Overview

Dataset statistics

Number of variables16
Number of observations240
Missing cells700
Missing cells (%)18.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.3 KiB
Average record size in memory133.6 B

Variable types

Text3
Categorical5
DateTime3
Numeric4
Unsupported1

Dataset

Description소규모 공공시설 위험지정 정보 현황(제공표준)
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=98794V0223GQQ9O1P4WA21654104&infSeq=1

Alerts

위험시설지정고시번호 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 4 other fieldsHigh correlation
위도 is highly overall correlated with 경도 and 4 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위험시설지정사유 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
소재지도로명주소 has 230 (95.8%) missing valuesMissing
위험시설해제일자 has 230 (95.8%) missing valuesMissing
시설부속물 has 240 (100.0%) missing valuesMissing
시설부속물 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-10 21:41:23.510453
Analysis finished2024-05-10 21:41:29.965546
Duration6.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct234
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-10T21:41:30.244071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length14
Mean length8.8625
Min length3

Characters and Unicode

Total characters2127
Distinct characters172
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique231 ?
Unique (%)96.2%

Sample

1st row원당리_세천0004
2nd row두일리_마을진입로0009
3rd row석장리_세천0006
4th row백석리_세천0002
5th row무등리_세천0005
ValueCountFrequency (%)
소교량 54
 
13.1%
세천 13
 
3.1%
마을진입로 12
 
2.9%
농로 7
 
1.7%
초과2리 5
 
1.2%
신읍동 4
 
1.0%
지현리 4
 
1.0%
취입보 4
 
1.0%
동교동 4
 
1.0%
주원리 3
 
0.7%
Other values (285) 303
73.4%
2024-05-10T21:41:31.195401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
8.2%
리 120
 
5.6%
1 115
 
5.4%
교 108
 
5.1%
- 90
 
4.2%
천 88
 
4.1%
소 84
 
3.9%
세 82
 
3.9%
0 81
 
3.8%
량 80
 
3.8%
Other values (162) 1105
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1281
60.2%
Decimal Number 559
26.3%
Space Separator 174
 
8.2%
Dash Punctuation 90
 
4.2%
Connector Punctuation 18
 
0.8%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 120
 
9.4%
교 108
 
8.4%
천 88
 
6.9%
소 84
 
6.6%
세 82
 
6.4%
량 80
 
6.2%
로 49
 
3.8%
동 39
 
3.0%
마 27
 
2.1%
입 27
 
2.1%
Other values (146) 577
45.0%
Decimal Number
ValueCountFrequency (%)
1 115
20.6%
0 81
14.5%
2 74
13.2%
4 57
10.2%
3 54
9.7%
7 48
8.6%
6 39
 
7.0%
5 38
 
6.8%
8 29
 
5.2%
9 24
 
4.3%
Space Separator
ValueCountFrequency (%)
174
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1281
60.2%
Common 846
39.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 120
 
9.4%
교 108
 
8.4%
천 88
 
6.9%
소 84
 
6.6%
세 82
 
6.4%
량 80
 
6.2%
로 49
 
3.8%
동 39
 
3.0%
마 27
 
2.1%
입 27
 
2.1%
Other values (146) 577
45.0%
Common
ValueCountFrequency (%)
174
20.6%
1 115
13.6%
- 90
10.6%
0 81
9.6%
2 74
8.7%
4 57
 
6.7%
3 54
 
6.4%
7 48
 
5.7%
6 39
 
4.6%
5 38
 
4.5%
Other values (6) 76
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1281
60.2%
ASCII 846
39.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
20.6%
1 115
13.6%
- 90
10.6%
0 81
9.6%
2 74
8.7%
4 57
 
6.7%
3 54
 
6.4%
7 48
 
5.7%
6 39
 
4.6%
5 38
 
4.5%
Other values (6) 76
9.0%
Hangul
ValueCountFrequency (%)
리 120
 
9.4%
교 108
 
8.4%
천 88
 
6.9%
소 84
 
6.6%
세 82
 
6.4%
량 80
 
6.2%
로 49
 
3.8%
동 39
 
3.0%
마 27
 
2.1%
입 27
 
2.1%
Other values (146) 577
45.0%

소재지도로명주소
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing230
Missing (%)95.8%
Memory size2.0 KiB
2024-05-10T21:41:31.575887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length21
Mean length19.1
Min length15

Characters and Unicode

Total characters191
Distinct characters52
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

Unique10 ?
Unique (%)100.0%

Sample

1st row경기도 양평군 개군면 독골길
2nd row경기도 양평군 용문면 장수길52번길 39
3rd row경기도 양평군 양평읍 봉성안2길 23
4th row경기도 양평군 용문면 강이대길38번길 5-5
5th row경기도 양평군 서종면 바치울길
ValueCountFrequency (%)
경기도 10
22.7%
양평군 9
20.5%
용문면 4
 
9.1%
장수길52번길 2
 
4.5%
양평읍 2
 
4.5%
바치울길 1
 
2.3%
도지울길12번길 1
 
2.3%
퇴촌면 1
 
2.3%
광주시 1
 
2.3%
대흥1길 1
 
2.3%
Other values (12) 12
27.3%
2024-05-10T21:41:32.376190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
17.8%
길 14
 
7.3%
평 12
 
6.3%
도 11
 
5.8%
양 11
 
5.8%
경 10
 
5.2%
군 10
 
5.2%
기 10
 
5.2%
면 8
 
4.2%
2 5
 
2.6%
Other values (42) 66
34.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135
70.7%
Space Separator 34
 
17.8%
Decimal Number 20
 
10.5%
Dash Punctuation 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 14
 
10.4%
평 12
 
8.9%
도 11
 
8.1%
양 11
 
8.1%
경 10
 
7.4%
군 10
 
7.4%
기 10
 
7.4%
면 8
 
5.9%
문 4
 
3.0%
번 4
 
3.0%
Other values (31) 41
30.4%
Decimal Number
ValueCountFrequency (%)
2 5
25.0%
3 4
20.0%
5 4
20.0%
1 2
 
10.0%
0 1
 
5.0%
6 1
 
5.0%
8 1
 
5.0%
9 1
 
5.0%
7 1
 
5.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135
70.7%
Common 56
29.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 14
 
10.4%
평 12
 
8.9%
도 11
 
8.1%
양 11
 
8.1%
경 10
 
7.4%
군 10
 
7.4%
기 10
 
7.4%
면 8
 
5.9%
문 4
 
3.0%
번 4
 
3.0%
Other values (31) 41
30.4%
Common
ValueCountFrequency (%)
34
60.7%
2 5
 
8.9%
3 4
 
7.1%
5 4
 
7.1%
- 2
 
3.6%
1 2
 
3.6%
0 1
 
1.8%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135
70.7%
ASCII 56
29.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
60.7%
2 5
 
8.9%
3 4
 
7.1%
5 4
 
7.1%
- 2
 
3.6%
1 2
 
3.6%
0 1
 
1.8%
6 1
 
1.8%
8 1
 
1.8%
9 1
 
1.8%
Hangul
ValueCountFrequency (%)
길 14
 
10.4%
평 12
 
8.9%
도 11
 
8.1%
양 11
 
8.1%
경 10
 
7.4%
군 10
 
7.4%
기 10
 
7.4%
면 8
 
5.9%
문 4
 
3.0%
번 4
 
3.0%
Other values (31) 41
30.4%

소재지지번주소
Text

Distinct239
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-05-10T21:41:32.965003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22.5
Mean length19.595833
Min length14

Characters and Unicode

Total characters4703
Distinct characters156
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

Unique238 ?
Unique (%)99.2%

Sample

1st row경기도 연천군 장남면 원당리 767
2nd row경기도 연천군 백학면 두일리 33-9
3rd row경기도 연천군 백학면 석장리 873
4th row경기도 연천군 미산면 백석리 163
5th row경기도 연천군 왕징면 무등리 238
ValueCountFrequency (%)
경기도 240
22.1%
광주시 96
 
8.8%
포천시 90
 
8.3%
여주시 20
 
1.8%
연천군 18
 
1.7%
곤지암읍 17
 
1.6%
오포읍 16
 
1.5%
초월읍 14
 
1.3%
퇴촌면 11
 
1.0%
양평군 9
 
0.8%
Other values (364) 556
51.1%
2024-05-10T21:41:34.061929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
847
18.0%
도 256
 
5.4%
기 243
 
5.2%
경 240
 
5.1%
시 213
 
4.5%
리 206
 
4.4%
- 166
 
3.5%
1 153
 
3.3%
면 139
 
3.0%
천 123
 
2.6%
Other values (146) 2117
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2807
59.7%
Decimal Number 883
 
18.8%
Space Separator 847
 
18.0%
Dash Punctuation 166
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 256
 
9.1%
기 243
 
8.7%
경 240
 
8.6%
시 213
 
7.6%
리 206
 
7.3%
면 139
 
5.0%
천 123
 
4.4%
주 119
 
4.2%
포 106
 
3.8%
광 97
 
3.5%
Other values (134) 1065
37.9%
Decimal Number
ValueCountFrequency (%)
1 153
17.3%
3 121
13.7%
2 102
11.6%
4 93
10.5%
7 84
9.5%
6 82
9.3%
5 73
8.3%
9 67
7.6%
8 54
 
6.1%
0 54
 
6.1%
Space Separator
ValueCountFrequency (%)
847
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2807
59.7%
Common 1896
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 256
 
9.1%
기 243
 
8.7%
경 240
 
8.6%
시 213
 
7.6%
리 206
 
7.3%
면 139
 
5.0%
천 123
 
4.4%
주 119
 
4.2%
포 106
 
3.8%
광 97
 
3.5%
Other values (134) 1065
37.9%
Common
ValueCountFrequency (%)
847
44.7%
- 166
 
8.8%
1 153
 
8.1%
3 121
 
6.4%
2 102
 
5.4%
4 93
 
4.9%
7 84
 
4.4%
6 82
 
4.3%
5 73
 
3.9%
9 67
 
3.5%
Other values (2) 108
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2807
59.7%
ASCII 1896
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
847
44.7%
- 166
 
8.8%
1 153
 
8.1%
3 121
 
6.4%
2 102
 
5.4%
4 93
 
4.9%
7 84
 
4.4%
6 82
 
4.3%
5 73
 
3.9%
9 67
 
3.5%
Other values (2) 108
 
5.7%
Hangul
ValueCountFrequency (%)
도 256
 
9.1%
기 243
 
8.7%
경 240
 
8.6%
시 213
 
7.6%
리 206
 
7.3%
면 139
 
5.0%
천 123
 
4.4%
주 119
 
4.2%
포 106
 
3.8%
광 97
 
3.5%
Other values (134) 1065
37.9%

시설유형
Categorical

Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
소교량
98 
세천
82 
농로
28 
마을진입로
22 
낙차공
 
6

Length

Max length5
Median length3
Mean length2.725
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row세천
2nd row마을진입로
3rd row세천
4th row세천
5th row세천

Common Values

ValueCountFrequency (%)
소교량 98
40.8%
세천 82
34.2%
농로 28
 
11.7%
마을진입로 22
 
9.2%
낙차공 6
 
2.5%
취입보 4
 
1.7%

Length

2024-05-10T21:41:34.420865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:41:34.794524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소교량 98
40.8%
세천 82
34.2%
농로 28
 
11.7%
마을진입로 22
 
9.2%
낙차공 6
 
2.5%
취입보 4
 
1.7%

위험시설지정고시번호
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
93 
제2021-321호
85 
2021-159
18 
제2018-267호
 
8
제2017-112호
 
6
Other values (15)
30 

Length

Max length10
Median length9
Mean length7.3625
Min length4

Unique

Unique10 ?
Unique (%)4.2%

Sample

1st row2021-159
2nd row2021-159
3rd row2021-159
4th row2021-159
5th row2021-159

Common Values

ValueCountFrequency (%)
<NA> 93
38.8%
제2021-321호 85
35.4%
2021-159 18
 
7.5%
제2018-267호 8
 
3.3%
제2017-112호 6
 
2.5%
제2021-32호 6
 
2.5%
2020-150 5
 
2.1%
제2017-284호 5
 
2.1%
제2017-12호 2
 
0.8%
제2022-166호 2
 
0.8%
Other values (10) 10
 
4.2%

Length

2024-05-10T21:41:35.236215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 93
38.8%
제2021-321호 85
35.4%
2021-159 18
 
7.5%
제2018-267호 8
 
3.3%
제2017-112호 6
 
2.5%
제2021-32호 6
 
2.5%
2020-150 5
 
2.1%
제2017-284호 5
 
2.1%
제2017-12호 2
 
0.8%
제2022-166호 2
 
0.8%
Other values (10) 10
 
4.2%

위험시설지정일자
Date

Distinct31
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2016-11-01 00:00:00
Maximum2023-04-20 00:00:00
2024-05-10T21:41:35.630425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:36.095013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

위험시설지정사유
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
위험도평가 불량
105 
<NA>
90 
위험도평가결과 불량
31 
위험도평가 보통
11 
도로폭 협소
 
2

Length

Max length10
Median length8
Mean length6.7333333
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row위험도평가결과 불량
2nd row위험도평가결과 불량
3rd row위험도평가결과 불량
4th row위험도평가결과 불량
5th row위험도평가결과 불량

Common Values

ValueCountFrequency (%)
위험도평가 불량 105
43.8%
<NA> 90
37.5%
위험도평가결과 불량 31
 
12.9%
위험도평가 보통 11
 
4.6%
도로폭 협소 2
 
0.8%
교량부분파손 1
 
0.4%

Length

2024-05-10T21:41:36.809046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:41:37.269348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불량 136
35.0%
위험도평가 116
29.8%
na 90
23.1%
위험도평가결과 31
 
8.0%
보통 11
 
2.8%
도로폭 2
 
0.5%
협소 2
 
0.5%
교량부분파손 1
 
0.3%

위험시설해제일자
Date

MISSING 

Distinct2
Distinct (%)20.0%
Missing230
Missing (%)95.8%
Memory size2.0 KiB
Minimum2018-10-11 00:00:00
Maximum2020-07-14 00:00:00
2024-05-10T21:41:37.585931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:37.914555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct239
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.647532
Minimum37.054922
Maximum38.214992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-10T21:41:38.480469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.054922
5-th percentile37.317649
Q137.382725
median37.489981
Q337.919461
95-th percentile38.113362
Maximum38.214992
Range1.1600702
Interquartile range (IQR)0.53673568

Descriptive statistics

Standard deviation0.29399534
Coefficient of variation (CV)0.0078091532
Kurtosis-1.4864952
Mean37.647532
Median Absolute Deviation (MAD)0.17241739
Skewness0.25152779
Sum9035.4076
Variance0.086433261
MonotonicityNot monotonic
2024-05-10T21:41:39.042216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3829039401 2
 
0.8%
37.99032812 1
 
0.4%
38.03420632 1
 
0.4%
37.581814 1
 
0.4%
37.577044 1
 
0.4%
37.592916 1
 
0.4%
37.3393374856 1
 
0.4%
37.3418407 1
 
0.4%
37.3594445 1
 
0.4%
37.3647241 1
 
0.4%
Other values (229) 229
95.4%
ValueCountFrequency (%)
37.054921645 1
0.4%
37.1021404203 1
0.4%
37.104579 1
0.4%
37.24001328 1
0.4%
37.257450202 1
0.4%
37.27255716 1
0.4%
37.2776018 1
0.4%
37.291586 1
0.4%
37.303215 1
0.4%
37.30721256 1
0.4%
ValueCountFrequency (%)
38.21499182 1
0.4%
38.1604623228 1
0.4%
38.14848353 1
0.4%
38.1479864223 1
0.4%
38.1477156 1
0.4%
38.1463099 1
0.4%
38.1435412702 1
0.4%
38.14007991 1
0.4%
38.12437639 1
0.4%
38.12256571 1
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct239
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.28001
Minimum126.88243
Maximum127.74621
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-10T21:41:39.555774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.88243
5-th percentile127.06709
Q1127.1889
median127.24777
Q3127.34411
95-th percentile127.59295
Maximum127.74621
Range0.8637746
Interquartile range (IQR)0.15521387

Descriptive statistics

Standard deviation0.15161423
Coefficient of variation (CV)0.0011911865
Kurtosis0.68287593
Mean127.28001
Median Absolute Deviation (MAD)0.074951478
Skewness0.70349945
Sum30547.202
Variance0.022986873
MonotonicityNot monotonic
2024-05-10T21:41:40.293288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.3181372915 2
 
0.8%
126.8824344 1
 
0.4%
126.9239504 1
 
0.4%
127.1400341 1
 
0.4%
127.135568 1
 
0.4%
127.163878 1
 
0.4%
127.2093660518 1
 
0.4%
127.2106067039 1
 
0.4%
127.1946507 1
 
0.4%
127.1590087161 1
 
0.4%
Other values (229) 229
95.4%
ValueCountFrequency (%)
126.8824344 1
0.4%
126.9160962 1
0.4%
126.9239504 1
0.4%
126.9691907 1
0.4%
127.0023197 1
0.4%
127.0209891 1
0.4%
127.0314256 1
0.4%
127.0353529 1
0.4%
127.0421967 1
0.4%
127.0536066 1
0.4%
ValueCountFrequency (%)
127.746209 1
0.4%
127.6824191 1
0.4%
127.6765951 1
0.4%
127.6576368 1
0.4%
127.6437201 1
0.4%
127.6367654 1
0.4%
127.6366677 1
0.4%
127.6257811 1
0.4%
127.6234629 1
0.4%
127.6233298 1
0.4%

연장
Real number (ℝ)

Distinct128
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean251.75417
Minimum1
Maximum2530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-10T21:41:40.700638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q110
median99.5
Q3369.25
95-th percentile950.7
Maximum2530
Range2529
Interquartile range (IQR)359.25

Descriptive statistics

Standard deviation361.58984
Coefficient of variation (CV)1.4362815
Kurtosis8.8514122
Mean251.75417
Median Absolute Deviation (MAD)95.5
Skewness2.4955355
Sum60421
Variance130747.22
MonotonicityNot monotonic
2024-05-10T21:41:41.151665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 17
 
7.1%
10 9
 
3.8%
5 8
 
3.3%
6 8
 
3.3%
3 7
 
2.9%
100 7
 
2.9%
8 6
 
2.5%
7 6
 
2.5%
15 5
 
2.1%
80 5
 
2.1%
Other values (118) 162
67.5%
ValueCountFrequency (%)
1 2
 
0.8%
2 2
 
0.8%
3 7
2.9%
4 17
7.1%
5 8
3.3%
6 8
3.3%
7 6
 
2.5%
8 6
 
2.5%
9 2
 
0.8%
10 9
3.8%
ValueCountFrequency (%)
2530 1
0.4%
1970 1
0.4%
1578 1
0.4%
1280 1
0.4%
1210 1
0.4%
1205 1
0.4%
1200 1
0.4%
1178 1
0.4%
1175 1
0.4%
1118 1
0.4%

폭
Real number (ℝ)

Distinct35
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5170833
Minimum0
Maximum26
Zeros2
Zeros (%)0.8%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-05-10T21:41:41.559838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q13
median4
Q35
95-th percentile9.24
Maximum26
Range26
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.7268692
Coefficient of variation (CV)0.60367919
Kurtosis17.888571
Mean4.5170833
Median Absolute Deviation (MAD)1
Skewness3.1779254
Sum1084.1
Variance7.4358157
MonotonicityNot monotonic
2024-05-10T21:41:41.981107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
4.0 57
23.8%
3.0 43
17.9%
5.0 27
11.2%
6.0 19
 
7.9%
2.5 14
 
5.8%
3.5 11
 
4.6%
8.0 10
 
4.2%
2.0 10
 
4.2%
4.5 7
 
2.9%
12.0 4
 
1.7%
Other values (25) 38
15.8%
ValueCountFrequency (%)
0.0 2
 
0.8%
0.4 3
 
1.2%
0.7 1
 
0.4%
1.0 1
 
0.4%
1.5 2
 
0.8%
2.0 10
4.2%
2.3 2
 
0.8%
2.5 14
5.8%
2.6 1
 
0.4%
2.7 1
 
0.4%
ValueCountFrequency (%)
26.0 1
 
0.4%
16.0 1
 
0.4%
15.0 1
 
0.4%
13.0 1
 
0.4%
12.0 4
 
1.7%
10.0 4
 
1.7%
9.2 1
 
0.4%
9.0 1
 
0.4%
8.0 10
4.2%
7.5 1
 
0.4%

시설부속물
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing240
Missing (%)100.0%
Memory size2.2 KiB

관리기관전화번호
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
031-760-2948
96 
031-538-3120
90 
031-887-2552
20 
031-839-2168
18 
031-770-3968
 
9
Other values (4)
 
7

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique2 ?
Unique (%)0.8%

Sample

1st row031-839-2168
2nd row031-839-2168
3rd row031-839-2168
4th row031-839-2168
5th row031-839-2168

Common Values

ValueCountFrequency (%)
031-760-2948 96
40.0%
031-538-3120 90
37.5%
031-887-2552 20
 
8.3%
031-839-2168 18
 
7.5%
031-770-3968 9
 
3.8%
031-644-2968 3
 
1.2%
031-550-2315 2
 
0.8%
031-550-8423 1
 
0.4%
031-644-2967 1
 
0.4%

Length

2024-05-10T21:41:42.385721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:41:42.715649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-760-2948 96
40.0%
031-538-3120 90
37.5%
031-887-2552 20
 
8.3%
031-839-2168 18
 
7.5%
031-770-3968 9
 
3.8%
031-644-2968 3
 
1.2%
031-550-2315 2
 
0.8%
031-550-8423 1
 
0.4%
031-644-2967 1
 
0.4%

관리기관명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
경기도 광주시청
96 
경기도 포천시청
90 
경기도 여주시청
20 
경기도 연천군청 건설과
18 
경기도 양평군청(도로과)
 
9
Other values (2)
 
7

Length

Max length13
Median length8
Mean length8.475
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 연천군청 건설과
2nd row경기도 연천군청 건설과
3rd row경기도 연천군청 건설과
4th row경기도 연천군청 건설과
5th row경기도 연천군청 건설과

Common Values

ValueCountFrequency (%)
경기도 광주시청 96
40.0%
경기도 포천시청 90
37.5%
경기도 여주시청 20
 
8.3%
경기도 연천군청 건설과 18
 
7.5%
경기도 양평군청(도로과) 9
 
3.8%
경기도 이천시청 4
 
1.7%
경기도 구리시 3
 
1.2%

Length

2024-05-10T21:41:43.218985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:41:43.600763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 240
48.2%
광주시청 96
 
19.3%
포천시청 90
 
18.1%
여주시청 20
 
4.0%
연천군청 18
 
3.6%
건설과 18
 
3.6%
양평군청(도로과 9
 
1.8%
이천시청 4
 
0.8%
구리시 3
 
0.6%

데이터기준일자
Date

Distinct7
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
Minimum2023-05-23 00:00:00
Maximum2023-12-01 00:00:00
2024-05-10T21:41:44.037303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:44.305709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

Interactions

2024-05-10T21:41:27.828900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:25.054664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:26.066177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:26.940694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:28.038760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:25.310939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:26.321244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:27.149402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:28.228404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:25.572586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:26.507449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:27.388581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:28.434592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:25.810938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:26.748827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:41:27.585029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:41:44.528433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지도로명주소시설유형위험시설지정고시번호위험시설지정일자위험시설지정사유위험시설해제일자위도경도연장폭관리기관전화번호관리기관명데이터기준일자
소재지도로명주소1.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.0001.000
시설유형1.0001.0000.3580.5260.4660.0920.2720.1380.5210.3450.4560.3980.398
위험시설지정고시번호1.0000.3581.0001.0000.8360.8470.9270.8260.0000.0681.0001.0001.000
위험시설지정일자1.0000.5261.0001.0000.9551.0000.9520.8770.0000.0001.0001.0001.000
위험시설지정사유1.0000.4660.8360.9551.000NaN0.7140.7210.3250.0560.9180.8080.808
위험시설해제일자NaN0.0920.8471.000NaN1.0000.3530.0000.7100.000NaNNaNNaN
위도1.0000.2720.9270.9520.7140.3531.0000.6670.2080.1970.8460.8720.872
경도1.0000.1380.8260.8770.7210.0000.6671.0000.1690.0000.7550.7770.777
연장1.0000.5210.0000.0000.3250.7100.2080.1691.0000.0000.4470.3450.345
폭1.0000.3450.0680.0000.0560.0000.1970.0000.0001.0000.1430.1330.133
관리기관전화번호1.0000.4561.0001.0000.918NaN0.8460.7550.4470.1431.0001.0001.000
관리기관명1.0000.3981.0001.0000.808NaN0.8720.7770.3450.1331.0001.0001.000
데이터기준일자1.0000.3981.0001.0000.808NaN0.8720.7770.3450.1331.0001.0001.000
2024-05-10T21:41:44.905470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위험시설지정고시번호위험시설지정사유관리기관전화번호시설유형관리기관명
위험시설지정고시번호1.0000.6330.9530.1750.949
위험시설지정사유0.6331.0000.8530.1890.696
관리기관전화번호0.9530.8531.0000.2440.996
시설유형0.1750.1890.2441.0000.249
관리기관명0.9490.6960.9960.2491.000
2024-05-10T21:41:45.201034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도연장폭시설유형위험시설지정고시번호위험시설지정사유관리기관전화번호관리기관명
위도1.000-0.508-0.0900.2170.1450.7060.5390.5970.690
경도-0.5081.000-0.111-0.1190.0710.4750.3740.4700.539
연장-0.090-0.1111.000-0.2140.2870.0000.2130.1560.188
폭0.217-0.119-0.2141.0000.1910.0000.0000.0530.052
시설유형0.1450.0710.2870.1911.0000.1750.1890.2440.249
위험시설지정고시번호0.7060.4750.0000.0000.1751.0000.6330.9530.949
위험시설지정사유0.5390.3740.2130.0000.1890.6331.0000.8530.696
관리기관전화번호0.5970.4700.1560.0530.2440.9530.8531.0000.996
관리기관명0.6900.5390.1880.0520.2490.9490.6960.9961.000

Missing values

2024-05-10T21:41:28.787731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:41:29.322548image/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.
2024-05-10T21:41:29.664948image/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

시설명소재지도로명주소소재지지번주소시설유형위험시설지정고시번호위험시설지정일자위험시설지정사유위험시설해제일자위도경도연장폭시설부속물관리기관전화번호관리기관명데이터기준일자
0원당리_세천0004<NA>경기도 연천군 장남면 원당리 767세천2021-1592021-08-01위험도평가결과 불량<NA>37.990328126.8824342564.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
1두일리_마을진입로0009<NA>경기도 연천군 백학면 두일리 33-9마을진입로2021-1592021-08-01위험도평가결과 불량<NA>38.034206126.923952863.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
2석장리_세천0006<NA>경기도 연천군 백학면 석장리 873세천2021-1592021-08-01위험도평가결과 불량<NA>38.054509126.91609612053.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
3백석리_세천0002<NA>경기도 연천군 미산면 백석리 163세천2021-1592021-08-01위험도평가결과 불량<NA>38.062621126.9691915115.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
4무등리_세천0005<NA>경기도 연천군 왕징면 무등리 238세천2021-1592021-08-01위험도평가결과 불량<NA>38.064333127.002323503.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
5남계리_마을진입로0006<NA>경기도 연천군 군남면 남계리 211-3마을진입로2021-1592021-08-01위험도평가결과 불량<NA>38.028618127.0314261503.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
6옥계리_마을진입로0008<NA>경기도 연천군 군남면 옥계리 269-29마을진입로2021-1592021-08-01위험도평가결과 불량<NA>38.122566127.0536071103.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
7남계리_세천0001<NA>경기도 연천군 군남면 남계리 196-8세천2021-1592021-08-01위험도평가결과 불량<NA>38.030312127.0353536602.5<NA>031-839-2168경기도 연천군청 건설과2023-06-07
8옥계리_세천0002<NA>경기도 연천군 군남면 옥계리 113세천2021-1592021-08-01위험도평가결과 불량<NA>38.124376127.06229211184.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
9전곡리_세천0001<NA>경기도 연천군 전곡읍 전곡리 33-7세천2021-1592021-08-01위험도평가결과 불량<NA>38.016248127.0749964805.0<NA>031-839-2168경기도 연천군청 건설과2023-06-07
시설명소재지도로명주소소재지지번주소시설유형위험시설지정고시번호위험시설지정일자위험시설지정사유위험시설해제일자위도경도연장폭시설부속물관리기관전화번호관리기관명데이터기준일자
230삼리5세천<NA>경기도 광주시 곤지암읍 삼리 536세천제2021-321호2021-07-05위험도평가 불량<NA>37.350503127.3147764534.0<NA>031-760-2948경기도 광주시청2023-12-01
231열미3세천<NA>경기도 광주시 곤지암읍 열미리 180-6세천제2021-321호2021-07-05위험도평가 보통<NA>37.364894127.3522972832.0<NA>031-760-2948경기도 광주시청2023-12-01
232성신세천<NA>경기도 광주시 도척면 진우리 396-1세천제2021-321호2021-07-05위험도평가 보통<NA>37.3181127.3376563573.5<NA>031-760-2948경기도 광주시청2023-12-01
233우산리3세천<NA>경기도 광주시 퇴촌면 우산리 135세천제2021-321호2021-07-05위험도평가 불량<NA>37.436809127.36856211123.5<NA>031-760-2948경기도 광주시청2023-12-01
234목현11세천<NA>경기도 광주시 목현동 772-2세천제2021-321호2021-07-05위험도평가 보통<NA>37.433541127.203017054.5<NA>031-760-2948경기도 광주시청2023-12-01
235회덕2세천<NA>경기도 광주시 회덕동 192-6세천제2021-321호2021-07-05위험도평가 불량<NA>37.433417127.2443127582.0<NA>031-760-2948경기도 광주시청2023-12-01
236능현세천<NA>경기도 여주시 능현동 339-16세천제2021-32호2021-02-15위험도평가 불량<NA>37.272557127.657637802.5<NA>031-887-2552경기도 여주시청2023-11-15
237소교량<NA>경기도 여주시 강천면 도전리 1344소교량제2021-32호2021-02-15위험도평가 불량<NA>37.317659127.74620942.0<NA>031-887-2552경기도 여주시청2023-11-15
238효지세천<NA>경기도 여주시 흥천면 효지리 79세천제2022-166호2022-05-09위험도평가 불량<NA>37.328117127.5396491004.0<NA>031-887-2552경기도 여주시청2023-11-15
239도수세천경기도 광주시 퇴촌면 도지울길12번길 60-37경기도 광주시 퇴촌면 도수리 487세천제2017-112호2017-04-10위험도평가 불량<NA>37.478637127.3216693002.5<NA>031-760-2948경기도 광주시청2023-12-01