Choropleth Mapで日本のCOVID19感染状況を表示する

ogr2ogr -f "KML" -mapFieldType Integer64=Real 'japansimple.kml'
jpn.shp

|inputlookup japanSimple

[individuals_csv]
KV_MODE = none
MAX_TIMESTAMP_LOOKAHEAD = 10
SHOULD_LINEMERGE = 0
TIME_FORMAT = %Y,%m,%d
TIME_PREFIX = \d+,\d+,
category = Splunk App Add-on Builder
pulldown_type = 1
REPORT-csv = REPORT-csv
LINE_BREAKER = ([\r\n]+)
NO_BINARY_CHECK = true
description = CSV
disabled = false
SEDCMD = s/^新.*$//

[REPORT-csv]
DELIMS = ","
FIELDS = "newNo","oldNo","year","month","day","old","gender","pref","city"

#!/bin/zsh

url='https://raw.githubusercontent.com/kaz-ogiwara/covid19/master/data/individuals.csv'
cd ../lookups
curl -fsX GET $url -o individuals.csv
{cat header.txt; tail -n +2 individuals.csv} > japan.csv

source="individuals.csv"
| stats count by pref
| lookup prefecture Kanji as pref OUTPUT Prefecture as featureId
| fields - pref
| geom japanSimple
| where isnotnull(featureId)

source="individuals.csv"
| timechart count as Counts by pref where sum in top5
| tail 60
| reverse
| predict 東京都 北海道 兵庫県 愛知県 大阪府 OTHER

[covid19_csv]
INDEXED_EXTRACTIONS = csv
KV_MODE = none
LINE_BREAKER = ([\r\n]+)
NO_BINARY_CHECK = true
SHOULD_LINEMERGE = false
TIMESTAMP_FIELDS = Date Announced
TIME_FORMAT = %F
category = Structured
description = Comma-separated value format. Set header and other settings in "Delimited Settings"
disabled = false
pulldown_type = true

source="COVID19Japan.com Data - Patient Data.csv" sourcetype="covid19_csv"
| stats count by "Residence City_ Prefecture"
| rename "Residence City_ Prefecture" as featureId
| geom japanSimple

.
├── bin
│   ├── README
│   └── dl_csv.sh
├── default
│   ├── app.conf
│   └── data
│       └── ui
│           ├── nav
│           │   └── default.xml
│           └── views
│               └── README
├── local
│   ├── app.conf
│   └── transforms.conf
├── lookups
│   ├── header.csv
│   ├── header.txt
│   ├── individuals.csv
│   ├── japan.csv
│   └── prefecture.csv
└── metadata
    ├── default.meta
    └── local.meta

9 directories, 14 files

| inputlookup japan.csv
| eval _time=strptime(year." ".month." ".day,"%Y %m %d")
| stats count by pref
| lookup prefecture.csv Kanji as pref OUTPUT  Prefecture as featureId
| geom japansimple
| fields - pref
| sort - count

| inputlookup japan.csv
| eval _time=strptime(year." ".month." ".day,"%Y %m %d")
| timechart count by pref where sum in top5
| fields - OTHER
| predict 東京都 北海道 兵庫県 愛知県 大阪府 future_timespan=30

cat data.json | sed 's/\\\u\(....\)/\&#x\1;/g' | sed 's$\\/$/$g' | nkf --numchar-input -w > japan.json

[covid19_json]
DATETIME_CONFIG = CURRENT
INDEXED_EXTRACTIONS = none
KV_MODE = json
LINE_BREAKER = (,)(\"data47|\"category|\"stacking|{\"data\")
NO_BINARY_CHECK = true
category = Structured
description = json
disabled = false
pulldown_type = true
SHOULD_LINEMERGE = false
TRUNCATE = 0
SEDCMD-json = s/^(\".*)/{\1/
SEDCMD-json_f = s/(.*(\]|\")$)/\1}/
JSON_TRIM_BRACES_IN_ARRAY_NAMES = true
SEDCMD-data47 = s/^.*data47\":\[|//
SEDCMD-trim = s/\],\"unit.*$//

source="japan.json" sourcetype="covid19_json"
| rename *{} as *
| fields - _*
| eventstats values(category) as category
| table category data name
| eval tmp=mvzip(category,data)
| streamstats count
| stats values(name) as name by count tmp
| eval date=mvindex(split(tmp,","),0), data=mvindex(split(tmp,","),1)
| table date data name
| eval _time= strptime(date,"%m/%d")
| timechart useother=f span=1d sum(data) by name where sum in top10

...
| table _time 東京都 神奈川県 埼玉県 千葉県 大阪府 兵庫県 福岡県
| predict 東京都 神奈川県 埼玉県 千葉県 大阪府 兵庫県 福岡県 future_timespan=30

...
| fields _time date name data
| stats sum(data) as count by name
| lookup prefecture.csv Kanji as name OUTPUT  Prefecture as featureId 
| geom japansimple
| fields - name
| sort - count