mirror
/
learn-python
kopia lustrzana https://github.com/animator/learn-python
1
0
Forkuj 0
Kod Zgłoszenia Packages Projekty Wydania Wiki Aktywność

Update matplotlib-violin_plots.md

pull/1276/head
RajKhanke 2024-06-23 18:55:53 +05:30 zatwierdzone przez GitHub
rodzic 7c7752dd94
commit e4ff080e31
Nie znaleziono w bazie danych klucza dla tego podpisu
ID klucza GPG: B5690EEEBB952194
1 zmienionych plików z 2 dodań i 2 usunięć
Pokaż statystyki Ściągnij plik aktualizacji Ściągnij plik porównania Expand all files Collapse all files

4
contrib/plotting-visualization/matplotlib-violin_plots.md
Wyświetl plik

@ -34,7 +34,7 @@ plt.show()
When executed, this would show the following pie chart: When executed, this would show the following pie chart:
![Basic violin plot](images\violinplotnocolor.png) ![Basic violin plot](images/violinplotnocolor.png)
The `Violinplot` function in matplotlib.pyplot creates a violin plot, which is a graphical representation of the distribution of data across different levels of a categorical variable. Here's a breakdown of its usage: The `Violinplot` function in matplotlib.pyplot creates a violin plot, which is a graphical representation of the distribution of data across different levels of a categorical variable. Here's a breakdown of its usage:
@ -96,7 +96,7 @@ plt.show()
This code snippet creates a violin plot with custom colors assigned to each violin, enhancing the visual appeal and clarity of the plot. This code snippet creates a violin plot with custom colors assigned to each violin, enhancing the visual appeal and clarity of the plot.
![Coloring violin](images\violenplotnormal.png) ![Coloring violin](images/violenplotnormal.png)
When customizing violin plots using `matplotlib.pyplot.subplots()`, you obtain a `Figure` object `fig` and an `Axes` object `ax`, allowing for extensive customization. Each `violin plot` consists of various components, including the `violin body`, `lines representing median and quartiles`, and `potential markers for mean and outliers`. You can customize these components using the appropriate methods and attributes of the Axes object. When customizing violin plots using `matplotlib.pyplot.subplots()`, you obtain a `Figure` object `fig` and an `Axes` object `ax`, allowing for extensive customization. Each `violin plot` consists of various components, including the `violin body`, `lines representing median and quartiles`, and `potential markers for mean and outliers`. You can customize these components using the appropriate methods and attributes of the Axes object.