统计变换

  1. What is the default geom associated with stat_summary()? How could you rewrite the previous plot to use that geom function instead of the stat function?

    统计变换函数stat_summary()的默认几何对象函数是什么？如何使用几何对象函数重绘上述图片？

    geom_pointrange()由于其stat的默认值为identity，需要数据中包含ymin与ymax。但数据中没有，简便起见，我们通过修改stat为summary实现。

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    ggplot(data = diamonds) +
 geom_pointrange(
     mapping = aes(x = cut, y = depth),
        stat = "summary"
     )
># No summary function supplied, defaulting to `mean_se()

    结果出图如下

    e3.1

    这是由于summary的默认输出使用mean与sd绘制点线图，所以还需要手动设置fun.ymin，fun.ymax与fun.y的值：

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    ggplot(data = diamonds) +
 geom_pointrange(
     mapping = aes(x=cut, y=depth),
     stat = "summary",
     fun.ymin = min,
     fun.ymax = max,
     fun.y = median
    )

    e3.1-2

  2. What does geom_col() do? How is it different to geom_bar()?

    geom_col()函数有什么功能？它与geom_bar()函数的区别是什么？

    geom_bar()函数使用每个group中的数量来计算条形图的高度。geom_col()默认使用stat_identity()作为统计变换函数，geom_bar()则默认使用stat_count()作为统计变换函数。

  3. Most geoms and stats come in pairs that are almost always used in concert. Read through the documentation and make a list of all the pairs. What do they have in common?

    大多数的几何对象函数与统计变换函数都是成对出现的。阅读说明文档，给出这些列表，它们有哪些共同之处？ ggplot2::geom_abline Reference lines: horizontal, vertical, and diagonal ggplot2::geom_bar Bar charts ggplot2::geom_bin2d Heatmap of 2d bin counts ggplot2::geom_blank Draw nothing ggplot2::geom_boxplot A box and whiskers plot (in the style of Tukey) ggplot2::geom_contour 2d contours of a 3d surface ggplot2::geom_count Count overlapping points ggplot2::geom_density Smoothed density estimates ggplot2::geom_density_2d Contours of a 2d density estimate ggplot2::geom_dotplot Dot plot ggplot2::geom_errorbarh Horizontal error bars ggplot2::geom_hex Hexagonal heatmap of 2d bin counts ggplot2::geom_freqpoly Histograms and frequency polygons ggplot2::geom_jitter Jittered points ggplot2::geom_crossbar Vertical intervals: lines, crossbars & errorbars ggplot2::geom_map Polygons from a reference map ggplot2::geom_path Connect observations ggplot2::geom_point Points ggplot2::geom_polygon Polygons ggplot2::geom_qq_line A quantile-quantile plot ggplot2::geom_quantile Quantile regression ggplot2::geom_ribbon Ribbons and area plots ggplot2::geom_rug Rug plots in the margins ggplot2::geom_segment Line segments and curves ggplot2::geom_smooth Smoothed conditional means ggplot2::geom_spoke Line segments parameterised by location, direction and distance ggplot2::geom_label Text ggplot2::geom_raster Rectangles ggplot2::geom_violin Violin plot

  4. What variables does stat_smooth() compute? What parameters control its behaviour?

    stat_smooth()函数计算了什么变量？什么参数控制它的行为？ |Computed variables| | | —- | —- | | y | predicted value | | ymin | lower pointwise confidence interval around the mean | | ymax | upper pointwise confidence interval around the mean | | se | standard error |

  5. In our proportion bar chart, we need to set group = 1. Why? In other words what is the problem with these two graphs?

    在我们部分的条形图中，需要设置group = 1, 这是为什么呢？

参考来源

https://r4ds.had.co.nz/data-visualisation.html#exercises-4

https://jrnold.github.io/r4ds-exercise-solutions/data-visualisation.html#statistical-transformations