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Home/ Questions/Q 8301735
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Editorial Team
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Editorial Team
Asked: June 8, 20262026-06-08T17:07:09+00:00 2026-06-08T17:07:09+00:00

Is it possible to create a time-series histogram like the one described in this

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Is it possible to create a time-series histogram like the one described in this presentation (slides 36-39) using either R or D3.js? Or is there a better way to show bucketed data as a time series?

Edit: Here is some pre-bucketed sample data. Ideally, D3 or R would do the bucketing by itself. And yes, if it wasn’t clear, I understand that I could write this myself. I’m just wondering if there’s already a package that does this and I just haven’t come across it yet. Thanks!

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  1. Editorial Team
    Editorial Team
    2026-06-08T17:07:10+00:00Added an answer on June 8, 2026 at 5:07 pm

    Here is one possible solution using R and ggplot2.

    Your data, ready to paste into R console:

    dat = structure(list(date = structure(c(15541, 15541, 15541, 15541, 
        15541, 15541, 15541, 15541, 15541, 15541, 15541, 15541, 15541, 
        15541, 15541, 15541, 15541, 15542, 15542, 15542, 15542, 15542, 
        15542, 15542, 15542, 15542, 15542, 15542, 15542, 15542, 15542, 
        15542, 15543, 15543, 15543, 15543, 15543, 15543, 15543, 15543, 
        15543, 15543, 15543, 15543, 15543, 15543, 15543, 15543, 15543, 
        15543, 15543, 15544, 15544, 15544, 15544, 15544, 15544, 15544, 
        15544, 15544, 15544, 15544, 15544, 15544, 15544, 15544, 15544, 
        15544, 15544, 15544, 15544, 15544, 15545, 15545, 15545, 15545, 
        15545, 15545, 15545, 15545, 15545, 15545, 15545, 15545, 15545, 
        15545, 15545, 15545, 15545, 15546, 15546, 15546, 15546, 15546, 
        15546, 15546, 15546, 15546, 15546, 15546, 15546, 15546, 15546, 
        15546, 15546, 15546, 15547, 15547, 15547, 15547, 15547, 15547, 
        15547, 15547, 15547, 15547, 15547, 15547, 15547, 15547, 15547, 
        15547, 15547, 15547, 15547), class = "Date"), bucket = c(800L, 
        900L, 1000L, 1100L, 1200L, 1300L, 1400L, 1500L, 1600L, 1700L, 
        1800L, 1900L, 2000L, 2100L, 2200L, 2300L, 2400L, 800L, 900L, 
        1000L, 1100L, 1200L, 1300L, 1400L, 1500L, 1600L, 1700L, 1800L, 
        1900L, 2000L, 2100L, 2200L, 900L, 1000L, 1100L, 1200L, 1300L, 
        1400L, 1500L, 1600L, 1700L, 1800L, 1900L, 2000L, 2100L, 2200L, 
        2300L, 2400L, 2500L, 2600L, 2800L, 800L, 900L, 1000L, 1100L, 
        1200L, 1300L, 1400L, 1500L, 1600L, 1700L, 1800L, 1900L, 2000L, 
        2100L, 2200L, 2300L, 2400L, 2500L, 2600L, 2700L, 2800L, 800L, 
        900L, 1000L, 1100L, 1200L, 1300L, 1400L, 1500L, 1600L, 1700L, 
        1800L, 1900L, 2000L, 2100L, 2200L, 2300L, 2400L, 800L, 900L, 
        1000L, 1100L, 1200L, 1300L, 1400L, 1500L, 1600L, 1700L, 1800L, 
        1900L, 2000L, 2100L, 2200L, 2300L, 2400L, 1300L, 1400L, 1500L, 
        1600L, 1700L, 1800L, 1900L, 2000L, 2100L, 2200L, 2300L, 2400L, 
        2500L, 2600L, 2700L, 2800L, 2900L, 3000L, 3200L), cnt = c(119L, 
        123L, 173L, 226L, 284L, 257L, 268L, 244L, 191L, 204L, 187L, 177L, 
        164L, 125L, 140L, 109L, 103L, 123L, 165L, 237L, 278L, 338L, 306L, 
        316L, 269L, 271L, 241L, 188L, 174L, 158L, 153L, 132L, 154L, 241L, 
        246L, 300L, 305L, 301L, 292L, 253L, 251L, 214L, 189L, 179L, 159L, 
        161L, 144L, 139L, 132L, 136L, 105L, 120L, 156L, 209L, 267L, 299L, 
        316L, 318L, 307L, 295L, 273L, 283L, 229L, 192L, 193L, 170L, 164L, 
        154L, 138L, 101L, 115L, 103L, 105L, 156L, 220L, 255L, 308L, 338L, 
        318L, 255L, 278L, 260L, 235L, 230L, 185L, 145L, 147L, 157L, 109L, 
        104L, 191L, 201L, 238L, 223L, 229L, 286L, 256L, 240L, 233L, 202L, 
        180L, 184L, 161L, 125L, 110L, 101L, 132L, 117L, 124L, 154L, 167L, 
        137L, 169L, 175L, 168L, 188L, 137L, 173L, 164L, 167L, 115L, 116L, 
        118L, 125L, 104L)), .Names = c("date", "bucket", "cnt"), 
        class = "data.frame", row.names = c(NA, -125L))
    

    Plotting code:

    library(ggplot2)
    
    plot_1 = ggplot(dat, aes(x=date, y=bucket, fill=cnt)) +
             geom_tile() +
             scale_fill_continuous(low="#F7FBFF", high="#2171B5") +
             theme_bw()
    
    ggsave("plot_1.png", plot_1, width=6, height=4)
    

    enter image description here
    The plot might look better if you include rows for zero bucket values in your data. Then you could change low="#F7FBFF" to low="white".

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