Overview

Dataset statistics

Number of variables8
Number of observations402
Missing cells239
Missing cells (%)7.4%
Duplicate rows15
Duplicate rows (%)3.7%
Total size in memory25.3 KiB
Average record size in memory64.3 B

Variable types

Text7
Boolean1

Dataset

Description경기도 양주시 도시계획정보시스템(UPIS) 지구단위계획 결정조서 현황으로 도면번호, 위치명, 지역명, 면적(기정), 면적(변경), 면적(변경후) 등의 항목을 제공합니다.
URLhttps://www.data.go.kr/data/15115922/fileData.do

Alerts

Dataset has 15 (3.7%) duplicate rowsDuplicates
도면번호 has 57 (14.2%) missing valuesMissing
비고 has 181 (45.0%) missing valuesMissing

Reproduction

Analysis started2023-10-09 18:53:04.388214
Analysis finished2023-10-09 18:53:05.905930
Duration1.52 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

도면번호
Text

MISSING 

Distinct77
Distinct (%)22.3%
Missing57
Missing (%)14.2%
Memory size3.3 KiB
2023-10-10T03:53:06.119844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.7710145
Min length1

Characters and Unicode

Total characters611
Distinct characters13
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)4.1%

Sample

1st row1
2nd row27
3rd row28
4th row1
5th row15
ValueCountFrequency (%)
1 66
 
19.1%
43 12
 
3.5%
45 12
 
3.5%
38 10
 
2.9%
50 9
 
2.6%
48 9
 
2.6%
36 9
 
2.6%
47 8
 
2.3%
39 8
 
2.3%
56 7
 
2.0%
Other values (67) 195
56.5%
2023-10-10T03:53:06.878004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 122
20.0%
4 89
14.6%
5 80
13.1%
3 75
12.3%
6 50
8.2%
7 45
 
7.4%
2 42
 
6.9%
8 39
 
6.4%
9 39
 
6.4%
0 23
 
3.8%
Other values (3) 7
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 604
98.9%
Other Letter 7
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 122
20.2%
4 89
14.7%
5 80
13.2%
3 75
12.4%
6 50
8.3%
7 45
 
7.5%
2 42
 
7.0%
8 39
 
6.5%
9 39
 
6.5%
0 23
 
3.8%
Other Letter
ValueCountFrequency (%)
용 3
42.9%
암 3
42.9%
옥 1
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Common 604
98.9%
Hangul 7
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 122
20.2%
4 89
14.7%
5 80
13.2%
3 75
12.4%
6 50
8.3%
7 45
 
7.5%
2 42
 
7.0%
8 39
 
6.5%
9 39
 
6.5%
0 23
 
3.8%
Hangul
ValueCountFrequency (%)
용 3
42.9%
암 3
42.9%
옥 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 604
98.9%
Hangul 7
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 122
20.2%
4 89
14.7%
5 80
13.2%
3 75
12.4%
6 50
8.3%
7 45
 
7.5%
2 42
 
7.0%
8 39
 
6.5%
9 39
 
6.5%
0 23
 
3.8%
Hangul
ValueCountFrequency (%)
용 3
42.9%
암 3
42.9%
옥 1
 
14.3%

위치명
Text

Distinct201
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-10-10T03:53:07.344295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length13.206468
Min length3

Characters and Unicode

Total characters5309
Distinct characters92
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

Unique126 ?
Unique (%)31.3%

Sample

1st row백석읍 홍죽리 산1-12번지 외 2필지
2nd row덕계동 11번지 외 16필지
3rd row광적면 비암리 산23-1번지 일원
4th row덕계동 467
5th row덕정동 185-1번지 일원
ValueCountFrequency (%)
일원 338
25.0%
삼숭동 48
 
3.6%
은현면 47
 
3.5%
백석읍 44
 
3.3%
장흥면 44
 
3.3%
남면 36
 
2.7%
고암동 31
 
2.3%
덕계동 29
 
2.1%
덕정동 28
 
2.1%
회정동 26
 
1.9%
Other values (209) 679
50.3%
2023-10-10T03:53:08.115351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
948
17.9%
일 359
 
6.8%
원 344
 
6.5%
동 317
 
6.0%
리 217
 
4.1%
1 212
 
4.0%
- 156
 
2.9%
지 153
 
2.9%
면 151
 
2.8%
, 133
 
2.5%
Other values (82) 2319
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3210
60.5%
Space Separator 948
 
17.9%
Decimal Number 862
 
16.2%
Dash Punctuation 156
 
2.9%
Other Punctuation 133
 
2.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 359
 
11.2%
원 344
 
10.7%
동 317
 
9.9%
리 217
 
6.8%
지 153
 
4.8%
면 151
 
4.7%
번 129
 
4.0%
암 97
 
3.0%
정 91
 
2.8%
산 69
 
2.1%
Other values (69) 1283
40.0%
Decimal Number
ValueCountFrequency (%)
1 212
24.6%
2 124
14.4%
6 96
11.1%
4 92
10.7%
3 64
 
7.4%
5 64
 
7.4%
0 62
 
7.2%
8 59
 
6.8%
7 50
 
5.8%
9 39
 
4.5%
Space Separator
ValueCountFrequency (%)
948
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 156
100.0%
Other Punctuation
ValueCountFrequency (%)
, 133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3210
60.5%
Common 2099
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 359
 
11.2%
원 344
 
10.7%
동 317
 
9.9%
리 217
 
6.8%
지 153
 
4.8%
면 151
 
4.7%
번 129
 
4.0%
암 97
 
3.0%
정 91
 
2.8%
산 69
 
2.1%
Other values (69) 1283
40.0%
Common
ValueCountFrequency (%)
948
45.2%
1 212
 
10.1%
- 156
 
7.4%
, 133
 
6.3%
2 124
 
5.9%
6 96
 
4.6%
4 92
 
4.4%
3 64
 
3.0%
5 64
 
3.0%
0 62
 
3.0%
Other values (3) 148
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3210
60.5%
ASCII 2099
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
948
45.2%
1 212
 
10.1%
- 156
 
7.4%
, 133
 
6.3%
2 124
 
5.9%
6 96
 
4.6%
4 92
 
4.4%
3 64
 
3.0%
5 64
 
3.0%
0 62
 
3.0%
Other values (3) 148
 
7.1%
Hangul
ValueCountFrequency (%)
일 359
 
11.2%
원 344
 
10.7%
동 317
 
9.9%
리 217
 
6.8%
지 153
 
4.8%
면 151
 
4.7%
번 129
 
4.0%
암 97
 
3.0%
정 91
 
2.8%
산 69
 
2.1%
Other values (69) 1283
40.0%

지역명
Text

Distinct202
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-10-10T03:53:08.555393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length15.402985
Min length4

Characters and Unicode

Total characters6192
Distinct characters176
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique129 ?
Unique (%)32.1%

Sample

1st row백석읍 홍죽리 제2종지구단위계획구역
2nd row덕계동 제2종지구단위계획구역
3rd row광적면 비암리 제2종지구단위계획구역
4th row국군덕정병원부지 제2종지구단위계획구역
5th row덕정동 제1종지구단위계획구역
ValueCountFrequency (%)
지구단위계획구역 206
24.8%
제2종지구단위계획구역 85
 
10.2%
제1종지구단위계획구역 66
 
7.9%
주거형 16
 
1.9%
회천 12
 
1.4%
부곡2지구 12
 
1.4%
양주신도시(옥정 12
 
1.4%
삼숭지구 11
 
1.3%
용암2지구 11
 
1.3%
gs자이apt 11
 
1.3%
Other values (174) 390
46.9%
2023-10-10T03:53:09.279336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 1042
16.8%
지 713
11.5%
430
 
6.9%
단 417
 
6.7%
계 397
 
6.4%
역 396
 
6.4%
위 385
 
6.2%
획 385
 
6.2%
제 155
 
2.5%
종 154
 
2.5%
Other values (166) 1718
27.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5361
86.6%
Space Separator 430
 
6.9%
Decimal Number 267
 
4.3%
Uppercase Letter 65
 
1.0%
Close Punctuation 27
 
0.4%
Open Punctuation 27
 
0.4%
Other Punctuation 15
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1042
19.4%
지 713
13.3%
단 417
 
7.8%
계 397
 
7.4%
역 396
 
7.4%
위 385
 
7.2%
획 385
 
7.2%
제 155
 
2.9%
종 154
 
2.9%
정 67
 
1.2%
Other values (146) 1250
23.3%
Decimal Number
ValueCountFrequency (%)
2 136
50.9%
1 104
39.0%
3 14
 
5.2%
5 6
 
2.2%
4 3
 
1.1%
6 2
 
0.7%
8 1
 
0.4%
7 1
 
0.4%
Uppercase Letter
ValueCountFrequency (%)
S 14
21.5%
T 11
16.9%
P 11
16.9%
A 11
16.9%
G 11
16.9%
C 4
 
6.2%
K 3
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 13
86.7%
. 2
 
13.3%
Space Separator
ValueCountFrequency (%)
430
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5361
86.6%
Common 766
 
12.4%
Latin 65
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1042
19.4%
지 713
13.3%
단 417
 
7.8%
계 397
 
7.4%
역 396
 
7.4%
위 385
 
7.2%
획 385
 
7.2%
제 155
 
2.9%
종 154
 
2.9%
정 67
 
1.2%
Other values (146) 1250
23.3%
Common
ValueCountFrequency (%)
430
56.1%
2 136
 
17.8%
1 104
 
13.6%
) 27
 
3.5%
( 27
 
3.5%
3 14
 
1.8%
, 13
 
1.7%
5 6
 
0.8%
4 3
 
0.4%
6 2
 
0.3%
Other values (3) 4
 
0.5%
Latin
ValueCountFrequency (%)
S 14
21.5%
T 11
16.9%
P 11
16.9%
A 11
16.9%
G 11
16.9%
C 4
 
6.2%
K 3
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5361
86.6%
ASCII 831
 
13.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 1042
19.4%
지 713
13.3%
단 417
 
7.8%
계 397
 
7.4%
역 396
 
7.4%
위 385
 
7.2%
획 385
 
7.2%
제 155
 
2.9%
종 154
 
2.9%
정 67
 
1.2%
Other values (146) 1250
23.3%
ASCII
ValueCountFrequency (%)
430
51.7%
2 136
 
16.4%
1 104
 
12.5%
) 27
 
3.2%
( 27
 
3.2%
S 14
 
1.7%
3 14
 
1.7%
, 13
 
1.6%
T 11
 
1.3%
P 11
 
1.3%
Other values (10) 44
 
5.3%

면적(기정)
Text

Distinct218
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-10-10T03:53:09.861479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.3830846
Min length1

Characters and Unicode

Total characters2164
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique161 ?
Unique (%)40.0%

Sample

1st row30830.5
2nd row31060.4
3rd row1401965
4th row43082
5th row19325
ValueCountFrequency (%)
0 52
 
12.2%
미집계 25
 
5.9%
데이터 25
 
5.9%
998836 9
 
2.1%
800646 6
 
1.4%
507586 6
 
1.4%
572484 6
 
1.4%
3213212 5
 
1.2%
108155 5
 
1.2%
646347 5
 
1.2%
Other values (209) 283
66.3%
2023-10-10T03:53:10.773255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 245
11.3%
1 230
10.6%
4 224
10.4%
6 192
8.9%
2 189
8.7%
8 188
8.7%
3 181
8.4%
7 181
8.4%
5 176
8.1%
9 161
7.4%
Other values (8) 197
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1967
90.9%
Other Letter 150
 
6.9%
Space Separator 25
 
1.2%
Other Punctuation 22
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 245
12.5%
1 230
11.7%
4 224
11.4%
6 192
9.8%
2 189
9.6%
8 188
9.6%
3 181
9.2%
7 181
9.2%
5 176
8.9%
9 161
8.2%
Other Letter
ValueCountFrequency (%)
집 25
16.7%
계 25
16.7%
데 25
16.7%
미 25
16.7%
터 25
16.7%
이 25
16.7%
Space Separator
ValueCountFrequency (%)
25
100.0%
Other Punctuation
ValueCountFrequency (%)
. 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2014
93.1%
Hangul 150
 
6.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 245
12.2%
1 230
11.4%
4 224
11.1%
6 192
9.5%
2 189
9.4%
8 188
9.3%
3 181
9.0%
7 181
9.0%
5 176
8.7%
9 161
8.0%
Other values (2) 47
 
2.3%
Hangul
ValueCountFrequency (%)
집 25
16.7%
계 25
16.7%
데 25
16.7%
미 25
16.7%
터 25
16.7%
이 25
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2014
93.1%
Hangul 150
 
6.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 245
12.2%
1 230
11.4%
4 224
11.1%
6 192
9.5%
2 189
9.4%
8 188
9.3%
3 181
9.0%
7 181
9.0%
5 176
8.7%
9 161
8.0%
Other values (2) 47
 
2.3%
Hangul
ValueCountFrequency (%)
집 25
16.7%
계 25
16.7%
데 25
16.7%
미 25
16.7%
터 25
16.7%
이 25
16.7%

면적(변경)
Text

Distinct233
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-10-10T03:53:11.545911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.6169154
Min length1

Characters and Unicode

Total characters2258
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique214 ?
Unique (%)53.2%

Sample

1st row86.5
2nd row28.9
3rd row데이터 미집계
4th row1418
5th row628
ValueCountFrequency (%)
데이터 152
27.4%
미집계 152
27.4%
33495 2
 
0.4%
30.2 2
 
0.4%
79 2
 
0.4%
65244 2
 
0.4%
169460 2
 
0.4%
78244 2
 
0.4%
39817 2
 
0.4%
146030 2
 
0.4%
Other values (224) 234
42.2%
2023-10-10T03:53:12.657576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 153
 
6.8%
데 152
 
6.7%
터 152
 
6.7%
152
 
6.7%
미 152
 
6.7%
집 152
 
6.7%
계 152
 
6.7%
이 152
 
6.7%
1 144
 
6.4%
0 138
 
6.1%
Other values (8) 759
33.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1166
51.6%
Other Letter 912
40.4%
Space Separator 152
 
6.7%
Other Punctuation 28
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 153
13.1%
1 144
12.3%
0 138
11.8%
4 126
10.8%
3 109
9.3%
6 104
8.9%
8 101
8.7%
9 99
8.5%
5 99
8.5%
7 93
8.0%
Other Letter
ValueCountFrequency (%)
데 152
16.7%
터 152
16.7%
미 152
16.7%
집 152
16.7%
계 152
16.7%
이 152
16.7%
Space Separator
ValueCountFrequency (%)
152
100.0%
Other Punctuation
ValueCountFrequency (%)
. 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1346
59.6%
Hangul 912
40.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 153
11.4%
152
11.3%
1 144
10.7%
0 138
10.3%
4 126
9.4%
3 109
8.1%
6 104
7.7%
8 101
7.5%
9 99
7.4%
5 99
7.4%
Other values (2) 121
9.0%
Hangul
ValueCountFrequency (%)
데 152
16.7%
터 152
16.7%
미 152
16.7%
집 152
16.7%
계 152
16.7%
이 152
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1346
59.6%
Hangul 912
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 153
11.4%
152
11.3%
1 144
10.7%
0 138
10.3%
4 126
9.4%
3 109
8.1%
6 104
7.7%
8 101
7.5%
9 99
7.4%
5 99
7.4%
Other values (2) 121
9.0%
Hangul
ValueCountFrequency (%)
데 152
16.7%
터 152
16.7%
미 152
16.7%
집 152
16.7%
계 152
16.7%
이 152
16.7%

면적(변경후)
Text

Distinct213
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2023-10-10T03:53:13.300977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.10199
Min length1

Characters and Unicode

Total characters2453
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)38.1%

Sample

1st row30744
2nd row31031.5
3rd row1401965
4th row41664
5th row18697
ValueCountFrequency (%)
데이터 49
 
10.9%
미집계 49
 
10.9%
0 13
 
2.9%
998836 10
 
2.2%
507586 7
 
1.6%
572484 7
 
1.6%
108155 6
 
1.3%
3213212 6
 
1.3%
646347 6
 
1.3%
563831 5
 
1.1%
Other values (204) 293
65.0%
2023-10-10T03:53:14.068848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 263
10.7%
1 254
10.4%
6 218
8.9%
0 201
8.2%
2 200
8.2%
3 194
7.9%
5 193
7.9%
8 190
7.7%
7 187
7.6%
9 168
6.8%
Other values (8) 385
15.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2068
84.3%
Other Letter 294
 
12.0%
Space Separator 49
 
2.0%
Other Punctuation 42
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 263
12.7%
1 254
12.3%
6 218
10.5%
0 201
9.7%
2 200
9.7%
3 194
9.4%
5 193
9.3%
8 190
9.2%
7 187
9.0%
9 168
8.1%
Other Letter
ValueCountFrequency (%)
데 49
16.7%
이 49
16.7%
계 49
16.7%
집 49
16.7%
미 49
16.7%
터 49
16.7%
Space Separator
ValueCountFrequency (%)
49
100.0%
Other Punctuation
ValueCountFrequency (%)
. 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2159
88.0%
Hangul 294
 
12.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 263
12.2%
1 254
11.8%
6 218
10.1%
0 201
9.3%
2 200
9.3%
3 194
9.0%
5 193
8.9%
8 190
8.8%
7 187
8.7%
9 168
7.8%
Other values (2) 91
 
4.2%
Hangul
ValueCountFrequency (%)
데 49
16.7%
이 49
16.7%
계 49
16.7%
집 49
16.7%
미 49
16.7%
터 49
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2159
88.0%
Hangul 294
 
12.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 263
12.2%
1 254
11.8%
6 218
10.1%
0 201
9.3%
2 200
9.3%
3 194
9.0%
5 193
8.9%
8 190
8.8%
7 187
8.7%
9 168
7.8%
Other values (2) 91
 
4.2%
Hangul
ValueCountFrequency (%)
데 49
16.7%
이 49
16.7%
계 49
16.7%
집 49
16.7%
미 49
16.7%
터 49
16.7%

비고
Text

MISSING 

Distinct91
Distinct (%)41.2%
Missing181
Missing (%)45.0%
Memory size3.3 KiB
2023-10-10T03:53:14.360867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length39
Mean length14.393665
Min length3

Characters and Unicode

Total characters3181
Distinct characters108
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)29.4%

Sample

1st row구적오차 및 공부상 면적반영에 따른 오류 정정
2nd row토지이용계획 변경
3rd row토지이용계획 변경
4th row입암지구
5th row경고03-5008(2003.2.14)
ValueCountFrequency (%)
변경 123
22.9%
건축물 52
 
9.7%
가구및획지 47
 
8.8%
기타사항 33
 
6.1%
관한 28
 
5.2%
가구의 19
 
3.5%
규모와 19
 
3.5%
조성에 19
 
3.5%
주거형 12
 
2.2%
10
 
1.9%
Other values (101) 175
32.6%
2023-10-10T03:53:15.298084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
316
 
9.9%
0 175
 
5.5%
2 160
 
5.0%
경 149
 
4.7%
. 131
 
4.1%
변 127
 
4.0%
1 112
 
3.5%
9 93
 
2.9%
지 84
 
2.6%
구 83
 
2.6%
Other values (98) 1751
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1648
51.8%
Decimal Number 778
24.5%
Space Separator 316
 
9.9%
Other Punctuation 202
 
6.4%
Close Punctuation 65
 
2.0%
Open Punctuation 65
 
2.0%
Uppercase Letter 55
 
1.7%
Dash Punctuation 51
 
1.6%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 149
 
9.0%
변 127
 
7.7%
지 84
 
5.1%
구 83
 
5.0%
가 74
 
4.5%
획 74
 
4.5%
건 67
 
4.1%
고 61
 
3.7%
물 60
 
3.6%
축 60
 
3.6%
Other values (74) 809
49.1%
Decimal Number
ValueCountFrequency (%)
0 175
22.5%
2 160
20.6%
1 112
14.4%
9 93
12.0%
5 53
 
6.8%
8 47
 
6.0%
6 44
 
5.7%
3 41
 
5.3%
4 31
 
4.0%
7 22
 
2.8%
Uppercase Letter
ValueCountFrequency (%)
P 11
20.0%
T 11
20.0%
A 11
20.0%
G 11
20.0%
S 11
20.0%
Other Punctuation
ValueCountFrequency (%)
. 131
64.9%
, 61
30.2%
: 5
 
2.5%
/ 5
 
2.5%
Space Separator
ValueCountFrequency (%)
316
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1648
51.8%
Common 1478
46.5%
Latin 55
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 149
 
9.0%
변 127
 
7.7%
지 84
 
5.1%
구 83
 
5.0%
가 74
 
4.5%
획 74
 
4.5%
건 67
 
4.1%
고 61
 
3.7%
물 60
 
3.6%
축 60
 
3.6%
Other values (74) 809
49.1%
Common
ValueCountFrequency (%)
316
21.4%
0 175
11.8%
2 160
10.8%
. 131
8.9%
1 112
 
7.6%
9 93
 
6.3%
) 65
 
4.4%
( 65
 
4.4%
, 61
 
4.1%
5 53
 
3.6%
Other values (9) 247
16.7%
Latin
ValueCountFrequency (%)
P 11
20.0%
T 11
20.0%
A 11
20.0%
G 11
20.0%
S 11
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1648
51.8%
ASCII 1532
48.2%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
316
20.6%
0 175
11.4%
2 160
10.4%
. 131
8.6%
1 112
 
7.3%
9 93
 
6.1%
) 65
 
4.2%
( 65
 
4.2%
, 61
 
4.0%
5 53
 
3.5%
Other values (13) 301
19.6%
Hangul
ValueCountFrequency (%)
경 149
 
9.0%
변 127
 
7.7%
지 84
 
5.1%
구 83
 
5.0%
가 74
 
4.5%
획 74
 
4.5%
건 67
 
4.1%
고 61
 
3.7%
물 60
 
3.6%
축 60
 
3.6%
Other values (74) 809
49.1%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

공간도형 존재여부
Boolean

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size936.0 B
True
319 
False
82 
(Missing)
 
1
ValueCountFrequency (%)
True 319
79.4%
False 82
 
20.4%
(Missing) 1
 
0.2%
2023-10-10T03:53:15.538394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-10-10T03:53:15.667048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
도면번호비고공간도형 존재여부
도면번호1.0000.9700.000
비고0.9701.0000.915
공간도형 존재여부0.0000.9151.000

Missing values

2023-10-10T03:53:05.405019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-10T03:53:05.645695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-10-10T03:53:05.809287image/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

도면번호위치명지역명면적(기정)면적(변경)면적(변경후)비고공간도형 존재여부
0<NA>백석읍 홍죽리 산1-12번지 외 2필지백석읍 홍죽리 제2종지구단위계획구역30830.586.530744<NA>N
1<NA>덕계동 11번지 외 16필지덕계동 제2종지구단위계획구역31060.428.931031.5<NA>Y
2<NA>광적면 비암리 산23-1번지 일원광적면 비암리 제2종지구단위계획구역1401965데이터 미집계1401965<NA>N
3<NA>덕계동 467국군덕정병원부지 제2종지구단위계획구역43082141841664구적오차 및 공부상 면적반영에 따른 오류 정정Y
41덕정동 185-1번지 일원덕정동 제1종지구단위계획구역1932562818697<NA>Y
527장흥면 삼하리 120-3 일원상촌지구 제1종지구단위계획구역62609데이터 미집계62609<NA>Y
628장흥면 삼하리 315 일원하촌지구 제1종지구단위계획구역101354데이터 미집계101354<NA>Y
71덕정동 185-1번지 일원덕정동 제1종지구단위계획구역데이터 미집계1932519325<NA>Y
815장흥면 일영리, 부곡리 일원부곡2지구 제1종지구단위계획구역572297185572482<NA>Y
925덕정동 일원덕정지구 제1종지구단위계획구역1161322609118741<NA>Y
도면번호위치명지역명면적(기정)면적(변경)면적(변경후)비고공간도형 존재여부
39239남면 상수리 일원상수지구 지구단위계획구역646347데이터 미집계646347가구및획지, 건축물 변경Y
39337은현면 봉암리 일원봉암지구 지구단위계획구역241064데이터 미집계241064가구및획지, 건축물 변경Y
39482덕계동 152번지 일원덕계공업지구 지구단위계획구역0173316173316<NA>Y
395<NA>삼숭동, 고암동, 회암동, 율정동, 옥정동 일원양주신도시(옥정, 회천) 지구단위계획구역(옥정)7060749.4데이터 미집계7060749.4가구및획지, 건축물 변경Y
3961고암동, 덕계동, 덕정동, 산북동, 회정동 일원회천지구 지구단위계획구역4105870147944120664<NA>Y
3971남방동 52번지 일원양주역세권643762데이터 미집계643762가구및획지 변경Y
39845삼숭동 일원삼숭지구 지구단위계획구역998836데이터 미집계998836가구및획지, 건축물 변경 / 최초결정일 : 경기도제2청고시제2009-5018호(2009.2.19)Y
39952봉양동 369번지 일원봉양공업지구 지구단위계획구역495472데이터 미집계495472가구및획지, 기타사항 변경 / 최초결정일 : 경기도제2청고시제2009-5203호Y
400<NA>남방동 52번지 일원양주역세권643762데이터 미집계643762건축물 변경Y
40136남면 신산리 일원신산지구 지구단위계획구역507586데이터 미집계507586가구및획지, 건축물 변경Y

Duplicate rows

Most frequently occurring

도면번호위치명지역명면적(기정)면적(변경)면적(변경후)비고공간도형 존재여부# duplicates
645삼숭동 일원삼숭지구 지구단위계획구역998836데이터 미집계998836가구및획지, 건축물 변경Y5
850장흥면 부곡리 491번지 일원부곡2지구 지구단위계획구역572484데이터 미집계572484가구및획지, 건축물 변경Y4
747백석읍 복지리 281번지 일원복지지구 지구단위계획구역3213212데이터 미집계3213212가구및획지, 건축물 변경Y3
12<NA>덕정동, 고암동 일원양주덕정1지구 택지개발사업구역563831데이터 미집계563831가구 및 획지 변경Y3
01광적면 가납리 905 일원가석지구단위계획구역185349.6데이터 미집계185349.6<NA>Y2
11은현면 용암리 784-8번지 일원용암3지구 지구단위계획구역0204674204674<NA>Y2
236남면 신산리 일원신산지구 지구단위계획구역507586데이터 미집계507586가구및획지, 건축물 변경Y2
337은현면 봉암리 일원봉암지구 지구단위계획구역241064데이터 미집계241064가구및획지, 건축물 변경Y2
438은현면 하패리 일원하패지구 지구단위계획구역71272679712805가구의 규모와 조성에 관한 변경Y2
539남면 상수리 일원상수지구 지구단위계획구역646347데이터 미집계646347가구및획지, 건축물 변경Y2