atherenergy / ggtimeseries Goto Github PK

Hi,
great package! I am using the function stat_calendar_heatmap and want to configure the size of a) the daily tiles and b) size of monthly tiles, i.e. the stroke width of the heatmaps / lines. Is this possible, if yes, how?
I have seen that this is possible in ggplot_calendar_heatmap but this function is not flexible enough for me.

Thanks

Hello, thank you for the helpful package.

Calling ggplot_calendar_heatmap() on a dataframe coerces it to class data.table permanently. This is surprising and unexpected behavior.

This also breaks code, because data.table overrides magritter / dplyr pipes, and completely changes the way the "." placeholder is treated.

Please make it so that ggplot_calendar_heatmap() does not modify data (as it shouldn't), or at a minimum, warn users with a message() that their data is being modified, or require them to convert to a data.table themselves.

Would be better if available BibTeX citation info could be provided.

How can I use local names for months and days of week on calendar heatmaps? I would like to have them in portuguese. Thanks.

This package was removed from CRAN recently for reasons mentioned here:
https://cran.r-project.org/web/packages/ggTimeSeries/index.html

Are there plans to resubmit it and unarchive it?

If date column is formatted as POSIXct, seq() function produces dates with daylight saving applied. This results in a sequence of days with hour components 23:00:00. When merge happens here

  dtDateValue = merge(dtDateValue, setnames(dtDateValue[ ,list(DateCol = seq(min(get(cDateColumnName)), max(get(cDateColumnName)),"days")), vcGroupingColumnNames], "DateCol", cDateColumnName),  c(vcGroupingColumnNames, cDateColumnName),  all = T)

dtDateValue is updated with NA values for days that have the daylight savings are applied.

Adding na.value = "white" to scale_fill_continuous() reveals those NA values like below.

One solutions is that user formats the dates with as.Date() before plotting. Or, you might consider using as.POSIXct() with tz set to UTC in seq() and then merge.

There are no NA values in the dataset, however this is plotting an N/A year.

require(ggTimeSeries)
#> Loading required package: ggTimeSeries
#> Loading required package: ggplot2
require(tidyverse)
#> Loading required package: tidyverse

x <- structure(list(year = c(2017, 2017, 2017, 2017, 2017, 2018, 2018, 
                             2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 2018, 
                             2018, 2018, 2018, 2018), 
                    date = structure(c(17479, 17480, 17483, 
                                       17505, 17528, 17534, 17569, 17581, 17591, 17611, 17639, 17640, 
                                       17644, 17655, 17694, 17701, 17702, 17704, 17709, 17714, 17715, 
                                       17735), class = "Date"), 
                    n = c(23L, 22L, 24L, 5L, 19L, 2L, 5L, 
                          10L, 5L, 6L, 13L, 2L, 1L, 6L, 2L, 13L, 1L, 32L, 17L, 1L, 3L, 
                          14L)), 
               class = c("tbl_df", "tbl", "data.frame"), 
               row.names = c(NA, -22L))
x
#> # A tibble: 22 x 3
#>     year date           n
#>    <dbl> <date>     <int>
#>  1  2017 2017-11-09    23
#>  2  2017 2017-11-10    22
#>  3  2017 2017-11-13    24
#>  4  2017 2017-12-05     5
#>  5  2017 2017-12-28    19
#>  6  2018 2018-01-03     2
#>  7  2018 2018-02-07     5
#>  8  2018 2018-02-19    10
#>  9  2018 2018-03-01     5
#> 10  2018 2018-03-21     6
#> # ... with 12 more rows

x %>% 
  ggTimeSeries::ggplot_calendar_heatmap(cDateColumnName = "date", cValueColumnName = "n") + 
  facet_grid(year ~ .)

Created on 2018-08-13 by the reprex
package (v0.2.0).