Overview

Dataset statistics

Number of variables15
Number of observations1996
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory241.8 KiB
Average record size in memory124.1 B

Variable types

Numeric4
Text5
Categorical5
DateTime1

Dataset

Description객체id,현황도형 관리번호,도형 대분류코드,도형 중분류코드,도형 소분류코드,도형 속성코드,도형 조서관리 코드,결정고시관리코드,라벨명,시군구코드,도면번호,집행상태코드 심볼,현황도형 생성일시,면적(도형),길이(도형)
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-21130/S/1/datasetView.do

Alerts

도형 소분류코드 has constant value ""Constant
도형 속성코드 is highly overall correlated with 면적(도형) and 2 other fieldsHigh correlation
도형 중분류코드 is highly overall correlated with 면적(도형) and 2 other fieldsHigh correlation
면적(도형) is highly overall correlated with 길이(도형) and 3 other fieldsHigh correlation
길이(도형) is highly overall correlated with 면적(도형)High correlation
도형 대분류코드 is highly overall correlated with 면적(도형) and 3 other fieldsHigh correlation
집행상태코드 심볼 is highly overall correlated with 도형 대분류코드High correlation
도형 대분류코드 is highly imbalanced (63.0%)Imbalance
집행상태코드 심볼 is highly imbalanced (98.6%)Imbalance
시군구코드 is highly skewed (γ1 = 44.21407147)Skewed
면적(도형) is highly skewed (γ1 = 42.13367129)Skewed
객체id has unique valuesUnique

Reproduction

Analysis started2024-05-10 22:54:20.068493
Analysis finished2024-05-10 22:54:29.605303
Duration9.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

객체id
Real number (ℝ)

UNIQUE 

Distinct1996
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80022.817
Minimum78787
Maximum81022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-05-10T22:54:29.914015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum78787
5-th percentile79126.75
Q179525.75
median80024.5
Q380523.25
95-th percentile80922.25
Maximum81022
Range2235
Interquartile range (IQR)997.5

Descriptive statistics

Standard deviation579.57497
Coefficient of variation (CV)0.0072426215
Kurtosis-1.1571933
Mean80022.817
Median Absolute Deviation (MAD)499
Skewness-0.023469455
Sum1.5972554 × 108
Variance335907.15
MonotonicityStrictly increasing
2024-05-10T22:54:30.533283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78787 1
 
0.1%
80354 1
 
0.1%
80367 1
 
0.1%
80366 1
 
0.1%
80365 1
 
0.1%
80364 1
 
0.1%
80363 1
 
0.1%
80362 1
 
0.1%
80361 1
 
0.1%
80360 1
 
0.1%
Other values (1986) 1986
99.5%
ValueCountFrequency (%)
78787 1
0.1%
78788 1
0.1%
78789 1
0.1%
78790 1
0.1%
78791 1
0.1%
78792 1
0.1%
78793 1
0.1%
78794 1
0.1%
78795 1
0.1%
78796 1
0.1%
ValueCountFrequency (%)
81022 1
0.1%
81021 1
0.1%
81020 1
0.1%
81019 1
0.1%
81018 1
0.1%
81017 1
0.1%
81016 1
0.1%
81015 1
0.1%
81014 1
0.1%
81013 1
0.1%

현황도형 관리번호
Text

Distinct1992
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-05-10T22:54:31.322057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters47904
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1990 ?
Unique (%)99.7%

Sample

1st row11440UQ152PS202012010001
2nd row11380UQ152PS202103160001
3rd row11000UQ152PS201912151461
4th row11000UQ152PS201912151462
5th row11000UQ152PS201912151704
ValueCountFrequency (%)
11000uq152ps202012080021 4
 
0.2%
11560uq152ps202208010003 2
 
0.1%
11000uq152ps202002030008 1
 
0.1%
11000uq152ps201912151127 1
 
0.1%
11440uq152ps202012010001 1
 
0.1%
11000uq152ps201912150141 1
 
0.1%
11000uq152ps201912151125 1
 
0.1%
11000uq152ps201912151124 1
 
0.1%
11000uq152ps201912151123 1
 
0.1%
11000uq152ps201912150790 1
 
0.1%
Other values (1982) 1982
99.3%
2024-05-10T22:54:32.253778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12589
26.3%
0 10805
22.6%
2 7022
14.7%
5 4225
 
8.8%
9 2076
 
4.3%
U 1996
 
4.2%
Q 1996
 
4.2%
P 1996
 
4.2%
S 1996
 
4.2%
3 797
 
1.7%
Other values (4) 2406
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39920
83.3%
Uppercase Letter 7984
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12589
31.5%
0 10805
27.1%
2 7022
17.6%
5 4225
 
10.6%
9 2076
 
5.2%
3 797
 
2.0%
4 657
 
1.6%
6 626
 
1.6%
7 587
 
1.5%
8 536
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
U 1996
25.0%
Q 1996
25.0%
P 1996
25.0%
S 1996
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39920
83.3%
Latin 7984
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12589
31.5%
0 10805
27.1%
2 7022
17.6%
5 4225
 
10.6%
9 2076
 
5.2%
3 797
 
2.0%
4 657
 
1.6%
6 626
 
1.6%
7 587
 
1.5%
8 536
 
1.3%
Latin
ValueCountFrequency (%)
U 1996
25.0%
Q 1996
25.0%
P 1996
25.0%
S 1996
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47904
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12589
26.3%
0 10805
22.6%
2 7022
14.7%
5 4225
 
8.8%
9 2076
 
4.3%
U 1996
 
4.2%
Q 1996
 
4.2%
P 1996
 
4.2%
S 1996
 
4.2%
3 797
 
1.7%
Other values (4) 2406
 
5.0%

도형 대분류코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct12
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
UQS200
998 
UQS500
874 
UQS300
109 
UQS400
 
4
UQS550
 
2
Other values (7)
 
9

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique5 ?
Unique (%)0.3%

Sample

1st rowUQS500
2nd rowUQS200
3rd rowUQS500
4th rowUQS500
5th rowUQS500

Common Values

ValueCountFrequency (%)
UQS200 998
50.0%
UQS500 874
43.8%
UQS300 109
 
5.5%
UQS400 4
 
0.2%
UQS550 2
 
0.1%
UQS999 2
 
0.1%
UQSA52 2
 
0.1%
UQS520 1
 
0.1%
UQS190 1
 
0.1%
UQS900 1
 
0.1%
Other values (2) 2
 
0.1%

Length

2024-05-10T22:54:32.656495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqs200 998
50.0%
uqs500 874
43.8%
uqs300 109
 
5.5%
uqs400 4
 
0.2%
uqs550 2
 
0.1%
uqs999 2
 
0.1%
uqsa52 2
 
0.1%
uqs520 1
 
0.1%
uqs190 1
 
0.1%
uqs900 1
 
0.1%
Other values (2) 2
 
0.1%

도형 중분류코드
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
UQS290
507 
UQS210
435 
UQSA52
391 
UQSA54
288 
UQS520
76 
Other values (15)
299 

Length

Max length6
Median length6
Mean length5.992485
Min length1

Unique

Unique5 ?
Unique (%)0.3%

Sample

1st rowUQSA52
2nd rowUQS290
3rd rowUQSA54
4th rowUQS549
5th rowUQSA52

Common Values

ValueCountFrequency (%)
UQS290 507
25.4%
UQS210 435
21.8%
UQSA52 391
19.6%
UQSA54 288
14.4%
UQS520 76
 
3.8%
UQS310 62
 
3.1%
UQS201 56
 
2.8%
UQS510 55
 
2.8%
UQS549 47
 
2.4%
UQS330 24
 
1.2%
Other values (10) 55
 
2.8%

Length

2024-05-10T22:54:33.029310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqs290 507
25.4%
uqs210 435
21.8%
uqsa52 391
19.6%
uqsa54 288
14.5%
uqs520 76
 
3.8%
uqs310 62
 
3.1%
uqs201 56
 
2.8%
uqs510 55
 
2.8%
uqs549 47
 
2.4%
uqs330 24
 
1.2%
Other values (9) 52
 
2.6%

도형 소분류코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
1996 

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 (%)
1996
100.0%

Length

2024-05-10T22:54:33.403358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:54:33.753954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
No values found.

도형 속성코드
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
UQS290
507 
UQS210
435 
UQSA52
391 
UQSA54
288 
UQS520
76 
Other values (17)
299 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique7 ?
Unique (%)0.4%

Sample

1st rowUQSA52
2nd rowUQS290
3rd rowUQSA54
4th rowUQS549
5th rowUQSA52

Common Values

ValueCountFrequency (%)
UQS290 507
25.4%
UQS210 435
21.8%
UQSA52 391
19.6%
UQSA54 288
14.4%
UQS520 76
 
3.8%
UQS310 62
 
3.1%
UQS201 55
 
2.8%
UQS510 55
 
2.8%
UQS549 47
 
2.4%
UQS330 24
 
1.2%
Other values (12) 56
 
2.8%

Length

2024-05-10T22:54:34.143175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
uqs290 507
25.4%
uqs210 435
21.8%
uqsa52 391
19.6%
uqsa54 288
14.4%
uqs520 76
 
3.8%
uqs310 62
 
3.1%
uqs201 55
 
2.8%
uqs510 55
 
2.8%
uqs549 47
 
2.4%
uqs330 24
 
1.2%
Other values (12) 56
 
2.8%

도형 조서관리 코드
Text

Distinct1663
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-05-10T22:54:34.601374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters39920
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1616 ?
Unique (%)81.0%

Sample

1st row11440URZ202011270001
2nd row11380URZ202103030008
3rd row11000URZ199705164161
4th row11000URZ000000001521
5th row11000URZ201402134231
ValueCountFrequency (%)
11000urz000000001521 205
 
10.3%
11230urz202008040058 14
 
0.7%
11710urz202010230002 13
 
0.7%
11380urz202103030008 12
 
0.6%
11410urz202203020010 8
 
0.4%
11000urz202001280120 6
 
0.3%
11000urz202001280123 6
 
0.3%
11000urz202001280122 6
 
0.3%
11000urz202001280121 6
 
0.3%
11000urz202001280148 6
 
0.3%
Other values (1653) 1714
85.9%
2024-05-10T22:54:35.472832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13037
32.7%
1 7964
19.9%
2 3826
 
9.6%
U 1996
 
5.0%
R 1996
 
5.0%
Z 1996
 
5.0%
9 1874
 
4.7%
3 1322
 
3.3%
5 1310
 
3.3%
7 1209
 
3.0%
Other values (3) 3390
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33932
85.0%
Uppercase Letter 5988
 
15.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13037
38.4%
1 7964
23.5%
2 3826
 
11.3%
9 1874
 
5.5%
3 1322
 
3.9%
5 1310
 
3.9%
7 1209
 
3.6%
4 1180
 
3.5%
8 1107
 
3.3%
6 1103
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
U 1996
33.3%
R 1996
33.3%
Z 1996
33.3%

Most occurring scripts

ValueCountFrequency (%)
Common 33932
85.0%
Latin 5988
 
15.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13037
38.4%
1 7964
23.5%
2 3826
 
11.3%
9 1874
 
5.5%
3 1322
 
3.9%
5 1310
 
3.9%
7 1209
 
3.6%
4 1180
 
3.5%
8 1107
 
3.3%
6 1103
 
3.3%
Latin
ValueCountFrequency (%)
U 1996
33.3%
R 1996
33.3%
Z 1996
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13037
32.7%
1 7964
19.9%
2 3826
 
9.6%
U 1996
 
5.0%
R 1996
 
5.0%
Z 1996
 
5.0%
9 1874
 
4.7%
3 1322
 
3.3%
5 1310
 
3.3%
7 1209
 
3.0%
Other values (3) 3390
 
8.5%

결정고시관리코드
Text

Distinct1106
Distinct (%)55.4%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-05-10T22:54:36.081480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length20
Mean length18.02004
Min length1

Characters and Unicode

Total characters35968
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

Unique894 ?
Unique (%)44.8%

Sample

1st row11440NTC202011270003
2nd row11380NTC202103030003
3rd row11000NTC199705166956
4th row
5th row11000NTC201402137088
ValueCountFrequency (%)
11000ntc199705166956 74
 
4.1%
11000ntc202001280023 54
 
3.0%
11000ntc199307313956 42
 
2.3%
11000ntc199404074430 26
 
1.5%
11000ntc199212213460 16
 
0.9%
11230ntc202008040003 14
 
0.8%
11000ntc202108170001 14
 
0.8%
11000ntc199303243684 13
 
0.7%
11710ntc202010230007 13
 
0.7%
11380ntc202103030003 12
 
0.7%
Other values (1095) 1510
84.5%
2024-05-10T22:54:37.568359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10867
30.2%
1 6867
19.1%
2 3614
 
10.0%
9 2015
 
5.6%
N 1788
 
5.0%
T 1788
 
5.0%
C 1788
 
5.0%
3 1436
 
4.0%
6 1236
 
3.4%
7 1160
 
3.2%
Other values (4) 3409
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30396
84.5%
Uppercase Letter 5364
 
14.9%
Space Separator 208
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10867
35.8%
1 6867
22.6%
2 3614
 
11.9%
9 2015
 
6.6%
3 1436
 
4.7%
6 1236
 
4.1%
7 1160
 
3.8%
4 1094
 
3.6%
5 1056
 
3.5%
8 1051
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
N 1788
33.3%
T 1788
33.3%
C 1788
33.3%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 30604
85.1%
Latin 5364
 
14.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10867
35.5%
1 6867
22.4%
2 3614
 
11.8%
9 2015
 
6.6%
3 1436
 
4.7%
6 1236
 
4.0%
7 1160
 
3.8%
4 1094
 
3.6%
5 1056
 
3.5%
8 1051
 
3.4%
Latin
ValueCountFrequency (%)
N 1788
33.3%
T 1788
33.3%
C 1788
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35968
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10867
30.2%
1 6867
19.1%
2 3614
 
10.0%
9 2015
 
5.6%
N 1788
 
5.0%
T 1788
 
5.0%
C 1788
 
5.0%
3 1436
 
4.0%
6 1236
 
3.4%
7 1160
 
3.2%
Other values (4) 3409
 
9.5%

라벨명
Text

Distinct364
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-05-10T22:54:38.018230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length5.5155311
Min length2

Characters and Unicode

Total characters11009
Distinct characters230
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

Unique317 ?
Unique (%)15.9%

Sample

1st row지하철역사
2nd row주차장시설 기타
3rd row6호선 환기구
4th row철도
5th row철도
ValueCountFrequency (%)
주차장 565
22.7%
환기구 262
 
10.5%
노외주차장 225
 
9.0%
철도 178
 
7.2%
기타주차장시설 142
 
5.7%
5호선 88
 
3.5%
7호선 75
 
3.0%
6호선 75
 
3.0%
기타 46
 
1.8%
주차장시설 44
 
1.8%
Other values (362) 788
31.7%
2024-05-10T22:54:38.956800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 1265
 
11.5%
차 1119
 
10.2%
주 998
 
9.1%
492
 
4.5%
기 484
 
4.4%
도 480
 
4.4%
선 480
 
4.4%
철 419
 
3.8%
호 404
 
3.7%
구 301
 
2.7%
Other values (220) 4567
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9672
87.9%
Decimal Number 518
 
4.7%
Space Separator 492
 
4.5%
Open Punctuation 156
 
1.4%
Close Punctuation 152
 
1.4%
Math Symbol 12
 
0.1%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 1265
 
13.1%
차 1119
 
11.6%
주 998
 
10.3%
기 484
 
5.0%
도 480
 
5.0%
선 480
 
5.0%
철 419
 
4.3%
호 404
 
4.2%
구 301
 
3.1%
시 300
 
3.1%
Other values (198) 3422
35.4%
Decimal Number
ValueCountFrequency (%)
5 108
20.8%
7 93
18.0%
6 85
16.4%
1 49
9.5%
8 38
 
7.3%
3 37
 
7.1%
2 32
 
6.2%
9 30
 
5.8%
4 26
 
5.0%
0 20
 
3.9%
Math Symbol
ValueCountFrequency (%)
= 3
25.0%
~ 3
25.0%
< 3
25.0%
> 3
25.0%
Other Punctuation
ValueCountFrequency (%)
: 2
50.0%
, 1
25.0%
. 1
25.0%
Space Separator
ValueCountFrequency (%)
492
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 152
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
H 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9672
87.9%
Common 1336
 
12.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 1265
 
13.1%
차 1119
 
11.6%
주 998
 
10.3%
기 484
 
5.0%
도 480
 
5.0%
선 480
 
5.0%
철 419
 
4.3%
호 404
 
4.2%
구 301
 
3.1%
시 300
 
3.1%
Other values (198) 3422
35.4%
Common
ValueCountFrequency (%)
492
36.8%
( 156
 
11.7%
) 152
 
11.4%
5 108
 
8.1%
7 93
 
7.0%
6 85
 
6.4%
1 49
 
3.7%
8 38
 
2.8%
3 37
 
2.8%
2 32
 
2.4%
Other values (11) 94
 
7.0%
Latin
ValueCountFrequency (%)
H 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9672
87.9%
ASCII 1337
 
12.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 1265
 
13.1%
차 1119
 
11.6%
주 998
 
10.3%
기 484
 
5.0%
도 480
 
5.0%
선 480
 
5.0%
철 419
 
4.3%
호 404
 
4.2%
구 301
 
3.1%
시 300
 
3.1%
Other values (198) 3422
35.4%
ASCII
ValueCountFrequency (%)
492
36.8%
( 156
 
11.7%
) 152
 
11.4%
5 108
 
8.1%
7 93
 
7.0%
6 85
 
6.4%
1 49
 
3.7%
8 38
 
2.8%
3 37
 
2.8%
2 32
 
2.4%
Other values (12) 95
 
7.1%

시군구코드
Real number (ℝ)

SKEWED 

Distinct27
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11105.748
Minimum11000
Maximum99999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-05-10T22:54:39.471105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11000
5-th percentile11000
Q111000
median11000
Q311000
95-th percentile11545
Maximum99999
Range88999
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1997.6365
Coefficient of variation (CV)0.1798741
Kurtosis1968.3859
Mean11105.748
Median Absolute Deviation (MAD)0
Skewness44.214071
Sum22167074
Variance3990551.6
MonotonicityNot monotonic
2024-05-10T22:54:39.963217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11000 1709
85.6%
11710 30
 
1.5%
11230 28
 
1.4%
11290 25
 
1.3%
11380 24
 
1.2%
11260 18
 
0.9%
11560 16
 
0.8%
11530 14
 
0.7%
11680 13
 
0.7%
11590 12
 
0.6%
Other values (17) 107
 
5.4%
ValueCountFrequency (%)
11000 1709
85.6%
11110 9
 
0.5%
11140 9
 
0.5%
11170 7
 
0.4%
11200 8
 
0.4%
11215 5
 
0.3%
11230 28
 
1.4%
11260 18
 
0.9%
11290 25
 
1.3%
11305 2
 
0.1%
ValueCountFrequency (%)
99999 1
 
0.1%
11740 7
 
0.4%
11710 30
1.5%
11680 13
0.7%
11650 11
 
0.6%
11620 7
 
0.4%
11590 12
 
0.6%
11560 16
0.8%
11545 4
 
0.2%
11530 14
0.7%

도면번호
Text

Distinct91
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
2024-05-10T22:54:40.515303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0886774
Min length1

Characters and Unicode

Total characters2173
Distinct characters57
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)2.4%

Sample

1st row
2nd row4
3rd row
4th row
5th row
ValueCountFrequency (%)
1 96
19.7%
2 50
 
10.3%
3 48
 
9.9%
① 45
 
9.2%
4 30
 
6.2%
② 19
 
3.9%
6 17
 
3.5%
7 11
 
2.3%
가 10
 
2.1%
5 9
 
1.8%
Other values (79) 152
31.2%
2024-05-10T22:54:41.552524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1509
69.4%
1 167
 
7.7%
2 81
 
3.7%
3 63
 
2.9%
① 45
 
2.1%
4 40
 
1.8%
0 28
 
1.3%
6 25
 
1.2%
② 20
 
0.9%
- 18
 
0.8%
Other values (47) 177
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 1509
69.4%
Decimal Number 464
 
21.4%
Other Number 105
 
4.8%
Other Letter 66
 
3.0%
Dash Punctuation 18
 
0.8%
Uppercase Letter 5
 
0.2%
Other Punctuation 2
 
0.1%
Other Symbol 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 11
16.7%
공 10
15.2%
나 6
 
9.1%
원 4
 
6.1%
주 4
 
6.1%
근 3
 
4.5%
린 3
 
4.5%
라 3
 
4.5%
장 2
 
3.0%
바 2
 
3.0%
Other values (14) 18
27.3%
Other Number
ValueCountFrequency (%)
① 45
42.9%
② 20
19.0%
④ 9
 
8.6%
③ 8
 
7.6%
⑤ 6
 
5.7%
⑥ 5
 
4.8%
⑧ 3
 
2.9%
⑦ 3
 
2.9%
⑩ 2
 
1.9%
⑬ 2
 
1.9%
Other values (2) 2
 
1.9%
Decimal Number
ValueCountFrequency (%)
1 167
36.0%
2 81
17.5%
3 63
 
13.6%
4 40
 
8.6%
0 28
 
6.0%
6 25
 
5.4%
8 16
 
3.4%
9 16
 
3.4%
5 15
 
3.2%
7 13
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
C 1
 
20.0%
J 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
, 1
50.0%
Space Separator
ValueCountFrequency (%)
1509
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Other Symbol
ValueCountFrequency (%)
㉮ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
a 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2100
96.6%
Hangul 67
 
3.1%
Latin 6
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1509
71.9%
1 167
 
8.0%
2 81
 
3.9%
3 63
 
3.0%
① 45
 
2.1%
4 40
 
1.9%
0 28
 
1.3%
6 25
 
1.2%
② 20
 
1.0%
- 18
 
0.9%
Other values (18) 104
 
5.0%
Hangul
ValueCountFrequency (%)
가 11
16.4%
공 10
14.9%
나 6
 
9.0%
원 4
 
6.0%
주 4
 
6.0%
근 3
 
4.5%
린 3
 
4.5%
라 3
 
4.5%
장 2
 
3.0%
바 2
 
3.0%
Other values (15) 19
28.4%
Latin
ValueCountFrequency (%)
A 3
50.0%
C 1
 
16.7%
a 1
 
16.7%
J 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2001
92.1%
Enclosed Alphanum 105
 
4.8%
Hangul 66
 
3.0%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1509
75.4%
1 167
 
8.3%
2 81
 
4.0%
3 63
 
3.1%
4 40
 
2.0%
0 28
 
1.4%
6 25
 
1.2%
- 18
 
0.9%
8 16
 
0.8%
9 16
 
0.8%
Other values (10) 38
 
1.9%
Enclosed Alphanum
ValueCountFrequency (%)
① 45
42.9%
② 20
19.0%
④ 9
 
8.6%
③ 8
 
7.6%
⑤ 6
 
5.7%
⑥ 5
 
4.8%
⑧ 3
 
2.9%
⑦ 3
 
2.9%
⑩ 2
 
1.9%
⑬ 2
 
1.9%
Other values (2) 2
 
1.9%
Hangul
ValueCountFrequency (%)
가 11
16.7%
공 10
15.2%
나 6
 
9.1%
원 4
 
6.1%
주 4
 
6.1%
근 3
 
4.5%
린 3
 
4.5%
라 3
 
4.5%
장 2
 
3.0%
바 2
 
3.0%
Other values (14) 18
27.3%
None
ValueCountFrequency (%)
㉮ 1
100.0%

집행상태코드 심볼
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
EMA0009
1991 
EMA0001
 
3
EMA0002
 
1
EMA0003
 
1

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
EMA0009 1991
99.7%
EMA0001 3
 
0.2%
EMA0002 1
 
0.1%
EMA0003 1
 
0.1%

Length

2024-05-10T22:54:42.132233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T22:54:42.505473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ema0009 1991
99.7%
ema0001 3
 
0.2%
ema0002 1
 
0.1%
ema0003 1
 
0.1%

현황도형 생성일시
Date

Distinct225
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size15.7 KiB
Minimum2019-05-17 00:00:00
Maximum2024-04-23 00:00:00
2024-05-10T22:54:42.854260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:43.340432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

면적(도형)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct1850
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12389.351
Minimum0.9729778
Maximum7509833.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-05-10T22:54:43.804804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9729778
5-th percentile109.85075
Q1518.76881
median1681.8247
Q35336.767
95-th percentile23427.401
Maximum7509833.7
Range7509832.7
Interquartile range (IQR)4817.9981

Descriptive statistics

Standard deviation171300.39
Coefficient of variation (CV)13.826421
Kurtosis1842.0797
Mean12389.351
Median Absolute Deviation (MAD)1434.7067
Skewness42.133671
Sum24729145
Variance2.9343823 × 1010
MonotonicityNot monotonic
2024-05-10T22:54:44.236037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6832.7693435 14
 
0.7%
56228.10792625 13
 
0.7%
5336.76695356 12
 
0.6%
1498.886367 8
 
0.4%
2064.23594762 7
 
0.4%
2835.25761196 6
 
0.3%
1342.77381792 6
 
0.3%
7584.44762816 6
 
0.3%
2344.009027 6
 
0.3%
2636.16023146 6
 
0.3%
Other values (1840) 1912
95.8%
ValueCountFrequency (%)
0.9729778 1
0.1%
6.26496294 1
0.1%
8.77876355 1
0.1%
8.85600196 1
0.1%
9.94785914 1
0.1%
10.60023663 1
0.1%
10.99799517 1
0.1%
11.82963417 1
0.1%
15.19442965 1
0.1%
17.86789919 1
0.1%
ValueCountFrequency (%)
7509833.72118 1
0.1%
516955.69394 1
0.1%
505020.470518 1
0.1%
416881.03956545 1
0.1%
386567.43597855 1
0.1%
381017.308584 1
0.1%
318709.69667037 1
0.1%
311685.042331 1
0.1%
307364.22208393 1
0.1%
258577.883246 1
0.1%

길이(도형)
Real number (ℝ)

HIGH CORRELATION 

Distinct1850
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean740.83261
Minimum4.2145218
Maximum73800.867
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.7 KiB
2024-05-10T22:54:44.726625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.2145218
5-th percentile50.236245
Q1104.17304
median192.08438
Q3493.0484
95-th percentile1465.6429
Maximum73800.867
Range73796.652
Interquartile range (IQR)388.87536

Descriptive statistics

Standard deviation3733.5234
Coefficient of variation (CV)5.0396316
Kurtosis217.25077
Mean740.83261
Median Absolute Deviation (MAD)115.63013
Skewness13.665411
Sum1478701.9
Variance13939197
MonotonicityNot monotonic
2024-05-10T22:54:45.165358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
684.17805775 14
 
0.7%
1040.07011779 13
 
0.7%
320.15668616 12
 
0.6%
163.39062738 8
 
0.4%
183.5950662 7
 
0.4%
253.26843294 6
 
0.3%
144.8311374 6
 
0.3%
374.15010141 6
 
0.3%
206.95611226 6
 
0.3%
210.11561495 6
 
0.3%
Other values (1840) 1912
95.8%
ValueCountFrequency (%)
4.21452183 1
0.1%
13.2681664 1
0.1%
16.67796391 1
0.1%
17.24627349 1
0.1%
18.12367624 1
0.1%
19.24121487 1
0.1%
21.59435891 1
0.1%
22.22670536 1
0.1%
22.28566465 1
0.1%
22.39155727 1
0.1%
ValueCountFrequency (%)
73800.86670217 1
0.1%
68820.7450681 1
0.1%
66370.8415577 1
0.1%
50738.99436801 1
0.1%
43494.3262397 1
0.1%
41603.85847772 1
0.1%
35952.9442239 1
0.1%
33666.18024303 1
0.1%
24759.254815 1
0.1%
23993.60751481 1
0.1%

Interactions

2024-05-10T22:54:26.753627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:22.587825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:23.973017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:25.343329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:27.156641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:22.991148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:24.240294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:25.705010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:27.421087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:23.272888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:24.513115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:25.985623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:27.740933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:23.568034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:24.896170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T22:54:26.318526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T22:54:45.481480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id도형 대분류코드도형 중분류코드도형 속성코드시군구코드도면번호집행상태코드 심볼면적(도형)길이(도형)
객체id1.0000.1420.3420.2990.0000.0000.0190.0000.000
도형 대분류코드0.1421.0000.9670.9770.0000.0000.8691.0000.398
도형 중분류코드0.3420.9671.0001.0000.2700.4200.0001.0000.439
도형 속성코드0.2990.9771.0001.0000.2700.7250.0001.0000.440
시군구코드0.0000.0000.2700.2701.0000.0000.000NaN0.000
도면번호0.0000.0000.4200.7250.0001.0000.0000.0000.099
집행상태코드 심볼0.0190.8690.0000.0000.0000.0001.0000.0000.345
면적(도형)0.0001.0001.0001.000NaN0.0000.0001.0000.348
길이(도형)0.0000.3980.4390.4400.0000.0990.3450.3481.000
2024-05-10T22:54:45.875808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
집행상태코드 심볼도형 속성코드도형 대분류코드도형 중분류코드
집행상태코드 심볼1.0000.0000.5730.000
도형 속성코드0.0001.0000.8510.999
도형 대분류코드0.5730.8511.0000.796
도형 중분류코드0.0000.9990.7961.000
2024-05-10T22:54:46.171558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객체id시군구코드면적(도형)길이(도형)도형 대분류코드도형 중분류코드도형 속성코드집행상태코드 심볼
객체id1.0000.0710.0280.0260.0600.1140.1140.011
시군구코드0.0711.0000.1690.1780.0000.0560.0460.000
면적(도형)0.0280.1691.0000.9630.9970.9950.9950.000
길이(도형)0.0260.1780.9631.0000.1810.1890.1870.227
도형 대분류코드0.0600.0000.9970.1811.0000.7960.8510.573
도형 중분류코드0.1140.0560.9950.1890.7961.0000.9990.000
도형 속성코드0.1140.0460.9950.1870.8510.9991.0000.000
집행상태코드 심볼0.0110.0000.0000.2270.5730.0000.0001.000

Missing values

2024-05-10T22:54:28.205320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T22:54:29.269651image/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 코드결정고시관리코드라벨명시군구코드도면번호집행상태코드 심볼현황도형 생성일시면적(도형)길이(도형)
07878711440UQ152PS202012010001UQS500UQSA52UQSA5211440URZ20201127000111440NTC202011270003지하철역사11440EMA00092020-12-01 00:00:00.04275.64526551.082113
17878811380UQ152PS202103160001UQS200UQS290UQS29011380URZ20210303000811380NTC202103030003주차장시설 기타113804EMA00092021-03-16 00:00:00.05336.766954320.156686
27878911000UQ152PS201912151461UQS500UQSA54UQSA5411000URZ19970516416111000NTC1997051669566호선 환기구11000EMA00092019-12-15 00:00:00.0162.65933468.882055
37879011000UQ152PS201912151462UQS500UQS549UQS54911000URZ000000001521철도11000EMA00092019-12-15 00:00:00.023.66514222.226705
47879111000UQ152PS201912151704UQS500UQSA52UQSA5211000URZ20140213423111000NTC201402137088철도11000EMA00092019-12-15 00:00:00.06435.049082838.212716
57879211000UQ152PS201912151430UQS500UQSA54UQSA5411000URZ19930324682911000NTC1993032436845호선 환기구11000EMA00092019-12-15 00:00:00.0327.377028110.014475
67879311000UQ152PS201912151493UQS500UQSA54UQSA5411000URZ19970516441211000NTC1997051669566호선 환기구11000EMA00092019-12-15 00:00:00.0372.882331108.628662
77879411000UQ152PS201912151431UQS500UQS549UQS54911000URZ000000001521철도11000EMA00092019-12-15 00:00:00.0540.974674191.974067
87879511000UQ152PS201912151432UQS500UQS549UQS54911000URZ000000001521철도11000EMA00092019-12-15 00:00:00.03151.647067246.531455
97879611000UQ152PS201912151610UQS500UQSA52UQSA5211000URZ20160519954911000NTC201605197782철도11000EMA00092019-12-15 00:00:00.05633.93055661.562268
객체id현황도형 관리번호도형 대분류코드도형 중분류코드도형 소분류코드도형 속성코드도형 조서관리 코드결정고시관리코드라벨명시군구코드도면번호집행상태코드 심볼현황도형 생성일시면적(도형)길이(도형)
19868101311000UQ152PS201912151556UQS500UQSA54UQSA5411000URZ000000001521환기구11000EMA00092019-12-15 00:00:00.0227.04602960.099445
19878101411000UQ152PS201912151557UQS500UQSA54UQSA5411000URZ19910315621011000NTC199103152233환기구11000EMA00092019-12-15 00:00:00.0131.30661458.164159
19888101511000UQ152PS201912151558UQS500UQSA54UQSA5411000URZ000000001521환기구11000EMA00092019-12-15 00:00:00.0806.770895242.888269
19898101611000UQ152PS201912151559UQS500UQSA54UQSA5411000URZ000000001521환기구11000EMA00092019-12-15 00:00:00.0527.946228625.386367
19908101711380UQ152PS202103160009UQS200UQS290UQS29011380URZ20210303000811380NTC202103030003주차장시설 기타113804EMA00092021-03-16 00:00:00.05336.766954320.156686
19918101811230UQ152PS202104080017UQS500UQS510UQS51011230URZ20200804005811230NTC202008040003일반철도112303EMA00092021-04-08 00:00:00.06832.769344684.178058
19928101911380UQ152PS202103160010UQS200UQS290UQS29011380URZ20210303000811380NTC202103030003주차장시설 기타113804EMA00092021-03-16 00:00:00.05336.766954320.156686
19938102011260UQ152PS202101070001UQS500UQSA52UQSA5211260URZ20201230000311260NTC202012300006지하철역사112601EMA00092021-01-07 00:00:00.05282.708754703.500552
19948102111000UQ152PS202012080019UQS500UQSA52UQSA5211000URZ20201116000711000NTC202011160004지하철역사11000104EMA00092020-12-08 00:00:00.03398.321422415.18154
19958102211680UQ152PS202201190001UQS500UQSA52UQSA5211680URZ20220119000111680NTC202201190001도시철도(3호선 대치역)11680EMA00092022-01-19 00:00:00.08218.2478621213.314925