Question

我对R还是很陌生，我一直坚持如何从列表中的多个数据帧创建热图。

每个数据帧中有3列：X位置，Y位置，PatchStatus

第一个数据帧如下：

>>> pd.to_datetime(df['dt'], format = '%d-%m-%Y')
Traceback (most recent call last):
  File "/home/vishnudev/anaconda3/envs/sumyag/lib/python3.7/site-packages/pandas/core/tools/datetimes.py", line 448, in _convert_listlike_datetimes
    values, tz = conversion.datetime_to_datetime64(arg)
  File "pandas/_libs/tslibs/conversion.pyx", line 200, in pandas._libs.tslibs.conversion.datetime_to_datetime64
TypeError: Unrecognized value type: <class 'str'>

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/vishnudev/anaconda3/envs/sumyag/lib/python3.7/site-packages/pandas/util/_decorators.py", line 208, in wrapper
    return func(*args, **kwargs)
  File "/home/vishnudev/anaconda3/envs/sumyag/lib/python3.7/site-packages/pandas/core/tools/datetimes.py", line 778, in to_datetime
    values = convert_listlike(arg._values, True, format)
  File "/home/vishnudev/anaconda3/envs/sumyag/lib/python3.7/site-packages/pandas/core/tools/datetimes.py", line 451, in _convert_listlike_datetimes
    raise e
  File "/home/vishnudev/anaconda3/envs/sumyag/lib/python3.7/site-packages/pandas/core/tools/datetimes.py", line 416, in _convert_listlike_datetimes
    arg, format, exact=exact, errors=errors
  File "pandas/_libs/tslibs/strptime.pyx", line 142, in pandas._libs.tslibs.strptime.array_strptime
ValueError: time data '3-24-2020' does not match format '%d-%m-%Y' (match)

...以此类推，最多100点

每个数据帧将具有相同的X和Y位置，但是补丁状态将有所不同（可以为0或1）。

我的目标是创建一个结合了所有数据帧（我打算有10-15个数据帧）的热图，这些数据帧显示了更容易出现“ 1”状态的补丁。任何帮助将不胜感激。谢谢。

Answer 1

数据：

df <- read.table(text = "allPoints.xLocs allPoints.yLocs allPoints.patchStatus
1       67.30330212       87.857495                     0
                 2       69.60800088       77.959314                     0
                 3       74.63313295       93.059260                     0
                 4       92.59099136       77.732215                     1
                 5       18.05288289       61.200910                     1
                 6       55.83499856       50.993785                     0
                 7       12.15664148       58.220179                     1
                 8       41.50413859       92.529054                     0
                 9       83.08209025       24.567501                     0
                 10      53.50615149       46.339927                     0", header = TRUE, stringsAsFactors = FALSE)

listofdfs <- list(df, df)

代码：

library('data.table')
listofdfs <- lapply(seq_len(length(listofdfs)), function(i){
  x <- listofdfs[[i]]
  # assign id and combine x and y coordinates
  setDT(x)[, `:=` ( id = i, coords = paste0(allPoints.xLocs, ",", allPoints.yLocs)) ]
} )

# combine list into a data table.
df2 <- rbindlist(l = listofdfs)

图解

library('ggplot2')
ggplot( data = df2, mapping = aes( x = coords, y = factor(id) ) ) +  # draw heatmap
  geom_tile( aes( fill = factor(allPoints.patchStatus) ),  colour = "white") +
  coord_flip() + 
  scale_fill_discrete(name = "Patch Status") +
  labs( x = "Coordinates", y = "Data Frame Number")

图形：

您可以遍历数据帧列表，并为每个数据帧创建热图。下面，我展示了如何获取一个数据帧的热图。

图2

ggplot( data = df, mapping = aes( x = factor(allPoints.xLocs), y = factor(allPoints.yLocs) ) ) + 
  geom_tile( aes( fill = factor(allPoints.patchStatus) ),  colour = "white") +
  scale_fill_discrete(name = "Patch Status") +
  labs( x = "X-Coordinate", y = "Y-Coordinate") +
  theme_bw() + 
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

图2

情节3 df数据是从上方使用的-请参阅顶部的数据部分。

library('data.table')
listofdfs <- list(df, df)
df2 <- rbindlist(l = listofdfs)
df2 <- df2[, .(sum_patch = sum(allPoints.patchStatus)), by = .(allPoints.xLocs, allPoints.yLocs)]

library('ggplot2')
ggplot( data = df2, mapping = aes( x = factor(allPoints.xLocs), y = factor(allPoints.yLocs) ) ) + 
  geom_tile( aes( fill = sum_patch ),  colour = "white") +
  labs( x = "X-Coordinate", y = "Y-Coordinate") +
  theme_bw() + 
  theme(axis.text.x = element_text(angle = 45, hjust = 1))

图3：

如何从多个数据帧创建热图

1 个答案: