Drawing dendrogram of time series data in d3heatmap
Question
I am trying to draw a dendrogram of a time-series data using d3heatmap library.
Right now, I cannot produce a nice heatmap with dendrogram with the following code:
library(d3heatmap)
d3heatmap(hour_flow, colors = "RdYlBu",
dendrogram = "row",
k_rows = 3)
Here is the reproducible data:
structure(list(county = c("강남구", "강남구", "강남구", "강남구",
"강남구", "강남구", "강남구", "강남구", "강남구", "강남구", "강남구",
"강남구", "강남구", "강남구", "강남구", "강남구", "강남구", "강남구",
"강남구", "강남구", "강남구", "강남구", "강남구", "강남구", "강동구",
"강동구", "강동구", "강동구", "강동구", "강동구", "강동구", "강동구",
"강동구", "강동구", "강동구", "강동구", "강동구", "강동구", "강동구",
"강동구", "강동구", "강동구", "강동구", "강동구", "강동구", "강동구",
"강동구", "강동구", "강북구", "강북구", "강북구", "강북구", "강북구",
"강북구", "강북구", "강북구", "강북구", "강북구", "강북구", "강북구",
"강북구", "강북구", "강북구", "강북구", "강북구", "강북구", "강북구",
"강북구", "강북구", "강북구", "강북구", "강북구", "강서구", "강서구",
"강서구", "강서구", "강서구", "강서구", "강서구", "강서구", "강서구",
"강서구", "강서구", "강서구", "강서구", "강서구", "강서구", "강서구",
"강서구", "강서구", "강서구", "강서구", "강서구", "강서구", "강서구",
"강서구", "관악구", "관악구", "관악구", "관악구", "관악구", "관악구",
"관악구", "관악구", "관악구", "관악구", "관악구", "관악구", "관악구",
"관악구", "관악구", "관악구", "관악구", "관악구", "관악구", "관악구",
"관악구", "관악구", "관악구", "관악구", "광진구", "광진구", "광진구",
"광진구", "광진구", "광진구", "광진구", "광진구", "광진구", "광진구",
"광진구", "광진구", "광진구", "광진구", "광진구", "광진구", "광진구",
"광진구", "광진구", "광진구", "광진구", "광진구", "광진구", "광진구",
"구로구", "구로구", "구로구", "구로구", "구로구", "구로구", "구로구",
"구로구", "구로구", "구로구", "구로구", "구로구", "구로구", "구로구",
"구로구", "구로구", "구로구", "구로구", "구로구", "구로구", "구로구",
"구로구", "구로구", "구로구", "금천구", "금천구", "금천구", "금천구",
"금천구", "금천구", "금천구", "금천구", "금천구", "금천구", "금천구",
"금천구", "금천구", "금천구", "금천구", "금천구", "금천구", "금천구",
"금천구", "금천구", "금천구", "금천구", "금천구", "금천구", "노원구",
"노원구", "노원구", "노원구", "노원구", "노원구", "노원구", "노원구",
"노원구", "노원구", "노원구", "노원구", "노원구", "노원구", "노원구",
"노원구", "노원구", "노원구", "노원구", "노원구", "노원구", "노원구",
"노원구", "노원구", "도봉구", "도봉구", "도봉구", "도봉구", "도봉구",
"도봉구", "도봉구", "도봉구", "도봉구", "도봉구", "도봉구", "도봉구",
"도봉구", "도봉구", "도봉구", "도봉구", "도봉구", "도봉구", "도봉구",
"도봉구", "도봉구", "도봉구", "도봉구", "도봉구", "동대문구",
"동대문구", "동대문구", "동대문구", "동대문구", "동대문구", "동대문구",
"동대문구", "동대문구", "동대문구", "동대문구", "동대문구", "동대문구",
"동대문구", "동대문구", "동대문구", "동대문구", "동대문구", "동대문구",
"동대문구", "동대문구", "동대문구", "동대문구", "동대문구", "동작구",
"동작구", "동작구", "동작구", "동작구", "동작구", "동작구", "동작구",
"동작구", "동작구", "동작구", "동작구", "동작구", "동작구", "동작구",
"동작구", "동작구", "동작구", "동작구", "동작구", "동작구", "동작구",
"동작구", "동작구", "마포구", "마포구", "마포구", "마포구", "마포구",
"마포구", "마포구", "마포구", "마포구", "마포구", "마포구", "마포구",
"마포구", "마포구", "마포구", "마포구", "마포구", "마포구", "마포구",
"마포구", "마포구", "마포구", "마포구", "마포구", "서대문구",
"서대문구", "서대문구", "서대문구", "서대문구", "서대문구", "서대문구",
"서대문구", "서대문구", "서대문구", "서대문구", "서대문구", "서대문구",
"서대문구", "서대문구", "서대문구", "서대문구", "서대문구", "서대문구",
"서대문구", "서대문구", "서대문구", "서대문구", "서대문구", "서초구",
"서초구", "서초구", "서초구", "서초구", "서초구", "서초구", "서초구",
"서초구", "서초구", "서초구", "서초구", "서초구", "서초구", "서초구",
"서초구", "서초구", "서초구", "서초구", "서초구", "서초구", "서초구",
"서초구", "서초구", "성동구", "성동구", "성동구", "성동구", "성동구",
"성동구", "성동구", "성동구", "성동구", "성동구", "성동구", "성동구",
"성동구", "성동구", "성동구", "성동구", "성동구", "성동구", "성동구",
"성동구", "성동구", "성동구", "성동구", "성동구", "성북구", "성북구",
"성북구", "성북구", "성북구", "성북구", "성북구", "성북구", "성북구",
"성북구", "성북구", "성북구", "성북구", "성북구", "성북구", "성북구",
"성북구", "성북구", "성북구", "성북구", "성북구", "성북구", "성북구",
"성북구", "송파구", "송파구", "송파구", "송파구", "송파구", "송파구",
"송파구", "송파구", "송파구", "송파구", "송파구", "송파구", "송파구",
"송파구", "송파구", "송파구", "송파구", "송파구", "송파구", "송파구",
"송파구", "송파구", "송파구", "송파구", "양천구", "양천구", "양천구",
"양천구", "양천구", "양천구", "양천구", "양천구", "양천구", "양천구",
"양천구", "양천구", "양천구", "양천구", "양천구", "양천구", "양천구",
"양천구", "양천구", "양천구", "양천구", "양천구", "양천구", "양천구",
"영등포구", "영등포구", "영등포구", "영등포구", "영등포구", "영등포구",
"영등포구", "영등포구", "영등포구", "영등포구", "영등포구", "영등포구",
"영등포구", "영등포구", "영등포구", "영등포구", "영등포구", "영등포구",
"영등포구", "영등포구", "영등포구", "영등포구", "영등포구", "영등포구",
"용산구", "용산구", "용산구", "용산구", "용산구", "용산구", "용산구",
"용산구", "용산구", "용산구", "용산구", "용산구", "용산구", "용산구",
"용산구", "용산구", "용산구", "용산구", "용산구", "용산구", "용산구",
"용산구", "용산구", "용산구", "은평구", "은평구", "은평구", "은평구",
"은평구", "은평구", "은평구", "은평구", "은평구", "은평구", "은평구",
"은평구", "은평구", "은평구", "은평구", "은평구", "은평구", "은평구",
"은평구", "은평구", "은평구", "은평구", "은평구", "은평구", "종로구",
"종로구", "종로구", "종로구", "종로구", "종로구", "종로구", "종로구",
"종로구", "종로구", "종로구", "종로구", "종로구", "종로구", "종로구",
"종로구", "종로구", "종로구", "종로구", "종로구", "종로구", "종로구",
"종로구", "종로구", "중구", "중구", "중구", "중구", "중구", "중구",
"중구", "중구", "중구", "중구", "중구", "중구", "중구", "중구",
"중구", "중구", "중구", "중구", "중구", "중구", "중구", "중구",
"중구", "중구", "중랑구", "중랑구", "중랑구", "중랑구", "중랑구",
"중랑구", "중랑구", "중랑구", "중랑구", "중랑구", "중랑구", "중랑구",
"중랑구", "중랑구", "중랑구", "중랑구", "중랑구", "중랑구", "중랑구",
"중랑구", "중랑구", "중랑구", "중랑구", "중랑구"), start_hour = c(0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L,
4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L,
18L, 19L, 20L, 21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L,
21L, 22L, 23L, 0L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L,
12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 0L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L), in_minus_out = c(-0.04,
-0.05, -0.02, -0.08, 0.02, -0.08, 0.07, 0.22, 0.14, 0.13, 0.08,
0.04, 0.03, 0.02, -0.02, -0.03, -0.06, -0.11, -0.14, -0.06, -0.09,
-0.07, -0.06, -0.01, 0.02, 0.09, 0.04, 0.06, 0.03, -0.06, -0.14,
-0.16, -0.1, -0.08, -0.06, -0.04, -0.04, -0.04, -0.02, 0.02,
0.01, 0.07, 0.13, 0.07, 0.04, 0.06, 0.07, 0.08, 0.01, 0.06, 0.06,
0.07, 0.02, 0.06, -0.13, -0.05, 0, -0.05, -0.05, -0.04, 0.01,
-0.04, -0.04, -0.06, -0.06, 0.08, 0.03, 0.04, -0.01, 0, 0.02,
-0.03, 0.04, 0.04, 0.02, 0.00999999999999998, -0.01, -0.09, -0.03,
-0.04, -0.01, -0.04, -0.04, -0.04, -0.04, -0.06, -0.03, -0.05,
0.02, 0.03, 0.04, 0.04, 0.03, 0.02, 0.05, 0.02, 0.12, 0.05, 0.01,
0.04, -0.05, -0.1, -0.01, -0.19, -0.26, -0.15, -0.08, -0.06,
-0.04, -0.06, -0.04, -0.04, 0.02, 0.07, 0.14, 0.02, 0.00999999999999998,
0.02, 0.03, 0.03, -0.06, -0.04, -0.08, -0.09, -0.08, -0.07, -0.14,
-0.09, -0.25, -0.08, 0.03, 0.03, 0, 0.03, 0.06, 0.09, 0.05, 0.08,
0.08, 0.03, 0.03, 0.02, -0.02, -0.02, -0.09, 0.04, 0.01, -0.05,
0.16, 0.1, 0.03, -0.07, -0.04, 0.01, -0.02, -0.05, -0.05, -0.04,
-0.05, -0.01, -0.02, 0.04, 0.04, 0, 0.04, 0.08, 0.02, 0, 0.05,
0.02, 0.04, -0.06, 0.02, 0.32, 0.14, 0.15, 0.19, 0.18, 0.05,
0.01, -0.03, -0.07, -0.12, -0.11, -0.07, -0.14, -0.05, 0.00999999999999995,
0, 0.04, 0.07, 0.04, -0.02, -0.01, -0.01, -0.01, -0.02, -0.01,
0, -0.1, 0.02, 0.09, -0.04, -0.01, 0.03, 0, -0.02, -0.02, -0.01,
0.00999999999999995, 0.07, 0.02, 0, -0.02, -0.03, -0.02, 0.01,
-0.01, -0.0499999999999999, 0, 0.1, -0.0700000000000001, -0.1,
-0.01, -0.11, -0.13, -0.04, -0.05, -0.07, -0.05, 0.02, -0.01,
0.02, -0.01, 0.05, 0.06, 0.04, 0.09, 0.07, 0.03, 0.11, 0.04,
0.0800000000000001, 0.07, 0.09, 0.04, -0.01, -0.1, -0.1, -0.09,
-0.09, -0.06, -0.08, -0.03, -0.01, -0.04, 0.02, 0.0800000000000001,
0.04, 0.03, 0.02, 0.06, 0.05, 0.05, 0.06, 0.0499999999999999,
0.08, -0.0199999999999999, -0.15, -0.08, -0.1, -0.1, -0.11, -0.12,
-0.06, -0.05, -0.06, -0.05, -0.07, -0.04, 0.04, 0.09, 0.07, 0.04,
0.05, 0.05, 0.04, 0.03, -0.07, -0.08, -0.01, -0.07, -0.07, 0.03,
0.06, 0.11, 0.16, 0.12, 0.1, 0.05, 0.07, 0.07, 0.04, 0.01, 0.01,
0.02, -0.05, -0.08, -0.07, -0.08, -0.11, -0.12, 0.0499999999999999,
0.0399999999999999, 0, 0.01, -0.01, -0.13, -0.0800000000000001,
-0.25, -0.21, -0.12, -0.08, -0.03, -0.05, -0.0700000000000001,
-0.02, -0.01, -0.02, 0.0099999999999999, 0.0599999999999999,
0.07, 0, 0.06, 0.07, 0.07, -0.09, -0.1, -0.16, 0.05, -0.09, -0.03,
0.2, -0.02, 0.02, 0.04, 0.04, 0.04, 0.02, 0.04, 0.05, 0.04, 0,
0, -0.03, -0.03, -0.02, -0.05, -0.05, -0.06, -0.05, 0.01, 0.03,
0.03, 0.05, 0.03, 0.07, 0.17, 0.22, 0.09, 0.06, 0.06, 0.06, 0.04,
0.07, 0.02, 0.02, -0.05, -0.11, -0.04, 0, -0.05, -0.07, -0.0700000000000001,
0.01, 0.03, 0.03, 0.05, 0.06, 0.05, -0.21, -0.23, -0.2, -0.14,
-0.07, -0.07, -0.02, -0.06, -0.05, -0.05, 0.01, 0.03, 0.08, 0.04,
0.01, 0.06, 0.06, 0.08, -0.01, -0.09, -0.01, -0.02, 0.02, 0.08,
-0.03, -0.02, 0.02, 0, 0, 0.02, 0.03, 0.04, 0.02, 0.02, 0.05,
0.04, 0.01, -0.01, 0, -0.02, -0.03, -0.03, 0.06, 0.01, 0.01,
0.03, -0.01, -0.02, -0.2, -0.11, -0.11, -0.07, -0.03, -0.06,
-0.01, 0.01, -0.02, -0.02, -0.02, 0.07, 0.07, 0.04, -0.01, 0.04,
0, 0.03, -0.05, -0.05, -0.00999999999999995, 0.07, 0.08, 0.09,
0.08, 0.22, 0.16, 0.07, 0.08, 0.07, 0.05, 0.05, 0.08, 0.05, 0,
-0.11, -0.1, -0.02, 0, -0.06, -0.04, -0.05, -0.04, -0.02, -0.01,
-0.03, -0.05, -0.1, 0.2, 0.02, -0.07, 0.00999999999999995, 0.01,
0.07, 0.02, 0.06, 0.03, 0.05, 0, 0, 0, -0.01, -0.02, -0.03, 0.04,
-0.04, 0.05, 0.09, 0.05, 0.12, 0.04, 0.06, -0.23, -0.21, -0.2,
-0.15, -0.18, -0.1, -0.07, -0.06, -0.06, -0.04, 0.04, 0.12, 0.14,
0.09, 0.08, 0.1, 0.13, 0.13, -0.02, -0.1, -0.14, -0.08, -0.11,
-0.01, 0.13, 0.16, 0.14, 0.12, 0.09, 0.05, 0, 0.01, -0.05, -0.06,
-0.08, -0.16, -0.18, -0.15, -0.07, -0.13, -0.09, -0.02, -0.09,
-0.08, -0.07, -0.16, -0.1, 0, 0.18, 0.15, 0.15, 0.1, 0.03, 0.01,
0.01, -0.0199999999999999, -0.0399999999999999, -0.01, -0.0700000000000001,
-0.11, -0.12, -0.0900000000000001, -0.0900000000000001, -0.08,
-0.0700000000000001, -0.0700000000000001, 0.08, 0.11, 0.06, 0.01,
-0.02, 0.05, -0.03, -0.24, -0.2, -0.14, -0.03, -0.07, -0.08,
-0.04, -0.06, -0.02, -0.01, 0.07, 0.13, 0.06, 0.07, 0.09, 0.09,
0.06)), row.names = c(NA, -600L), class = "data.frame")
I currently have a tilemap without dendrogram features. I want to have a dendrogram feature displayed with the current tilemap as shown below:
ggplot(hour_flow, aes(x= start_hour, y= county, fill = in_minus_out)) +
geom_tile() +
scale_fill_gradient(low = "white",
high = "orange") +
theme_bw()
1 answers
solution1
1 2021-06-03 22:06:14
You need to spread out your data into matrix format, transpose and get rid of start_hour . This would work:
library(d3heatmap)
library(dplyr)
library(tidyr)
hour_flow %>%
pivot_wider(names_from=county, values_from=in_minus_out) %>%
data.frame(., row.names =.$start_hour) %>% t() %>% .[-1,] %>%
d3heatmap(colors = "RdYlBu",
dendrogram = "row",
k_rows = 3)
The technical post webpages of this site follow the CC BY-SA 4.0 protocol. If you need to reprint, please indicate the site URL or the original address.Any question please contact:yoyou2525@163.com.
Related Question
d3heatmap - dendrogram row names and colnames without dendrogram plot
d3heatmap returns selection to server
R - d3heatmap - implement breaks
D3heatmap not found for R Version 4.0
save image of d3heatmap in a file
drawing heatmap with dendrogram along with sample labels
d3heatmap() after leaflet() in R Markdown causes addLegend() to disappear
echarts4r: zoom like in d3heatmap
R / d3heatmap - is there a way to rotate the axis label?
R - d3heatmap - ordering rownames and X axis
Related Tags