Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells996
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory122.0 B

Variable types

Text3
Categorical9
Numeric2

Dataset

Description울산광역시 북구의 가로등 및 보안등 위치정보에 대한 데이터입니다. (관리번호, 노선명, 설치구간, 위도, 경도 등)공란은 미수집데이터입니다.
Author울산광역시 북구
URLhttps://www.data.go.kr/data/15127498/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 행정동 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정동 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
설치형태 is highly overall correlated with 등기구회사High correlation
등기구회사 is highly overall correlated with 위도 and 8 other fieldsHigh correlation
램프종류 is highly overall correlated with 등기구회사 and 1 other fieldsHigh correlation
등주종류 is highly overall correlated with 등기구회사High correlation
등주모양 is highly overall correlated with 등기구회사High correlation
등기구형태 is highly overall correlated with 등기구회사 and 1 other fieldsHigh correlation
등주길이 is highly overall correlated with 등기구회사High correlation
등기구회사 is highly imbalanced (75.1%)Imbalance
등주모양 is highly imbalanced (70.2%)Imbalance
위도 has 498 (5.0%) missing valuesMissing
경도 has 498 (5.0%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:19:34.278064
Analysis finished2024-04-06 08:19:40.705276
Duration6.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:19:41.190495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length6.6367
Min length3

Characters and Unicode

Total characters66367
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st row마-120-14
2nd row가-77-16
3rd row사-19-17
4th row가-33-2
5th row가-22-12
ValueCountFrequency (%)
마-120-14 1
 
< 0.1%
마-110-3 1
 
< 0.1%
바-23-2 1
 
< 0.1%
가-85-1 1
 
< 0.1%
바-55-5 1
 
< 0.1%
가-40-19 1
 
< 0.1%
가-22-2 1
 
< 0.1%
마-109-8 1
 
< 0.1%
나-9-18 1
 
< 0.1%
다-51 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-04-06T17:19:42.418388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 19553
29.5%
1 7630
 
11.5%
2 5403
 
8.1%
3 3620
 
5.5%
4 3303
 
5.0%
5 3210
 
4.8%
6 3038
 
4.6%
7 2799
 
4.2%
8 2274
 
3.4%
9 2164
 
3.3%
Other values (10) 13373
20.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 35204
53.0%
Dash Punctuation 19553
29.5%
Other Letter 10000
 
15.1%
Open Punctuation 805
 
1.2%
Close Punctuation 805
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 7630
21.7%
2 5403
15.3%
3 3620
10.3%
4 3303
9.4%
5 3210
9.1%
6 3038
 
8.6%
7 2799
 
8.0%
8 2274
 
6.5%
9 2164
 
6.1%
0 1763
 
5.0%
Other Letter
ValueCountFrequency (%)
마 2117
21.2%
라 1750
17.5%
가 1470
14.7%
바 1418
14.2%
나 1395
14.0%
다 1307
13.1%
사 543
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 19553
100.0%
Open Punctuation
ValueCountFrequency (%)
( 805
100.0%
Close Punctuation
ValueCountFrequency (%)
) 805
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56367
84.9%
Hangul 10000
 
15.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 19553
34.7%
1 7630
 
13.5%
2 5403
 
9.6%
3 3620
 
6.4%
4 3303
 
5.9%
5 3210
 
5.7%
6 3038
 
5.4%
7 2799
 
5.0%
8 2274
 
4.0%
9 2164
 
3.8%
Other values (3) 3373
 
6.0%
Hangul
ValueCountFrequency (%)
마 2117
21.2%
라 1750
17.5%
가 1470
14.7%
바 1418
14.2%
나 1395
14.0%
다 1307
13.1%
사 543
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56367
84.9%
Hangul 10000
 
15.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 19553
34.7%
1 7630
 
13.5%
2 5403
 
9.6%
3 3620
 
6.4%
4 3303
 
5.9%
5 3210
 
5.7%
6 3038
 
5.4%
7 2799
 
5.0%
8 2274
 
4.0%
9 2164
 
3.8%
Other values (3) 3373
 
6.0%
Hangul
ValueCountFrequency (%)
마 2117
21.2%
라 1750
17.5%
가 1470
14.7%
바 1418
14.2%
나 1395
14.0%
다 1307
13.1%
사 543
 
5.4%

노선명
Text

Distinct81
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:19:42.875200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length6.1253
Min length3

Characters and Unicode

Total characters61253
Distinct characters135
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

Unique0 ?
Unique (%)0.0%

Sample

1st row진장유통로
2nd row호계매곡지구
3rd row염포로
4th row구국도7호선
5th row매곡지방산업단지
ValueCountFrequency (%)
송정택지개발 865
 
8.2%
산업로 809
 
7.7%
오토밸리로 709
 
6.7%
강동산하지구도시개발사업 501
 
4.7%
강동해안도로 402
 
3.8%
호계매곡지구 369
 
3.5%
자전거전용도로내 362
 
3.4%
효문공단내 334
 
3.2%
터널등 314
 
3.0%
염포로 275
 
2.6%
Other values (79) 5628
53.3%
2024-04-06T17:19:43.582043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 4638
 
7.6%
지 3891
 
6.4%
산 2688
 
4.4%
도 2263
 
3.7%
업 2155
 
3.5%
내 1689
 
2.8%
택 1683
 
2.7%
구 1468
 
2.4%
개 1383
 
2.3%
발 1383
 
2.3%
Other values (125) 38012
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56221
91.8%
Decimal Number 2930
 
4.8%
Space Separator 568
 
0.9%
Dash Punctuation 546
 
0.9%
Close Punctuation 431
 
0.7%
Open Punctuation 431
 
0.7%
Math Symbol 126
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 4638
 
8.2%
지 3891
 
6.9%
산 2688
 
4.8%
도 2263
 
4.0%
업 2155
 
3.8%
내 1689
 
3.0%
택 1683
 
3.0%
구 1468
 
2.6%
개 1383
 
2.5%
발 1383
 
2.5%
Other values (113) 32980
58.7%
Decimal Number
ValueCountFrequency (%)
2 996
34.0%
3 677
23.1%
1 664
22.7%
9 249
 
8.5%
7 146
 
5.0%
4 111
 
3.8%
8 87
 
3.0%
Space Separator
ValueCountFrequency (%)
568
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 546
100.0%
Close Punctuation
ValueCountFrequency (%)
) 431
100.0%
Open Punctuation
ValueCountFrequency (%)
( 431
100.0%
Math Symbol
ValueCountFrequency (%)
~ 126
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56221
91.8%
Common 5032
 
8.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 4638
 
8.2%
지 3891
 
6.9%
산 2688
 
4.8%
도 2263
 
4.0%
업 2155
 
3.8%
내 1689
 
3.0%
택 1683
 
3.0%
구 1468
 
2.6%
개 1383
 
2.5%
발 1383
 
2.5%
Other values (113) 32980
58.7%
Common
ValueCountFrequency (%)
2 996
19.8%
3 677
13.5%
1 664
13.2%
568
11.3%
- 546
10.9%
) 431
8.6%
( 431
8.6%
9 249
 
4.9%
7 146
 
2.9%
~ 126
 
2.5%
Other values (2) 198
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56221
91.8%
ASCII 5032
 
8.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 4638
 
8.2%
지 3891
 
6.9%
산 2688
 
4.8%
도 2263
 
4.0%
업 2155
 
3.8%
내 1689
 
3.0%
택 1683
 
3.0%
구 1468
 
2.6%
개 1383
 
2.5%
발 1383
 
2.5%
Other values (113) 32980
58.7%
ASCII
ValueCountFrequency (%)
2 996
19.8%
3 677
13.5%
1 664
13.2%
568
11.3%
- 546
10.9%
) 431
8.6%
( 431
8.6%
9 249
 
4.9%
7 146
 
2.9%
~ 126
 
2.5%
Other values (2) 198
 
3.9%

설치구간
Text

Distinct206
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-06T17:19:44.062089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length8.9733
Min length2

Characters and Unicode

Total characters89733
Distinct characters226
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row진장유통2단계1
2nd row호계매곡지구 도시개발사업 중1-75
3rd row효문사거리~동구경계
4th row호계사거리~농소2동사무소
5th row매곡지방산업단지내
ValueCountFrequency (%)
송정택지가로등 721
 
5.3%
중1-75 369
 
2.7%
호계매곡지구 369
 
2.7%
도시개발사업 369
 
2.7%
344
 
2.5%
효문공단내 334
 
2.5%
내 331
 
2.4%
이예로 314
 
2.3%
주변 305
 
2.2%
신상안교 275
 
2.0%
Other values (233) 9851
72.5%
2024-04-06T17:19:45.016980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 4112
 
4.6%
4045
 
4.5%
로 3603
 
4.0%
산 2816
 
3.1%
교 2208
 
2.5%
~ 2162
 
2.4%
내 2153
 
2.4%
리 1886
 
2.1%
택 1845
 
2.1%
정 1837
 
2.0%
Other values (216) 63066
70.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73572
82.0%
Decimal Number 4136
 
4.6%
Space Separator 4045
 
4.5%
Math Symbol 2162
 
2.4%
Open Punctuation 1587
 
1.8%
Close Punctuation 1565
 
1.7%
Dash Punctuation 1482
 
1.7%
Uppercase Letter 1180
 
1.3%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 4112
 
5.6%
로 3603
 
4.9%
산 2816
 
3.8%
교 2208
 
3.0%
내 2153
 
2.9%
리 1886
 
2.6%
택 1845
 
2.5%
정 1837
 
2.5%
동 1703
 
2.3%
사 1586
 
2.2%
Other values (196) 49823
67.7%
Decimal Number
ValueCountFrequency (%)
1 1458
35.3%
2 1051
25.4%
5 459
 
11.1%
7 455
 
11.0%
3 324
 
7.8%
4 121
 
2.9%
6 77
 
1.9%
9 75
 
1.8%
8 63
 
1.5%
0 53
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
P 501
42.5%
L 501
42.5%
I 89
 
7.5%
C 89
 
7.5%
Space Separator
ValueCountFrequency (%)
4045
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1587
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1565
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1482
100.0%
Other Punctuation
ValueCountFrequency (%)
? 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73572
82.0%
Common 14981
 
16.7%
Latin 1180
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 4112
 
5.6%
로 3603
 
4.9%
산 2816
 
3.8%
교 2208
 
3.0%
내 2153
 
2.9%
리 1886
 
2.6%
택 1845
 
2.5%
정 1837
 
2.5%
동 1703
 
2.3%
사 1586
 
2.2%
Other values (196) 49823
67.7%
Common
ValueCountFrequency (%)
4045
27.0%
~ 2162
14.4%
( 1587
 
10.6%
) 1565
 
10.4%
- 1482
 
9.9%
1 1458
 
9.7%
2 1051
 
7.0%
5 459
 
3.1%
7 455
 
3.0%
3 324
 
2.2%
Other values (6) 393
 
2.6%
Latin
ValueCountFrequency (%)
P 501
42.5%
L 501
42.5%
I 89
 
7.5%
C 89
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73572
82.0%
ASCII 16161
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 4112
 
5.6%
로 3603
 
4.9%
산 2816
 
3.8%
교 2208
 
3.0%
내 2153
 
2.9%
리 1886
 
2.6%
택 1845
 
2.5%
정 1837
 
2.5%
동 1703
 
2.3%
사 1586
 
2.2%
Other values (196) 49823
67.7%
ASCII
ValueCountFrequency (%)
4045
25.0%
~ 2162
13.4%
( 1587
 
9.8%
) 1565
 
9.7%
- 1482
 
9.2%
1 1458
 
9.0%
2 1051
 
6.5%
P 501
 
3.1%
L 501
 
3.1%
5 459
 
2.8%
Other values (10) 1350
 
8.4%

행정동
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
효문동
2115 
농소1동
1470 
강동동
1418 
농소2동
1395 
농소3동
1307 
Other values (4)
2295 

Length

Max length4
Median length3
Mean length3.4172
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row효문동
2nd row농소1동
3rd row염포동
4th row농소1동
5th row농소1동

Common Values

ValueCountFrequency (%)
효문동 2115
21.1%
농소1동 1470
14.7%
강동동 1418
14.2%
농소2동 1395
14.0%
농소3동 1307
13.1%
송정동 903
9.0%
화봉동 845
 
8.5%
양정동 280
 
2.8%
염포동 267
 
2.7%

Length

2024-04-06T17:19:45.386823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:45.627369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
효문동 2115
21.1%
농소1동 1470
14.7%
강동동 1418
14.2%
농소2동 1395
14.0%
농소3동 1307
13.1%
송정동 903
9.0%
화봉동 845
 
8.5%
양정동 280
 
2.8%
염포동 267
 
2.7%

설치형태
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
편측
6974 
양측
2576 
<NA>
 
450

Length

Max length4
Median length2
Mean length2.09
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row편측
2nd row편측
3rd row편측
4th row편측
5th row양측

Common Values

ValueCountFrequency (%)
편측 6974
69.7%
양측 2576
 
25.8%
<NA> 450
 
4.5%

Length

2024-04-06T17:19:45.970680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:46.243001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
편측 6974
69.7%
양측 2576
 
25.8%
na 450
 
4.5%

등기구회사
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8476 
다노테크
 
286
달빛
 
127
세영종합건설
 
86
신한전기
 
84
Other values (30)
941 

Length

Max length10
Median length4
Mean length4.0931
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 8476
84.8%
다노테크 286
 
2.9%
달빛 127
 
1.3%
세영종합건설 86
 
0.9%
신한전기 84
 
0.8%
샐빛 79
 
0.8%
우리기업 77
 
0.8%
진흥패턴 76
 
0.8%
예광 72
 
0.7%
구구라이팅 66
 
0.7%
Other values (25) 571
 
5.7%

Length

2024-04-06T17:19:46.477486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 8476
84.7%
다노테크 286
 
2.9%
달빛 127
 
1.3%
세영종합건설 86
 
0.9%
신한전기 84
 
0.8%
샐빛 79
 
0.8%
우리기업 77
 
0.8%
진흥패턴 76
 
0.8%
예광 72
 
0.7%
구구라이팅 67
 
0.7%
Other values (24) 577
 
5.8%

램프종류
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
LED램프
5529 
CDM램프
2990 
CPO램프
 
535
<NA>
 
450
나트륨
 
333
Other values (2)
 
163

Length

Max length5
Median length5
Mean length4.8878
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLED램프
2nd rowCDM램프
3rd rowLED램프
4th rowLED램프
5th rowLED램프

Common Values

ValueCountFrequency (%)
LED램프 5529
55.3%
CDM램프 2990
29.9%
CPO램프 535
 
5.3%
<NA> 450
 
4.5%
나트륨 333
 
3.3%
무전극램프 160
 
1.6%
삼파장 3
 
< 0.1%

Length

2024-04-06T17:19:46.753365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:47.078808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
led램프 5529
55.3%
cdm램프 2990
29.9%
cpo램프 535
 
5.3%
na 450
 
4.5%
나트륨 333
 
3.3%
무전극램프 160
 
1.6%
삼파장 3
 
< 0.1%

등주종류
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
팔각테파
4498 
원형테파
2282 
스텐등주
1759 
철제디자인
767 
<NA>
450 
Other values (4)
 
244

Length

Max length9
Median length4
Mean length4.0428
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row원형테파
2nd row팔각테파
3rd row팔각테파
4th row팔각테파
5th row팔각테파

Common Values

ValueCountFrequency (%)
팔각테파 4498
45.0%
원형테파 2282
22.8%
스텐등주 1759
 
17.6%
철제디자인 767
 
7.7%
<NA> 450
 
4.5%
한전주 142
 
1.4%
기타 87
 
0.9%
주철 14
 
0.1%
원형테파(스텐암) 1
 
< 0.1%

Length

2024-04-06T17:19:47.402861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:47.665172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
팔각테파 4498
45.0%
원형테파 2282
22.8%
스텐등주 1759
 
17.6%
철제디자인 767
 
7.7%
na 450
 
4.5%
한전주 142
 
1.4%
기타 87
 
0.9%
주철 14
 
0.1%
원형테파(스텐암 1
 
< 0.1%

등주모양
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기본형
8706 
<NA>
 
450
용형성화
 
423
돌고래
 
195
자전거
 
101
Other values (2)
 
125

Length

Max length4
Median length3
Mean length3.0748
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기본형 8706
87.1%
<NA> 450
 
4.5%
용형성화 423
 
4.2%
돌고래 195
 
1.9%
자전거 101
 
1.0%
기타 70
 
0.7%
접시 55
 
0.5%

Length

2024-04-06T17:19:47.959575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:48.231335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기본형 8706
87.1%
na 450
 
4.5%
용형성화 423
 
4.2%
돌고래 195
 
1.9%
자전거 101
 
1.0%
기타 70
 
0.7%
접시 55
 
0.5%

등기구형태
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
LED등기구
5279 
오션형
3009 
무역로
553 
<NA>
 
450
세종로
 
390
Other values (4)
 
319

Length

Max length6
Median length6
Mean length4.6525
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLED등기구
2nd row오션형
3rd rowLED등기구
4th rowLED등기구
5th rowLED등기구

Common Values

ValueCountFrequency (%)
LED등기구 5279
52.8%
오션형 3009
30.1%
무역로 553
 
5.5%
<NA> 450
 
4.5%
세종로 390
 
3.9%
글러브형 128
 
1.3%
디자인등 110
 
1.1%
터널등 50
 
0.5%
투광기 31
 
0.3%

Length

2024-04-06T17:19:48.575694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:48.832865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
led등기구 5279
52.8%
오션형 3009
30.1%
무역로 553
 
5.5%
na 450
 
4.5%
세종로 390
 
3.9%
글러브형 128
 
1.3%
디자인등 110
 
1.1%
터널등 50
 
0.5%
투광기 31
 
0.3%

등주길이
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
9
3217 
8
2065 
10
2037 
5
846 
11
591 
Other values (10)
1244 

Length

Max length4
Median length1
Mean length1.4763
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row9
2nd row9
3rd row9
4th row9
5th row8

Common Values

ValueCountFrequency (%)
9 3217
32.2%
8 2065
20.6%
10 2037
20.4%
5 846
 
8.5%
11 591
 
5.9%
<NA> 450
 
4.5%
9 10 257
 
2.6%
6 156
 
1.6%
7 139
 
1.4%
4 110
 
1.1%
Other values (5) 132
 
1.3%

Length

2024-04-06T17:19:49.107321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9 3474
33.9%
10 2294
22.4%
8 2065
20.1%
5 846
 
8.2%
11 591
 
5.8%
na 450
 
4.4%
6 156
 
1.5%
7 139
 
1.4%
4 110
 
1.1%
0 95
 
0.9%
Other values (4) 37
 
0.4%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9141
Distinct (%)96.2%
Missing498
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean35.60738
Minimum35.521074
Maximum35.675371
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:19:49.388329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.521074
5-th percentile35.547502
Q135.58203
median35.607719
Q335.634697
95-th percentile35.651772
Maximum35.675371
Range0.15429633
Interquartile range (IQR)0.052667038

Descriptive statistics

Standard deviation0.033465001
Coefficient of variation (CV)0.00093983328
Kurtosis-0.64034611
Mean35.60738
Median Absolute Deviation (MAD)0.026638115
Skewness-0.45454868
Sum338341.32
Variance0.0011199063
MonotonicityNot monotonic
2024-04-06T17:19:49.727944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.58835101 3
 
< 0.1%
35.58552223 3
 
< 0.1%
35.63107643 3
 
< 0.1%
35.57066789 3
 
< 0.1%
35.55705294 3
 
< 0.1%
35.59986859 2
 
< 0.1%
35.58837625 2
 
< 0.1%
35.59397433 2
 
< 0.1%
35.60338665 2
 
< 0.1%
35.62943662 2
 
< 0.1%
Other values (9131) 9477
94.8%
(Missing) 498
 
5.0%
ValueCountFrequency (%)
35.52107418 1
< 0.1%
35.5213306 1
< 0.1%
35.52141367 1
< 0.1%
35.52153849 1
< 0.1%
35.52165334 1
< 0.1%
35.52174841 1
< 0.1%
35.52182592 1
< 0.1%
35.52186179 1
< 0.1%
35.52186434 1
< 0.1%
35.52186656 1
< 0.1%
ValueCountFrequency (%)
35.67537051 1
< 0.1%
35.67525315 1
< 0.1%
35.67497488 1
< 0.1%
35.67466646 1
< 0.1%
35.67436362 1
< 0.1%
35.67409489 1
< 0.1%
35.67383527 1
< 0.1%
35.67354348 1
< 0.1%
35.6722734 1
< 0.1%
35.6720907 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9053
Distinct (%)95.3%
Missing498
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean129.37022
Minimum129.30405
Maximum129.46302
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-06T17:19:50.016813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum129.30405
5-th percentile129.32821
Q1129.35237
median129.36242
Q3129.37268
95-th percentile129.44066
Maximum129.46302
Range0.1589701
Interquartile range (IQR)0.02031315

Descriptive statistics

Standard deviation0.032414405
Coefficient of variation (CV)0.00025055539
Kurtosis0.80219034
Mean129.37022
Median Absolute Deviation (MAD)0.01016935
Skewness1.1786167
Sum1229275.8
Variance0.0010506936
MonotonicityNot monotonic
2024-04-06T17:19:50.329838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.3615904 3
 
< 0.1%
129.3350579 3
 
< 0.1%
129.3617073 3
 
< 0.1%
129.3610241 3
 
< 0.1%
129.3535589 3
 
< 0.1%
129.4378837 3
 
< 0.1%
129.3548241 3
 
< 0.1%
129.3613479 3
 
< 0.1%
129.3410536 3
 
< 0.1%
129.3654304 2
 
< 0.1%
Other values (9043) 9473
94.7%
(Missing) 498
 
5.0%
ValueCountFrequency (%)
129.3040502 1
< 0.1%
129.3105251 1
< 0.1%
129.3112614 1
< 0.1%
129.3112907 1
< 0.1%
129.3113385 1
< 0.1%
129.3114588 1
< 0.1%
129.3115209 1
< 0.1%
129.3115233 1
< 0.1%
129.3115587 1
< 0.1%
129.3116117 1
< 0.1%
ValueCountFrequency (%)
129.4630203 1
< 0.1%
129.4630108 1
< 0.1%
129.4630085 1
< 0.1%
129.4629288 1
< 0.1%
129.4629222 1
< 0.1%
129.4628864 1
< 0.1%
129.4628591 1
< 0.1%
129.4628496 1
< 0.1%
129.4628475 1
< 0.1%
129.4628339 1
< 0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-03
10000 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-03
2nd row2024-04-03
3rd row2024-04-03
4th row2024-04-03
5th row2024-04-03

Common Values

ValueCountFrequency (%)
2024-04-03 10000
100.0%

Length

2024-04-06T17:19:50.611783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:19:50.812886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-03 10000
100.0%

Interactions

2024-04-06T17:19:38.344872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:37.781663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:38.691038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:19:38.029962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:19:50.945853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선명행정동설치형태등기구회사램프종류등주종류등주모양등기구형태등주길이위도경도
노선명1.0000.9840.7960.9840.8340.8960.8170.8430.9100.9400.955
행정동0.9841.0000.2830.9360.3870.5050.3190.3990.4970.8390.840
설치형태0.7960.2831.0000.9230.2100.3350.1560.1390.2730.3310.265
등기구회사0.9840.9360.9231.0000.8190.9250.9160.9550.9370.9300.940
램프종류0.8340.3870.2100.8191.0000.3640.3690.7960.4050.4260.458
등주종류0.8960.5050.3350.9250.3641.0000.6020.8370.7040.4500.431
등주모양0.8170.3190.1560.9160.3690.6021.0000.6860.7400.2630.269
등기구형태0.8430.3990.1390.9550.7960.8370.6861.0000.6580.3420.318
등주길이0.9100.4970.2730.9370.4050.7040.7400.6581.0000.4800.421
위도0.9400.8390.3310.9300.4260.4500.2630.3420.4801.0000.821
경도0.9550.8400.2650.9400.4580.4310.2690.3180.4210.8211.000
2024-04-06T17:19:51.210094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등주길이등주종류등기구형태램프종류행정동설치형태등주모양등기구회사
등주길이1.0000.4050.3620.2120.2360.2130.4810.716
등주종류0.4051.0000.4280.2120.2760.2520.3890.717
등기구형태0.3620.4281.0000.6040.2080.1040.4700.795
램프종류0.2120.2120.6041.0000.2040.1510.1410.570
행정동0.2360.2760.2080.2041.0000.2830.1640.702
설치형태0.2130.2520.1040.1510.2831.0000.1120.793
등주모양0.4810.3890.4700.1410.1640.1121.0000.710
등기구회사0.7160.7170.7950.5700.7020.7930.7101.000
2024-04-06T17:19:51.454410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동설치형태등기구회사램프종류등주종류등주모양등기구형태등주길이
위도1.000-0.3930.5870.2540.6690.1900.2340.1410.1710.216
경도-0.3931.0000.5880.2030.7090.2070.2220.1450.1580.184
행정동0.5870.5881.0000.2830.7020.2040.2760.1640.2080.236
설치형태0.2540.2030.2831.0000.7930.1510.2520.1120.1040.213
등기구회사0.6690.7090.7020.7931.0000.5700.7170.7100.7950.716
램프종류0.1900.2070.2040.1510.5701.0000.2120.1410.6040.212
등주종류0.2340.2220.2760.2520.7170.2121.0000.3890.4280.405
등주모양0.1410.1450.1640.1120.7100.1410.3891.0000.4700.481
등기구형태0.1710.1580.2080.1040.7950.6040.4280.4701.0000.362
등주길이0.2160.1840.2360.2130.7160.2120.4050.4810.3621.000

Missing values

2024-04-06T17:19:39.029052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:19:39.457921image/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.
2024-04-06T17:19:40.348615image/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

관리번호노선명설치구간행정동설치형태등기구회사램프종류등주종류등주모양등기구형태등주길이위도경도데이터기준일자
10473마-120-14진장유통로진장유통2단계1효문동편측<NA>LED램프원형테파기본형LED등기구935.577608129.3561412024-04-03
1322가-77-16호계매곡지구호계매곡지구 도시개발사업 중1-75농소1동편측<NA>CDM램프팔각테파기본형오션형935.632615129.3658522024-04-03
12933사-19-17염포로효문사거리~동구경계염포동편측<NA>LED램프팔각테파기본형LED등기구935.526274129.3985332024-04-03
525가-33-2구국도7호선호계사거리~농소2동사무소농소1동편측<NA>LED램프팔각테파기본형LED등기구935.626502129.3518692024-04-03
328가-22-12매곡지방산업단지매곡지방산업단지내농소1동양측<NA>LED램프팔각테파기본형LED등기구835.645949129.3635272024-04-03
9234마-54-3염포로효문사거리~동구경계효문동편측<NA>LED램프팔각테파기본형LED등기구935.560229129.3723792024-04-03
10206마-105-10자전거도로내황교~양정1교효문동편측한일전설(주)LED램프스텐등주자전거LED등기구535.548728129.3559672024-04-03
7340라-61-6송정택지1송정택지내송정동편측<NA>LED램프원형테파기본형LED등기구535.599187129.363312024-04-03
11821바-53-2강동산하지구도시개발사업산하중앙1로(LP-6)강동동편측샐빛LED램프스텐등주기본형LED등기구935.632858129.4388172024-04-03
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