 4 2 heterosexual 1.78 81.65 \n",
"66 45 female 6 4 heterosexual 1.57 72.57 \n",
"... ... ... ... ... ... ... ... \n",
"166407 18 male 5 2 heterosexual 1.68 68.04 \n",
"166409 25 male 6 2 heterosexual 1.57 58.51 \n",
"166414 55 female 8 3 heterosexual 1.63 88.45 \n",
"166416 65 female 5 2 heterosexual 1.50 55.34 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"\n",
" health no_doctor exercise sleep \n",
"0 2 True True 7 \n",
"2 4 True True 7 \n",
"24 4 True False 8 \n",
"50 4 True False 10 \n",
"66 4 True True 7 \n",
"... ... ... ... ... \n",
"166407 3 True True 8 \n",
"166409 4 True False 7 \n",
"166414 3 True False 6 \n",
"166416 3 True False 6 \n",
"166423 4 True True 6 \n",
"\n",
"[13784 rows x 11 columns]"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"nodoc=people[people.no_doctor]\n",
"nodoc"
]
},
{
"cell_type": "markdown",
"id": "9d213707-a15b-4751-8df9-48aa568af209",
"metadata": {},
"source": [
"**1.3.1.** `health` asks people for their general health, with the meanings of numbers shown below. Create a dataframe which contains people whose general health is good or better. \n",
"\n",
"| number | health status | \n",
"| ------ | ----------- |\n",
"| 1 | Poor |\n",
"| 2 | Fair |\n",
"| 3 | Good |\n",
"| 4 | Very good |\n",
"| 5 | Excellent |"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "8a8c1ad6-4c1e-4996-ab5e-5212dadb1851",
"metadata": {},
"outputs": [
{
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" <th>income</th>\n",
" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
" <th>weight</th>\n",
" <th>health</th>\n",
" <th>no_doctor</th>\n",
" <th>exercise</th>\n",
" <th>sleep</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>65</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>heterosexual</td>\n",
" <td>1.65</td>\n",
" <td>78.02</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.65</td>\n",
" <td>77.11</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>55</td>\n",
" <td>male</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.83</td>\n",
" <td>81.65</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
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" <td>55</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
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" <td>heterosexual</td>\n",
" <td>1.80</td>\n",
" <td>76.66</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
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" <td>male</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.80</td>\n",
" <td>74.84</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
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" <tr>\n",
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" <td>55</td>\n",
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" <td>7</td>\n",
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" <td>heterosexual</td>\n",
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" <td>63.50</td>\n",
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" <td>8</td>\n",
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" <td>45</td>\n",
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" <td>8</td>\n",
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" <td>68.04</td>\n",
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" <td>False</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
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" <tr>\n",
" <th>166421</th>\n",
" <td>25</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.78</td>\n",
" <td>86.18</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
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" <tr>\n",
" <th>166424</th>\n",
" <td>35</td>\n",
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" <td>7</td>\n",
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" <td>heterosexual</td>\n",
" <td>1.75</td>\n",
" <td>86.18</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>142249 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"1 65 female 8 1 heterosexual 1.65 78.02 \n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"3 55 male 8 4 heterosexual 1.83 81.65 \n",
"4 55 female 8 4 heterosexual 1.80 76.66 \n",
"5 55 male 8 4 heterosexual 1.80 74.84 \n",
"... ... ... ... ... ... ... ... \n",
"166418 55 male 7 2 heterosexual 1.57 63.50 \n",
"166419 45 female 8 2 heterosexual 1.52 68.04 \n",
"166421 25 male 7 2 heterosexual 1.78 86.18 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"166424 35 male 7 2 heterosexual 1.75 86.18 \n",
"\n",
" health no_doctor exercise sleep \n",
"1 3 False False 8 \n",
"2 4 True True 7 \n",
"3 5 False True 8 \n",
"4 4 False True 8 \n",
"5 5 False True 7 \n",
"... ... ... ... ... \n",
"166418 3 False True 8 \n",
"166419 3 False True 7 \n",
"166421 4 False True 6 \n",
"166423 4 True True 6 \n",
"166424 3 False False 8 \n",
"\n",
"[142249 rows x 11 columns]"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"atleastgood=people[people.health >= 3]\n",
"atleastgood\n"
]
},
{
"cell_type": "markdown",
"id": "7add542b-bfd2-481a-b5b4-4e1ca744078a",
"metadata": {},
"source": [
"**1.3.2.**. `education` indicates the highest level of education completed, with codes as follows. Create a dataframe which only contains female college graduates who needed a doctor but couldn't afford one. (The survey asked people for their current sex, and only had options for male and female.)\n",
"\n",
"| number | education level | \n",
"| ------ | ----------- |\n",
"| 1 | Did not graduate from high school |\n",
"| 2 | Graduated from high school |\n",
"| 3 | Attended some college |\n",
"| 4 | Graduated from college |"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "315682ae-7d54-4d78-9a63-d23c83ba1576",
"metadata": {},
"outputs": [
{
"data": {
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"<p>2321 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"66 45 female 6 4 heterosexual 1.57 72.57 \n",
"135 55 female 6 4 heterosexual 1.70 81.65 \n",
"146 65 female 5 4 heterosexual 1.55 72.57 \n",
"259 65 female 4 4 heterosexual 1.57 56.70 \n",
"... ... ... ... ... ... ... ... \n",
"166121 35 female 8 4 heterosexual 1.65 136.08 \n",
"166219 55 female 5 4 other 1.52 59.87 \n",
"166272 25 female 8 4 heterosexual 1.52 98.88 \n",
"166381 45 female 5 4 heterosexual 1.52 49.90 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"\n",
" health no_doctor exercise sleep \n",
"2 4 True True 7 \n",
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},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"femalegrads_nodoc=nodoc[(nodoc.sex == \"female\") & (nodoc.education ==4)]\n",
"femalegrads_nodoc"
]
},
{
"cell_type": "markdown",
"id": "646d1148-7d94-4521-a04a-fbf17ade1235",
"metadata": {},
"source": [
"### 1.4. Grouping\n",
"\n",
"Now things get crazy. You can group a dataframe using one or more columns, and then compare their statistics. \n",
"\n",
"#### Demo\n",
"\n",
"Do different types of pokémon move at different speeds? We'll use `sort_values` to put these in order from slow to fast."
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "a79d96b5-2e3a-4bf3-b3ce-d41e8c6ea3c8",
"metadata": {},
"outputs": [
{
"data": {
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" <td>Bulbasaur</td>\n",
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" <td>60</td>\n",
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" <td>130</td>\n",
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" <td>80</td>\n",
" <td>110</td>\n",
" <td>120</td>\n",
" <td>130</td>\n",
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" <td>70</td>\n",
" <td>6</td>\n",
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"</table>\n",
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"</div>"
],
"text/plain": [
" name type subtype total hp attack defense \\\n",
"0 Bulbasaur Grass Poison 318 45 49 49 \n",
"1 Ivysaur Grass Poison 405 60 62 63 \n",
"2 Venusaur Grass Poison 525 80 82 83 \n",
"3 VenusaurMega Venusaur Grass Poison 625 80 100 123 \n",
"4 Charmander Fire NaN 309 39 52 43 \n",
".. ... ... ... ... .. ... ... \n",
"795 Diancie Rock Fairy 600 50 100 150 \n",
"796 DiancieMega Diancie Rock Fairy 700 50 160 110 \n",
"797 HoopaHoopa Confined Psychic Ghost 600 80 110 60 \n",
"798 HoopaHoopa Unbound Psychic Dark 680 80 160 60 \n",
"799 Volcanion Fire Water 600 80 110 120 \n",
"\n",
" special_attack special_defense speed generation legendary \n",
"0 65 65 45 1 False \n",
"1 80 80 60 1 False \n",
"2 100 100 80 1 False \n",
"3 122 120 80 1 False \n",
"4 60 50 65 1 False \n",
".. ... ... ... ... ... \n",
"795 100 150 50 6 True \n",
"796 160 110 110 6 True \n",
"797 150 130 70 6 True \n",
"798 170 130 80 6 True \n",
"799 130 90 70 6 True \n",
"\n",
"[800 rows x 12 columns]"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "069ea0ab-eff6-4985-9f46-db956fe1df91",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type\n",
"Fairy 48.588235\n",
"Steel 55.259259\n",
"Rock 55.909091\n",
"Bug 61.681159\n",
"Grass 61.928571\n",
"Ice 63.458333\n",
"Poison 63.571429\n",
"Ground 63.906250\n",
"Ghost 64.343750\n",
"Water 65.964286\n",
"Fighting 66.074074\n",
"Normal 71.551020\n",
"Fire 74.442308\n",
"Dark 76.161290\n",
"Psychic 81.491228\n",
"Dragon 83.031250\n",
"Electric 84.500000\n",
"Flying 102.500000\n",
"Name: speed, dtype: float64"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pokemon.groupby(\"type\").speed.mean().sort_values()"
]
},
{
"cell_type": "markdown",
"id": "bdc801b7-d3ae-45bb-80f4-ebeb474e20a1",
"metadata": {},
"source": [
"Do types differ in other stats? Let's sort by hit points. "
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "5c420c0e-b5d2-49ae-ab98-3305ee076169",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>hp</th>\n",
" <th>attack</th>\n",
" <th>defense</th>\n",
" </tr>\n",
" <tr>\n",
" <th>type</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>Bug</th>\n",
" <td>56.884058</td>\n",
" <td>70.971014</td>\n",
" <td>70.724638</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Electric</th>\n",
" <td>59.795455</td>\n",
" <td>69.090909</td>\n",
" <td>66.295455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ghost</th>\n",
" <td>64.437500</td>\n",
" <td>73.781250</td>\n",
" <td>81.187500</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Steel</th>\n",
" <td>65.222222</td>\n",
" <td>92.703704</td>\n",
" <td>126.370370</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Rock</th>\n",
" <td>65.363636</td>\n",
" <td>92.863636</td>\n",
" <td>100.795455</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dark</th>\n",
" <td>66.806452</td>\n",
" <td>88.387097</td>\n",
" <td>70.225806</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Poison</th>\n",
" <td>67.250000</td>\n",
" <td>74.678571</td>\n",
" <td>68.821429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Grass</th>\n",
" <td>67.271429</td>\n",
" <td>73.214286</td>\n",
" <td>70.800000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fighting</th>\n",
" <td>69.851852</td>\n",
" <td>96.777778</td>\n",
" <td>65.925926</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fire</th>\n",
" <td>69.903846</td>\n",
" <td>84.769231</td>\n",
" <td>67.769231</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Psychic</th>\n",
" <td>70.631579</td>\n",
" <td>71.456140</td>\n",
" <td>67.684211</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Flying</th>\n",
" <td>70.750000</td>\n",
" <td>78.750000</td>\n",
" <td>66.250000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ice</th>\n",
" <td>72.000000</td>\n",
" <td>72.750000</td>\n",
" <td>71.416667</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Water</th>\n",
" <td>72.062500</td>\n",
" <td>74.151786</td>\n",
" <td>72.946429</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Ground</th>\n",
" <td>73.781250</td>\n",
" <td>95.750000</td>\n",
" <td>84.843750</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Fairy</th>\n",
" <td>74.117647</td>\n",
" <td>61.529412</td>\n",
" <td>65.705882</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Normal</th>\n",
" <td>77.275510</td>\n",
" <td>73.469388</td>\n",
" <td>59.846939</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Dragon</th>\n",
" <td>83.312500</td>\n",
" <td>112.125000</td>\n",
" <td>86.375000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" hp attack defense\n",
"type \n",
"Bug 56.884058 70.971014 70.724638\n",
"Electric 59.795455 69.090909 66.295455\n",
"Ghost 64.437500 73.781250 81.187500\n",
"Steel 65.222222 92.703704 126.370370\n",
"Rock 65.363636 92.863636 100.795455\n",
"Dark 66.806452 88.387097 70.225806\n",
"Poison 67.250000 74.678571 68.821429\n",
"Grass 67.271429 73.214286 70.800000\n",
"Fighting 69.851852 96.777778 65.925926\n",
"Fire 69.903846 84.769231 67.769231\n",
"Psychic 70.631579 71.456140 67.684211\n",
"Flying 70.750000 78.750000 66.250000\n",
"Ice 72.000000 72.750000 71.416667\n",
"Water 72.062500 74.151786 72.946429\n",
"Ground 73.781250 95.750000 84.843750\n",
"Fairy 74.117647 61.529412 65.705882\n",
"Normal 77.275510 73.469388 59.846939\n",
"Dragon 83.312500 112.125000 86.375000"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ptypes = pokemon.groupby(\"type\")\n",
"ptypes[[\"hp\", \"attack\", \"defense\"]].mean().sort_values(\"hp\")"
]
},
{
"cell_type": "markdown",
"id": "cc9a3d19-0ecd-487b-b34f-b748c44fc9c9",
"metadata": {},
"source": [
"Which type/subtype combinations are most likely to have legendary pokémon?"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "444a580d-e70c-48a1-bf87-77f98b8c9f85",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"type subtype \n",
"Electric Flying 0.600000\n",
"Rock Fairy 0.666667\n",
"Ghost Dragon 1.000000\n",
"Ground Fire 1.000000\n",
"Fire Water 1.000000\n",
" Steel 1.000000\n",
"Steel Dragon 1.000000\n",
"Dragon Electric 1.000000\n",
"Psychic Ghost 1.000000\n",
"Dragon Psychic 1.000000\n",
" Ice 1.000000\n",
"Rock Fighting 1.000000\n",
"Steel Fighting 1.000000\n",
"Dragon Fire 1.000000\n",
"Psychic Dark 1.000000\n",
" Fire 1.000000\n",
"Name: legendary, dtype: float64"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"legendary_percentages = pokemon.groupby([\"type\", \"subtype\"]).legendary.mean().sort_values() \n",
"legendary_percentages[legendary_percentages > 0.5]"
]
},
{
"cell_type": "markdown",
"id": "de23775b-8670-4371-913d-d8fa1d1f3a76",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.4.0.** `income` records peoples' annual income, in the following bands. `sleep` records the average hours of sleep someone gets per night. Is there a difference in the average hours of sleep by income level?\n",
"\n",
"| number | annual income, in $1000 | \n",
"| ------ | ----------- |\n",
"| 1 | Less than 10 |\n",
"| 2 | 10-15 |\n",
"| 3 | 15-20 |\n",
"| 4 | 20-25 |\n",
"| 5 | 25-35 |\n",
"| 6 | 35-50 |\n",
"| 7 | 50-75 |\n",
"| 8 | More than 75 |"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "38d0c0f1-5b2f-4120-a1cf-c980243a1db8",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
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" vertical-align: middle;\n",
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" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
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" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>age</th>\n",
" <th>sex</th>\n",
" <th>income</th>\n",
" <th>education</th>\n",
" <th>sexual_orientation</th>\n",
" <th>height</th>\n",
" <th>weight</th>\n",
" <th>health</th>\n",
" <th>no_doctor</th>\n",
" <th>exercise</th>\n",
" <th>sleep</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>55</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>2</td>\n",
" <td>other</td>\n",
" <td>1.55</td>\n",
" <td>83.01</td>\n",
" <td>2</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>65</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>1</td>\n",
" <td>heterosexual</td>\n",
" <td>1.65</td>\n",
" <td>78.02</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.65</td>\n",
" <td>77.11</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>7</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>55</td>\n",
" <td>male</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.83</td>\n",
" <td>81.65</td>\n",
" <td>5</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>55</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.80</td>\n",
" <td>76.66</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166420</th>\n",
" <td>45</td>\n",
" <td>female</td>\n",
" <td>8</td>\n",
" <td>3</td>\n",
" <td>heterosexual</td>\n",
" <td>1.63</td>\n",
" <td>86.18</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166421</th>\n",
" <td>25</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.78</td>\n",
" <td>86.18</td>\n",
" <td>4</td>\n",
" <td>False</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166422</th>\n",
" <td>25</td>\n",
" <td>female</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.91</td>\n",
" <td>45.36</td>\n",
" <td>1</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166423</th>\n",
" <td>35</td>\n",
" <td>female</td>\n",
" <td>5</td>\n",
" <td>4</td>\n",
" <td>heterosexual</td>\n",
" <td>1.60</td>\n",
" <td>68.04</td>\n",
" <td>4</td>\n",
" <td>True</td>\n",
" <td>True</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>166424</th>\n",
" <td>35</td>\n",
" <td>male</td>\n",
" <td>7</td>\n",
" <td>2</td>\n",
" <td>heterosexual</td>\n",
" <td>1.75</td>\n",
" <td>86.18</td>\n",
" <td>3</td>\n",
" <td>False</td>\n",
" <td>False</td>\n",
" <td>8</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>166425 rows × 11 columns</p>\n",
"</div>"
],
"text/plain": [
" age sex income education sexual_orientation height weight \\\n",
"0 55 female 5 2 other 1.55 83.01 \n",
"1 65 female 8 1 heterosexual 1.65 78.02 \n",
"2 35 female 8 4 heterosexual 1.65 77.11 \n",
"3 55 male 8 4 heterosexual 1.83 81.65 \n",
"4 55 female 8 4 heterosexual 1.80 76.66 \n",
"... ... ... ... ... ... ... ... \n",
"166420 45 female 8 3 heterosexual 1.63 86.18 \n",
"166421 25 male 7 2 heterosexual 1.78 86.18 \n",
"166422 25 female 1 2 heterosexual 1.91 45.36 \n",
"166423 35 female 5 4 heterosexual 1.60 68.04 \n",
"166424 35 male 7 2 heterosexual 1.75 86.18 \n",
"\n",
" health no_doctor exercise sleep \n",
"0 2 True True 7 \n",
"1 3 False False 8 \n",
"2 4 True True 7 \n",
"3 5 False True 8 \n",
"4 4 False True 8 \n",
"... ... ... ... ... \n",
"166420 1 False False 6 \n",
"166421 4 False True 6 \n",
"166422 1 False False 8 \n",
"166423 4 True True 6 \n",
"166424 3 False False 8 \n",
"\n",
"[166425 rows x 11 columns]"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people"
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "75c1ac4f-3914-4c0a-a156-2e084002df66",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"income\n",
"1 6.952208\n",
"2 6.985627\n",
"6 7.055784\n",
"8 7.074626\n",
"7 7.078495\n",
"4 7.079627\n",
"3 7.083274\n",
"5 7.100286\n",
"Name: sleep, dtype: float64"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"people.groupby(\"income\").sleep.mean().sort_values()"
]
},
{
"cell_type": "markdown",
"id": "f6413f2b-26a0-4b70-976f-90e45558c4bb",
"metadata": {},
"source": [
"**1.4.0.** Is there a difference in peoples' income or general health, by sex and education level? "
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "d46df8a1-bbc2-45a4-9be1-cee1858cbf21",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>income</th>\n",
" <th>health</th>\n",
" </tr>\n",
" <tr>\n",
" <th>sex</th>\n",
" <th>education</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">female</th>\n",
" <th>1</th>\n",
" <td>3.554701</td>\n",
" <td>2.848040</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5.049022</td>\n",
" <td>3.315797</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>5.779390</td>\n",
" <td>3.483379</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>6.960652</td>\n",
" <td>3.844340</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">male</th>\n",
" <th>1</th>\n",
" <td>4.433009</td>\n",
" <td>3.031525</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>5.742876</td>\n",
" <td>3.440818</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>6.270230</td>\n",
" <td>3.549105</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>7.190582</td>\n",
" <td>3.826512</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" income health\n",
"sex education \n",
"female 1 3.554701 2.848040\n",
" 2 5.049022 3.315797\n",
" 3 5.779390 3.483379\n",
" 4 6.960652 3.844340\n",
"male 1 4.433009 3.031525\n",
" 2 5.742876 3.440818\n",
" 3 6.270230 3.549105\n",
" 4 7.190582 3.826512"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sex=people.groupby([\"sex\",\"education\"])\n",
"sex[[\"income\", \"health\"]].mean()"
]
},
{
"cell_type": "markdown",
"id": "931d602b-ddf4-4c8b-80e0-f886267cce76",
"metadata": {},
"source": [
"### 1.5. Plotting \n",
"\n",
"Pandas has excellent built-in plotting capabilities, but \n",
"we are going to use the [seaborn](https://seaborn.pydata.org/) library because it's a bit \n",
"more intuitive and produces more beautiful plots. `set_theme`, called here without any arguments, assigns the default color palette. "
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "b1e06e4f-6b9e-42af-a27c-dbb525a259ce",
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"sns.set_theme()"
]
},
{
"cell_type": "markdown",
"id": "a15ad672-13e8-4bdd-bc31-a489a1730daf",
"metadata": {},
"source": [
"#### Demo\n",
"\n",
"**When you want to visualize the distribution of a series**, a [histogram](https://seaborn.pydata.org/generated/seaborn.histplot.html) puts data into bins and plots the number of data points in each bin.\n",
"\n",
"Let's see the distribution of pokémon attack values. Note how assigning `x=\"attack\"` spreads attack values over the x-axis, while `y=\"attack\"` spreads attack values over the y-axis. The number of bins is selected automatically, but you can specify this with the optional `bins` argument. "
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "5ce066fe-f81d-4b78-a394-c5c2f4dc9f46",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='attack', ylabel='Count'>"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(data=pokemon, x=\"attack\")"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "bceb253b-ef4f-4aa2-aef4-cab2b3ca6d59",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='Count', ylabel='attack'>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(data=pokemon, y=\"attack\", bins=5)"
]
},
{
"cell_type": "markdown",
"id": "2aac9186-86c0-41db-a1c4-8719bb78b46b",
"metadata": {},
"source": [
"**When you want to compare the distribution of a numeric variable across categories**, a [barplot](https://seaborn.pydata.org/generated/seaborn.barplot.html) is a good choice. Choose one numeric column and one categorical column. \n",
"\n",
"Let's see pokémon hit points by legendary/non-legendary. `errorbar=\"sd\"` shows the standard deviation for each category. "
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "92be1ad0-12bb-49f0-a3f6-85fcfd98e943",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='legendary', ylabel='hp'>"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=pokemon, x=\"legendary\", y=\"hp\", errorbar=\"sd\")"
]
},
{
"cell_type": "markdown",
"id": "4f75e1fa-a5d7-4d2c-a458-8190a7cd700e",
"metadata": {},
"source": [
"Here, we use a barplot to show average hit points by type. `errorbar=None` removes the standard deviation bars, because they clutter up the plot with too much detail. "
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "17f1c289-5990-4420-bfcb-e50eee0b8af6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='hp', ylabel='type'>"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data=pokemon, x=\"hp\", y=\"type\", hue=\"type\", errorbar=None, palette=\"muted\")"
]
},
{
"cell_type": "markdown",
"id": "213d6139-203f-4d81-a4b1-6f98cb184662",
"metadata": {},
"source": [
"**When you want to show how many observations are the intersection of multiple categories,** a [countplot](https://seaborn.pydata.org/generated/seaborn.countplot.html) is a good choice. \n",
"\n",
"To demonstrate this, let's convert the numeric variable `speed` into a categorical variable, `speed_category`, using the built-in function [cut](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.cut.html). "
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "3c8e9f47-9aea-4bf0-a628-7aa1a66a8eee",
"metadata": {},
"outputs": [],
"source": [
"bins = [0, 50, 100, 200]\n",
"labels = [\"slow\", \"medium\", \"fast\"]\n",
"pokemon[\"speed_category\"] = pd.cut(pokemon.speed, bins=bins, labels=labels)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "22f78bec-3d18-4133-ba9f-6595d7181ded",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='speed_category', ylabel='count'>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.countplot(data=pokemon, x=\"speed_category\", hue=\"legendary\")"
]
},
{
"cell_type": "markdown",
"id": "fd508c13-9900-4be1-958f-4f9e9e9b633a",
"metadata": {},
"source": [
"**When you want to show the relationship between two numeric variables**, a [scatterplot](https://seaborn.pydata.org/generated/seaborn.scatterplot.html) is a good choice. \n",
"\n",
"Here, we plot pokémon hit points against their speed. "
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "444d9832-bd57-4238-9ea4-5ee898847170",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='hp', ylabel='speed'>"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=pokemon, x=\"hp\", y=\"speed\")"
]
},
{
"cell_type": "markdown",
"id": "03e81709-393d-4c41-bce5-2dffc9cf5553",
"metadata": {},
"source": [
"You can distinguish between categories within a scatter plot by assigning a categorical variable to `hue`. We set the marker size with `s` and their opacity with `alpha`. "
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "86f9747b-00a3-407f-9b73-0bce40bac50d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='hp', ylabel='speed'>"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.scatterplot(data=pokemon, x=\"hp\", y=\"speed\", hue=\"legendary\", alpha=0.5, s=60)"
]
},
{
"cell_type": "markdown",
"id": "f3741251-2a2b-437e-b68f-084fb4399e9f",
"metadata": {},
"source": [
"Finally, if you want scatter plots across multiple categories, a [relplot](https://seaborn.pydata.org/generated/seaborn.relplot.html) lets you distribute categories across rows and colums in a grid. "
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "7385237c-6a5c-4041-af46-559d6d84d1fa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0x131a01e80>"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 1592.5x500 with 3 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"favorite_types = pokemon[pokemon.type.isin([\"Fire\", \"Water\", \"Grass\"])]\n",
"sns.relplot(data=favorite_types, x=\"hp\", y=\"speed\", hue=\"legendary\", col=\"type\", s=100)"
]
},
{
"cell_type": "markdown",
"id": "c6a20904-416d-44be-a4f3-2107200fb3c2",
"metadata": {},
"source": [
"#### Your turn\n",
"\n",
"**1.5.0.** Plot a histogram of peoples' heights."
]
},
{
"cell_type": "code",
"execution_count": 124,
"id": "3b268a30-42ff-4ab8-b2cd-c58a76121f9c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='height', ylabel='Count'>"
]
},
"execution_count": 124,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.histplot(data=people, x=\"height\", bins=30, color=\"green\")"
]
},
{
"cell_type": "markdown",
"id": "9b0c9120-fff4-42b2-8ab6-3aa2eba47806",
"metadata": {},
"source": [
"**1.5.1.** Plot a bar chart showing peoples' average hours of sleep by age. "
]
},
{
"cell_type": "code",
"execution_count": 132,
"id": "1317e77c-8cd9-449e-8ec6-4897914103da",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='age', ylabel='sleep'>"
]
},
"execution_count": 132,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"avgsleep=people.groupby('age')['sleep'].mean().reset_index()\n",
"sns.barplot(data=avgsleep, x='age', y='sleep', color='red')"
]
},
{
"cell_type": "markdown",
"id": "15d94323-2d65-4100-9916-101516f6ccf1",
"metadata": {},
"source": [
"**1.5.2.** Plot a bar chart showing peoples' likelihood of getting exercise by income. "
]
},
{
"cell_type": "code",
"execution_count": 133,
"id": "810870e3-392e-4036-9321-502c6e418d45",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='income', ylabel='exercise'>"
]
},
"execution_count": 133,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"exercise_income=people.groupby('income')['exercise'].mean().reset_index()\n",
"sns.barplot(data=exercise_income, x='income', y='exercise', color='purple')"
]
},
{
"cell_type": "markdown",
"id": "b2705fef-470d-494c-86c1-8b3bd34b3660",
"metadata": {},
"source": [
"**1.5.3.** Plot a bar chart showing average reported health by age. For each age, show average health for those who get exercise and those who don't."
]
},
{
"cell_type": "code",
"execution_count": 118,
"id": "4ee2eb69-2f9a-42e7-b5d3-9499631bfd06",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='age', ylabel='health'>"
]
},
"execution_count": 118,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"avghealth=people.groupby(['age','exercise'])\n",
"avghealth=avghealth.health.mean().reset_index()\n",
"\n",
"sns.barplot(data=avghealth, x='age', y='health', hue='exercise')"
]
},
{
"cell_type": "markdown",
"id": "84b1e240-4f75-4c86-8c1f-1026aa223717",
"metadata": {},
"source": [
"**1.5.4.** Create a plot showing the number of people at each income level, for each education level. "
]
},
{
"cell_type": "code",
"execution_count": 138,
"id": "d7e02da8-beab-40e7-95d0-74a5c2bc838e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='income', ylabel='count'>"
]
},
"execution_count": 138,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"inc_ed=people.groupby(['education', 'income']).size().reset_index(name='count')\n",
"sns.barplot(data=inc_ed, x=\"income\", y=\"count\", hue=\"education\")"
]
},
{
"cell_type": "markdown",
"id": "ac717580-4157-402c-9262-b2b50dfe606f",
"metadata": {},
"source": [
"**1.5.5.** Plot side-by-side scatter plots showing the relationship between height and weight for males and females. (There are so many overlapping dots that the plot will be more informative if you lower the opacity of each dot. Try using `alpha=0.1` and `edgecolor=None`.)"
]
},
{
"cell_type": "code",
"execution_count": 142,
"id": "b00dd7d6-226b-469c-86d8-b71b328aa576",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<seaborn.axisgrid.FacetGrid at 0xfa0c34187860>"
]
},
"execution_count": 142,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 1000x500 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.relplot(data=people, x='height', y='weight', col='sex', s=20)"
]
},
{
"cell_type": "markdown",
"id": "e9ff7225-5d08-428b-90e8-ee60f4a4049a",
"metadata": {},
"source": [
"## 2. Crafting a data argument\n",
"\n",
"Everything up to here are just tools, worthless without a clear research question and a convincing argument. Choose a research question that interests you which might be answerable using the `people` dataset. Then do your best to find the answer in the space below. This answer should include data analysis (code cells) as well as written argument (text cells) explaining what the data means and why you believe it answers your question. \n",
"\n",
"Examples of research questions might include:\n",
"\n",
"- Do older people tend to have higher incomes?\n",
"- Do people who sleep at least 6 hours a night tend to report better health? \n",
"- Is it more common for males to be bisexual than females?\n",
"\n",
"**A note of caution:** this lab has given you tools for exploring associations--patterns that tend to co-occur. These tools *do not* equip you to argue that one variable causes another to change. For example: Plot 1.5.4 showed that people who are taller also tend to be heaver, with a lot of individual variation. But are people heavier *because* they are taller? Are they taller because they are heavier? Or maybe neither variable causes the other--perhaps they're both caused by something else. If you want to be able to answer questions like these, take a course on statistics."
]
},
{
"cell_type": "markdown",
"id": "d8e49878-e2b4-4196-b9bf-6e74142f57bc",
"metadata": {},
"source": [
"### Research Question\n",
"#### Is higher weight associated with lower reported health?\n",
"##### Hypothesis: People with higher weight will report lower health ratings on average"
]
},
{
"cell_type": "code",
"execution_count": 148,
"id": "8b4b852b-402c-45d4-b3bb-840e47b249ed",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(-0.17225826656795756)"
]
},
"execution_count": 148,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#correlation btwn weight and health\n",
"r = people['weight'].corr(people['health'])\n",
"r"
]
},
{
"cell_type": "code",
"execution_count": 150,
"id": "ef7cbeb1-5fe2-440c-9598-656cac0ee665",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='weight', ylabel='health'>"
]
},
"execution_count": 150,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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",
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.regplot(data=people, x='weight', y='health')\n"
]
},
{
"cell_type": "markdown",
"id": "6f7306f0-27ff-4997-81f9-240db4f8d445",
"metadata": {},
"source": [
"When searching for a correlation between weigth and health, we get our coefficient, r= -0.172. This mean there is a weak negative correlation, i.e. as weight increases, reported health tends to decrease a little. Since the coefficient is closer to 0, it is a mild to weak relationship and weight alone cannot strongly predict how healthy people are. \n"
]
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