{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Wrap-up Challenge\n", "\n", "We've provided a file called `starwars.csv` in this folder (you should see it in the file explorer on the left). This is a *tidy* dataset that you're going to practice your Polars and Seaborn skills on by answering the following questions.\n", "\n", "*Note: if you find it helpful to see similar commands on this same data using `dplyr` in R, they're available [here](https://psych252.github.io/psych252book/data-wrangling-1.html#looking-at-data)*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "For clarity we're going to re-import everything you normally might when working with real data." ] }, { "cell_type": "code", "execution_count": 97, "metadata": {}, "outputs": [], "source": [ "import polars as pl\n", "from polars import col, when, lit\n", "import polars.selectors as cs\n", "\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt # for customization if needed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspecting data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Load the file and print the first few rows:" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 98, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (5, 11)
nameheightmasshair_colorskin_coloreye_colorbirth_yearsexgenderhomeworldspecies
strf64f64strstrstrf64strstrstrstr
"Luke Skywalker"172.077.0"blond""fair""blue"19.0"male""masculine""Tatooine""Human"
"C-3PO"167.075.0null"gold""yellow"112.0"none""masculine""Tatooine""Droid"
"R2-D2"96.032.0null"white, blue""red"33.0"none""masculine""Naboo""Droid"
"Darth Vader"202.0136.0"none""white""yellow"41.9"male""masculine""Tatooine""Human"
"Leia Organa"150.049.0"brown""light""brown"19.0"female""feminine""Alderaan""Human"
" ], "text/plain": [ "shape: (5, 11)\n", "┌────────────────┬────────┬───────┬────────────┬───┬────────┬───────────┬───────────┬─────────┐\n", "│ name ┆ height ┆ mass ┆ hair_color ┆ … ┆ sex ┆ gender ┆ homeworld ┆ species │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ f64 ┆ str ┆ ┆ str ┆ str ┆ str ┆ str │\n", "╞════════════════╪════════╪═══════╪════════════╪═══╪════════╪═══════════╪═══════════╪═════════╡\n", "│ Luke Skywalker ┆ 172.0 ┆ 77.0 ┆ blond ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ C-3PO ┆ 167.0 ┆ 75.0 ┆ null ┆ … ┆ none ┆ masculine ┆ Tatooine ┆ Droid │\n", "│ R2-D2 ┆ 96.0 ┆ 32.0 ┆ null ┆ … ┆ none ┆ masculine ┆ Naboo ┆ Droid │\n", "│ Darth Vader ┆ 202.0 ┆ 136.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Leia Organa ┆ 150.0 ┆ 49.0 ┆ brown ┆ … ┆ female ┆ feminine ┆ Alderaan ┆ Human │\n", "└────────────────┴────────┴───────┴────────────┴───┴────────┴───────────┴───────────┴─────────┘" ] }, "execution_count": 98, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw = pl.read_csv('starwars.csv')\n", "sw.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How many rows are in the DataFrame total?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 99, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(87, 11)" ] }, "execution_count": 99, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How many missing values are in each column?\n", "\n", "*Hint: checkout `.null_count()`*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 100, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (1, 11)
nameheightmasshair_colorskin_coloreye_colorbirth_yearsexgenderhomeworldspecies
u32u32u32u32u32u32u32u32u32u32u32
06285004444104
" ], "text/plain": [ "shape: (1, 11)\n", "┌──────┬────────┬──────┬────────────┬───┬─────┬────────┬───────────┬─────────┐\n", "│ name ┆ height ┆ mass ┆ hair_color ┆ … ┆ sex ┆ gender ┆ homeworld ┆ species │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ u32 ┆ u32 ┆ u32 ┆ u32 ┆ ┆ u32 ┆ u32 ┆ u32 ┆ u32 │\n", "╞══════╪════════╪══════╪════════════╪═══╪═════╪════════╪═══════════╪═════════╡\n", "│ 0 ┆ 6 ┆ 28 ┆ 5 ┆ … ┆ 4 ┆ 4 ┆ 10 ┆ 4 │\n", "└──────┴────────┴──────┴────────────┴───┴─────┴────────┴───────────┴─────────┘" ] }, "execution_count": 100, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.null_count()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How many unique characters are there?\n", "\n", "*Hint: for quick operations you can directly refer to a rows/columns using slicing `[]` syntax*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 101, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "87" ] }, "execution_count": 101, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw['name'].n_unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Return a list of the unique \"species\" in the data and sort them alphabetically" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 102, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (38,)
species
str
null
"Aleena"
"Besalisk"
"Cerean"
"Chagrian"
…
"Vulptereen"
"Wookiee"
"Xexto"
"Yoda's species"
"Zabrak"
" ], "text/plain": [ "shape: (38,)\n", "Series: 'species' [str]\n", "[\n", "\tnull\n", "\t\"Aleena\"\n", "\t\"Besalisk\"\n", "\t\"Cerean\"\n", "\t\"Chagrian\"\n", "\t…\n", "\t\"Vulptereen\"\n", "\t\"Wookiee\"\n", "\t\"Xexto\"\n", "\t\"Yoda's species\"\n", "\t\"Zabrak\"\n", "]" ] }, "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw['species'].unique().sort()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Return the number of observations for each unique \"eye-color\"\n", "\n", "*Hint: checkout `.value_counts()`*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 103, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (15, 2)
eye_colorcount
stru32
"dark"1
"red, blue"1
"unknown"3
"gold"1
"orange"8
……
"blue"19
"white"1
"pink"1
"green, yellow"1
"brown"21
" ], "text/plain": [ "shape: (15, 2)\n", "┌───────────────┬───────┐\n", "│ eye_color ┆ count │\n", "│ --- ┆ --- │\n", "│ str ┆ u32 │\n", "╞═══════════════╪═══════╡\n", "│ dark ┆ 1 │\n", "│ red, blue ┆ 1 │\n", "│ unknown ┆ 3 │\n", "│ gold ┆ 1 │\n", "│ orange ┆ 8 │\n", "│ … ┆ … │\n", "│ blue ┆ 19 │\n", "│ white ┆ 1 │\n", "│ pink ┆ 1 │\n", "│ green, yellow ┆ 1 │\n", "│ brown ┆ 21 │\n", "└───────────────┴───────┘" ] }, "execution_count": 103, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw['eye_color'].value_counts()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Wrangling Data\n", "\n", "Ok lets use the **contexts** and **expressions** we've learned to about filter and aggregate this data in different ways." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Filter rows to get character's whose \"gender\" is \"masculine\" and \"height\" is above the median height of all characters.\n", "\n", "How many rows in the result?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 104, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (39, 11)
nameheightmasshair_colorskin_coloreye_colorbirth_yearsexgenderhomeworldspecies
strf64f64strstrstrf64strstrstrstr
"Darth Vader"202.0136.0"none""white""yellow"41.9"male""masculine""Tatooine""Human"
"Biggs Darklighter"183.084.0"black""light""brown"24.0"male""masculine""Tatooine""Human"
"Obi-Wan Kenobi"182.077.0"auburn, white""fair""blue-gray"57.0"male""masculine""Stewjon""Human"
"Anakin Skywalker"188.084.0"blond""fair""blue"41.9"male""masculine""Tatooine""Human"
"Wilhuff Tarkin"180.0null"auburn, grey""fair""blue"64.0"male""masculine""Eriadu""Human"
……………………………
"San Hill"191.0null"none""grey""gold"null"male""masculine""Muunilinst""Muun"
"Grievous"216.0159.0"none""brown, white""green, yellow"null"male""masculine""Kalee""Kaleesh"
"Tarfful"234.0136.0"brown""brown""blue"null"male""masculine""Kashyyyk""Wookiee"
"Raymus Antilles"188.079.0"brown""light""brown"null"male""masculine""Alderaan""Human"
"Tion Medon"206.080.0"none""grey""black"null"male""masculine""Utapau""Pau'an"
" ], "text/plain": [ "shape: (39, 11)\n", "┌───────────────────┬────────┬───────┬───────────────┬───┬──────┬───────────┬────────────┬─────────┐\n", "│ name ┆ height ┆ mass ┆ hair_color ┆ … ┆ sex ┆ gender ┆ homeworld ┆ species │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ f64 ┆ str ┆ ┆ str ┆ str ┆ str ┆ str │\n", "╞═══════════════════╪════════╪═══════╪═══════════════╪═══╪══════╪═══════════╪════════════╪═════════╡\n", "│ Darth Vader ┆ 202.0 ┆ 136.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Biggs Darklighter ┆ 183.0 ┆ 84.0 ┆ black ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Obi-Wan Kenobi ┆ 182.0 ┆ 77.0 ┆ auburn, white ┆ … ┆ male ┆ masculine ┆ Stewjon ┆ Human │\n", "│ Anakin Skywalker ┆ 188.0 ┆ 84.0 ┆ blond ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Wilhuff Tarkin ┆ 180.0 ┆ null ┆ auburn, grey ┆ … ┆ male ┆ masculine ┆ Eriadu ┆ Human │\n", "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", "│ San Hill ┆ 191.0 ┆ null ┆ none ┆ … ┆ male ┆ masculine ┆ Muunilinst ┆ Muun │\n", "│ Grievous ┆ 216.0 ┆ 159.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Kalee ┆ Kaleesh │\n", "│ Tarfful ┆ 234.0 ┆ 136.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Kashyyyk ┆ Wookiee │\n", "│ Raymus Antilles ┆ 188.0 ┆ 79.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Alderaan ┆ Human │\n", "│ Tion Medon ┆ 206.0 ┆ 80.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Utapau ┆ Pau'an │\n", "└───────────────────┴────────┴───────┴───────────────┴───┴──────┴───────────┴────────────┴─────────┘" ] }, "execution_count": 104, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.filter(\n", " col('gender').eq('masculine') & col('height').ge(col('height').median())\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Expand your filter to also exclude rows where a character's \"mass\" is missing (null).\n", "\n", "How many rows remain?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 105, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (28, 11)
nameheightmasshair_colorskin_coloreye_colorbirth_yearsexgenderhomeworldspecies
strf64f64strstrstrf64strstrstrstr
"Darth Vader"202.0136.0"none""white""yellow"41.9"male""masculine""Tatooine""Human"
"Biggs Darklighter"183.084.0"black""light""brown"24.0"male""masculine""Tatooine""Human"
"Obi-Wan Kenobi"182.077.0"auburn, white""fair""blue-gray"57.0"male""masculine""Stewjon""Human"
"Anakin Skywalker"188.084.0"blond""fair""blue"41.9"male""masculine""Tatooine""Human"
"Chewbacca"228.0112.0"brown""unknown""blue"200.0"male""masculine""Kashyyyk""Wookiee"
……………………………
"Wat Tambor"193.048.0"none""green, grey""unknown"null"male""masculine""Skako""Skakoan"
"Grievous"216.0159.0"none""brown, white""green, yellow"null"male""masculine""Kalee""Kaleesh"
"Tarfful"234.0136.0"brown""brown""blue"null"male""masculine""Kashyyyk""Wookiee"
"Raymus Antilles"188.079.0"brown""light""brown"null"male""masculine""Alderaan""Human"
"Tion Medon"206.080.0"none""grey""black"null"male""masculine""Utapau""Pau'an"
" ], "text/plain": [ "shape: (28, 11)\n", "┌───────────────────┬────────┬───────┬───────────────┬───┬──────┬───────────┬───────────┬─────────┐\n", "│ name ┆ height ┆ mass ┆ hair_color ┆ … ┆ sex ┆ gender ┆ homeworld ┆ species │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ f64 ┆ str ┆ ┆ str ┆ str ┆ str ┆ str │\n", "╞═══════════════════╪════════╪═══════╪═══════════════╪═══╪══════╪═══════════╪═══════════╪═════════╡\n", "│ Darth Vader ┆ 202.0 ┆ 136.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Biggs Darklighter ┆ 183.0 ┆ 84.0 ┆ black ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Obi-Wan Kenobi ┆ 182.0 ┆ 77.0 ┆ auburn, white ┆ … ┆ male ┆ masculine ┆ Stewjon ┆ Human │\n", "│ Anakin Skywalker ┆ 188.0 ┆ 84.0 ┆ blond ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Chewbacca ┆ 228.0 ┆ 112.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Kashyyyk ┆ Wookiee │\n", "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", "│ Wat Tambor ┆ 193.0 ┆ 48.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Skako ┆ Skakoan │\n", "│ Grievous ┆ 216.0 ┆ 159.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Kalee ┆ Kaleesh │\n", "│ Tarfful ┆ 234.0 ┆ 136.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Kashyyyk ┆ Wookiee │\n", "│ Raymus Antilles ┆ 188.0 ┆ 79.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Alderaan ┆ Human │\n", "│ Tion Medon ┆ 206.0 ┆ 80.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Utapau ┆ Pau'an │\n", "└───────────────────┴────────┴───────┴───────────────┴───┴──────┴───────────┴───────────┴─────────┘" ] }, "execution_count": 105, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.filter(\n", " col('gender').eq('masculine') & col('height').ge(col('height').median()) & col('mass').is_not_null()\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Expand your filter to include the previous result *or* characters whose \"skin_color\" is 'dark' or 'pale'\n", "\n", "How many rows in this result?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 106, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (37, 11)
nameheightmasshair_colorskin_coloreye_colorbirth_yearsexgenderhomeworldspecies
strf64f64strstrstrf64strstrstrstr
"Darth Vader"202.0136.0"none""white""yellow"41.9"male""masculine""Tatooine""Human"
"Biggs Darklighter"183.084.0"black""light""brown"24.0"male""masculine""Tatooine""Human"
"Obi-Wan Kenobi"182.077.0"auburn, white""fair""blue-gray"57.0"male""masculine""Stewjon""Human"
"Anakin Skywalker"188.084.0"blond""fair""blue"41.9"male""masculine""Tatooine""Human"
"Chewbacca"228.0112.0"brown""unknown""blue"200.0"male""masculine""Kashyyyk""Wookiee"
……………………………
"Tarfful"234.0136.0"brown""brown""blue"null"male""masculine""Kashyyyk""Wookiee"
"Raymus Antilles"188.079.0"brown""light""brown"null"male""masculine""Alderaan""Human"
"Sly Moore"178.048.0"none""pale""white"nullnullnull"Umbara"null
"Tion Medon"206.080.0"none""grey""black"null"male""masculine""Utapau""Pau'an"
"Finn"nullnull"black""dark""dark"null"male""masculine"null"Human"
" ], "text/plain": [ "shape: (37, 11)\n", "┌───────────────────┬────────┬───────┬───────────────┬───┬──────┬───────────┬───────────┬─────────┐\n", "│ name ┆ height ┆ mass ┆ hair_color ┆ … ┆ sex ┆ gender ┆ homeworld ┆ species │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ f64 ┆ str ┆ ┆ str ┆ str ┆ str ┆ str │\n", "╞═══════════════════╪════════╪═══════╪═══════════════╪═══╪══════╪═══════════╪═══════════╪═════════╡\n", "│ Darth Vader ┆ 202.0 ┆ 136.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Biggs Darklighter ┆ 183.0 ┆ 84.0 ┆ black ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Obi-Wan Kenobi ┆ 182.0 ┆ 77.0 ┆ auburn, white ┆ … ┆ male ┆ masculine ┆ Stewjon ┆ Human │\n", "│ Anakin Skywalker ┆ 188.0 ┆ 84.0 ┆ blond ┆ … ┆ male ┆ masculine ┆ Tatooine ┆ Human │\n", "│ Chewbacca ┆ 228.0 ┆ 112.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Kashyyyk ┆ Wookiee │\n", "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", "│ Tarfful ┆ 234.0 ┆ 136.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Kashyyyk ┆ Wookiee │\n", "│ Raymus Antilles ┆ 188.0 ┆ 79.0 ┆ brown ┆ … ┆ male ┆ masculine ┆ Alderaan ┆ Human │\n", "│ Sly Moore ┆ 178.0 ┆ 48.0 ┆ none ┆ … ┆ null ┆ null ┆ Umbara ┆ null │\n", "│ Tion Medon ┆ 206.0 ┆ 80.0 ┆ none ┆ … ┆ male ┆ masculine ┆ Utapau ┆ Pau'an │\n", "│ Finn ┆ null ┆ null ┆ black ┆ … ┆ male ┆ masculine ┆ null ┆ Human │\n", "└───────────────────┴────────┴───────┴───────────────┴───┴──────┴───────────┴───────────┴─────────┘" ] }, "execution_count": 106, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.filter(\n", " (col('gender').eq('masculine') & \n", " col('height').ge(col('height').median()) & \n", " col('mass').is_not_null()) | \n", " col('skin_color').is_in(['dark', 'pale'])\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What is the average height and average mass of characters who are from a \"homeworld\" whose name starts with the letters 'Co'?\n", "\n", "\n", "*Hint: you can \"chain\" a `.select()` onto the result of a `.filter()`*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code\n" ] }, { "cell_type": "code", "execution_count": 107, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (1, 2)
heightmass
f64f64
175.66666771.5
" ], "text/plain": [ "shape: (1, 2)\n", "┌────────────┬──────┐\n", "│ height ┆ mass │\n", "│ --- ┆ --- │\n", "│ f64 ┆ f64 │\n", "╞════════════╪══════╡\n", "│ 175.666667 ┆ 71.5 │\n", "└────────────┴──────┘" ] }, "execution_count": 107, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sw.filter(\n", " col('homeworld').str.starts_with('Co')\n", ").select(\n", " col('height','mass').mean()\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Summarize the mean and standard-deviation of the \"height\" and \"mass\" of all non-Human characters, split by \"sex\", and sort the result by the mean height in *descending order*.\n", "\n", "\n", "*Hint: you can chain a `.group_by()` after a `.filter()`, and chain `.sort()` at the end*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 108, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (4, 5)
sexheight_meanheight_stdmass_meanmass_std
strf64f64f64f64
"female"179.57142916.08163753.8666673.089768
"male"176.91176546.29900776.4834.240717
"hermaphroditic"175.0null1358.0null
"none"131.249.14977169.7551.031853
" ], "text/plain": [ "shape: (4, 5)\n", "┌────────────────┬─────────────┬────────────┬───────────┬───────────┐\n", "│ sex ┆ height_mean ┆ height_std ┆ mass_mean ┆ mass_std │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n", "╞════════════════╪═════════════╪════════════╪═══════════╪═══════════╡\n", "│ female ┆ 179.571429 ┆ 16.081637 ┆ 53.866667 ┆ 3.089768 │\n", "│ male ┆ 176.911765 ┆ 46.299007 ┆ 76.48 ┆ 34.240717 │\n", "│ hermaphroditic ┆ 175.0 ┆ null ┆ 1358.0 ┆ null │\n", "│ none ┆ 131.2 ┆ 49.149771 ┆ 69.75 ┆ 51.031853 │\n", "└────────────────┴─────────────┴────────────┴───────────┴───────────┘" ] }, "execution_count": 108, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.filter(\n", " ~col('species').eq('Human')\n", ").group_by('sex').agg(\n", " height_mean = col('height').mean(),\n", " height_std = col('height').std(),\n", " mass_mean = col('mass').mean(),\n", " mass_std = col('mass').std(),\n", ").sort('height_mean', descending=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Extend your summary to filter out any values of \"sex\" that are \"hermaphroditic\" or \"none\" (not missing/null!)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (2, 5)
sexheight_meanheight_stdmass_meanmass_std
strf64f64f64f64
"female"179.57142916.08163753.8666673.089768
"male"176.91176546.29900776.4834.240717
" ], "text/plain": [ "shape: (2, 5)\n", "┌────────┬─────────────┬────────────┬───────────┬───────────┐\n", "│ sex ┆ height_mean ┆ height_std ┆ mass_mean ┆ mass_std │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n", "╞════════╪═════════════╪════════════╪═══════════╪═══════════╡\n", "│ female ┆ 179.571429 ┆ 16.081637 ┆ 53.866667 ┆ 3.089768 │\n", "│ male ┆ 176.911765 ┆ 46.299007 ┆ 76.48 ┆ 34.240717 │\n", "└────────┴─────────────┴────────────┴───────────┴───────────┘" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw.filter(\n", " ~col('species').eq('Human') & ~col('sex').is_in(['hermaphroditic', 'none'])\n", ").group_by('sex').agg(\n", " height_mean = col('height').mean(),\n", " height_std = col('height').std(),\n", " mass_mean = col('mass').mean(),\n", " mass_std = col('mass').std(),\n", ").sort('height_mean', descending=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Add a column to the original DataFrame called \"mass_lbs\" that converts \"mass\" to lbs by multiplying by 2.2 and drop all remaining columns except: name, height, and species.\n", "\n", "Remove any rows with null values and save the result to a new DataFrame called `sw_processed`" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 110, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (56, 4)
nameheightspeciesmass_lbs
strf64strf64
"Luke Skywalker"172.0"Human"169.4
"C-3PO"167.0"Droid"165.0
"R2-D2"96.0"Droid"70.4
"Darth Vader"202.0"Human"299.2
"Leia Organa"150.0"Human"107.8
…………
"Shaak Ti"178.0"Togruta"125.4
"Grievous"216.0"Kaleesh"349.8
"Tarfful"234.0"Wookiee"299.2
"Raymus Antilles"188.0"Human"173.8
"Tion Medon"206.0"Pau'an"176.0
" ], "text/plain": [ "shape: (56, 4)\n", "┌─────────────────┬────────┬─────────┬──────────┐\n", "│ name ┆ height ┆ species ┆ mass_lbs │\n", "│ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ str ┆ f64 │\n", "╞═════════════════╪════════╪═════════╪══════════╡\n", "│ Luke Skywalker ┆ 172.0 ┆ Human ┆ 169.4 │\n", "│ C-3PO ┆ 167.0 ┆ Droid ┆ 165.0 │\n", "│ R2-D2 ┆ 96.0 ┆ Droid ┆ 70.4 │\n", "│ Darth Vader ┆ 202.0 ┆ Human ┆ 299.2 │\n", "│ Leia Organa ┆ 150.0 ┆ Human ┆ 107.8 │\n", "│ … ┆ … ┆ … ┆ … │\n", "│ Shaak Ti ┆ 178.0 ┆ Togruta ┆ 125.4 │\n", "│ Grievous ┆ 216.0 ┆ Kaleesh ┆ 349.8 │\n", "│ Tarfful ┆ 234.0 ┆ Wookiee ┆ 299.2 │\n", "│ Raymus Antilles ┆ 188.0 ┆ Human ┆ 173.8 │\n", "│ Tion Medon ┆ 206.0 ┆ Pau'an ┆ 176.0 │\n", "└─────────────────┴────────┴─────────┴──────────┘" ] }, "execution_count": 110, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_processed = (\n", " sw.with_columns(\n", " mass_lbs = col('mass') * 2.2\n", " ).select(['name','height','species','mass_lbs']).drop_nulls()\n", ")\n", "sw_processed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the new DataFrame you created `sw_processed` to add 2 additional columns called \"height_z_species\" and \"mass_lbs_z_species\" that are z-scored versions of height and mass_lbs by \"species\"\n", "\n", "Save the DataFrame by overwriting the previous variable `sw_processed`" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 111, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (56, 6)
nameheightspeciesmass_lbsheight_z_speciesmass_lbs_z_species
strf64strf64f64f64
"Luke Skywalker"172.0"Human"169.4-0.71983-0.222945
"C-3PO"167.0"Droid"165.00.5191670.102877
"R2-D2"96.0"Droid"70.4-0.84605-0.739734
"Darth Vader"202.0"Human"299.21.8977352.828964
"Leia Organa"150.0"Human"107.8-2.639378-1.671308
………………
"Shaak Ti"178.0"Togruta"125.4nullnull
"Grievous"216.0"Kaleesh"349.8nullnull
"Tarfful"234.0"Wookiee"299.20.7071070.707107
"Raymus Antilles"188.0"Human"173.80.676204-0.11949
"Tion Medon"206.0"Pau'an"176.0nullnull
" ], "text/plain": [ "shape: (56, 6)\n", "┌─────────────────┬────────┬─────────┬──────────┬──────────────────┬────────────────────┐\n", "│ name ┆ height ┆ species ┆ mass_lbs ┆ height_z_species ┆ mass_lbs_z_species │\n", "│ --- ┆ --- ┆ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ f64 ┆ str ┆ f64 ┆ f64 ┆ f64 │\n", "╞═════════════════╪════════╪═════════╪══════════╪══════════════════╪════════════════════╡\n", "│ Luke Skywalker ┆ 172.0 ┆ Human ┆ 169.4 ┆ -0.71983 ┆ -0.222945 │\n", "│ C-3PO ┆ 167.0 ┆ Droid ┆ 165.0 ┆ 0.519167 ┆ 0.102877 │\n", "│ R2-D2 ┆ 96.0 ┆ Droid ┆ 70.4 ┆ -0.84605 ┆ -0.739734 │\n", "│ Darth Vader ┆ 202.0 ┆ Human ┆ 299.2 ┆ 1.897735 ┆ 2.828964 │\n", "│ Leia Organa ┆ 150.0 ┆ Human ┆ 107.8 ┆ -2.639378 ┆ -1.671308 │\n", "│ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", "│ Shaak Ti ┆ 178.0 ┆ Togruta ┆ 125.4 ┆ null ┆ null │\n", "│ Grievous ┆ 216.0 ┆ Kaleesh ┆ 349.8 ┆ null ┆ null │\n", "│ Tarfful ┆ 234.0 ┆ Wookiee ┆ 299.2 ┆ 0.707107 ┆ 0.707107 │\n", "│ Raymus Antilles ┆ 188.0 ┆ Human ┆ 173.8 ┆ 0.676204 ┆ -0.11949 │\n", "│ Tion Medon ┆ 206.0 ┆ Pau'an ┆ 176.0 ┆ null ┆ null │\n", "└─────────────────┴────────┴─────────┴──────────┴──────────────────┴────────────────────┘" ] }, "execution_count": 111, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "zscore = lambda name: ( col(name) - col(name).mean() ) / col(name).std()\n", "\n", "sw_processed = sw_processed.with_columns(\n", " height_z_species = zscore('height').over('species'),\n", " mass_lbs_z_species = zscore('mass_lbs').over('species'),\n", ")\n", "\n", "sw_processed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Whats the shape of the result?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 112, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(56, 6)" ] }, "execution_count": 112, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_processed.shape" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "How many unique characters are in the result?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 113, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "56" ] }, "execution_count": 113, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sw_processed['name'].n_unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Drop all non-zscored numeric columns and once again save the result to `sw_processed`, overwriting your previous DataFrame" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (56, 4)
namespeciesheight_z_speciesmass_lbs_z_species
strstrf64f64
"Luke Skywalker""Human"-0.71983-0.222945
"C-3PO""Droid"0.5191670.102877
"R2-D2""Droid"-0.84605-0.739734
"Darth Vader""Human"1.8977352.828964
"Leia Organa""Human"-2.639378-1.671308
…………
"Shaak Ti""Togruta"nullnull
"Grievous""Kaleesh"nullnull
"Tarfful""Wookiee"0.7071070.707107
"Raymus Antilles""Human"0.676204-0.11949
"Tion Medon""Pau'an"nullnull
" ], "text/plain": [ "shape: (56, 4)\n", "┌─────────────────┬─────────┬──────────────────┬────────────────────┐\n", "│ name ┆ species ┆ height_z_species ┆ mass_lbs_z_species │\n", "│ --- ┆ --- ┆ --- ┆ --- │\n", "│ str ┆ str ┆ f64 ┆ f64 │\n", "╞═════════════════╪═════════╪══════════════════╪════════════════════╡\n", "│ Luke Skywalker ┆ Human ┆ -0.71983 ┆ -0.222945 │\n", "│ C-3PO ┆ Droid ┆ 0.519167 ┆ 0.102877 │\n", "│ R2-D2 ┆ Droid ┆ -0.84605 ┆ -0.739734 │\n", "│ Darth Vader ┆ Human ┆ 1.897735 ┆ 2.828964 │\n", "│ Leia Organa ┆ Human ┆ -2.639378 ┆ -1.671308 │\n", "│ … ┆ … ┆ … ┆ … │\n", "│ Shaak Ti ┆ Togruta ┆ null ┆ null │\n", "│ Grievous ┆ Kaleesh ┆ null ┆ null │\n", "│ Tarfful ┆ Wookiee ┆ 0.707107 ┆ 0.707107 │\n", "│ Raymus Antilles ┆ Human ┆ 0.676204 ┆ -0.11949 │\n", "│ Tion Medon ┆ Pau'an ┆ null ┆ null │\n", "└─────────────────┴─────────┴──────────────────┴────────────────────┘" ] }, "execution_count": 114, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_processed = sw_processed.drop(['height', 'mass_lbs'])\n", "sw_processed" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What is Leia Organa's height in z-scores?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (1, 2)
nameheight_z_species
strf64
"Leia Organa"-2.639378
" ], "text/plain": [ "shape: (1, 2)\n", "┌─────────────┬──────────────────┐\n", "│ name ┆ height_z_species │\n", "│ --- ┆ --- │\n", "│ str ┆ f64 │\n", "╞═════════════╪══════════════════╡\n", "│ Leia Organa ┆ -2.639378 │\n", "└─────────────┴──────────────────┘" ] }, "execution_count": 117, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_processed.filter(\n", " col('name').eq('Leia Organa')\n", ").select('name', 'height_z_species')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Who's heavier in z-scores, Owen Lars or Darth Vader and by how much approximately?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (2, 2)
namemass_lbs_z_species
strf64
"Darth Vader"2.828964
"Owen Lars"2.001328
" ], "text/plain": [ "shape: (2, 2)\n", "┌─────────────┬────────────────────┐\n", "│ name ┆ mass_lbs_z_species │\n", "│ --- ┆ --- │\n", "│ str ┆ f64 │\n", "╞═════════════╪════════════════════╡\n", "│ Darth Vader ┆ 2.828964 │\n", "│ Owen Lars ┆ 2.001328 │\n", "└─────────────┴────────────────────┘" ] }, "execution_count": 118, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_processed.filter(\n", " col('name').is_in(['Owen Lars', 'Darth Vader'])\n", ").select('name', 'mass_lbs_z_species')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Add in a column to your DataFrame `sw_processed` called \"height_category\" that splits characters based upon the z-scored height. \n", "\n", "If their height is between (or including) -2 and 2 their height_category should be in the \"normal\". \n", "If their height is < -2 their height_category should be in the \"short\". \n", "If their height is > 2 their height_category should be in the \"tall\". \n", "\n", "Take the resulting column along with the \"name\" and \"species\" columns and save them to a new DataFrame variable called `sw_heights`" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (56, 3)
namespeciesheight_category
strstrstr
"Luke Skywalker""Human""normal"
"C-3PO""Droid""normal"
"R2-D2""Droid""normal"
"Darth Vader""Human""normal"
"Leia Organa""Human""short"
………
"Shaak Ti""Togruta""tall"
"Grievous""Kaleesh""tall"
"Tarfful""Wookiee""normal"
"Raymus Antilles""Human""normal"
"Tion Medon""Pau'an""tall"
" ], "text/plain": [ "shape: (56, 3)\n", "┌─────────────────┬─────────┬─────────────────┐\n", "│ name ┆ species ┆ height_category │\n", "│ --- ┆ --- ┆ --- │\n", "│ str ┆ str ┆ str │\n", "╞═════════════════╪═════════╪═════════════════╡\n", "│ Luke Skywalker ┆ Human ┆ normal │\n", "│ C-3PO ┆ Droid ┆ normal │\n", "│ R2-D2 ┆ Droid ┆ normal │\n", "│ Darth Vader ┆ Human ┆ normal │\n", "│ Leia Organa ┆ Human ┆ short │\n", "│ … ┆ … ┆ … │\n", "│ Shaak Ti ┆ Togruta ┆ tall │\n", "│ Grievous ┆ Kaleesh ┆ tall │\n", "│ Tarfful ┆ Wookiee ┆ normal │\n", "│ Raymus Antilles ┆ Human ┆ normal │\n", "│ Tion Medon ┆ Pau'an ┆ tall │\n", "└─────────────────┴─────────┴─────────────────┘" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_heights = sw_processed.with_columns(\n", " height_category = when(col('height_z_species').ge(-2).and_(col('height_z_species').le(2)))\n", " .then(lit('normal'))\n", " .when(col('height_z_species').lt(-2))\n", " .then(lit('short'))\n", " .otherwise(lit('tall'))\n", " \n", ").select('name','species', 'height_category')\n", "sw_heights" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Summarize the number of unique species by \"height_category\". How many of each are there?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (3, 2)
height_categoryspecies
stru32
"short"1
"tall"26
"normal"5
" ], "text/plain": [ "shape: (3, 2)\n", "┌─────────────────┬─────────┐\n", "│ height_category ┆ species │\n", "│ --- ┆ --- │\n", "│ str ┆ u32 │\n", "╞═════════════════╪═════════╡\n", "│ short ┆ 1 │\n", "│ tall ┆ 26 │\n", "│ normal ┆ 5 │\n", "└─────────────────┴─────────┘" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_heights.group_by('height_category').agg(\n", " col('species').n_unique()\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Are there any humans in the \"tall\" category?\n", "\n", "*Hint: try using `.unique()` inside of a `.group_by()` context. Then use a `.select()` context on the result that includes an expression using the [`.list` attribute operations](https://docs.pola.rs/api/python/stable/reference/expressions/list.html) to check if 'Human' is one of the list items*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "shape: (3, 2)
height_categoryspecies
strbool
"normal"true
"short"true
"tall"false
" ], "text/plain": [ "shape: (3, 2)\n", "┌─────────────────┬─────────┐\n", "│ height_category ┆ species │\n", "│ --- ┆ --- │\n", "│ str ┆ bool │\n", "╞═════════════════╪═════════╡\n", "│ normal ┆ true │\n", "│ short ┆ true │\n", "│ tall ┆ false │\n", "└─────────────────┴─────────┘" ] }, "execution_count": 121, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Solution\n", "sw_heights.group_by('height_category').agg(\n", " col('species').unique()\n", ").select(\n", " col('height_category'),\n", " col('species').list.contains('Human')\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Visualizing Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Using the original (unfiltered/aggregated) DataFrame, create a bar-plot showing the mean height for each homeworld and rotate the x-labels by `90` degrees\n", "\n", "*Hint: You can use `sns.barplot` to get back a matplotlib `axis` that you can customize \n", "Or `sns.catplot` with `kind='bar'` to get back a Seaborn [FacetGrid](https://seaborn.pydata.org/generated/seaborn.FacetGrid.html) that is customized slightly differently*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 122, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 582, "width": 507 } }, "output_type": "display_data" } ], "source": [ "g = sns.catplot(data=sw, x='homeworld', y='height', kind='bar')\n", "g.set_xticklabels(rotation=90)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Make a box plot of \"mass\" for only male and female characters who's homeworld is Tatooine, Naboo, or Kashyyyk\n", "\n", "*Hint: you'll have to filter the data first*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 542, "width": 581 } }, "output_type": "display_data" } ], "source": [ "to_plot = sw.filter(\n", " col('sex').is_in(['male', 'female']),\n", " col('homeworld').is_in(['Tatooine', 'Naboo', 'Kashyyyk'])\n", ")\n", "g = sns.catplot(data=to_plot, x='homeworld', y='mass', kind='box', hue='sex')\n", "g.set_xticklabels(rotation=90)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Create a facet-grid of 2 scatter plots between height and mass separately for Tatooine and Naboo\n", "\n", "*Hint: you'll have to filter again first \n", "Then check-out the [multi-plot grid tutorial](https://seaborn.pydata.org/tutorial/axis_grids.html) for help*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 124, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 124, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 290, "width": 625 } }, "output_type": "display_data" } ], "source": [ "to_plot = sw.filter(\n", " col('homeworld').is_in(['Tatooine', 'Naboo'])\n", ")\n", "g = sns.FacetGrid(to_plot, col='homeworld', col_wrap=4)\n", "g.map(sns.scatterplot, 'height', 'mass')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Update the plot to color points by sex\n", "\n", "*Hint: you can use the `.add_legend()` method on a FaceGrid to display the legend* " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 125, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "" ] }, "execution_count": 125, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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HLV26VKdPn1ZycrJOnz6tpUuXqmPHjho2bFiep2wDALJnMXupbd2Kmtk/IsfBmb/VrFkDItSmTkWnW7M80QcAAABKBk/cEn8jYU8Dz7PZ/p4VnN2ap9OnT3f7HK1bt3bk9qZPn65Lly653deNoNCv7CpXriwpbbHdjI9ZrWkfiP3792dqExOT9peda9euFUKEeWOz2dS5c2cdOHBAktSgQQPNnTtX27Zt05o1azR69Gj5+6f9opg8ebImTpzosp/XXntNM2bMkJT2V4CFCxdq586dWrhwoeOvAjNmzGCJBAAoAGYvk9rUCdKOV+/W613CMw3wagb56/Uu4dr56t1qXTvI5UxVT/QBAACAG58nbom/kaTvi+COjPsi4G+1a9d2rLH6+eefu6zz/fffa8qUKW6fo1SpUho1apQk6dy5c+rTp48SErL+w8Hly5c1depUt893vSv0NVhvu+02xcTE6LffftOdd96ZFoTFokaNGmnnzp2aM2eOOnfu7NTms88+kyTVqFGjsMPN0bJlyxzJ1ZYtW2rz5s1OSx7cc889euCBB9SyZUulpKTonXfe0XPPPSeL5e+XPioqSu+//74kKSIiQps2bZKvr68kqWnTpnrggQfUrl07RUZG6r333tOgQYNUq1atQnyWAHDjs5i9FGD2Uv+WoRrcuqbiE5OVkGyXv9WsQD9rrjaj8kQfAAAAuLFxS7wzT+2LgL9VqFBBnTp10vLly7VixQrdf//9GjZsmKpXr67z589ryZIlmjt3rmrWrKn4+HhduHDBrfO8+OKL+uGHH/TDDz9o5cqVql+/vp544gm1bNlSgYGBunz5sg4fPqwNGzbom2++UalSpTR8+HAPP9vrQ6G/C9u3by/DMLRu3Tqnxx999FHHOqv9+/fX8uXL9b///U9du3bV6tWrZTKZ1K1bt8ION0c//fST4/jll192Sq6ma9Kkibp06SIpbfHgQ4cOOZVPnjzZMX17ypQpjuRqOj8/P8dfFWw2mz788ENPPgUAQAbpA7RAP6uqBfo6bjnKy8DNE30AAADgxsQt8Zmxp4HnTZs2TdWrp80MXr16tXr06KGIiAh16tRJs2bNUrVq1fTNN9/Iz8/9HcLMZrO+++479e/fX1LaHeivvPKK7rzzTjVq1Eht27bV0KFDNX/+fCUkJKhMmTIeeW7Xo0J/J3bv3l1S2mZOv//+u+PxYcOGqXHjxjIMQ/Pnz9cDDzygPn36aMWKFZKk6tWr66WXXirscHOUnPz32ic1a9bMsl7GGacZN/IyDEPLli2TJNWrV08tWrRw2b5Fixa6+eabJUnffPMNa7ECAAAAAFAMcUt8Zuxp4HkhISHas2ePXnjhBdWtW1c+Pj4qW7asbr/9do0ZM0b79u1T/fr1830eX19fzZs3T5GRkXryySd1yy23qGzZsrJYLAoMDFTDhg01ePBgffXVVzp48KAHntn1yWQUQaYuOjpadrtdVatWdZqtefHiRT3zzDNavHixY7czk8mkTp06adq0aQoODi7sUHP08ccf69lnn5Ukffvtt+ratavLej169NDSpUtlMpkUHx/vyNofP37ckXwdNmxYtgsMDxs2zLFO6/HjxxUWFuaR5xAbG6uQkBBJaRt2XY+vMwAAuH4xlgAAIG+uJNnUfNy6PN8Sv/PVu+XvU+irPRYamz1V12ypWrQrRv/dHuO0GVjNIH/1bVFdfZpWl4/Fi+QqritF8qkMDQ11+Xi5cuX0xRdf6NNPP9XRo0dls9lUu3Ztx65k16OHH35Yr7/+ui5duqT33ntPnTp1yrRMwN69e7V8+XJJUp8+fZymRGfM3terVy/bc2UsP3jwoMcSrAAAAAAAoPCk3xI/5PNI2VNznvdWUm6JZ08DFFfX5Z89SpcurcaNGxd1GLlSsWJFzZ07V3379tVPP/2kpk2bauTIkapbt66uXLmin376SZMmTVJycrIaNmyoDz74wKn9qVOnHMc5zfZInxnyz3Y5iY2Nzbb87Nmzue4LAACUPIwlAADwrIy3xA9fsCfbmaz+VrM+6dtYbepUzPUapcVdxj0NAv0yPw5cb67LBGtx0717d0VGRuqDDz7Q7NmzNWDAAKfyypUr64033tDjjz8uf3/nhawvX77sOA4ICMj2PBnbXrlyJdfxZUzMAgAA5BVjCQAAPM/sZVKbOkHa8erdubolvqQkV4HiqMgSrDabTcuXL9fmzZt1/PhxXb58WXZ79muPmEwm/fDDD4UUYe6lpKRowYIF+u6771xuPvX7779r4cKFqlu3rjp37uxUdu3aNcex1Zr9ToA+Pj6O46tXr+YzagAAAAAAUJS4JR64MRRJgnXDhg0aNGiQYmJiHI9lt9eWyWSSYRgyma6/v9YkJCSoU6dO2rRpk8xms1588UUNGjRINWvW1LVr17Rjxw69+eab2rJli7p27arJkyc7NsWSpFKlSjmOk5OTsz1XUlKS4zjj5mA5yWk5gbNnz6pZs2a57g8AAJQsjCUAAChY3BIPFG+FnmDdt2+fOnbsqOTkZBmGoVKlSqlOnToKDAyUl1fx+8UxZswYbdq0SZI0a9Ysp+UBrFar7rnnHt1555269957tX79ev373//WnXfeqQYNGkhKW282XU63/Sck/H2rQE7LCWTETr4Arkfpf42/mJCshGSb/K0WlfPnr/TA9YixBAAAAJC1Qk+wjh07VklJSfLx8dEHH3ygQYMGOc3iLE4Mw9CcOXMkSXXr1s209mo6i8Wit956S61bt1ZqaqrmzJmjyZMnS3K+YMlpA4mMs0dYCw1AcWWzp+qaLVVf7ozR/B3O60yFBfmrb/Pq6tOsukpZvGQh0QoAAAAAuM4VeoJ1y5YtMplMevXVV/Xkk08W9uk96vfff9eff/4pSWrUqFG2dZs0aeI4PnTokOO4fv36Lh93JWN5eHh4nmIFgOuBPdXQ5qNxWe6UeiIuQW8vP6jJa49o6iON1bZuydkpFQAAAABQPBX61KD0TZ3uv//+wj61x1ksf+enbTZbtnVTUlJctgsLC1PVqlUlSRs3bsy2j/SlCKpVq6bQ0NC8hgsARcpmT9WmIxc05PNIl8nVjBKS7RryeaQ2H70gmz21kCIEAAAAACDvCj3Bmp4YzJhwLK7Kly+vMmXKSJK2bduWbZI1Y/I0LCzMcWwymdStWzdJaTNUt2/f7rL99u3bHTNYu3Xrdl1u+AUA2blmS9XwBXtkT816U8OM7KmGnp6/R0k2EqwAAAAAgOtXoSdYH3zwQUl/z8Yszry8vNS5c2dJ0pkzZzRu3DiX9S5evKiXXnrJ8X2XLl2cykeOHOmY1TpixAhdvXrVqfzq1asaMWKEpLTZryNHjvTUUwCAQpFiT1tzNaeZq/+UkGzXl7tilMIsVgAAAADAdarQE6zPPvusqlSpookTJyo6OrqwT+9xo0ePlp+fn6S0DbweeOABLVmyRHv37tW2bds0efJkNWzYUL/99psk6a677tK9997r1EfdunU1atQoSVJkZKRatWqlRYsWKTIyUosWLVKrVq0UGRkpSXrhhRdUp06dQnyGAJB/3mYvzd8R41bb+dtj5M1mVwAAAACA65TJMIzc3avpQfv371eXLl2UlJSkcePGqVevXipbtmxhh+Ex69at08MPP6y4uLhs63Xo0EFfffWVypUrl6ksNTVVQ4cO1ezZs7NsP3jwYM2YMUNeXp5NNMTGxiokJESSdOrUKQUHB3u0fwC4mJCsRm+tdbv9vtH3KNDP6sGIAHgSYwkAAACUZEWSYJWk6OhoNW/eXHFxcTKZTAoKCnLMBM2KyWTSsWPHCinCvPnjjz80a9YsrVy5Ur/++qvi4+NlsVh00003qWnTpnrkkUf0wAMP5Lh26ooVKzRjxgzt2rVLcXFxCgoKUtOmTTVs2DB17NixQGLnogjAP6Wkpsjby1vx1+KVaEuUn8VPgaUC0x6Xl+RllhL/kJITJKu/5FdBsqdIZm+X/cVeTFTr99a7Hc9P/9dB1QJ93W4PoGAxlgBQEFLsqfI2e+liQrISkm3yt1pUzt/qeBwAgOtFkSRYlyxZosGDB+vy5cvKy+lNJpPs9ryt34eccVEEIJ0t1aYke5KWHFmixUcW6+Slk46yGmVqqHfd3upZp7t87DZZ5veSYnelFVaoJUU8JjUeKFlKSWaLU7/MYAVubIwlAHiSzZ6qa7a09dvn74jRibgER1lYkL/6Nq+uPs2qq5TFSxYSrQCA60ChJ1i3bdumtm3bOhKlNWrUUIMGDRQYGJirW9/nzJlT0CGWOFwUAZAku2HX1tNbNWrjKCXaErOs52fx08Q27+mOKs1lntf17ySrJFkDpF5zpFp3pc1yzeDOiRucLpByq2aQv34c1T7P7QAUHsYSADzFnmpo05ELGr5gT7abY/pbzZr6SGO1rVtRZq/s7xIEAKCgWXKu4llvv/227Ha7ypYtqwULFhTYbe8AgNyzpdq07cw2jfhxhOxG9ncKJNoSNWLDSE2980O1eGSRLFObpi0XIEnJV6SFfaSHF0k173TMZE2xp6pv8+p6e/nBPMfWt0V1bgUEAKAEsNlTtflonIZ8Hil7avbzgBKS7RryeaRmDYhQ69pBzGQFABSpQv9faPfu3TKZTHrjjTdIrgLAdSLJnqRRG0flmFxNZzfsen7TS0o2e0uN+zsXptql/w2U7NccD3mbvdSnWXX5W51ntebE32pWn6bVSa4CAFACXLOlaviCPTkmV9PZUw09PX+PkmypBRwZAADZK/Qr1oSEtNtDW7duXdinBgC4kJKaoiVHlmS7LIAribZELTm2TCkRj0mmf/x3knxF2j0vbeOr/6+UxUtTH2mc69v4zF4mfdK3sXwsJFcBALjRpdjT1lzNblkAVxKS7fpyV4xS7CRZAQBFp9CvWsPCwiRJiYl5u5AHABQMby9vLT6y2K22iw8vlndgdalWh8yFkbMls7fjW4vZS23rVtTM/hE5zmT1t5o1a0CE2tSpyC1/AACUAN5mL83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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 290, "width": 684 } }, "output_type": "display_data" } ], "source": [ "to_plot = sw.filter(\n", " col('homeworld').is_in(['Tatooine', 'Naboo'])\n", ")\n", "g = sns.FacetGrid(to_plot, col='homeworld', hue='sex')\n", "g.map(sns.scatterplot, 'height', 'mass')\n", "g.add_legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Remove the color by gender and add a regression line to each plot. \n", "For which homeworld is there a stronger relationship?\n", "\n", "*Hint: you can use the `.add_legend()` method on a FaceGrid to display the legend* " ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here\n" ] }, { "cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 126, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "" ] }, "execution_count": 126, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 290, "width": 607 } }, "output_type": "display_data" } ], "source": [ "to_plot = sw.filter(\n", " col('homeworld').is_in(['Tatooine', 'Naboo'])\n", ")\n", "g = sns.FacetGrid(to_plot, col='homeworld')\n", "g.map(sns.regplot, 'height', 'mass')\n", "g.add_legend()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Take a look at the pairwise relationships between all *numeric* columns\n", "\n", "*Hint: you'll have to select the columns you want first \n", "Then take a look at `sns.pairplot()` \n", "If you run into an error, remember you can eaasily convert between a Polars and Pandas DataFrame*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Your code here" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 127, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "image/png": { "height": 741, "width": 740 } }, "output_type": "display_data" } ], "source": [ "to_plot = sw.select(\n", " cs.numeric()\n", ").to_pandas()\n", "\n", "sns.pairplot(to_plot)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [] } ], "metadata": { "kernelspec": { "display_name": "201b", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.10" } }, "nbformat": 4, "nbformat_minor": 2 }