diff --git a/03.ipynb b/03.ipynb
new file mode 100644
index 0000000..35ff2b9
--- /dev/null
+++ b/03.ipynb
@@ -0,0 +1,5868 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Wizualizacja danych (Lab 3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "library(repr) # To resize plots in Jupyter\n",
+ "options(repr.plot.width = 16, repr.plot.height = 9)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Biblioteka plotly"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Pakiet *plotly* jest pakietem graficznym, który umożliwia tworzenie interaktywnych wykresów. Cała biblioteka jest napisana w JavaScript i dostępna również dla Pythona. Składania i pomysł na tworzenie grafiki są bardzo podobne do *ggplot2*.\n",
+ "\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Karta pomocy"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ " \n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Konwersja grafiki ggplot2 na plotly"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Warning message:\n",
+ "“package ‘plotly’ was built under R version 3.6.2”\n",
+ "Loading required package: ggplot2\n",
+ "\n",
+ "Warning message:\n",
+ "“package ‘ggplot2’ was built under R version 3.6.2”\n",
+ "\n",
+ "Attaching package: ‘plotly’\n",
+ "\n",
+ "\n",
+ "The following object is masked from ‘package:ggplot2’:\n",
+ "\n",
+ " last_plot\n",
+ "\n",
+ "\n",
+ "The following object is masked from ‘package:stats’:\n",
+ "\n",
+ " filter\n",
+ "\n",
+ "\n",
+ "The following object is masked from ‘package:graphics’:\n",
+ "\n",
+ " layout\n",
+ "\n",
+ "\n",
+ "Warning message:\n",
+ "“package ‘dplyr’ was built under R version 3.6.2”\n",
+ "\n",
+ "Attaching package: ‘dplyr’\n",
+ "\n",
+ "\n",
+ "The following objects are masked from ‘package:stats’:\n",
+ "\n",
+ " filter, lag\n",
+ "\n",
+ "\n",
+ "The following objects are masked from ‘package:base’:\n",
+ "\n",
+ " intersect, setdiff, setequal, union\n",
+ "\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "library(plotly)\n",
+ "library(ggplot2)\n",
+ "library(dplyr)"
+ ]
+ },
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+ "execution_count": 3,
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+ "# Scatterplot\n",
+ "rattle.data::wine %>% # data set\n",
+ " plot_ly(x = ~Phenols, \n",
+ " y = ~Alcohol, \n",
+ " hoverinfo = 'text',\n",
+ " text = ~paste('Phenols:', Phenols, '
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+ }
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+ "plotly_click",
+ "plotly_selected",
+ "plotly_relayout",
+ "plotly_brushed",
+ "plotly_brushing",
+ "plotly_clickannotation",
+ "plotly_doubleclick",
+ "plotly_deselect",
+ "plotly_afterplot",
+ "plotly_sunburstclick"
+ ],
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+ ],
+ "source": [
+ "# Barplot\n",
+ "rattle.data::wine %>%\n",
+ " count(Type) %>%\n",
+ " plot_ly(x = ~Type, y = ~n) %>%\n",
+ " add_bars()\n",
+ "\n",
+ "rattle.data::wine %>%\n",
+ " count(Type) %>%\n",
+ " mutate(Type = forcats::fct_reorder(Type, n, .desc = TRUE)) %>%\n",
+ " plot_ly(x = ~Type, y = ~n) %>%\n",
+ " add_bars()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
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+ "name": "1",
+ "textfont": {
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+ "Weak"
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+ {
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+ "highlight": {
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+ "dynamic": false,
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+ "opacityDim": 0.2,
+ "persistent": false,
+ "selected": {
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+ },
+ "selectize": false
+ },
+ "layout": {
+ "barmode": "stack",
+ "hovermode": "closest",
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+ "l": 60,
+ "r": 10,
+ "t": 25
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+ "xaxis": {
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+ "categoryarray": [
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+ "Weak"
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+ "categoryorder": "array",
+ "domain": [
+ 0,
+ 1
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+ "title": "Power",
+ "type": "category"
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+ "yaxis": {
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+ }
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+ "plotly_selected",
+ "plotly_relayout",
+ "plotly_brushed",
+ "plotly_brushing",
+ "plotly_clickannotation",
+ "plotly_doubleclick",
+ "plotly_deselect",
+ "plotly_afterplot",
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+ ],
+ "source": [
+ "# Stacked barplot\n",
+ "rattle.data::wine %>%\n",
+ " mutate(Power = ifelse(Alcohol < 13, 'Weak', 'Strong')) %>%\n",
+ " as_tibble() %>% \n",
+ " count(Type, Power) %>% \n",
+ " plot_ly(x = ~Power, y = ~n, color = ~Type) %>%\n",
+ " add_bars() %>%\n",
+ " layout(barmode = 'stack')"
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+ {
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+ " group_by(Type) %>% \n",
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+ "rattle.data::wine %>% \n",
+ " plot_ly(x = ~Phenols, \n",
+ " y = ~Alcohol) %>% \n",
+ " add_markers(color = ~Type) %>% \n",
+ " layout(xaxis = list(title = 'Alcohol', showgrid = FALSE, zeroline = FALSE),\n",
+ " yaxis = list(title = 'Total phenols', showgrid = FALSE, zeroline = FALSE),\n",
+ " title = 'Alcohol and Phenols',\n",
+ " paper_bgcolor = '#ebebeb')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Zadania"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "1. Narysuj wykres przebiegu dla zbioru danych *LakeHuron*.\n",
+ "2. Dla cech *Petal.Length* i *Petal.Width* ze zbioru danych *iris* narysuj wykres rozrzutu.\n",
+ "3. Narysuj taki sam wykres jak w zadaniu poprzednim. Tym razem jednak, każdy gatunek irysa ma mieć swój kolor. Po najechaniu na punkt powinna wyświetlić się informacja o współrzędnych punktu oraz jego przynależności klasowej.\n",
+ "4. Dla zbioru danych *esoph* wykonaj wykres słupkowy dla cechy *agegp*. \n",
+ "5. Dla zbioru danych *volcano* narysuj wykres typu „mapa ciepła”.\n",
+ "6. Niech dane będą wartości: 0,12, 0,3, 0,26, 0,16, 0,04, 0,12. Narysuj dla niech wykres kołowy z otworem w środku.\n",
+ "7. Narysuj wykres pokazujący histogramy wszystkich cech numerycznych ze zbioru *iris*. Powinny się na nim zatem znaleźć 4 histogramy rozmieszczone w dwóch wierszach i dwóch kolumnach."
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "R",
+ "language": "R",
+ "name": "ir"
+ },
+ "language_info": {
+ "codemirror_mode": "r",
+ "file_extension": ".r",
+ "mimetype": "text/x-r-source",
+ "name": "R",
+ "pygments_lexer": "r",
+ "version": "3.6.1"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
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