Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory163.0 B

Variable types

Numeric3
Text5
Categorical10
DateTime1

Dataset

Description객체id,현황도형 관리번호,도형 대분류코드,도형 중분류코드,도형 소분류코드,도형 속성코드,도형 조서관리 코드,결정고시관리코드,라벨명,시군구코드,규모_등급_심볼,규모_류별_심볼,규모_번호_심볼,도로기능_심볼,도면번호,집행상태코드 심볼,현황도형 생성일시,면적(도형),길이(도형)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21134/S/1/datasetView.do

Alerts

도형 중분류코드 has constant value ""Constant
라벨명 is highly overall correlated with 도형 대분류코드 and 3 other fieldsHigh correlation
도형 대분류코드 is highly overall correlated with 도형 속성코드 and 3 other fieldsHigh correlation
도형 속성코드 is highly overall correlated with 도형 대분류코드 and 3 other fieldsHigh correlation
면적(도형) is highly overall correlated with 길이(도형)High correlation
길이(도형) is highly overall correlated with 면적(도형)High correlation
규모_등급_심볼 is highly overall correlated with 도형 대분류코드 and 2 other fieldsHigh correlation
규모_류별_심볼 is highly overall correlated with 도형 대분류코드 and 2 other fieldsHigh correlation
도형 소분류코드 is highly imbalanced (99.9%)Imbalance
시군구코드 is highly imbalanced (83.6%)Imbalance
도로기능_심볼 is highly imbalanced (53.2%)Imbalance
집행상태코드 심볼 is highly imbalanced (96.6%)Imbalance
길이(도형) is highly skewed (γ1 = 20.13773984)Skewed
객체id has unique valuesUnique

Reproduction

Analysis started2024-05-11 09:57:26.053362
Analysis finished2024-05-11 09:57:33.349390
Duration7.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean651563.59
Minimum642400
Maximum660631
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:57:33.488933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum642400
5-th percentile643404.85
Q1646986.25
median651562
Q3656116.25
95-th percentile659761.05
Maximum660631
Range18231
Interquartile range (IQR)9130

Descriptive statistics

Standard deviation5263.3816
Coefficient of variation (CV)0.0080780781
Kurtosis-1.2122735
Mean651563.59
Median Absolute Deviation (MAD)4565.5
Skewness0.0068308868
Sum6.5156359 × 109
Variance27703186
MonotonicityNot monotonic
2024-05-11T09:57:33.861930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
650003 1
 
< 0.1%
651477 1
 
< 0.1%
651945 1
 
< 0.1%
655474 1
 
< 0.1%
649347 1
 
< 0.1%
655864 1
 
< 0.1%
644630 1
 
< 0.1%
650229 1
 
< 0.1%
648238 1
 
< 0.1%
650631 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
642400 1
< 0.1%
642561 1
< 0.1%
642562 1
< 0.1%
642563 1
< 0.1%
642564 1
< 0.1%
642565 1
< 0.1%
642566 1
< 0.1%
642568 1
< 0.1%
642569 1
< 0.1%
642570 1
< 0.1%
ValueCountFrequency (%)
660631 1
< 0.1%
660629 1
< 0.1%
660627 1
< 0.1%
660626 1
< 0.1%
660625 1
< 0.1%
660623 1
< 0.1%
660622 1
< 0.1%
660621 1
< 0.1%
660616 1
< 0.1%
660613 1
< 0.1%
Distinct9995
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:57:34.460122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length23.9977
Min length1

Characters and Unicode

Total characters239977
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9992 ?
Unique (%)99.9%

Sample

1st row11000UQ151PS201912152770
2nd row11000UQ151PS201912157023
3rd row11000UQ151PS201912154824
4th row11740UQ151PS202108240003
5th row11000UQ151PS201912163292
ValueCountFrequency (%)
11000uq151ps201912161369 4
 
< 0.1%
11000uq151ps201912159503 2
 
< 0.1%
11000uq151ps201912158858 2
 
< 0.1%
11000uq151ps202011100263 1
 
< 0.1%
11000uq151ps201912161080 1
 
< 0.1%
11000uq151ps201912155513 1
 
< 0.1%
11000uq151ps201912161643 1
 
< 0.1%
11000uq151ps201912162524 1
 
< 0.1%
11000uq151ps201912152770 1
 
< 0.1%
11000uq151ps201912164117 1
 
< 0.1%
Other values (9984) 9984
99.8%
2024-05-11T09:57:35.495438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 70668
29.4%
0 51105
21.3%
2 25637
 
10.7%
5 19087
 
8.0%
9 11303
 
4.7%
U 9999
 
4.2%
Q 9999
 
4.2%
P 9999
 
4.2%
S 9999
 
4.2%
6 6276
 
2.6%
Other values (5) 15905
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 199980
83.3%
Uppercase Letter 39996
 
16.7%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 70668
35.3%
0 51105
25.6%
2 25637
 
12.8%
5 19087
 
9.5%
9 11303
 
5.7%
6 6276
 
3.1%
3 4624
 
2.3%
4 4212
 
2.1%
8 3551
 
1.8%
7 3517
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
U 9999
25.0%
Q 9999
25.0%
P 9999
25.0%
S 9999
25.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 199981
83.3%
Latin 39996
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 70668
35.3%
0 51105
25.6%
2 25637
 
12.8%
5 19087
 
9.5%
9 11303
 
5.7%
6 6276
 
3.1%
3 4624
 
2.3%
4 4212
 
2.1%
8 3551
 
1.8%
7 3517
 
1.8%
Latin
ValueCountFrequency (%)
U 9999
25.0%
Q 9999
25.0%
P 9999
25.0%
S 9999
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 239977
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 70668
29.4%
0 51105
21.3%
2 25637
 
10.7%
5 19087
 
8.0%
9 11303
 
4.7%
U 9999
 
4.2%
Q 9999
 
4.2%
P 9999
 
4.2%
S 9999
 
4.2%
6 6276
 
2.6%
Other values (5) 15905
 
6.6%

도형 대분류코드
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
UQS190
3455 
UQS122
2581 
UQS121
1089 
UQS119
687 
UQS120
667 
Other values (10)
1521 

Length

Max length6
Median length6
Mean length5.9975
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQS121
2nd rowUQS122
3rd rowUQS121
4th rowUQS119
5th rowUQS122

Common Values

ValueCountFrequency (%)
UQS190 3455
34.5%
UQS122 2581
25.8%
UQS121 1089
 
10.9%
UQS119 687
 
6.9%
UQS120 667
 
6.7%
UQS118 598
 
6.0%
UQS117 484
 
4.8%
UQS116 171
 
1.7%
UQS115 97
 
1.0%
UQS114 84
 
0.8%
Other values (5) 87
 
0.9%

Length

2024-05-11T09:57:35.861287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqs190 3455
34.6%
uqs122 2581
25.8%
uqs121 1089
 
10.9%
uqs119 687
 
6.9%
uqs120 667
 
6.7%
uqs118 598
 
6.0%
uqs117 484
 
4.8%
uqs116 171
 
1.7%
uqs115 97
 
1.0%
uqs114 84
 
0.8%
Other values (4) 82
 
0.8%

도형 중분류코드
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
10000
100.0%

Length

2024-05-11T09:57:36.164695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:57:36.454400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 소분류코드
Categorical

IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
9999 
UQS118
 
1

Length

Max length6
Median length1
Mean length1.0005
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
9999
> 99.9%
UQS118 1
 
< 0.1%

Length

2024-05-11T09:57:36.768372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:57:37.030558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
uqs118 1
100.0%

도형 속성코드
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
UQS190
3454 
UQS122
2587 
UQS121
1086 
UQS119
687 
UQS120
666 
Other values (9)
1520 

Length

Max length6
Median length6
Mean length5.9975
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUQS121
2nd rowUQS122
3rd rowUQS121
4th rowUQS119
5th rowUQS122

Common Values

ValueCountFrequency (%)
UQS190 3454
34.5%
UQS122 2587
25.9%
UQS121 1086
 
10.9%
UQS119 687
 
6.9%
UQS120 666
 
6.7%
UQS118 599
 
6.0%
UQS117 484
 
4.8%
UQS116 171
 
1.7%
UQS115 97
 
1.0%
UQS114 84
 
0.8%
Other values (4) 85
 
0.9%

Length

2024-05-11T09:57:37.352008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqs190 3454
34.6%
uqs122 2587
25.9%
uqs121 1086
 
10.9%
uqs119 687
 
6.9%
uqs120 666
 
6.7%
uqs118 599
 
6.0%
uqs117 484
 
4.8%
uqs116 171
 
1.7%
uqs115 97
 
1.0%
uqs114 84
 
0.8%
Other values (3) 80
 
0.8%
Distinct5150
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:57:37.936438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length19.9962
Min length1

Characters and Unicode

Total characters199962
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4840 ?
Unique (%)48.4%

Sample

1st row11000URZ199710092958
2nd row11000URZ200707120644
3rd row11000URZ200811201701
4th row11740URZ202108240004
5th row11000URZ201509244296
ValueCountFrequency (%)
11000urz000000001511 3995
40.0%
11710urz202010230042 12
 
0.1%
11710urz202010230029 12
 
0.1%
11230urz202008040034 11
 
0.1%
11230urz202008040044 10
 
0.1%
11710urz202010230013 10
 
0.1%
11710urz202010230011 10
 
0.1%
11710urz202010230055 10
 
0.1%
11710urz202010230003 10
 
0.1%
11230urz202008040038 9
 
0.1%
Other values (5139) 5909
59.1%
2024-05-11T09:57:38.970835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 81469
40.7%
1 43626
21.8%
2 14357
 
7.2%
U 9998
 
5.0%
R 9998
 
5.0%
Z 9998
 
5.0%
5 7343
 
3.7%
9 4309
 
2.2%
3 4266
 
2.1%
7 3981
 
2.0%
Other values (4) 10617
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 169966
85.0%
Uppercase Letter 29994
 
15.0%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 81469
47.9%
1 43626
25.7%
2 14357
 
8.4%
5 7343
 
4.3%
9 4309
 
2.5%
3 4266
 
2.5%
7 3981
 
2.3%
8 3679
 
2.2%
6 3605
 
2.1%
4 3331
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
U 9998
33.3%
R 9998
33.3%
Z 9998
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 169968
85.0%
Latin 29994
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 81469
47.9%
1 43626
25.7%
2 14357
 
8.4%
5 7343
 
4.3%
9 4309
 
2.5%
3 4266
 
2.5%
7 3981
 
2.3%
8 3679
 
2.2%
6 3605
 
2.1%
4 3331
 
2.0%
Latin
ValueCountFrequency (%)
U 9998
33.3%
R 9998
33.3%
Z 9998
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 199962
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 81469
40.7%
1 43626
21.8%
2 14357
 
7.2%
U 9998
 
5.0%
R 9998
 
5.0%
Z 9998
 
5.0%
5 7343
 
3.7%
9 4309
 
2.2%
3 4266
 
2.1%
7 3981
 
2.0%
Other values (4) 10617
 
5.3%
Distinct2051
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:57:39.566225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length12.3886
Min length1

Characters and Unicode

Total characters123886
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1276 ?
Unique (%)12.8%

Sample

1st row11000NTC199710097290
2nd row11000NTC200707121247
3rd row11000NTC200811202369
4th row11740NTC202108240004
5th row11000NTC201509247601
ValueCountFrequency (%)
11710ntc202010230007 364
 
6.1%
11000ntc202001280023 244
 
4.1%
11110ntc202008270010 81
 
1.4%
11230ntc202008040003 67
 
1.1%
11000ntc202012150002 57
 
1.0%
11000ntc196801231003 56
 
0.9%
11000ntc200906183489 54
 
0.9%
11000ntc199010311975 51
 
0.9%
11260ntc202112160004 50
 
0.8%
11000ntc198309075490 43
 
0.7%
Other values (2040) 4927
82.2%
2024-05-11T09:57:40.540726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38544
31.1%
1 23189
18.7%
2 14356
 
11.6%
N 5994
 
4.8%
T 5994
 
4.8%
C 5994
 
4.8%
9 4350
 
3.5%
3 4337
 
3.5%
7 4222
 
3.4%
4006
 
3.2%
Other values (4) 12900
 
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101898
82.3%
Uppercase Letter 17982
 
14.5%
Space Separator 4006
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38544
37.8%
1 23189
22.8%
2 14356
 
14.1%
9 4350
 
4.3%
3 4337
 
4.3%
7 4222
 
4.1%
8 3530
 
3.5%
6 3417
 
3.4%
5 3024
 
3.0%
4 2929
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
N 5994
33.3%
T 5994
33.3%
C 5994
33.3%
Space Separator
ValueCountFrequency (%)
4006
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 105904
85.5%
Latin 17982
 
14.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38544
36.4%
1 23189
21.9%
2 14356
 
13.6%
9 4350
 
4.1%
3 4337
 
4.1%
7 4222
 
4.0%
4006
 
3.8%
8 3530
 
3.3%
6 3417
 
3.2%
5 3024
 
2.9%
Latin
ValueCountFrequency (%)
N 5994
33.3%
T 5994
33.3%
C 5994
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123886
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38544
31.1%
1 23189
18.7%
2 14356
 
11.6%
N 5994
 
4.8%
T 5994
 
4.8%
C 5994
 
4.8%
9 4350
 
3.5%
3 4337
 
3.5%
7 4222
 
3.4%
4006
 
3.2%
Other values (4) 12900
 
10.4%

라벨명
Categorical

HIGH CORRELATION 

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
기타도로시설
3414 
소로3류
2582 
소로2류
1086 
중로3류
683 
소로1류
664 
Other values (29)
1571 

Length

Max length8
Median length4
Mean length4.6907
Min length1

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st row소로2류
2nd row소로3류
3rd row소로2류
4th row중로3류
5th row소로3류

Common Values

ValueCountFrequency (%)
기타도로시설 3414
34.1%
소로3류 2582
25.8%
소로2류 1086
 
10.9%
중로3류 683
 
6.8%
소로1류 664
 
6.6%
중로2류 597
 
6.0%
중로1류 485
 
4.9%
대로3류 172
 
1.7%
대로2류 96
 
1.0%
대로1류 85
 
0.9%
Other values (24) 136
 
1.4%

Length

2024-05-11T09:57:41.070190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기타도로시설 3414
34.1%
소로3류 2582
25.8%
소로2류 1086
 
10.8%
중로3류 683
 
6.8%
소로1류 664
 
6.6%
중로2류 597
 
6.0%
중로1류 485
 
4.8%
대로3류 172
 
1.7%
대로2류 96
 
1.0%
대로1류 85
 
0.8%
Other values (24) 154
 
1.5%

시군구코드
Categorical

IMBALANCE 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
11000
9162 
11260
 
68
11410
 
64
11380
 
56
11290
 
55
Other values (23)
 
595

Length

Max length5
Median length5
Mean length4.9992
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11000
2nd row11000
3rd row11000
4th row11740
5th row11000

Common Values

ValueCountFrequency (%)
11000 9162
91.6%
11260 68
 
0.7%
11410 64
 
0.6%
11380 56
 
0.6%
11290 55
 
0.5%
11110 47
 
0.5%
11200 47
 
0.5%
11650 45
 
0.4%
11590 42
 
0.4%
11140 42
 
0.4%
Other values (18) 372
 
3.7%

Length

2024-05-11T09:57:41.632390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
11000 9162
91.6%
11260 68
 
0.7%
11410 64
 
0.6%
11380 56
 
0.6%
11290 55
 
0.6%
11110 47
 
0.5%
11200 47
 
0.5%
11650 45
 
0.5%
11590 42
 
0.4%
11140 42
 
0.4%
Other values (17) 370
 
3.7%

규모_등급_심볼
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
소로
4395 
3385 
중로
1770 
대로
 
355
광로
 
87
Other values (4)
 
8

Length

Max length4
Median length2
Mean length1.6623
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row소로
2nd row소로
3rd row소로
4th row중로
5th row소로

Common Values

ValueCountFrequency (%)
소로 4395
44.0%
3385
33.9%
중로 1770
17.7%
대로 355
 
3.5%
광로 87
 
0.9%
기타 4
 
< 0.1%
??濡? 2
 
< 0.1%
중로1류 1
 
< 0.1%
기타도로 1
 
< 0.1%

Length

2024-05-11T09:57:42.034705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:57:42.391140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소로 4395
66.4%
중로 1770
26.8%
대로 355
 
5.4%
광로 87
 
1.3%
기타 4
 
0.1%
??濡? 2
 
< 0.1%
중로1류 1
 
< 0.1%
기타도로 1
 
< 0.1%

규모_류별_심볼
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3470 
3
3454 
2
1802 
1
1241 
4
 
30
Other values (3)
 
3

Length

Max length3
Median length1
Mean length1.0003
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row3
3rd row2
4th row3
5th row3

Common Values

ValueCountFrequency (%)
3470
34.7%
3 3454
34.5%
2 1802
18.0%
1 1241
 
12.4%
4 30
 
0.3%
竊? 1
 
< 0.1%
2-3 1
 
< 0.1%
6 1
 
< 0.1%

Length

2024-05-11T09:57:42.902570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:57:43.298972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 3454
52.9%
2 1802
27.6%
1 1241
 
19.0%
4 30
 
0.5%
竊? 1
 
< 0.1%
2-3 1
 
< 0.1%
6 1
 
< 0.1%
Distinct620
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:57:43.965793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.3786
Min length1

Characters and Unicode

Total characters13786
Distinct characters81
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique274 ?
Unique (%)2.7%

Sample

1st row22
2nd row11
3rd row-
4th row407
5th row4
ValueCountFrequency (%)
1 644
 
12.9%
2 408
 
8.1%
3 271
 
5.4%
4 203
 
4.1%
5 185
 
3.7%
6 129
 
2.6%
7 122
 
2.4%
a 118
 
2.4%
8 108
 
2.2%
9 99
 
2.0%
Other values (570) 2722
54.3%
2024-05-11T09:57:45.001780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4991
36.2%
1 2027
14.7%
2 1274
 
9.2%
3 919
 
6.7%
4 723
 
5.2%
5 702
 
5.1%
6 503
 
3.6%
0 454
 
3.3%
7 438
 
3.2%
9 418
 
3.0%
Other values (71) 1337
 
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7834
56.8%
Space Separator 4991
36.2%
Uppercase Letter 249
 
1.8%
Open Punctuation 215
 
1.6%
Close Punctuation 215
 
1.6%
Other Letter 106
 
0.8%
Dash Punctuation 96
 
0.7%
Lowercase Letter 54
 
0.4%
Other Number 22
 
0.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
34
32.1%
12
 
11.3%
11
 
10.4%
9
 
8.5%
8
 
7.5%
5
 
4.7%
5
 
4.7%
4
 
3.8%
4
 
3.8%
3
 
2.8%
Other values (11) 11
 
10.4%
Lowercase Letter
ValueCountFrequency (%)
b 14
25.9%
a 11
20.4%
d 3
 
5.6%
c 3
 
5.6%
i 3
 
5.6%
s 3
 
5.6%
e 3
 
5.6%
h 2
 
3.7%
f 2
 
3.7%
g 2
 
3.7%
Other values (8) 8
14.8%
Uppercase Letter
ValueCountFrequency (%)
A 109
43.8%
B 54
21.7%
C 41
 
16.5%
K 9
 
3.6%
F 9
 
3.6%
D 8
 
3.2%
E 5
 
2.0%
G 4
 
1.6%
S 2
 
0.8%
H 2
 
0.8%
Other values (6) 6
 
2.4%
Decimal Number
ValueCountFrequency (%)
1 2027
25.9%
2 1274
16.3%
3 919
11.7%
4 723
 
9.2%
5 702
 
9.0%
6 503
 
6.4%
0 454
 
5.8%
7 438
 
5.6%
9 418
 
5.3%
8 376
 
4.8%
Other Number
ValueCountFrequency (%)
10
45.5%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
4991
100.0%
Open Punctuation
ValueCountFrequency (%)
( 215
100.0%
Close Punctuation
ValueCountFrequency (%)
) 215
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%
Other Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13376
97.0%
Latin 303
 
2.2%
Hangul 107
 
0.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 109
36.0%
B 54
17.8%
C 41
 
13.5%
b 14
 
4.6%
a 11
 
3.6%
K 9
 
3.0%
F 9
 
3.0%
D 8
 
2.6%
E 5
 
1.7%
G 4
 
1.3%
Other values (24) 39
 
12.9%
Common
ValueCountFrequency (%)
4991
37.3%
1 2027
15.2%
2 1274
 
9.5%
3 919
 
6.9%
4 723
 
5.4%
5 702
 
5.2%
6 503
 
3.8%
0 454
 
3.4%
7 438
 
3.3%
9 418
 
3.1%
Other values (15) 927
 
6.9%
Hangul
ValueCountFrequency (%)
34
31.8%
12
 
11.2%
11
 
10.3%
9
 
8.4%
8
 
7.5%
5
 
4.7%
5
 
4.7%
4
 
3.7%
4
 
3.7%
3
 
2.8%
Other values (12) 12
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13654
99.0%
Hangul 104
 
0.8%
Enclosed Alphanum 23
 
0.2%
None 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4991
36.6%
1 2027
14.8%
2 1274
 
9.3%
3 919
 
6.7%
4 723
 
5.3%
5 702
 
5.1%
6 503
 
3.7%
0 454
 
3.3%
7 438
 
3.2%
9 418
 
3.1%
Other values (38) 1205
 
8.8%
Hangul
ValueCountFrequency (%)
34
32.7%
12
 
11.5%
11
 
10.6%
9
 
8.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
3
 
2.9%
Other values (9) 9
 
8.7%
Enclosed Alphanum
ValueCountFrequency (%)
10
43.5%
2
 
8.7%
2
 
8.7%
2
 
8.7%
2
 
8.7%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
1
 
4.3%
None
ValueCountFrequency (%)
2
66.7%
1
33.3%
Compat Jamo
ValueCountFrequency (%)
1
50.0%
1
50.0%

도로기능_심볼
Categorical

IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4976 
PMI0004
3130 
PMI0003
988 
PMI0008
 
231
PMI0002
 
225
Other values (12)
 
450

Length

Max length7
Median length7
Mean length4.0133
Min length1

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowPMI0004
2nd row
3rd rowPMI0004
4th rowPMI0002
5th rowPMI0004

Common Values

ValueCountFrequency (%)
4976
49.8%
PMI0004 3130
31.3%
PMI0003 988
 
9.9%
PMI0008 231
 
2.3%
PMI0002 225
 
2.2%
PMI0001 164
 
1.6%
PMH0003 101
 
1.0%
PMI0010 93
 
0.9%
PMI0006 54
 
0.5%
PMI0009 17
 
0.2%
Other values (7) 21
 
0.2%

Length

2024-05-11T09:57:45.453974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
pmi0004 3130
62.3%
pmi0003 988
 
19.7%
pmi0008 231
 
4.6%
pmi0002 225
 
4.5%
pmi0001 164
 
3.3%
pmh0003 101
 
2.0%
pmi0010 93
 
1.9%
pmi0006 54
 
1.1%
pmi0009 17
 
0.3%
null 7
 
0.1%
Other values (6) 14
 
0.3%
Distinct734
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T09:57:46.008613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length1
Mean length2.047
Min length1

Characters and Unicode

Total characters20470
Distinct characters81
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique450 ?
Unique (%)4.5%

Sample

1st row
2nd row
3rd row
4th row중로3-407
5th row
ValueCountFrequency (%)
소로3 77
 
3.3%
소로2-1 37
 
1.6%
소로3-1 37
 
1.6%
소로3-2 34
 
1.5%
소로2 32
 
1.4%
중로3-1 30
 
1.3%
소로2-2 30
 
1.3%
소로3-4 26
 
1.1%
소로1-1 26
 
1.1%
소로3-3 25
 
1.1%
Other values (694) 1972
84.8%
2024-05-11T09:57:46.901553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7674
37.5%
2228
 
10.9%
- 2196
 
10.7%
3 1466
 
7.2%
1 1341
 
6.6%
1284
 
6.3%
2 1185
 
5.8%
763
 
3.7%
4 291
 
1.4%
5 267
 
1.3%
Other values (71) 1775
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Space Separator 7674
37.5%
Decimal Number 5423
26.5%
Other Letter 4530
22.1%
Dash Punctuation 2196
 
10.7%
Uppercase Letter 213
 
1.0%
Close Punctuation 184
 
0.9%
Open Punctuation 184
 
0.9%
Lowercase Letter 43
 
0.2%
Other Number 11
 
0.1%
Other Punctuation 8
 
< 0.1%
Other values (2) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2228
49.2%
1284
28.3%
763
 
16.8%
129
 
2.8%
41
 
0.9%
18
 
0.4%
6
 
0.1%
6
 
0.1%
6
 
0.1%
5
 
0.1%
Other values (19) 44
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
b 9
20.9%
a 6
14.0%
e 3
 
7.0%
c 3
 
7.0%
d 3
 
7.0%
i 3
 
7.0%
f 2
 
4.7%
s 2
 
4.7%
g 2
 
4.7%
h 2
 
4.7%
Other values (8) 8
18.6%
Uppercase Letter
ValueCountFrequency (%)
A 90
42.3%
B 46
21.6%
C 38
17.8%
F 9
 
4.2%
K 9
 
4.2%
D 6
 
2.8%
E 5
 
2.3%
G 3
 
1.4%
H 2
 
0.9%
O 1
 
0.5%
Other values (4) 4
 
1.9%
Decimal Number
ValueCountFrequency (%)
3 1466
27.0%
1 1341
24.7%
2 1185
21.9%
4 291
 
5.4%
5 267
 
4.9%
6 199
 
3.7%
0 192
 
3.5%
7 170
 
3.1%
9 167
 
3.1%
8 145
 
2.7%
Other Number
ValueCountFrequency (%)
8
72.7%
3
 
27.3%
Other Symbol
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
7674
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2196
100.0%
Close Punctuation
ValueCountFrequency (%)
) 184
100.0%
Open Punctuation
ValueCountFrequency (%)
( 184
100.0%
Other Punctuation
ValueCountFrequency (%)
8
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15683
76.6%
Hangul 4529
 
22.1%
Latin 256
 
1.3%
Han 2
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 90
35.2%
B 46
18.0%
C 38
14.8%
F 9
 
3.5%
K 9
 
3.5%
b 9
 
3.5%
a 6
 
2.3%
D 6
 
2.3%
E 5
 
2.0%
e 3
 
1.2%
Other values (22) 35
 
13.7%
Hangul
ValueCountFrequency (%)
2228
49.2%
1284
28.4%
763
 
16.8%
129
 
2.8%
41
 
0.9%
18
 
0.4%
6
 
0.1%
6
 
0.1%
6
 
0.1%
5
 
0.1%
Other values (19) 43
 
0.9%
Common
ValueCountFrequency (%)
7674
48.9%
- 2196
 
14.0%
3 1466
 
9.3%
1 1341
 
8.6%
2 1185
 
7.6%
4 291
 
1.9%
5 267
 
1.7%
6 199
 
1.3%
0 192
 
1.2%
) 184
 
1.2%
Other values (9) 688
 
4.4%
Han
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15919
77.8%
Hangul 4527
 
22.1%
Enclosed Alphanum 12
 
0.1%
None 9
 
< 0.1%
CJK 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7674
48.2%
- 2196
 
13.8%
3 1466
 
9.2%
1 1341
 
8.4%
2 1185
 
7.4%
4 291
 
1.8%
5 267
 
1.7%
6 199
 
1.3%
0 192
 
1.2%
) 184
 
1.2%
Other values (37) 924
 
5.8%
Hangul
ValueCountFrequency (%)
2228
49.2%
1284
28.4%
763
 
16.9%
129
 
2.8%
41
 
0.9%
18
 
0.4%
6
 
0.1%
6
 
0.1%
6
 
0.1%
5
 
0.1%
Other values (17) 41
 
0.9%
Enclosed Alphanum
ValueCountFrequency (%)
8
66.7%
3
 
25.0%
1
 
8.3%
None
ValueCountFrequency (%)
8
88.9%
1
 
11.1%
CJK
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

집행상태코드 심볼
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
EMA0009
9918 
 
49
EMA0001
 
27
EMA0002
 
4
EMA0003
 
2

Length

Max length7
Median length7
Mean length6.9706
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowEMA0009
2nd rowEMA0009
3rd rowEMA0009
4th rowEMA0009
5th rowEMA0009

Common Values

ValueCountFrequency (%)
EMA0009 9918
99.2%
49
 
0.5%
EMA0001 27
 
0.3%
EMA0002 4
 
< 0.1%
EMA0003 2
 
< 0.1%

Length

2024-05-11T09:57:47.328069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T09:57:47.660048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ema0009 9918
99.7%
ema0001 27
 
0.3%
ema0002 4
 
< 0.1%
ema0003 2
 
< 0.1%
Distinct373
Distinct (%)3.7%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
Minimum1899-12-29 23:27:52
Maximum2024-04-24 00:00:00
2024-05-11T09:57:48.025844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:48.386115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct9106
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6043.8759
Minimum0.00011461
Maximum1367885
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:57:48.665376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.00011461
5-th percentile59.969548
Q1366.69987
median995.7172
Q32889.6841
95-th percentile21585.856
Maximum1367885
Range1367885
Interquartile range (IQR)2522.9843

Descriptive statistics

Standard deviation29924.795
Coefficient of variation (CV)4.951259
Kurtosis612.42937
Mean6043.8759
Median Absolute Deviation (MAD)793.11026
Skewness19.598068
Sum60438759
Variance8.9549336 × 108
MonotonicityNot monotonic
2024-05-11T09:57:48.949766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.39984132 28
 
0.3%
62.08116256 12
 
0.1%
2116.44804011 12
 
0.1%
1573.63999955 11
 
0.1%
11526.50080001 10
 
0.1%
15671.80368954 10
 
0.1%
29227.4762406 10
 
0.1%
86.22851306 10
 
0.1%
707.11896269 10
 
0.1%
10754.81046015 9
 
0.1%
Other values (9096) 9878
98.8%
ValueCountFrequency (%)
0.00011461 1
< 0.1%
0.00020814 1
< 0.1%
0.00026003 1
< 0.1%
0.00031162 1
< 0.1%
0.00057616 1
< 0.1%
0.00099507 1
< 0.1%
0.0017619 1
< 0.1%
0.00191669 1
< 0.1%
0.00290892 1
< 0.1%
0.00775295 1
< 0.1%
ValueCountFrequency (%)
1367885.04685589 1
 
< 0.1%
843980.27910135 1
 
< 0.1%
719904.53358278 1
 
< 0.1%
664752.83889004 1
 
< 0.1%
495567.37549038 5
0.1%
449974.39116649 1
 
< 0.1%
435126.15952933 1
 
< 0.1%
412127.57948265 1
 
< 0.1%
380162.36708408 1
 
< 0.1%
363171.44588422 1
 
< 0.1%

길이(도형)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct9108
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean811.74396
Minimum0
Maximum134208.03
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T09:57:49.265672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile40.742927
Q1141.6105
median290.00703
Q3601.18054
95-th percentile2319.6617
Maximum134208.03
Range134208.03
Interquartile range (IQR)459.57004

Descriptive statistics

Standard deviation3416.0198
Coefficient of variation (CV)4.2082479
Kurtosis575.76814
Mean811.74396
Median Absolute Deviation (MAD)181.29483
Skewness20.13774
Sum8117439.6
Variance11669191
MonotonicityNot monotonic
2024-05-11T09:57:49.557582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23.19999999 15
 
0.1%
88.0 14
 
0.1%
68.0 14
 
0.1%
23.2 13
 
0.1%
451.64063879 12
 
0.1%
105.0 12
 
0.1%
36.1768615 12
 
0.1%
334.91988955 11
 
0.1%
1471.23892964 10
 
0.1%
1523.34735027 10
 
0.1%
Other values (9098) 9877
98.8%
ValueCountFrequency (%)
0.0 2
< 0.1%
0.08771003 1
< 0.1%
0.12184356 1
< 0.1%
0.20720251 1
< 0.1%
0.21904335 1
< 0.1%
0.25337525 1
< 0.1%
0.30715802 1
< 0.1%
0.32754062 1
< 0.1%
0.37911381 1
< 0.1%
0.45390048 1
< 0.1%
ValueCountFrequency (%)
134208.026646 1
< 0.1%
127137.730547 1
< 0.1%
82515.9850855 1
< 0.1%
80172.9698261 1
< 0.1%
75495.13927293 1
< 0.1%
68061.56816121 1
< 0.1%
64675.5497348 1
< 0.1%
58319.0617994 1
< 0.1%
57619.81879458 1
< 0.1%
54690.7912294 1
< 0.1%

Interactions

2024-05-11T09:57:31.573261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:29.933126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:30.683293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:31.792195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:30.230843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:30.941011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:31.992893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:30.484709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T09:57:31.288561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T09:57:49.771963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id도형 대분류코드도형 소분류코드도형 속성코드라벨명시군구코드규모_등급_심볼규모_류별_심볼도로기능_심볼집행상태코드 심볼면적(도형)길이(도형)
객체id1.0000.0280.0050.0320.0500.0840.0310.0220.0000.0770.0000.000
도형 대분류코드0.0281.0000.4870.9980.9950.3920.9150.8870.7310.3190.3240.207
도형 소분류코드0.0050.4871.0000.0210.0000.0000.0000.0000.0000.0000.0000.000
도형 속성코드0.0320.9980.0211.0001.0000.6050.9060.8800.7360.2840.3170.203
라벨명0.0500.9950.0001.0001.0000.6300.9580.9310.8060.3010.3420.205
시군구코드0.0840.3920.0000.6050.6301.0000.3320.4010.3350.4320.2270.106
규모_등급_심볼0.0310.9150.0000.9060.9580.3321.0000.7220.7430.0560.1890.099
규모_류별_심볼0.0220.8870.0000.8800.9310.4010.7221.0000.5870.0570.0000.044
도로기능_심볼0.0000.7310.0000.7360.8060.3350.7430.5871.0000.1630.2650.162
집행상태코드 심볼0.0770.3190.0000.2840.3010.4320.0560.0570.1631.0000.0000.000
면적(도형)0.0000.3240.0000.3170.3420.2270.1890.0000.2650.0001.0000.902
길이(도형)0.0000.2070.0000.2030.2050.1060.0990.0440.1620.0000.9021.000
2024-05-11T09:57:50.037888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
라벨명도형 소분류코드시군구코드규모_등급_심볼도형 대분류코드도형 속성코드도로기능_심볼집행상태코드 심볼규모_류별_심볼
라벨명1.0000.0000.1840.7770.9470.9970.3180.1450.705
도형 소분류코드0.0001.0000.0000.0000.4460.0160.0000.0000.000
시군구코드0.1840.0001.0000.1300.1270.2020.1010.2240.167
규모_등급_심볼0.7770.0000.1301.0000.6910.6910.4110.0320.463
도형 대분류코드0.9470.4460.1270.6911.0000.9860.3420.1410.648
도형 속성코드0.9970.0160.2020.6910.9861.0000.3550.1520.649
도로기능_심볼0.3180.0000.1010.4110.3420.3551.0000.0840.292
집행상태코드 심볼0.1450.0000.2240.0320.1410.1520.0841.0000.035
규모_류별_심볼0.7050.0000.1670.4630.6480.6490.2920.0351.000
2024-05-11T09:57:50.347687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id면적(도형)길이(도형)도형 대분류코드도형 소분류코드도형 속성코드라벨명시군구코드규모_등급_심볼규모_류별_심볼도로기능_심볼집행상태코드 심볼
객체id1.000-0.005-0.0090.0100.0030.0130.0170.0300.0140.0100.0000.032
면적(도형)-0.0051.0000.9570.1450.0000.1450.1400.0900.0930.0000.1140.000
길이(도형)-0.0090.9571.0000.0900.0000.0900.0810.0410.0490.0150.0680.000
도형 대분류코드0.0100.1450.0901.0000.4460.9860.9470.1270.6910.6480.3420.141
도형 소분류코드0.0030.0000.0000.4461.0000.0160.0000.0000.0000.0000.0000.000
도형 속성코드0.0130.1450.0900.9860.0161.0000.9970.2020.6910.6490.3550.152
라벨명0.0170.1400.0810.9470.0000.9971.0000.1840.7770.7050.3180.145
시군구코드0.0300.0900.0410.1270.0000.2020.1841.0000.1300.1670.1010.224
규모_등급_심볼0.0140.0930.0490.6910.0000.6910.7770.1301.0000.4630.4110.032
규모_류별_심볼0.0100.0000.0150.6480.0000.6490.7050.1670.4631.0000.2920.035
도로기능_심볼0.0000.1140.0680.3420.0000.3550.3180.1010.4110.2921.0000.084
집행상태코드 심볼0.0320.0000.0000.1410.0000.1520.1450.2240.0320.0350.0841.000

Missing values

2024-05-11T09:57:32.377486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T09:57:33.116953image/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.

Sample

객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드규모_등급_심볼규모_류별_심볼규모_번호_심볼도로기능_심볼도면번호집행상태코드 심볼현황도형 생성일시면적(도형)길이(도형)
744465000311000UQ151PS201912152770UQS121UQS12111000URZ19971009295811000NTC199710097290소로2류11000소로222PMI0004EMA00092019-12-15 00:00:00.0734.68785213.732327
472464728311000UQ151PS201912157023UQS122UQS12211000URZ20070712064411000NTC200707121247소로3류11000소로311EMA00092019-12-15 00:00:00.0232.955265121.050957
1804566060411000UQ151PS201912154824UQS121UQS12111000URZ20081120170111000NTC200811202369소로2류11000소로2-PMI0004EMA00092019-12-15 00:00:00.03081.483624574.136912
139464395311740UQ151PS202108240003UQS119UQS11911740URZ20210824000411740NTC202108240004중로3류11740중로3407PMI0002중로3-407EMA00092021-08-24 00:00:00.02757.112703623.450532
1047765303611000UQ151PS201912163292UQS122UQS12211000URZ20150924429611000NTC201509247601소로3류11000소로34PMI0004EMA00092019-12-15 00:00:00.01328.248154365.548843
1433665689511000UQ151PS201912158920UQS190UQS19011000URZ000000001511기타도로시설11000EMA00092019-12-15 00:00:00.032109.4866934147.20757
1058665314511000UQ151PS201912155665UQS122UQS12211000URZ19751201919411000NTC197512011508소로3류11000소로37EMA00092019-12-15 00:00:00.0984.172382351.247431
1556165812011000UQ151PS202008270032UQS121UQS12111305URZ20200804007911000NTC202008040029소로2류11000소로2PMI0004소로2-EMA00092020-08-27 00:00:00.0371.347948158.280877
194564450411000UQ151PS201912159336UQS190UQS19011000URZ000000001511기타도로시설11000EMA00092019-12-15 00:00:00.06.25394312.073129
1864257711000UQ151PS202101110021UQS122UQS12211000URZ20210106000811305NTC202101060005소로3류11000소로37PMI0004소로3-7EMA00092021-01-11 00:00:00.0344.469194167.226819
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드규모_등급_심볼규모_류별_심볼규모_번호_심볼도로기능_심볼도면번호집행상태코드 심볼현황도형 생성일시면적(도형)길이(도형)
475564731411000UQ151PS201912155248UQS122UQS12211000URZ19680123651211000NTC196801231003소로3류11000소로335EMA00092019-12-15 00:00:00.0753.375169292.631815
1387765643611000UQ151PS202009180106UQS122UQS12211110URZ20200827004711110NTC202008270010소로3류11000소로31PMI0004소로3-1EMA00092020-09-18 00:00:00.0300.287429260.799255
1546965802811200UQ151PS202110280020UQS121UQS12111200URZ20210531000811200NTC202110200004소로2류11200소로2CPMI0004소로2-CEMA00092021-10-28 00:00:00.02801.134567778.157098
1157965413811000UQ151PS202002030039UQS118UQS11811000URZ20200128004511000NTC202001280023중로2류11000중로230PMI0004중로2-30EMA00092020-02-03 00:00:00.01438.912674237.600567
1516865772711000UQ151PS201912158785UQS190UQS19011000URZ000000001511기타도로시설11000EMA00092019-12-15 00:00:00.038513.9098854849.540212
145964401811000UQ151PS202311030022UQS122UQS12211000URZ20230927002411000NTC202309270009소로3류11000소로3gPMI0004소로3-gEMA00092023-11-03 00:00:00.02430.965198764.525609
1456365712211000UQ151PS202011100263UQS122UQS12211710URZ20201023006611710NTC202010230007소로3류11000소로333PMH0003소로3-33EMA00092020-11-10 00:00:00.0160.00033988.0
310364566211000UQ151PS201912156478UQS122UQS12211000URZ20051230713411000NTC200512309445소로3류11000소로338PMI0008EMA00092019-12-15 00:00:00.0263.06835106.222773
1381465637311000UQ151PS201912165622UQS121UQS12111000URZ20160908426811000NTC201609087866소로2류11000소로2802PMI0004EMA00092019-12-15 00:00:00.01098.021133290.377666
374264630111000UQ151PS202401300030UQS121UQS12111000URZ20230629003511000NTC202310040001소로2류11000소로2iPMI0004소로2-iEMA00092024-01-30 00:00:00.01210.86453320.54738