Pythonjoypy和Rggridges峰峦图制作

Z时代
2024-01-10
分类：综合

python

本文的文字及图片来源于网络,仅供学习、交流使用,不具有任何商业用途,版权归原作者所有,如有问题请及时联系我们以作处理。

以下文章来源于DataCharm，作者宁海涛

转载地址

https://www.zhihu.com/people/qi-shi-huan-hao-la-14/posts

Python-joypy 制作

Python 制作峰峦图有直接的第三方库joypy进行绘制，该库可以直接通过pip安装。可视化代码如下：

import matplotlib.pyplot as plt
plt.rcParams["font.family"] = ["Times New Roman"]
colors = ["#791E94","#58C9B9","#519D9E","#D1B6E1"]
fig,axs = joypy.joyplot(data_ed, by="source",fill=True, legend=True,alpha=.8,
                         range_style="own",xlabelsize=22,ylabelsize=22,
                         grid="both", linewidth=.8,linecolor="k", figsize=(12,6),color=colors,
                       )ax = plt.gca()#设置x刻度为时间形式x = np.arange(6)
xlabel=["8-21","8-28","9-4","9-11","9-18","9-25"]
ax.set_xlim(left=-.5,right=5.5)
ax.set_xticks(x)ax.set_xticklabels(xlabel)ax.text(.47,1.1,"Joyplot plots of media shares (TV, Online News and Google Trends)",
        transform = ax.transAxes,ha="center", va="center",fontsize = 25,color="black")
ax.text(.5,1.03,"Python Joyplot Test",
        transform = ax.transAxes,ha="center", va="center",fontsize = 15,color="black")
ax.text(.90,-.11,"
Visualization by DataCharm",transform = ax.transAxes,
        ha="center", va="center",fontsize = 12,color="black")
plt.savefig(r"F:DataCharmArtist_charts_make_python_RjoyplotsJoyplot_python.png",
            width=7,height=5,dpi=900,bbox_inches="tight")

可视化结果如下：

关于 joypy库其他详细的参数设置，可以去官网(https://github.com/sbebo/joypy) 下载 Joyplot.ipynb 文件查看，最好查看所绘制数据的格式，有助于更好绘制峰峦图。

R-ggridges 绘制

借助于R语言丰富且强大的第三方绘图包，在应对不同类型图表时，机会都会有对应的包进行绘制。本次就使用ggridges包（https://wilkelab.org/ggridges/）进行峰峦图的绘制。官网的例子如下：

ggplot(lincoln_weather, aes(x = `Mean Temperature [F]`, y = Month, fill = stat(x))) +
  geom_density_ridges_gradient(scale = 3, rel_min_height = 0.01, gradient_lwd = 1.) +
  scale_x_continuous(expand = c(0, 0)) +
  scale_y_discrete(expand = expand_scale(mult = c(0.01, 0.25))) +
  scale_fill_viridis_c(name = "Temp. [F]", option = "C") +
  labs(
    title = "Temperatures in Lincoln NE",
    subtitle = "Mean temperatures (Fahrenheit) by month for 2016"
  ) +  theme_ridges(font_size = 13, grid = TRUE) +
  theme(axis.title.y = element_blank())

结果如下：

这里我们没有使用 geom_density_ridges_gradient()进行绘制，使用了 geom_ridgeline() 进行类似于山脊线图的绘制。

绘制代码如下：

library(ggthemes)
library(hrbrthemes)plot <- ggplot(all_data, aes(x = date, y = source)) +
  geom_ridgeline(aes(height = value, fill = factor(hurricane)), size = 0.1, scale = 0.8, alpha = 0.8) +
  labs(title = "Ridgeline plots of media shares (TV, Online News and Google Trends)",
       subtitle = "ggridges ridgeline plot test",
       caption = "Visualization by DataCharm",
       y = NULL,
       x = NULL) +
  scale_x_date(expand = c(0,0)) +
  scale_fill_manual(values = c("#791E94","#58C9B9","#D1B6E1","#519D9E"),name="Hurricane")+
  theme_ipsum()+
  theme(text = element_text(family = "Poppins",face = "bold"),
        axis.text.y = element_text(vjust = -2))
plot