{"id":8710,"date":"2024-05-21T17:52:48","date_gmt":"2024-05-21T15:52:48","guid":{"rendered":"https:\/\/softinery.com\/pl\/?page_id=8710"},"modified":"2025-02-10T15:45:04","modified_gmt":"2025-02-10T14:45:04","slug":"wykresy-python","status":"publish","type":"page","link":"https:\/\/softinery.com\/pl\/blog\/wykresy-python\/","title":{"rendered":"Wykresy Python: matplotlib i inne biblioteki do wizualizacji"},"content":{"rendered":"<style>.kb-table-of-content-nav.kb-table-of-content-id8710_faa9ff-57 .kb-table-of-content-wrap{padding-top:var(--global-kb-spacing-sm, 1.5rem);padding-right:var(--global-kb-spacing-sm, 1.5rem);padding-bottom:var(--global-kb-spacing-sm, 1.5rem);padding-left:var(--global-kb-spacing-sm, 1.5rem);}.kb-table-of-content-nav.kb-table-of-content-id8710_faa9ff-57 .kb-table-of-contents-title-wrap{padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.kb-table-of-content-nav.kb-table-of-content-id8710_faa9ff-57 .kb-table-of-contents-title{font-weight:regular;font-style:normal;}.kb-table-of-content-nav.kb-table-of-content-id8710_faa9ff-57 .kb-table-of-content-wrap .kb-table-of-content-list{font-weight:regular;font-style:normal;margin-top:var(--global-kb-spacing-sm, 1.5rem);margin-right:0px;margin-bottom:0px;margin-left:0px;}<\/style>\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_657e59-89, .wp-block-kadence-advancedheading.kt-adv-heading8710_657e59-89[data-kb-block=\"kb-adv-heading8710_657e59-89\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_657e59-89 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_657e59-89[data-kb-block=\"kb-adv-heading8710_657e59-89\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_657e59-89 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_657e59-89[data-kb-block=\"kb-adv-heading8710_657e59-89\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h2 class=\"kt-adv-heading8710_657e59-89 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_657e59-89\">Wst\u0119p<\/h2>\n\n\n\n<p>Tworzenie wykres\u00f3w jest jednym z podstawowych zada\u0144 w wielu zagadnieniach, w analizie danych i statystyce, <a href=\"https:\/\/softinery.com\/pl\/blog\/wizualizacja-danych\/\">wizualizacji danych w tym danych biznesowych<\/a>, oraz naukach in\u017cynierskich i przyrodniczych. St\u0105d te\u017c mamy bardzo wiele r\u00f3\u017cnych typ\u00f3w wykres\u00f3w, przeznaczonych do przedstawiania r\u00f3\u017cnego rodzaju danych. Z tych wzgl\u0119d\u00f3w dla j\u0119zyka Python stworzono kilka bibliotek, kt\u00f3re dedykowane s\u0105 tworzeniu wykres\u00f3w. Om\u00f3wi\u0119 je w tym artykule.<\/p>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_43f04a-cf, .wp-block-kadence-advancedheading.kt-adv-heading8710_43f04a-cf[data-kb-block=\"kb-adv-heading8710_43f04a-cf\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_43f04a-cf mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_43f04a-cf[data-kb-block=\"kb-adv-heading8710_43f04a-cf\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_43f04a-cf img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_43f04a-cf[data-kb-block=\"kb-adv-heading8710_43f04a-cf\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h2 class=\"kt-adv-heading8710_43f04a-cf wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_43f04a-cf\">Wykresy w Python &#8211; biblioteki<\/h2>\n\n\n\n<p>Poni\u017cej zestawi\u0142em kilka najpopularniejszych bibliotek i kr\u00f3tko opisa\u0142em ich przeznaczenie. W nast\u0119pnym akapicie przedstawi\u0119 praktyczne przyk\u0142ady ich zastosowania.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"http:\/\/matplotlib.org\">matplotlib<\/a> &#8211; chyba najpopularniejsza biblioteka dla Pythona przeznaczona do tworzenia wykres\u00f3w. S\u0142ynie ona z mo\u017cliwo\u015bci tworzenia wysokiej jako\u015bci diagram\u00f3w, ale r\u00f3wnie\u017c z prostoty. Przy u\u017cyciu tej biblioteki stworzymy wi\u0119kszo\u015b\u0107 typ\u00f3w wykres\u00f3w, takich jak ko\u0142owe, s\u0142upkowe, punktowe, jak r\u00f3wnie\u017c wykresy tr\u00f3jwymiarowe.<\/li>\n\n\n\n<li><a href=\"http:\/\/plotly.com\">plotly<\/a> &#8211; zalet\u0105 tej biblioteki jest mo\u017cliwo\u015b\u0107 tworzenia wykres\u00f3w interaktywnych, pozwalaj\u0105cych na modyfikacj\u0119 wy\u015bwietlanych wynik\u00f3w przez u\u017cytkownika. Dzi\u0119ki temu doskonale przydaje si\u0119 w analizie danych, gdzie bardzo wygodne jest np. filtrowanie danych.  Z jej u\u017cyciem tworzone s\u0105 r\u00f3wnie\u017c tzw. dashboardy, czyli strony internetowe przedstawiaj\u0105ce kompleksowe zestawienie danych dotycz\u0105cych konkretnego zagadnienia.<\/li>\n\n\n\n<li><a href=\"https:\/\/seaborn.pydata.org\/\">seaborn<\/a> &#8211; biblioteka, kt\u00f3ra jest cz\u0119sto stosowana w statystyce i analizie danych. Dzi\u0119ki integracji z dedykowan\u0105 do <a href=\"https:\/\/softinery.com\/pl\/katalog-szkolen\/python-data-science-kurs\/\">data science<\/a> bibliotek\u0105 pandas, z \u0142atwo\u015bci\u0105 stworzymy takie wykresy jak histogramy, czy wykresy pude\u0142kowe.<\/li>\n<\/ul>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_7daac3-d2, .wp-block-kadence-advancedheading.kt-adv-heading8710_7daac3-d2[data-kb-block=\"kb-adv-heading8710_7daac3-d2\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_7daac3-d2 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_7daac3-d2[data-kb-block=\"kb-adv-heading8710_7daac3-d2\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_7daac3-d2 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_7daac3-d2[data-kb-block=\"kb-adv-heading8710_7daac3-d2\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h2 class=\"kt-adv-heading8710_7daac3-d2 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_7daac3-d2\">Instalacja bibliotek do tworzenia wykres\u00f3w w Pythonie<\/h2>\n\n\n\n<p>Najprostszym sposobem na zainstalowanie biblioteki Pythona jest skorzystanie z komendy pip. Wymogiem jest wcze\u015bniejsza <a href=\"https:\/\/softinery.com\/pl\/blog\/python-instalacja-srodowiska-ide\/\">instalacja Pythona w systemie<\/a>. Bibliotek\u0119 instalujemy w terminalu (w systemie Windows jest to cmd) przy u\u017cyciu komendy:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>pip install nazwa_biblioteki<\/code><\/pre>\n\n\n\n<p>Zgodnie z powy\u017csz\u0105 komend\u0105, bibliotek\u0119 matplotlib instalujemy komend\u0105:<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code>pip install matplotlib<\/code><\/pre>\n\n\n\n<p>Analogicznie instalujemy pozosta\u0142e biblioteki.<\/p>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_866eb9-d9, .wp-block-kadence-advancedheading.kt-adv-heading8710_866eb9-d9[data-kb-block=\"kb-adv-heading8710_866eb9-d9\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_866eb9-d9 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_866eb9-d9[data-kb-block=\"kb-adv-heading8710_866eb9-d9\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_866eb9-d9 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_866eb9-d9[data-kb-block=\"kb-adv-heading8710_866eb9-d9\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h2 class=\"kt-adv-heading8710_866eb9-d9 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_866eb9-d9\">Tworzenie wykresu przy u\u017cyciu biblioteki matplotlib<\/h2>\n\n\n\n<p>Zaczniemy od najpopularniejszej biblioteki, czyli matplotlib. Do napisania programu potrzebna jest podstawowa wiedza na temat programowania w Pythonie (mo\u017cesz j\u0105 naby\u0107 podczas <a href=\"https:\/\/softinery.com\/pl\/katalog-szkolen\/kurs-python-dla-poczatkujacych\/\">kursu podstawowego z Pythona<\/a>). <\/p>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_4870fe-04, .wp-block-kadence-advancedheading.kt-adv-heading8710_4870fe-04[data-kb-block=\"kb-adv-heading8710_4870fe-04\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_4870fe-04 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_4870fe-04[data-kb-block=\"kb-adv-heading8710_4870fe-04\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_4870fe-04 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_4870fe-04[data-kb-block=\"kb-adv-heading8710_4870fe-04\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h3 class=\"kt-adv-heading8710_4870fe-04 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_4870fe-04\">Wykres liniowy w bilbiotece matplotlib<\/h3>\n\n\n\n<p>Prosty wykres liniowy stworzymy przy u\u017cyciu nast\u0119puj\u0105cego kodu:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers cbp-highlight-hover\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#24292e;--cbp-line-number-width:calc(1 * 0.6 * .875rem);--cbp-line-highlight-color:rgba(16, 41, 67, 0.2);line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:16px 0 0 16px;width:100%;text-align:left;background-color:#ffffff\"><span style=\"background:#2f363c;padding:0.3rem 0.5rem 0.2rem;border-radius:1rem;font-size:0.8em;line-height:1;height:1.25rem;text-align:center;display:inline-flex;align-items:center;justify-content:center;color:#ffffff\">Python<\/span><\/span><span role=\"button\" tabindex=\"0\" data-code=\"import matplotlib.pyplot as plt\nx = [1, 2, 3, 4]\ny = [1, 4, 9, 16]\nplt.plot(x,y)\n\nplt.xlabel('x')\nplt.ylabel('y')\nplt.show()\" style=\"color:#24292e;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki github-light\" style=\"background-color: #fff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #D73A49\">import<\/span><span style=\"color: #24292E\"> matplotlib.pyplot <\/span><span style=\"color: #D73A49\">as<\/span><span style=\"color: #24292E\"> plt<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">x <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">2<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">3<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">y <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">9<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">16<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.plot(x,y)<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.xlabel(<\/span><span style=\"color: #032F62\">&#39;x&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.ylabel(<\/span><span style=\"color: #032F62\">&#39;y&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.show()<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p>W linii 1 importujemy <a href=\"https:\/\/softinery.com\/pl\/blog\/kurs-python-moduly-i-pakiety\/\">modu\u0142<\/a> matplotlib.pyplot i nadajemy mu skr\u00f3t plt. W linii 2 i 3 definiujemy nasze dane w postaci <a href=\"https:\/\/softinery.com\/pl\/darmowy-kurs-python-online\/python-listy\/\">list pythona<\/a>. Nast\u0119pnie (linia 4) tworzymy wykres przy u\u017cyciu metody <code>plot<\/code>, podaj\u0105c jako argumenty wcze\u015bniej stworzone listy <em>x<\/em> oraz <em>y<\/em>. Tak wywo\u0142ana metoda stworzy graficzn\u0105 zale\u017cno\u015b\u0107 <em>y<\/em>(<em>x<\/em>). W liniach 6 i 7 nadajemy etykiety osiom. W tym przyk\u0142adzie s\u0105 to po prostu: &#8216;x&#8217; oraz &#8216;y&#8217;. Na ko\u0144cu metoda show() powoduje wy\u015bwietlenie tak zdefiniowanego wykresu.<\/p>\n\n\n<style>.kb-image8710_94b040-7d.kb-image-is-ratio-size, .kb-image8710_94b040-7d .kb-image-is-ratio-size{max-width:450px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_94b040-7d.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_94b040-7d .kb-image-is-ratio-size{align-self:unset;}.kb-image8710_94b040-7d figure{max-width:450px;}.kb-image8710_94b040-7d .image-is-svg, .kb-image8710_94b040-7d .image-is-svg img{width:100%;}.kb-image8710_94b040-7d .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image8710_94b040-7d\"><figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"563\" height=\"432\" src=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-_rys.-1_.webp\" alt=\"Przyk\u0142ad wykresu w matplotlib - python wykresy\" class=\"kb-img wp-image-8729\" srcset=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-_rys.-1_.webp 563w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-_rys.-1_-300x230.webp 300w\" sizes=\"auto, (max-width: 563px) 100vw, 563px\" \/><figcaption>Rys. 1. Przyk\u0142ad wykresu liniowego stworzonego w bibliotece matplotlib dla Pythona<\/figcaption><\/figure><\/div>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_88bf7f-62, .wp-block-kadence-advancedheading.kt-adv-heading8710_88bf7f-62[data-kb-block=\"kb-adv-heading8710_88bf7f-62\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_88bf7f-62 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_88bf7f-62[data-kb-block=\"kb-adv-heading8710_88bf7f-62\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_88bf7f-62 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_88bf7f-62[data-kb-block=\"kb-adv-heading8710_88bf7f-62\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h3 class=\"kt-adv-heading8710_88bf7f-62 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_88bf7f-62\">Wykres punktowy w bibliotece matplotlib<\/h3>\n\n\n\n<p>Je\u017celi chcemy narysowa\u0107 seri\u0119 danych w postaci punkt\u00f3w, to mo\u017cemy zmodyfikowa\u0107 kod do nast\u0119puj\u0105cej postaci:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers cbp-highlight-hover\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#24292e;--cbp-line-number-width:calc(1 * 0.6 * .875rem);--cbp-line-highlight-color:rgba(16, 41, 67, 0.2);line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:16px 0 0 16px;width:100%;text-align:left;background-color:#ffffff\"><span style=\"background:#2f363c;padding:0.3rem 0.5rem 0.2rem;border-radius:1rem;font-size:0.8em;line-height:1;height:1.25rem;text-align:center;display:inline-flex;align-items:center;justify-content:center;color:#ffffff\">Python<\/span><\/span><span role=\"button\" tabindex=\"0\" data-code=\"# import i defnicja danych jak w poprzednim przyk\u0142adzie\n\nplt.plot(x,y, 'ro')\nplt.xlabel('x')\nplt.ylabel('y')\nplt.show()\" style=\"color:#24292e;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki github-light\" style=\"background-color: #fff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #6A737D\"># import i defnicja danych jak w poprzednim przyk\u0142adzie<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.plot(x,y, <\/span><span style=\"color: #032F62\">&#39;ro&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.xlabel(<\/span><span style=\"color: #032F62\">&#39;x&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.ylabel(<\/span><span style=\"color: #032F62\">&#39;y&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.show()<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p>W metodzie <code>plot<\/code> dodany jest argument <code>'ro'<\/code>. Oznacza on u\u017cycie koloru czerwonego i punkt\u00f3w. Skr\u00f3t <code>r<\/code> pochodzi od koloru czerwonego (red), a <code>o<\/code> oznacza okr\u0105g\u0142e symbole. Oznaczenia s\u0105 do\u015b\u0107 intuicyjne i przy odrobinie wprawy bardzo \u0142atwo okre\u015bli\u0107 interesuj\u0105ce nas oznaczenie (np. <code>b<\/code> to blue, <code>--<\/code> to linia przerywana, itd.). Pe\u0142n\u0105 list\u0119 skr\u00f3t\u00f3w znajdziemy na stronie z <a href=\"https:\/\/matplotlib.org\/2.1.1\/api\/_as_gen\/matplotlib.pyplot.plot.html\">dokumentacj\u0105 matplotlib<\/a>.<\/p>\n\n\n<style>.kb-image8710_c3dfab-df.kb-image-is-ratio-size, .kb-image8710_c3dfab-df .kb-image-is-ratio-size{max-width:450px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_c3dfab-df.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_c3dfab-df .kb-image-is-ratio-size{align-self:unset;}.kb-image8710_c3dfab-df figure{max-width:450px;}.kb-image8710_c3dfab-df .image-is-svg, .kb-image8710_c3dfab-df .image-is-svg img{width:100%;}.kb-image8710_c3dfab-df .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image8710_c3dfab-df\"><figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"563\" height=\"432\" src=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-rysunku-punktowego-_rys.-2_.webp\" alt=\"Przyk\u0142ad wykresu punktowego w matplotlib w Pythonie\" class=\"kb-img wp-image-8731\" srcset=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-rysunku-punktowego-_rys.-2_.webp 563w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-rysunku-punktowego-_rys.-2_-300x230.webp 300w\" sizes=\"auto, (max-width: 563px) 100vw, 563px\" \/><figcaption>Rys. 2. Przyk\u0142ad wykresu punktowego stworzonego w bibliotece matplotlib dla Pythona<\/figcaption><\/figure><\/div>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_e1ffb7-2b, .wp-block-kadence-advancedheading.kt-adv-heading8710_e1ffb7-2b[data-kb-block=\"kb-adv-heading8710_e1ffb7-2b\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_e1ffb7-2b mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_e1ffb7-2b[data-kb-block=\"kb-adv-heading8710_e1ffb7-2b\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_e1ffb7-2b img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_e1ffb7-2b[data-kb-block=\"kb-adv-heading8710_e1ffb7-2b\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h3 class=\"kt-adv-heading8710_e1ffb7-2b wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_e1ffb7-2b\">Wykres z wieloma seriami danych w bibliotece matplotlib<\/h3>\n\n\n\n<p>Kolejny przyk\u0142ad dotyczy wykresu z wieloma seriami danych.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers cbp-highlight-hover\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#24292e;--cbp-line-number-width:calc(2 * 0.6 * .875rem);--cbp-line-highlight-color:rgba(16, 41, 67, 0.2);line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:16px 0 0 16px;width:100%;text-align:left;background-color:#ffffff\"><span style=\"background:#2f363c;padding:0.3rem 0.5rem 0.2rem;border-radius:1rem;font-size:0.8em;line-height:1;height:1.25rem;text-align:center;display:inline-flex;align-items:center;justify-content:center;color:#ffffff\">Python<\/span><\/span><span role=\"button\" tabindex=\"0\" data-code=\"import matplotlib.pyplot as plt\n\nx = [1, 2, 3, 4]\ny1 = [1, 4, 9, 16]\ny2 = [1, 2, 3, 4]\ny3 = [1, 8, 29, 64]\nplt.plot(x,y1,'ro',x,y2,'bv',x,y3,'gs')\nplt.xlabel('x')\nplt.ylabel('y')\nplt.show()\" style=\"color:#24292e;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki github-light\" style=\"background-color: #fff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #D73A49\">import<\/span><span style=\"color: #24292E\"> matplotlib.pyplot <\/span><span style=\"color: #D73A49\">as<\/span><span style=\"color: #24292E\"> plt<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">x <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">2<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">3<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">y1 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">9<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">16<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">y2 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">2<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">3<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">y3 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">8<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">29<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">64<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.plot(x,y1,<\/span><span style=\"color: #032F62\">&#39;ro&#39;<\/span><span style=\"color: #24292E\">,x,y2,<\/span><span style=\"color: #032F62\">&#39;bv&#39;<\/span><span style=\"color: #24292E\">,x,y3,<\/span><span style=\"color: #032F62\">&#39;gs&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.xlabel(<\/span><span style=\"color: #032F62\">&#39;x&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.ylabel(<\/span><span style=\"color: #032F62\">&#39;y&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.show()<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p>W liniach 3-6 stworzyli\u015bmy kilka serii danych. Mamy jedn\u0105 list\u0119 <code>x<\/code> oraz trzy listy <code>y<\/code> (<code>y1<\/code>, <code>y2<\/code>, <code>y3<\/code>). W linii 7 w kodzie powy\u017cej wywo\u0142ali\u015bmy metod\u0119 <code>plot<\/code>, podaj\u0105c kolejno serie danych i styl, w jakim maj\u0105 by\u0107 wyrysowane. Seria <code>x<\/code>, <code>y1<\/code> b\u0119dzie wyrysowana z u\u017cyciem czerwonych k\u00f3\u0142ek, seria <code>x<\/code>, <code>y2<\/code> przy u\u017cyciu niebieskich tr\u00f3jk\u0105t\u00f3w, a seria <code>x<\/code>, <code>y3<\/code> przy u\u017cyciu zielonych kwadrat\u00f3w (rys. 3).<\/p>\n\n\n<style>.kb-image8710_dcd1d0-de.kb-image-is-ratio-size, .kb-image8710_dcd1d0-de .kb-image-is-ratio-size{max-width:450px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_dcd1d0-de.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_dcd1d0-de .kb-image-is-ratio-size{align-self:unset;}.kb-image8710_dcd1d0-de figure{max-width:450px;}.kb-image8710_dcd1d0-de .image-is-svg, .kb-image8710_dcd1d0-de .image-is-svg img{width:100%;}.kb-image8710_dcd1d0-de .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image8710_dcd1d0-de\"><figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"562\" height=\"432\" src=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-rysunku-z-wieloma-seriami-danych-_rys.-3_.webp\" alt=\"Przyk\u0142ad wykresu matplotlib w pythonie z wieloma seriami danych\" class=\"kb-img wp-image-8737\" srcset=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-rysunku-z-wieloma-seriami-danych-_rys.-3_.webp 562w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-rysunku-z-wieloma-seriami-danych-_rys.-3_-300x231.webp 300w\" sizes=\"auto, (max-width: 562px) 100vw, 562px\" \/><figcaption>Rys. 3. Przyk\u0142ad wykresu matplotlib w Pythonie z wieloma seriami danych<\/figcaption><\/figure><\/div>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_6c3893-53, .wp-block-kadence-advancedheading.kt-adv-heading8710_6c3893-53[data-kb-block=\"kb-adv-heading8710_6c3893-53\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_6c3893-53 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_6c3893-53[data-kb-block=\"kb-adv-heading8710_6c3893-53\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_6c3893-53 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_6c3893-53[data-kb-block=\"kb-adv-heading8710_6c3893-53\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h3 class=\"kt-adv-heading8710_6c3893-53 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_6c3893-53\">Histogram z u\u017cyciem biblioteki matplotlib<\/h3>\n\n\n\n<p>Histogram to rodzaj wykresu, kt\u00f3ry przedstawia rozk\u0142ad cz\u0119sto\u015bci wyst\u0119powania warto\u015bci w zbiorze danych. Przedstawia szereg s\u0142upk\u00f3w, kt\u00f3rych szeroko\u015b\u0107 reprezentuje przedzia\u0142 warto\u015bci, a wysoko\u015b\u0107 odpowiada liczbie obserwacji w tym przedziale. W przyk\u0142adzie poni\u017cej najpierw genereujemy dane w postaci rozk\u0142adu normalnego (linie 4-10) przy u\u017cyciu biblioteki <a href=\"https:\/\/numpy.org\/\">numpy<\/a>. Jest to jedna z podstawowych bibliotek wykorzystywanych w <a href=\"https:\/\/softinery.com\/pl\/katalog-szkolen\/wprowadzenie-do-obliczen-naukowych\/\">r\u00f3\u017cnego rodzaju obliczeniach<\/a> i analizie danych. W dalszej cz\u0119\u015bci programu tworzymy wykres przy u\u017cyciu funkcji <code>hist()<\/code>. Jednym z argument\u00f3w jest <code>bins<\/code> czyi liczba przedzia\u0142\u00f3w na wykresie.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers cbp-highlight-hover\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#24292e;--cbp-line-number-width:calc(2 * 0.6 * .875rem);--cbp-line-highlight-color:rgba(16, 41, 67, 0.2);line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:16px 0 0 16px;width:100%;text-align:left;background-color:#ffffff\"><span style=\"background:#2f363c;padding:0.3rem 0.5rem 0.2rem;border-radius:1rem;font-size:0.8em;line-height:1;height:1.25rem;text-align:center;display:inline-flex;align-items:center;justify-content:center;color:#ffffff\">Python<\/span><\/span><span role=\"button\" tabindex=\"0\" data-code=\"import numpy as np\n\n# Generowanie danych\nrng = np.random.default_rng(19680801)\n\nN_points = 100000\nn_bins = 20\n\n# Wygenerowanie rozk\u0142adu normalnego\ndist1 = rng.standard_normal(N_points)\n\n# Tworzenie wykresu\n\n# Liczb\u0119 przedzia\u0142\u00f3w mo\u017cemy ustawi\u0107 za pomoc\u0105 argumentu *bins*.\nplt.hist(dist1, bins=n_bins)\nplt.xlabel('Warto\u015b\u0107')\nplt.ylabel('Cz\u0119stotliwo\u015b\u0107')\n\nplt.show()\" style=\"color:#24292e;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki github-light\" style=\"background-color: #fff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #D73A49\">import<\/span><span style=\"color: #24292E\"> numpy <\/span><span style=\"color: #D73A49\">as<\/span><span style=\"color: #24292E\"> np<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Generowanie danych<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">rng <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> np.random.default_rng(<\/span><span style=\"color: #005CC5\">19680801<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">N_points <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> <\/span><span style=\"color: #005CC5\">100000<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">n_bins <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> <\/span><span style=\"color: #005CC5\">20<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Wygenerowanie rozk\u0142adu normalnego<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">dist1 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> rng.standard_normal(N_points)<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Tworzenie wykresu<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Liczb\u0119 przedzia\u0142\u00f3w mo\u017cemy ustawi\u0107 za pomoc\u0105 argumentu *bins*.<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.hist(dist1, <\/span><span style=\"color: #E36209\">bins<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\">n_bins)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.xlabel(<\/span><span style=\"color: #032F62\">&#39;Warto\u015b\u0107&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.ylabel(<\/span><span style=\"color: #032F62\">&#39;Cz\u0119stotliwo\u015b\u0107&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">plt.show()<\/span><\/span><\/code><\/pre><\/div>\n\n\n<style>.kb-image8710_76c470-7a.kb-image-is-ratio-size, .kb-image8710_76c470-7a .kb-image-is-ratio-size{max-width:450px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_76c470-7a.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_76c470-7a .kb-image-is-ratio-size{align-self:unset;}.kb-image8710_76c470-7a figure{max-width:450px;}.kb-image8710_76c470-7a .image-is-svg, .kb-image8710_76c470-7a .image-is-svg img{width:100%;}.kb-image8710_76c470-7a .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image8710_76c470-7a\"><figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"589\" height=\"432\" src=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-histogramu-_rys.-4_.webp\" alt=\"Histogram w matplotlib - python wykresy\" class=\"kb-img wp-image-8857\" srcset=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-histogramu-_rys.-4_.webp 589w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/python-wykresy-matplotlib-przyklad-histogramu-_rys.-4_-300x220.webp 300w\" sizes=\"auto, (max-width: 589px) 100vw, 589px\" \/><figcaption>Rys. 4. Przyk\u0142ad histogramu stworzonego w bibliotece matplotlib w Pythonie<\/figcaption><\/figure><\/div>\n\n\n\n<p>Om\u00f3wili\u015bmy kilka prostych przyk\u0142ad\u00f3w tworzenia wykres\u00f3w przy u\u017cyciu biblioteki matplotlib. Opr\u00f3cz nich mamy do dyspozycji mn\u00f3stwo innych typ\u00f3w, takich jak np. wykresy s\u0142upkowe, konturowe, czy tr\u00f3jwymiarowe. S\u0105 one bardzo dok\u0142adnie opisane w <a href=\"https:\/\/matplotlib.org\/stable\/tutorials\/pyplot.html#sphx-glr-tutorials-pyplot-py\">dokumentacji matplotlib<\/a>.<\/p>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_adacaa-51, .wp-block-kadence-advancedheading.kt-adv-heading8710_adacaa-51[data-kb-block=\"kb-adv-heading8710_adacaa-51\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_adacaa-51 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_adacaa-51[data-kb-block=\"kb-adv-heading8710_adacaa-51\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_adacaa-51 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_adacaa-51[data-kb-block=\"kb-adv-heading8710_adacaa-51\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h2 class=\"kt-adv-heading8710_adacaa-51 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_adacaa-51\">Wykresy Python: biblioteka plotly<\/h2>\n\n\n\n<p>Biblioteka Plotly oferuje kilka <a href=\"https:\/\/softinery.com\/pl\/blog\/kurs-python-funkcje\/\">funkcji<\/a>, kt\u00f3re sprawiaj\u0105, \u017ce jest atrakcyjnym narz\u0119dziem do <a href=\"https:\/\/softinery.com\/pl\/blog\/wizualizacja-danych\/\">wizualizacji danych<\/a> w Pythonie. Jedn\u0105 z nich jest mo\u017cliwo\u015b\u0107 tworzenia interaktywnych wizualizacji, pozwalaj\u0105cych na zbli\u017canie, oddalanie, czy filtrowanie danych, co znacznie u\u0142atwia przeprowadzenie <a href=\"https:\/\/softinery.com\/pl\/katalog-szkolen\/python-data-science-kurs\/\">analizy danych<\/a>. Jest to r\u00f3wnie\u017c wszechstronna biblioteka, przy u\u017cyciu kt\u00f3rej stworzymy wszystkie popularne typy wykres\u00f3w, w tym mapy cieplne, histogramy i wiele innych. Poni\u017cej zobaczymy kilka podstawowych przyk\u0142ad\u00f3w pozwalaj\u0105cych na zaznajomienie si\u0119 z t\u0105 bibliotek\u0105.<\/p>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_7cd5a7-b8, .wp-block-kadence-advancedheading.kt-adv-heading8710_7cd5a7-b8[data-kb-block=\"kb-adv-heading8710_7cd5a7-b8\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_7cd5a7-b8 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_7cd5a7-b8[data-kb-block=\"kb-adv-heading8710_7cd5a7-b8\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_7cd5a7-b8 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_7cd5a7-b8[data-kb-block=\"kb-adv-heading8710_7cd5a7-b8\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h3 class=\"kt-adv-heading8710_7cd5a7-b8 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_7cd5a7-b8\">Wykres punktowy w bibliotece plotly<\/h3>\n\n\n\n<p>Zaczniemy od najprostszego typu wykresu, a wi\u0119c od wykresu punktowego. W poni\u017cszym przyk\u0142adzie importujemy <a href=\"https:\/\/softinery.com\/pl\/blog\/kurs-python-moduly-i-pakiety\/\">modu\u0142<\/a> <code>graph_objects<\/code> z biblioteki <code>ploty<\/code>, kt\u00f3remu przypisujemy skr\u00f3t <code>go<\/code>. Nast\u0119pnie definiujemy dwie serie danych (linie 4-8). W linii 11 tworzymy obiekt <code>fig<\/code>, czyli nasz wykres. Nast\u0119pnie, korzystaj\u0105c z funkcji <code>add_trace<\/code> dodajemy serie danych (linia 14 oraz 17). Widzimy, \u017ce u\u017cywamy wykresu typu <code>Scatter<\/code>, czyli punktowego. Jako <a href=\"https:\/\/softinery.com\/pl\/blog\/kurs-python-funkcje\/\">argumenty funkcji<\/a> podajemy zbi\u00f3r danych x oraz y, styl (mode) i nazw\u0119 serii. Jako styl mo\u017cemy u\u017cy\u0107 punkty (markers), linie (lines), albo punkty z liniami (lines+markers). W linii 20 dodajemy takie elementy jak tytu\u0142 i podpisy osi. Funkcja <code>show()<\/code> wy\u015bwietla wykres.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers cbp-highlight-hover\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#24292e;--cbp-line-number-width:calc(2 * 0.6 * .875rem);--cbp-line-highlight-color:rgba(16, 41, 67, 0.2);line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:16px 0 0 16px;width:100%;text-align:left;background-color:#ffffff\"><span style=\"background:#2f363c;padding:0.3rem 0.5rem 0.2rem;border-radius:1rem;font-size:0.8em;line-height:1;height:1.25rem;text-align:center;display:inline-flex;align-items:center;justify-content:center;color:#ffffff\">Python<\/span><\/span><span role=\"button\" tabindex=\"0\" data-code=\"import plotly.graph_objects as go\n\n# Przyk\u0142adowe dane\nx_data1 = [1, 2, 3, 4, 5]\ny_data1 = [10, 11, 12, 13, 14]\n\nx_data2 = [1, 2, 3, 4, 5]\ny_data2 = [8, 9, 10, 11, 12]\n\n# Tworzenie wykresu punktowego\nfig = go.Figure()\n\n# Dodanie pierwszej serii danych\nfig.add_trace(go.Scatter(x=x_data1, y=y_data1, mode='markers', name='Seria 1'))\n\n# Dodanie drugiej serii danych\nfig.add_trace(go.Scatter(x=x_data2, y=y_data2, mode='markers', name='Seria 2'))\n\n# Konfiguracja wykresu\nfig.update_layout(title='Wykres punktowy z dwiema seriami danych',\n                  xaxis_title='Warto\u015b\u0107 X',\n                  yaxis_title='Warto\u015b\u0107 Y')\n\n# Wy\u015bwietlenie wykresu\nfig.show()\" style=\"color:#24292e;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki github-light\" style=\"background-color: #fff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #D73A49\">import<\/span><span style=\"color: #24292E\"> plotly.graph_objects <\/span><span style=\"color: #D73A49\">as<\/span><span style=\"color: #24292E\"> go<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Przyk\u0142adowe dane<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">x_data1 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">2<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">3<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">5<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">y_data1 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">10<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">11<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">12<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">13<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">14<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">x_data2 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">1<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">2<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">3<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">4<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">5<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">y_data2 <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> [<\/span><span style=\"color: #005CC5\">8<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">9<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">10<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">11<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #005CC5\">12<\/span><span style=\"color: #24292E\">]<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Tworzenie wykresu punktowego<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">fig <\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\"> go.Figure()<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Dodanie pierwszej serii danych<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">fig.add_trace(go.Scatter(<\/span><span style=\"color: #E36209\">x<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\">x_data1, <\/span><span style=\"color: #E36209\">y<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\">y_data1, <\/span><span style=\"color: #E36209\">mode<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;markers&#39;<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #E36209\">name<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Seria 1&#39;<\/span><span style=\"color: #24292E\">))<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Dodanie drugiej serii danych<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">fig.add_trace(go.Scatter(<\/span><span style=\"color: #E36209\">x<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\">x_data2, <\/span><span style=\"color: #E36209\">y<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #24292E\">y_data2, <\/span><span style=\"color: #E36209\">mode<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;markers&#39;<\/span><span style=\"color: #24292E\">, <\/span><span style=\"color: #E36209\">name<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Seria 2&#39;<\/span><span style=\"color: #24292E\">))<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Konfiguracja wykresu<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">fig.update_layout(<\/span><span style=\"color: #E36209\">title<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Wykres punktowy z dwiema seriami danych&#39;<\/span><span style=\"color: #24292E\">,<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">xaxis_title<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Warto\u015b\u0107 X&#39;<\/span><span style=\"color: #24292E\">,<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">yaxis_title<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Warto\u015b\u0107 Y&#39;<\/span><span style=\"color: #24292E\">)<\/span><\/span>\n<span class=\"line\"><\/span>\n<span class=\"line\"><span style=\"color: #6A737D\"># Wy\u015bwietlenie wykresu<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">fig.show()<\/span><\/span><\/code><\/pre><\/div>\n\n\n<style>.kb-image8710_e0729a-37.kb-image-is-ratio-size, .kb-image8710_e0729a-37 .kb-image-is-ratio-size{max-width:550px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_e0729a-37.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_e0729a-37 .kb-image-is-ratio-size{align-self:unset;}.kb-image8710_e0729a-37 figure{max-width:550px;}.kb-image8710_e0729a-37 .image-is-svg, .kb-image8710_e0729a-37 .image-is-svg img{width:100%;}.kb-image8710_e0729a-37 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image8710_e0729a-37\"><figure class=\"aligncenter size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"316\" src=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-_Rys.-5_-1024x316.webp\" alt=\"wykres punktowy w plotly - python wykresy\" class=\"kb-img wp-image-8882\" srcset=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-_Rys.-5_-1024x316.webp 1024w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-_Rys.-5_-300x93.webp 300w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-_Rys.-5_-768x237.webp 768w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-_Rys.-5_.webp 1458w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption>Rys. 5. Wykres punktowy w bibliotece plotly w Pythonie<\/figcaption><\/figure><\/div>\n\n\n\n<p>Jak ju\u017c wiemy, zalet\u0105 biblioteki plotly jest mo\u017cliwo\u015b\u0107 tworzenia wykres\u00f3w interaktywnych. Tak\u0105 wersj\u0119 mo\u017cemy zobaczy\u0107 na stronie <a href=\"https:\/\/softinery.com\/wp-content\/uploads\/blog\/python_wykresy\/wykres_punktowy_plotly.html\">interaktywny wykres plotly<\/a>.<\/p>\n\n\n\n<p>Widzimy, \u017ce wykres jest do\u015b\u0107 nieczytelny, dlatego wprowadzimy par\u0119 poprawek. Aby zmieni\u0107 wymiary wykresu, zmodyfikujemy lini\u0119 20, tak aby uwzgl\u0119dnia\u0142a szeroko\u015b\u0107 i wysoko\u015b\u0107. Rozmiar czcionki zwi\u0119kszymy do 13.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro cbp-has-line-numbers cbp-highlight-hover\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;--cbp-line-number-color:#24292e;--cbp-line-number-width:calc(1 * 0.6 * .875rem);--cbp-line-highlight-color:rgba(16, 41, 67, 0.2);line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:flex;align-items:center;padding:16px 0 0 16px;width:100%;text-align:left;background-color:#ffffff\"><span style=\"background:#2f363c;padding:0.3rem 0.5rem 0.2rem;border-radius:1rem;font-size:0.8em;line-height:1;height:1.25rem;text-align:center;display:inline-flex;align-items:center;justify-content:center;color:#ffffff\">Python<\/span><\/span><span role=\"button\" tabindex=\"0\" data-code=\"# Konfiguracja wykresu\nfig.update_layout(title='Wykres punktowy z dwiema seriami danych',\n                  xaxis_title='Warto\u015b\u0107 X',\n                  yaxis_title='Warto\u015b\u0107 Y',\n                  width=700,  # Szeroko\u015b\u0107 wykresu\n                  height=700,  # Wysoko\u015b\u0107 wykresu\n                  font=dict(size=14), \n                  )\" style=\"color:#24292e;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki github-light\" style=\"background-color: #fff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #6A737D\"># Konfiguracja wykresu<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">fig.update_layout(<\/span><span style=\"color: #E36209\">title<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Wykres punktowy z dwiema seriami danych&#39;<\/span><span style=\"color: #24292E\">,<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">xaxis_title<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Warto\u015b\u0107 X&#39;<\/span><span style=\"color: #24292E\">,<\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">yaxis_title<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #032F62\">&#39;Warto\u015b\u0107 Y&#39;<\/span><span style=\"color: #24292E\">,<\/span><\/span>\n<span class=\"line cbp-line-highlight\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">width<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #005CC5\">700<\/span><span style=\"color: #24292E\">,  <\/span><span style=\"color: #6A737D\"># Szeroko\u015b\u0107 wykresu<\/span><\/span>\n<span class=\"line cbp-line-highlight\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">height<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #005CC5\">700<\/span><span style=\"color: #24292E\">,  <\/span><span style=\"color: #6A737D\"># Wysoko\u015b\u0107 wykresu<\/span><\/span>\n<span class=\"line cbp-line-highlight\"><span style=\"color: #24292E\">                  <\/span><span style=\"color: #E36209\">font<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #005CC5\">dict<\/span><span style=\"color: #24292E\">(<\/span><span style=\"color: #E36209\">size<\/span><span style=\"color: #D73A49\">=<\/span><span style=\"color: #005CC5\">14<\/span><span style=\"color: #24292E\">), <\/span><\/span>\n<span class=\"line\"><span style=\"color: #24292E\">                  )<\/span><\/span><\/code><\/pre><\/div>\n\n\n<style>.kb-image8710_e7040f-f0.kb-image-is-ratio-size, .kb-image8710_e7040f-f0 .kb-image-is-ratio-size{max-width:500px;width:100%;}.wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_e7040f-f0.kb-image-is-ratio-size, .wp-block-kadence-column > .kt-inside-inner-col > .kb-image8710_e7040f-f0 .kb-image-is-ratio-size{align-self:unset;}.kb-image8710_e7040f-f0 figure{max-width:500px;}.kb-image8710_e7040f-f0 .image-is-svg, .kb-image8710_e7040f-f0 .image-is-svg img{width:100%;}.kb-image8710_e7040f-f0 .kb-image-has-overlay:after{opacity:0.3;}<\/style>\n<div class=\"wp-block-kadence-image kb-image8710_e7040f-f0\"><figure class=\"aligncenter size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"700\" height=\"700\" src=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-kwadratowy_Rys.-6_-1.webp\" alt=\"Wykres punktowy w bibliotece plotly w proporcjach 1:1\" class=\"kb-img wp-image-8892\" srcset=\"https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-kwadratowy_Rys.-6_-1.webp 700w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-kwadratowy_Rys.-6_-1-300x300.webp 300w, https:\/\/softinery.com\/pl\/wp-content\/uploads\/sites\/5\/2024\/05\/wykres-punktowy-plotly-kwadratowy_Rys.-6_-1-150x150.webp 150w\" sizes=\"auto, (max-width: 700px) 100vw, 700px\" \/><figcaption>Rys. 6. Wykres punktowy w bibliotece plotly w proporcjach 1:1<\/figcaption><\/figure><\/div>\n\n\n<style>.wp-block-kadence-advancedheading.kt-adv-heading8710_67af28-f7, .wp-block-kadence-advancedheading.kt-adv-heading8710_67af28-f7[data-kb-block=\"kb-adv-heading8710_67af28-f7\"]{font-style:normal;}.wp-block-kadence-advancedheading.kt-adv-heading8710_67af28-f7 mark.kt-highlight, .wp-block-kadence-advancedheading.kt-adv-heading8710_67af28-f7[data-kb-block=\"kb-adv-heading8710_67af28-f7\"] mark.kt-highlight{font-style:normal;color:#f76a0c;-webkit-box-decoration-break:clone;box-decoration-break:clone;padding-top:0px;padding-right:0px;padding-bottom:0px;padding-left:0px;}.wp-block-kadence-advancedheading.kt-adv-heading8710_67af28-f7 img.kb-inline-image, .wp-block-kadence-advancedheading.kt-adv-heading8710_67af28-f7[data-kb-block=\"kb-adv-heading8710_67af28-f7\"] img.kb-inline-image{width:150px;vertical-align:baseline;}<\/style>\n<h2 class=\"kt-adv-heading8710_67af28-f7 wp-block-kadence-advancedheading\" data-kb-block=\"kb-adv-heading8710_67af28-f7\">Seaborn<\/h2>\n\n\n\n<p>W kr\u00f3tce&#8230;<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>Je\u015bli chcesz dowiedzie\u0107 si\u0119 wi\u0119cej na temat tworzenia wykres\u00f3w w Pythonie, zobacz nasz <a href=\"https:\/\/softinery.com\/pl\/katalog-szkolen\/python-data-science-kurs\/\">kurs: Python w analizie danych<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Wst\u0119p Tworzenie wykres\u00f3w jest jednym z podstawowych zada\u0144 w wielu zagadnieniach, w analizie danych i statystyce, wizualizacji danych w tym danych biznesowych, oraz naukach in\u017cynierskich i przyrodniczych. St\u0105d te\u017c mamy bardzo wiele r\u00f3\u017cnych typ\u00f3w wykres\u00f3w, przeznaczonych do przedstawiania r\u00f3\u017cnego rodzaju danych. Z tych wzgl\u0119d\u00f3w dla j\u0119zyka Python stworzono kilka bibliotek, kt\u00f3re dedykowane s\u0105 tworzeniu wykres\u00f3w.&hellip;&nbsp;<a href=\"https:\/\/softinery.com\/pl\/blog\/wykresy-python\/\" rel=\"bookmark\">Dowiedz si\u0119 wi\u0119cej &raquo;<span class=\"screen-reader-text\">Wykresy Python: matplotlib i inne biblioteki do wizualizacji<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":578,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"categories":[],"tags":[],"class_list":["post-8710","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Wykresy Python: matplotlib i inne biblioteki do wizualizacji<\/title>\n<meta name=\"description\" content=\"Wykresy Python mo\u017cna stworzy\u0107 na wiele spos\u00f3b. 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