Overview

Dataset statistics

Number of variables10
Number of observations386
Missing cells434
Missing cells (%)11.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.0 KiB
Average record size in memory82.3 B

Variable types

DateTime3
Text3
Numeric1
Categorical3

Dataset

Description관내 아프리카돼지열병(ASF) 처리 현황에 대한 데이터로 신고일, 신고 시간, 발견장소 주소, 확인방법(포획틀, 수렵, 폐사체, 기타), 확인두수 등의 항목을 제공합니다.
Author경기도 양주시
URLhttps://www.data.go.kr/data/15066221/fileData.do

Alerts

확인두수 has constant value ""Constant
관리기관명 has constant value ""Constant
데이터기준일 has constant value ""Constant
확인방법(포획틀_수렵_폐사체 등) is highly imbalanced (59.4%)Imbalance
신고 시간 has 57 (14.8%) missing valuesMissing
비고 has 377 (97.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 04:25:20.715835
Analysis finished2023-12-12 04:25:21.556795
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

신고일
Date

Distinct145
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2019-10-03 00:00:00
Maximum2020-11-23 00:00:00
2023-12-12T13:25:21.648272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:21.881117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신고 시간
Date

MISSING 

Distinct135
Distinct (%)41.0%
Missing57
Missing (%)14.8%
Memory size3.1 KiB
Minimum2023-12-12 00:00:00
Maximum2023-12-12 17:10:00
2023-12-12T13:25:22.100248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:22.287855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

발견장소 주소
Text

Distinct247
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T13:25:22.713619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length18.753886
Min length14

Characters and Unicode

Total characters7239
Distinct characters92
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique178 ?
Unique (%)46.1%

Sample

1st row경기도 양주시 광사동 486
2nd row경기도 양주시 장흥면 일영리 산92-2
3rd row경기도 양주시 남면 한산리 423-3
4th row경기도 양주시 남방동 226-2
5th row경기도 양주시 광적면 비암리 693-14
ValueCountFrequency (%)
경기도 386
21.2%
양주시 386
21.2%
장흥면 74
 
4.1%
광적면 71
 
3.9%
남면 53
 
2.9%
비암리 43
 
2.4%
은현면 34
 
1.9%
백석읍 33
 
1.8%
봉양동 25
 
1.4%
일영리 24
 
1.3%
Other values (258) 696
38.1%
2023-12-12T13:25:23.366275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1439
19.9%
양 423
 
5.8%
도 403
 
5.6%
기 389
 
5.4%
경 386
 
5.3%
주 386
 
5.3%
시 386
 
5.3%
산 327
 
4.5%
리 262
 
3.6%
1 245
 
3.4%
Other values (82) 2593
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4546
62.8%
Space Separator 1439
 
19.9%
Decimal Number 1068
 
14.8%
Dash Punctuation 169
 
2.3%
Other Punctuation 7
 
0.1%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 423
 
9.3%
도 403
 
8.9%
기 389
 
8.6%
경 386
 
8.5%
주 386
 
8.5%
시 386
 
8.5%
산 327
 
7.2%
리 262
 
5.8%
면 232
 
5.1%
동 128
 
2.8%
Other values (66) 1224
26.9%
Decimal Number
ValueCountFrequency (%)
1 245
22.9%
2 139
13.0%
3 125
11.7%
5 112
10.5%
6 96
 
9.0%
4 83
 
7.8%
9 77
 
7.2%
7 68
 
6.4%
8 67
 
6.3%
0 56
 
5.2%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
: 3
42.9%
Space Separator
ValueCountFrequency (%)
1439
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 169
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4546
62.8%
Common 2693
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 423
 
9.3%
도 403
 
8.9%
기 389
 
8.6%
경 386
 
8.5%
주 386
 
8.5%
시 386
 
8.5%
산 327
 
7.2%
리 262
 
5.8%
면 232
 
5.1%
동 128
 
2.8%
Other values (66) 1224
26.9%
Common
ValueCountFrequency (%)
1439
53.4%
1 245
 
9.1%
- 169
 
6.3%
2 139
 
5.2%
3 125
 
4.6%
5 112
 
4.2%
6 96
 
3.6%
4 83
 
3.1%
9 77
 
2.9%
7 68
 
2.5%
Other values (6) 140
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4546
62.8%
ASCII 2693
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1439
53.4%
1 245
 
9.1%
- 169
 
6.3%
2 139
 
5.2%
3 125
 
4.6%
5 112
 
4.2%
6 96
 
3.6%
4 83
 
3.1%
9 77
 
2.9%
7 68
 
2.5%
Other values (6) 140
 
5.2%
Hangul
ValueCountFrequency (%)
양 423
 
9.3%
도 403
 
8.9%
기 389
 
8.6%
경 386
 
8.5%
주 386
 
8.5%
시 386
 
8.5%
산 327
 
7.2%
리 262
 
5.8%
면 232
 
5.1%
동 128
 
2.8%
Other values (66) 1224
26.9%

위도
Real number (ℝ)

Distinct295
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.816886
Minimum37.673225
Maximum37.999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.5 KiB
2023-12-12T13:25:23.571431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.673225
5-th percentile37.703614
Q137.766825
median37.811312
Q337.86475
95-th percentile37.928076
Maximum37.999
Range0.325775
Interquartile range (IQR)0.097925

Descriptive statistics

Standard deviation0.069317083
Coefficient of variation (CV)0.0018329664
Kurtosis-0.78912896
Mean37.816886
Median Absolute Deviation (MAD)0.0472555
Skewness0.10720458
Sum14597.318
Variance0.004804858
MonotonicityNot monotonic
2023-12-12T13:25:23.777024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.811327 9
 
2.3%
37.923419 4
 
1.0%
37.840935 4
 
1.0%
37.801236 4
 
1.0%
37.72329 4
 
1.0%
37.89945 3
 
0.8%
37.718831 3
 
0.8%
37.805978 3
 
0.8%
37.843813 3
 
0.8%
37.818928 3
 
0.8%
Other values (285) 346
89.6%
ValueCountFrequency (%)
37.673225 1
0.3%
37.681408 1
0.3%
37.682277 1
0.3%
37.690172 1
0.3%
37.692427 1
0.3%
37.692923 1
0.3%
37.693116 1
0.3%
37.694983 2
0.5%
37.69613 2
0.5%
37.698809 1
0.3%
ValueCountFrequency (%)
37.999 1
0.3%
37.975521 1
0.3%
37.941385 1
0.3%
37.935585 1
0.3%
37.935081 1
0.3%
37.934791 2
0.5%
37.933689 1
0.3%
37.933247 1
0.3%
37.93294 2
0.5%
37.931019 1
0.3%

경도
Text

Distinct301
Distinct (%)78.0%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T13:25:24.160601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.9326425
Min length8

Characters and Unicode

Total characters3834
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)64.5%

Sample

1st row127.066458
2nd row126.931175
3rd row126.993596
4th row127.040631
5th row126.921399
ValueCountFrequency (%)
126.956117 9
 
2.3%
126.937822 9
 
2.3%
126.979927 4
 
1.0%
127.022429 4
 
1.0%
127.110101 4
 
1.0%
127.036378 4
 
1.0%
127.02717 3
 
0.8%
126.933088 3
 
0.8%
127.096571 3
 
0.8%
127.032466 3
 
0.8%
Other values (291) 340
88.1%
2023-12-12T13:25:24.769363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 610
15.9%
2 572
14.9%
9 397
10.4%
7 396
10.3%
6 394
10.3%
. 387
10.1%
0 298
7.8%
3 234
 
6.1%
8 211
 
5.5%
4 174
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3447
89.9%
Other Punctuation 387
 
10.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 610
17.7%
2 572
16.6%
9 397
11.5%
7 396
11.5%
6 394
11.4%
0 298
8.6%
3 234
 
6.8%
8 211
 
6.1%
4 174
 
5.0%
5 161
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 387
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3834
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 610
15.9%
2 572
14.9%
9 397
10.4%
7 396
10.3%
6 394
10.3%
. 387
10.1%
0 298
7.8%
3 234
 
6.1%
8 211
 
5.5%
4 174
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3834
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 610
15.9%
2 572
14.9%
9 397
10.4%
7 396
10.3%
6 394
10.3%
. 387
10.1%
0 298
7.8%
3 234
 
6.1%
8 211
 
5.5%
4 174
 
4.5%

확인방법(포획틀_수렵_폐사체 등)
Categorical

IMBALANCE 

Distinct6
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
수렵
298 
포획틀
66 
폐사체
 
10
로드킬
 
9
살처분
 
2

Length

Max length8
Median length2
Mean length2.2409326
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row살처분
2nd row로드킬
3rd row로드킬
4th row살처분
5th row로드킬

Common Values

ValueCountFrequency (%)
수렵 298
77.2%
포획틀 66
 
17.1%
폐사체 10
 
2.6%
로드킬 9
 
2.3%
살처분 2
 
0.5%
기타(울타리망) 1
 
0.3%

Length

2023-12-12T13:25:24.958501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:25.139917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수렵 298
77.2%
포획틀 66
 
17.1%
폐사체 10
 
2.6%
로드킬 9
 
2.3%
살처분 2
 
0.5%
기타(울타리망 1
 
0.3%

확인두수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
1
386 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 386
100.0%

Length

2023-12-12T13:25:25.313237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:25.444508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 386
100.0%

비고
Text

MISSING 

Distinct9
Distinct (%)100.0%
Missing377
Missing (%)97.7%
Memory size3.1 KiB
2023-12-12T13:25:25.650392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9
Mean length6.8888889
Min length3

Characters and Unicode

Total characters62
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)100.0%

Sample

1st row기타(쇠몽둥이)
2nd row폐사체(광적면 비암리)
3rd row조소앙선생묘 주변
4th row남면 황방리 폭포산장 뒤
5th row운경공원
ValueCountFrequency (%)
기타(쇠몽둥이 1
 
6.7%
폐사체(광적면 1
 
6.7%
비암리 1
 
6.7%
조소앙선생묘 1
 
6.7%
주변 1
 
6.7%
남면 1
 
6.7%
황방리 1
 
6.7%
폭포산장 1
 
6.7%
뒤 1
 
6.7%
운경공원 1
 
6.7%
Other values (5) 5
33.3%
2023-12-12T13:25:26.086356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
 
9.7%
리 3
 
4.8%
면 2
 
3.2%
( 2
 
3.2%
산 2
 
3.2%
) 2
 
3.2%
공 2
 
3.2%
원 2
 
3.2%
불 1
 
1.6%
폭 1
 
1.6%
Other values (39) 39
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
83.9%
Space Separator 6
 
9.7%
Open Punctuation 2
 
3.2%
Close Punctuation 2
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 3
 
5.8%
면 2
 
3.8%
산 2
 
3.8%
공 2
 
3.8%
원 2
 
3.8%
불 1
 
1.9%
폭 1
 
1.9%
포 1
 
1.9%
장 1
 
1.9%
뒤 1
 
1.9%
Other values (36) 36
69.2%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
83.9%
Common 10
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 3
 
5.8%
면 2
 
3.8%
산 2
 
3.8%
공 2
 
3.8%
원 2
 
3.8%
불 1
 
1.9%
폭 1
 
1.9%
포 1
 
1.9%
장 1
 
1.9%
뒤 1
 
1.9%
Other values (36) 36
69.2%
Common
ValueCountFrequency (%)
6
60.0%
( 2
 
20.0%
) 2
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
83.9%
ASCII 10
 
16.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
60.0%
( 2
 
20.0%
) 2
 
20.0%
Hangul
ValueCountFrequency (%)
리 3
 
5.8%
면 2
 
3.8%
산 2
 
3.8%
공 2
 
3.8%
원 2
 
3.8%
불 1
 
1.9%
폭 1
 
1.9%
포 1
 
1.9%
장 1
 
1.9%
뒤 1
 
1.9%
Other values (36) 36
69.2%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
양주시 환경관리과
386 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시 환경관리과
2nd row양주시 환경관리과
3rd row양주시 환경관리과
4th row양주시 환경관리과
5th row양주시 환경관리과

Common Values

ValueCountFrequency (%)
양주시 환경관리과 386
100.0%

Length

2023-12-12T13:25:26.240594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:25:26.345470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양주시 386
50.0%
환경관리과 386
50.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
Minimum2020-11-25 00:00:00
Maximum2020-11-25 00:00:00
2023-12-12T13:25:26.790340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:25:26.915558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:25:21.013222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:25:27.009975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도확인방법(포획틀_수렵_폐사체 등)비고
위도1.0000.2981.000
확인방법(포획틀_수렵_폐사체 등)0.2981.0001.000
비고1.0001.0001.000
2023-12-12T13:25:27.129437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도확인방법(포획틀_수렵_폐사체 등)
위도1.0000.160
확인방법(포획틀_수렵_폐사체 등)0.1601.000

Missing values

2023-12-12T13:25:21.160004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:25:21.383171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T13:25:21.497349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

신고일신고 시간발견장소 주소위도경도확인방법(포획틀_수렵_폐사체 등)확인두수비고관리기관명데이터기준일
02019-10-03<NA>경기도 양주시 광사동 48637.770512127.066458살처분1<NA>양주시 환경관리과2020-11-25
12019-10-09<NA>경기도 양주시 장흥면 일영리 산92-237.709613126.931175로드킬1<NA>양주시 환경관리과2020-11-25
22019-10-14<NA>경기도 양주시 남면 한산리 423-337.907322126.993596로드킬1<NA>양주시 환경관리과2020-11-25
32019-10-21<NA>경기도 양주시 남방동 226-237.768266127.040631살처분1기타(쇠몽둥이)양주시 환경관리과2020-11-25
42019-10-22<NA>경기도 양주시 광적면 비암리 693-1437.807118126.921399로드킬1폐사체(광적면 비암리)양주시 환경관리과2020-11-25
52019-10-28<NA>경기도 양주시 장흥면 울대리 381-337.718944126.978346로드킬1<NA>양주시 환경관리과2020-11-25
62019-10-29<NA>경기도 양주시 만송동 산11237.777963127.087078수렵1<NA>양주시 환경관리과2020-11-25
72019-10-3009:50경기도 양주시 남면 황방리 산2237.930694126.99783수렵1조소앙선생묘 주변양주시 환경관리과2020-11-25
82019-10-3010:10경기도 양주시 은현면 봉암리 284-237.925268127.003135수렵1<NA>양주시 환경관리과2020-11-25
92019-10-3011:00경기도 양주시 남면 황방리 산10837.930566126.983923수렵1<NA>양주시 환경관리과2020-11-25
신고일신고 시간발견장소 주소위도경도확인방법(포획틀_수렵_폐사체 등)확인두수비고관리기관명데이터기준일
3762020-11-02<NA>경기도 양주시 백석읍 복지리 463-137.762505126.994225수렵1<NA>양주시 환경관리과2020-11-25
3772020-11-03<NA>경기도 양주시 광적면 비암리 산1337.811281126.938181수렵1<NA>양주시 환경관리과2020-11-25
3782020-11-04<NA>경기도 양주시 광사동 산15737.76652127.065538수렵1<NA>양주시 환경관리과2020-11-25
3792020-11-06<NA>경기도 양주시 광적면 비암리 산23-1937.80105126.933981수렵1<NA>양주시 환경관리과2020-11-25
3802020-11-06<NA>경기도 양주시 은현면 선암리 산2-537.876575127.042932수렵1<NA>양주시 환경관리과2020-11-25
3812020-11-16<NA>경기도 양주시 남면 한산리 산3037.89945127.0032수렵1<NA>양주시 환경관리과2020-11-25
3822020-11-20<NA>경기도 양주시 백석읍 방성리 48237.79685127.009693포획틀1<NA>양주시 환경관리과2020-11-25
3832020-11-20<NA>경기도 양주시 남면 황방리 산237.935081126.999298수렵1<NA>양주시 환경관리과2020-11-25
3842020-11-20<NA>경기도 양주시 백석읍 방성리 산10937.796228127.013778수렵1<NA>양주시 환경관리과2020-11-25
3852020-11-23<NA>경기도 양주시 산북동 253-637.798951127.040518포획틀1<NA>양주시 환경관리과2020-11-25