Overview

Dataset statistics

Number of variables36
Number of observations754
Missing cells2889
Missing cells (%)10.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory213.7 KiB
Average record size in memory290.2 B

Variable types

Categorical13
Unsupported1
Text20
DateTime2

Alerts

시도 is highly imbalanced (98.2%)Imbalance
대분류 is highly imbalanced (97.3%)Imbalance
Unnamed: 12 is highly imbalanced (51.6%)Imbalance
Unnamed: 14 is highly imbalanced (85.3%)Imbalance
결정연장 is highly imbalanced (98.5%)Imbalance
집행 is highly imbalanced (98.5%)Imbalance
미집행면적 is highly imbalanced (98.5%)Imbalance
Unnamed: 28 is highly imbalanced (92.3%)Imbalance
미집행 필지수 is highly imbalanced (77.3%)Imbalance
Unnamed: 35 is highly imbalanced (76.9%)Imbalance
세분류 has 754 (100.0%) missing valuesMissing
Unnamed: 10 has 62 (8.2%) missing valuesMissing
Unnamed: 11 has 548 (72.7%) missing valuesMissing
Unnamed: 13 has 61 (8.1%) missing valuesMissing
Unnamed: 22 has 718 (95.2%) missing valuesMissing
Unnamed: 23 has 716 (95.0%) missing valuesMissing
최초결정일 has 19 (2.5%) missing valuesMissing
세분류 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 00:40:24.165949
Analysis finished2024-03-14 00:40:25.199023
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
전라북도
752 
<NA>
 
1
조회건수 : 752
 
1

Length

Max length10
Median length4
Mean length4.0079576
Min length4

Unique

Unique2 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
전라북도 752
99.7%
<NA> 1
 
0.1%
조회건수 : 752 1
 
0.1%

Length

2024-03-14T09:40:25.254724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:25.335141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전라북도 752
99.5%
na 1
 
0.1%
조회건수 1
 
0.1%
1
 
0.1%
752 1
 
0.1%

시군구
Categorical

Distinct15
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
전주시
241 
군산시
154 
익산시
100 
완주군
54 
정읍시
53 
Other values (10)
152 

Length

Max length4
Median length3
Mean length3.0026525
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 241
32.0%
군산시 154
20.4%
익산시 100
13.3%
완주군 54
 
7.2%
정읍시 53
 
7.0%
남원시 32
 
4.2%
김제시 32
 
4.2%
부안군 25
 
3.3%
고창군 17
 
2.3%
무주군 16
 
2.1%
Other values (5) 30
 
4.0%

Length

2024-03-14T09:40:25.423520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 241
32.0%
군산시 154
20.4%
익산시 100
13.3%
완주군 54
 
7.2%
정읍시 53
 
7.0%
남원시 32
 
4.2%
김제시 32
 
4.2%
부안군 25
 
3.3%
고창군 17
 
2.3%
무주군 16
 
2.1%
Other values (5) 30
 
4.0%

대분류
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
공원
752 
<NA>
 
2

Length

Max length4
Median length2
Mean length2.005305
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공원 752
99.7%
<NA> 2
 
0.3%

Length

2024-03-14T09:40:25.547190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:25.641012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공원 752
99.7%
na 2
 
0.3%

중분류
Categorical

Distinct10
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
어린이공원
338 
근린공원
251 
소공원
118 
문화공원
 
18
수변공원
 
9
Other values (5)
 
20

Length

Max length10
Median length5
Mean length4.3076923
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이공원 338
44.8%
근린공원 251
33.3%
소공원 118
 
15.6%
문화공원 18
 
2.4%
수변공원 9
 
1.2%
역사공원 7
 
0.9%
체육공원 5
 
0.7%
묘지공원 4
 
0.5%
<NA> 2
 
0.3%
(기존)도시자연공원 2
 
0.3%

Length

2024-03-14T09:40:25.748404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:25.843056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이공원 338
44.8%
근린공원 251
33.3%
소공원 118
 
15.6%
문화공원 18
 
2.4%
수변공원 9
 
1.2%
역사공원 7
 
0.9%
체육공원 5
 
0.7%
묘지공원 4
 
0.5%
na 2
 
0.3%
기존)도시자연공원 2
 
0.3%

세분류
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing754
Missing (%)100.0%
Memory size6.8 KiB

시설명
Text

Distinct689
Distinct (%)91.6%
Missing2
Missing (%)0.3%
Memory size6.0 KiB
2024-03-14T09:40:26.272484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18
Mean length8.0212766
Min length1

Characters and Unicode

Total characters6032
Distinct characters250
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique651 ?
Unique (%)86.6%

Sample

1st row1호근린공원 188
2nd row가련산공원 3
3rd row거마공원 14
4th row공원 1 만성지구
5th row공원 1 하가지구
ValueCountFrequency (%)
공원 49
 
4.4%
김제 24
 
2.1%
봉동 19
 
1.7%
혁신도시 15
 
1.3%
1 15
 
1.3%
삼례 14
 
1.2%
이서 12
 
1.1%
2 11
 
1.0%
소공원 10
 
0.9%
만성지구 9
 
0.8%
Other values (795) 944
84.1%
2024-03-14T09:40:26.726693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 741
 
12.3%
원 733
 
12.2%
486
 
8.1%
1 329
 
5.5%
제 256
 
4.2%
2 210
 
3.5%
호 180
 
3.0%
3 142
 
2.4%
린 139
 
2.3%
) 135
 
2.2%
Other values (240) 2681
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4100
68.0%
Decimal Number 1175
 
19.5%
Space Separator 486
 
8.1%
Close Punctuation 135
 
2.2%
Open Punctuation 135
 
2.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 741
18.1%
원 733
17.9%
제 256
 
6.2%
호 180
 
4.4%
린 139
 
3.4%
지 115
 
2.8%
이 88
 
2.1%
산 80
 
2.0%
근 76
 
1.9%
택 73
 
1.8%
Other values (226) 1619
39.5%
Decimal Number
ValueCountFrequency (%)
1 329
28.0%
2 210
17.9%
3 142
12.1%
4 105
 
8.9%
5 81
 
6.9%
6 81
 
6.9%
7 75
 
6.4%
8 61
 
5.2%
0 55
 
4.7%
9 36
 
3.1%
Space Separator
ValueCountFrequency (%)
486
100.0%
Close Punctuation
ValueCountFrequency (%)
) 135
100.0%
Open Punctuation
ValueCountFrequency (%)
( 135
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4100
68.0%
Common 1932
32.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 741
18.1%
원 733
17.9%
제 256
 
6.2%
호 180
 
4.4%
린 139
 
3.4%
지 115
 
2.8%
이 88
 
2.1%
산 80
 
2.0%
근 76
 
1.9%
택 73
 
1.8%
Other values (226) 1619
39.5%
Common
ValueCountFrequency (%)
486
25.2%
1 329
17.0%
2 210
10.9%
3 142
 
7.3%
) 135
 
7.0%
( 135
 
7.0%
4 105
 
5.4%
5 81
 
4.2%
6 81
 
4.2%
7 75
 
3.9%
Other values (4) 153
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4100
68.0%
ASCII 1932
32.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 741
18.1%
원 733
17.9%
제 256
 
6.2%
호 180
 
4.4%
린 139
 
3.4%
지 115
 
2.8%
이 88
 
2.1%
산 80
 
2.0%
근 76
 
1.9%
택 73
 
1.8%
Other values (226) 1619
39.5%
ASCII
ValueCountFrequency (%)
486
25.2%
1 329
17.0%
2 210
10.9%
3 142
 
7.3%
) 135
 
7.0%
( 135
 
7.0%
4 105
 
5.4%
5 81
 
4.2%
6 81
 
4.2%
7 75
 
3.9%
Other values (4) 153
 
7.9%

최종변경일
Date

Distinct249
Distinct (%)33.1%
Missing2
Missing (%)0.3%
Memory size6.0 KiB
Minimum1938-05-08 00:00:00
Maximum2015-12-04 00:00:00
2024-03-14T09:40:26.870011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:40:26.994306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

최초고시번호
Text

Distinct207
Distinct (%)27.5%
Missing2
Missing (%)0.3%
Memory size6.0 KiB
2024-03-14T09:40:27.196613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length10.30984
Min length1

Characters and Unicode

Total characters7753
Distinct characters54
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

Unique91 ?
Unique (%)12.1%

Sample

1st row전주시고시 제2012-67호
2nd row건설교통부고시 제2188호
3rd row건설부고시 제206호
4th row전주시고시 제2008-108호
5th row전라북도고시 제2005-193호
ValueCountFrequency (%)
확인중 137
 
11.2%
전라북도고시 107
 
8.7%
고시 99
 
8.1%
건설부고시 57
 
4.6%
전라북도 56
 
4.6%
전주시고시 42
 
3.4%
31
 
2.5%
제2008-91호 25
 
2.0%
건설교통부 19
 
1.5%
건설교통부고시 18
 
1.5%
Other values (211) 637
51.9%
2024-03-14T09:40:27.517350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
고 554
 
7.1%
2 516
 
6.7%
0 515
 
6.6%
1 478
 
6.2%
477
 
6.2%
시 473
 
6.1%
제 435
 
5.6%
호 418
 
5.4%
- 364
 
4.7%
전 306
 
3.9%
Other values (44) 3217
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4032
52.0%
Decimal Number 2873
37.1%
Space Separator 477
 
6.2%
Dash Punctuation 364
 
4.7%
Other Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 554
13.7%
시 473
11.7%
제 435
10.8%
호 418
10.4%
전 306
 
7.6%
북 264
 
6.5%
라 191
 
4.7%
도 191
 
4.7%
건 173
 
4.3%
부 140
 
3.5%
Other values (31) 887
22.0%
Decimal Number
ValueCountFrequency (%)
2 516
18.0%
0 515
17.9%
1 478
16.6%
9 297
10.3%
3 285
9.9%
5 179
 
6.2%
8 173
 
6.0%
4 168
 
5.8%
7 156
 
5.4%
6 106
 
3.7%
Space Separator
ValueCountFrequency (%)
477
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 364
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4032
52.0%
Common 3721
48.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 554
13.7%
시 473
11.7%
제 435
10.8%
호 418
10.4%
전 306
 
7.6%
북 264
 
6.5%
라 191
 
4.7%
도 191
 
4.7%
건 173
 
4.3%
부 140
 
3.5%
Other values (31) 887
22.0%
Common
ValueCountFrequency (%)
2 516
13.9%
0 515
13.8%
1 478
12.8%
477
12.8%
- 364
9.8%
9 297
8.0%
3 285
7.7%
5 179
 
4.8%
8 173
 
4.6%
4 168
 
4.5%
Other values (3) 269
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4032
52.0%
ASCII 3721
48.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
고 554
13.7%
시 473
11.7%
제 435
10.8%
호 418
10.4%
전 306
 
7.6%
북 264
 
6.5%
라 191
 
4.7%
도 191
 
4.7%
건 173
 
4.3%
부 140
 
3.5%
Other values (31) 887
22.0%
ASCII
ValueCountFrequency (%)
2 516
13.9%
0 515
13.8%
1 478
12.8%
477
12.8%
- 364
9.8%
9 297
8.0%
3 285
7.7%
5 179
 
4.8%
8 173
 
4.6%
4 168
 
4.5%
Other values (3) 269
7.2%

최종변경고시번호
Text

Distinct102
Distinct (%)13.6%
Missing2
Missing (%)0.3%
Memory size6.0 KiB
2024-03-14T09:40:27.685320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length5.8949468
Min length1

Characters and Unicode

Total characters4433
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)6.8%

Sample

1st row전주시고시 제2015-172호
2nd row전주시고시 제2015-112호
3rd row-
4th row-
5th row-
ValueCountFrequency (%)
356
35.8%
확인중 134
 
13.5%
고시 89
 
8.9%
전라북도 33
 
3.3%
제2013-1호 19
 
1.9%
부안군고시 19
 
1.9%
전북고2014-144 18
 
1.8%
완주군 16
 
1.6%
김제시 16
 
1.6%
국토교통부 14
 
1.4%
Other values (106) 281
28.2%
2024-03-14T09:40:27.955282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 593
 
13.4%
1 343
 
7.7%
0 331
 
7.5%
2 325
 
7.3%
244
 
5.5%
고 230
 
5.2%
시 215
 
4.8%
제 210
 
4.7%
호 191
 
4.3%
4 165
 
3.7%
Other values (46) 1586
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2008
45.3%
Decimal Number 1580
35.6%
Dash Punctuation 593
 
13.4%
Space Separator 244
 
5.5%
Other Punctuation 7
 
0.2%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
고 230
11.5%
시 215
10.7%
제 210
10.5%
호 191
 
9.5%
중 134
 
6.7%
인 134
 
6.7%
확 134
 
6.7%
전 88
 
4.4%
군 85
 
4.2%
북 76
 
3.8%
Other values (32) 511
25.4%
Decimal Number
ValueCountFrequency (%)
1 343
21.7%
0 331
20.9%
2 325
20.6%
4 165
10.4%
3 131
 
8.3%
9 78
 
4.9%
7 71
 
4.5%
5 58
 
3.7%
6 48
 
3.0%
8 30
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 593
100.0%
Space Separator
ValueCountFrequency (%)
244
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2425
54.7%
Hangul 2008
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
고 230
11.5%
시 215
10.7%
제 210
10.5%
호 191
 
9.5%
중 134
 
6.7%
인 134
 
6.7%
확 134
 
6.7%
전 88
 
4.4%
군 85
 
4.2%
북 76
 
3.8%
Other values (32) 511
25.4%
Common
ValueCountFrequency (%)
- 593
24.5%
1 343
14.1%
0 331
13.6%
2 325
13.4%
244
10.1%
4 165
 
6.8%
3 131
 
5.4%
9 78
 
3.2%
7 71
 
2.9%
5 58
 
2.4%
Other values (4) 86
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2425
54.7%
Hangul 2008
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 593
24.5%
1 343
14.1%
0 331
13.6%
2 325
13.4%
244
10.1%
4 165
 
6.8%
3 131
 
5.4%
9 78
 
3.2%
7 71
 
2.9%
5 58
 
2.4%
Other values (4) 86
 
3.5%
Hangul
ValueCountFrequency (%)
고 230
11.5%
시 215
10.7%
제 210
10.5%
호 191
 
9.5%
중 134
 
6.7%
인 134
 
6.7%
확 134
 
6.7%
전 88
 
4.4%
군 85
 
4.2%
북 76
 
3.8%
Other values (32) 511
25.4%

대표지번
Categorical

Distinct17
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
전주시 완산구
141 
군산시
107 
익산시
100 
전주시 덕진구
100 
<NA>
61 
Other values (12)
245 

Length

Max length7
Median length3
Mean length4.3594164
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row시군구
2nd row전주시 덕진구
3rd row전주시 덕진구
4th row전주시 완산구
5th row전주시 덕진구

Common Values

ValueCountFrequency (%)
전주시 완산구 141
18.7%
군산시 107
14.2%
익산시 100
13.3%
전주시 덕진구 100
13.3%
<NA> 61
8.1%
완주군 54
 
7.2%
정읍시 47
 
6.2%
남원시 32
 
4.2%
김제시 32
 
4.2%
부안군 25
 
3.3%
Other values (7) 55
 
7.3%

Length

2024-03-14T09:40:28.065079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 241
24.2%
완산구 141
14.2%
군산시 107
10.8%
익산시 100
10.1%
덕진구 100
10.1%
na 61
 
6.1%
완주군 54
 
5.4%
정읍시 47
 
4.7%
김제시 32
 
3.2%
남원시 32
 
3.2%
Other values (8) 80
 
8.0%

Unnamed: 10
Text

MISSING 

Distinct163
Distinct (%)23.6%
Missing62
Missing (%)8.2%
Memory size6.0 KiB
2024-03-14T09:40:28.311663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.5578035
Min length2

Characters and Unicode

Total characters2462
Distinct characters133
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

Unique50 ?
Unique (%)7.2%

Sample

1st row읍면동
2nd row팔복동2가
3rd row덕진동2가
4th row삼천동1가
5th row만성동
ValueCountFrequency (%)
나운동 24
 
3.5%
효자동2가 23
 
3.3%
봉동읍 19
 
2.7%
효자동3가 19
 
2.7%
중화산동2가 17
 
2.5%
인후동1가 17
 
2.5%
미장동 17
 
2.5%
송천동2가 16
 
2.3%
이서면 15
 
2.2%
만성동 14
 
2.0%
Other values (153) 511
73.8%
2024-03-14T09:40:28.715690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 519
21.1%
가 190
 
7.7%
면 119
 
4.8%
2 91
 
3.7%
읍 88
 
3.6%
1 66
 
2.7%
산 65
 
2.6%
효 54
 
2.2%
자 54
 
2.2%
서 52
 
2.1%
Other values (123) 1164
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2272
92.3%
Decimal Number 190
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 519
22.8%
가 190
 
8.4%
면 119
 
5.2%
읍 88
 
3.9%
산 65
 
2.9%
효 54
 
2.4%
자 54
 
2.4%
서 52
 
2.3%
화 46
 
2.0%
천 40
 
1.8%
Other values (119) 1045
46.0%
Decimal Number
ValueCountFrequency (%)
2 91
47.9%
1 66
34.7%
3 32
 
16.8%
4 1
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2272
92.3%
Common 190
 
7.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 519
22.8%
가 190
 
8.4%
면 119
 
5.2%
읍 88
 
3.9%
산 65
 
2.9%
효 54
 
2.4%
자 54
 
2.4%
서 52
 
2.3%
화 46
 
2.0%
천 40
 
1.8%
Other values (119) 1045
46.0%
Common
ValueCountFrequency (%)
2 91
47.9%
1 66
34.7%
3 32
 
16.8%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2272
92.3%
ASCII 190
 
7.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 519
22.8%
가 190
 
8.4%
면 119
 
5.2%
읍 88
 
3.9%
산 65
 
2.9%
효 54
 
2.4%
자 54
 
2.4%
서 52
 
2.3%
화 46
 
2.0%
천 40
 
1.8%
Other values (119) 1045
46.0%
ASCII
ValueCountFrequency (%)
2 91
47.9%
1 66
34.7%
3 32
 
16.8%
4 1
 
0.5%

Unnamed: 11
Text

MISSING 

Distinct106
Distinct (%)51.5%
Missing548
Missing (%)72.7%
Memory size6.0 KiB
2024-03-14T09:40:29.040003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9854369
Min length1

Characters and Unicode

Total characters615
Distinct characters104
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)30.6%

Sample

1st row리
2nd row산월리
3rd row산월리
4th row통사리
5th row통사리
ValueCountFrequency (%)
읍내리 12
 
5.8%
온수리 6
 
2.9%
갈산리 6
 
2.9%
수계리 5
 
2.4%
삼례리 5
 
2.4%
쌍암리 5
 
2.4%
둔산리 5
 
2.4%
월곡리 5
 
2.4%
용암리 5
 
2.4%
용서리 5
 
2.4%
Other values (96) 147
71.4%
2024-03-14T09:40:29.387698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 206
33.5%
산 29
 
4.7%
내 15
 
2.4%
수 14
 
2.3%
암 14
 
2.3%
용 13
 
2.1%
읍 12
 
2.0%
계 11
 
1.8%
평 10
 
1.6%
동 10
 
1.6%
Other values (94) 281
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 615
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 206
33.5%
산 29
 
4.7%
내 15
 
2.4%
수 14
 
2.3%
암 14
 
2.3%
용 13
 
2.1%
읍 12
 
2.0%
계 11
 
1.8%
평 10
 
1.6%
동 10
 
1.6%
Other values (94) 281
45.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 615
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 206
33.5%
산 29
 
4.7%
내 15
 
2.4%
수 14
 
2.3%
암 14
 
2.3%
용 13
 
2.1%
읍 12
 
2.0%
계 11
 
1.8%
평 10
 
1.6%
동 10
 
1.6%
Other values (94) 281
45.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 615
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 206
33.5%
산 29
 
4.7%
내 15
 
2.4%
수 14
 
2.3%
암 14
 
2.3%
용 13
 
2.1%
읍 12
 
2.0%
계 11
 
1.8%
평 10
 
1.6%
동 10
 
1.6%
Other values (94) 281
45.7%

Unnamed: 12
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
675 
산
79 

Length

Max length4
Median length4
Mean length3.6856764
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 675
89.5%
산 79
 
10.5%

Length

2024-03-14T09:40:29.497715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:29.589804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 675
89.5%
산 79
 
10.5%

Unnamed: 13
Text

MISSING 

Distinct501
Distinct (%)72.3%
Missing61
Missing (%)8.1%
Memory size6.0 KiB
2024-03-14T09:40:29.893723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8686869
Min length1

Characters and Unicode

Total characters1988
Distinct characters11
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

Unique377 ?
Unique (%)54.4%

Sample

1st row본
2nd row505
3rd row27
4th row707
5th row458
ValueCountFrequency (%)
5 15
 
2.2%
1 10
 
1.4%
3 7
 
1.0%
58 6
 
0.9%
2 5
 
0.7%
377 5
 
0.7%
6 4
 
0.6%
83 4
 
0.6%
802 4
 
0.6%
156 4
 
0.6%
Other values (491) 629
90.8%
2024-03-14T09:40:30.294441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 313
15.7%
5 224
11.3%
3 204
10.3%
8 204
10.3%
7 202
10.2%
6 190
9.6%
2 173
8.7%
4 171
8.6%
0 156
7.8%
9 150
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1987
99.9%
Other Letter 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 313
15.8%
5 224
11.3%
3 204
10.3%
8 204
10.3%
7 202
10.2%
6 190
9.6%
2 173
8.7%
4 171
8.6%
0 156
7.9%
9 150
7.5%
Other Letter
ValueCountFrequency (%)
본 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1987
99.9%
Hangul 1
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 313
15.8%
5 224
11.3%
3 204
10.3%
8 204
10.3%
7 202
10.2%
6 190
9.6%
2 173
8.7%
4 171
8.6%
0 156
7.9%
9 150
7.5%
Hangul
ValueCountFrequency (%)
본 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1987
99.9%
Hangul 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 313
15.8%
5 224
11.3%
3 204
10.3%
8 204
10.3%
7 202
10.2%
6 190
9.6%
2 173
8.7%
4 171
8.6%
0 156
7.9%
9 150
7.5%
Hangul
ValueCountFrequency (%)
본 1
100.0%

Unnamed: 14
Categorical

IMBALANCE 

Distinct21
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
697 
1
 
20
2
 
9
12
 
3
4
 
3
Other values (16)
 
22

Length

Max length4
Median length4
Mean length3.7917772
Min length1

Unique

Unique10 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 697
92.4%
1 20
 
2.7%
2 9
 
1.2%
12 3
 
0.4%
4 3
 
0.4%
7 2
 
0.3%
5 2
 
0.3%
6 2
 
0.3%
27 2
 
0.3%
9 2
 
0.3%
Other values (11) 12
 
1.6%

Length

2024-03-14T09:40:30.409631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 697
92.4%
1 20
 
2.7%
2 9
 
1.2%
12 3
 
0.4%
4 3
 
0.4%
27 2
 
0.3%
9 2
 
0.3%
3 2
 
0.3%
6 2
 
0.3%
5 2
 
0.3%
Other values (11) 12
 
1.6%

위치
Text

Distinct721
Distinct (%)95.9%
Missing2
Missing (%)0.3%
Memory size6.0 KiB
2024-03-14T09:40:30.607322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length14.25
Min length2

Characters and Unicode

Total characters10716
Distinct characters297
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique709 ?
Unique (%)94.3%

Sample

1st row팔복동2가 505대(팔복지구근린공원)
2nd row덕진동2가 산 27-1 일원(가련산공원)
3rd row삼천동1가 707공(거마공원)
4th row만성동 458답 일원(만성1공원)
5th row덕진동2가 682일원(하늘공원)
ValueCountFrequency (%)
일원 183
 
9.9%
나운동 24
 
1.3%
효자동2가 23
 
1.2%
산 20
 
1.1%
효자동3가 19
 
1.0%
봉동읍 19
 
1.0%
미장동 17
 
0.9%
인후동1가 17
 
0.9%
중화산동2가 17
 
0.9%
조촌동 17
 
0.9%
Other values (993) 1493
80.7%
2024-03-14T09:40:31.060639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1106
 
10.3%
1 620
 
5.8%
원 568
 
5.3%
동 560
 
5.2%
- 454
 
4.2%
2 394
 
3.7%
일 329
 
3.1%
3 320
 
3.0%
공 308
 
2.9%
5 270
 
2.5%
Other values (287) 5787
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5613
52.4%
Decimal Number 2893
27.0%
Space Separator 1106
 
10.3%
Dash Punctuation 454
 
4.2%
Close Punctuation 270
 
2.5%
Open Punctuation 270
 
2.5%
Uppercase Letter 61
 
0.6%
Other Punctuation 49
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 568
 
10.1%
동 560
 
10.0%
일 329
 
5.9%
공 308
 
5.5%
리 224
 
4.0%
산 202
 
3.6%
가 197
 
3.5%
지 137
 
2.4%
면 95
 
1.7%
내 89
 
1.6%
Other values (265) 2904
51.7%
Decimal Number
ValueCountFrequency (%)
1 620
21.4%
2 394
13.6%
3 320
11.1%
5 270
9.3%
4 258
8.9%
6 246
 
8.5%
7 221
 
7.6%
8 218
 
7.5%
0 173
 
6.0%
9 173
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 29
59.2%
, 19
38.8%
@ 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
B 29
47.5%
L 29
47.5%
D 3
 
4.9%
Close Punctuation
ValueCountFrequency (%)
) 248
91.9%
] 22
 
8.1%
Open Punctuation
ValueCountFrequency (%)
( 248
91.9%
[ 22
 
8.1%
Space Separator
ValueCountFrequency (%)
1106
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 454
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5613
52.4%
Common 5042
47.1%
Latin 61
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 568
 
10.1%
동 560
 
10.0%
일 329
 
5.9%
공 308
 
5.5%
리 224
 
4.0%
산 202
 
3.6%
가 197
 
3.5%
지 137
 
2.4%
면 95
 
1.7%
내 89
 
1.6%
Other values (265) 2904
51.7%
Common
ValueCountFrequency (%)
1106
21.9%
1 620
12.3%
- 454
9.0%
2 394
 
7.8%
3 320
 
6.3%
5 270
 
5.4%
4 258
 
5.1%
) 248
 
4.9%
( 248
 
4.9%
6 246
 
4.9%
Other values (9) 878
17.4%
Latin
ValueCountFrequency (%)
B 29
47.5%
L 29
47.5%
D 3
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5613
52.4%
ASCII 5103
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1106
21.7%
1 620
12.1%
- 454
8.9%
2 394
 
7.7%
3 320
 
6.3%
5 270
 
5.3%
4 258
 
5.1%
) 248
 
4.9%
( 248
 
4.9%
6 246
 
4.8%
Other values (12) 939
18.4%
Hangul
ValueCountFrequency (%)
원 568
 
10.1%
동 560
 
10.0%
일 329
 
5.9%
공 308
 
5.5%
리 224
 
4.0%
산 202
 
3.6%
가 197
 
3.5%
지 137
 
2.4%
면 95
 
1.7%
내 89
 
1.6%
Other values (265) 2904
51.7%

결정연장
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
753 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0039788
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 753
99.9%
<NA> 1
 
0.1%

Length

2024-03-14T09:40:31.210855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:31.304036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 753
99.9%
na 1
 
0.1%

결정면적
Text

Distinct633
Distinct (%)84.1%
Missing1
Missing (%)0.1%
Memory size6.0 KiB
2024-03-14T09:40:31.596312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length5.3373174
Min length2

Characters and Unicode

Total characters4019
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique595 ?
Unique (%)79.0%

Sample

1st row10,788
2nd row324,560
3rd row9,926
4th row58,582
5th row25,864
ValueCountFrequency (%)
1,500 44
 
5.8%
2,800 10
 
1.3%
1,571 9
 
1.2%
1,510 9
 
1.2%
2,000 6
 
0.8%
10,000 6
 
0.8%
1,572 5
 
0.7%
1,550 4
 
0.5%
1,512 4
 
0.5%
1,502 4
 
0.5%
Other values (623) 652
86.6%
2024-03-14T09:40:32.046015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 700
17.4%
0 585
14.6%
1 570
14.2%
2 374
9.3%
5 367
9.1%
3 270
 
6.7%
4 244
 
6.1%
6 244
 
6.1%
7 236
 
5.9%
8 227
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3319
82.6%
Other Punctuation 700
 
17.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 585
17.6%
1 570
17.2%
2 374
11.3%
5 367
11.1%
3 270
8.1%
4 244
7.4%
6 244
7.4%
7 236
7.1%
8 227
 
6.8%
9 202
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 700
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4019
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 700
17.4%
0 585
14.6%
1 570
14.2%
2 374
9.3%
5 367
9.1%
3 270
 
6.7%
4 244
 
6.1%
6 244
 
6.1%
7 236
 
5.9%
8 227
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4019
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 700
17.4%
0 585
14.6%
1 570
14.2%
2 374
9.3%
5 367
9.1%
3 270
 
6.7%
4 244
 
6.1%
6 244
 
6.1%
7 236
 
5.9%
8 227
 
5.6%

집행
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
753 
집행연장
 
1

Length

Max length4
Median length1
Mean length1.0039788
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row집행연장
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 753
99.9%
집행연장 1
 
0.1%

Length

2024-03-14T09:40:32.165316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:32.244724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 753
99.9%
집행연장 1
 
0.1%

Unnamed: 19
Text

Distinct504
Distinct (%)66.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:32.519227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.4084881
Min length1

Characters and Unicode

Total characters3324
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique474 ?
Unique (%)62.9%

Sample

1st row집행면적
2nd row10,788
3rd row324,560
4th row9,926
5th row58,582
ValueCountFrequency (%)
0 149
 
19.8%
1,500 40
 
5.3%
2,800 10
 
1.3%
1,571 9
 
1.2%
1,510 7
 
0.9%
2,000 6
 
0.8%
1,572 5
 
0.7%
10,000 5
 
0.7%
1,512 4
 
0.5%
1,502 4
 
0.5%
Other values (494) 515
68.3%
2024-03-14T09:40:32.914614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 558
16.8%
, 558
16.8%
1 472
14.2%
2 319
9.6%
5 301
9.1%
3 218
 
6.6%
7 191
 
5.7%
6 191
 
5.7%
4 187
 
5.6%
8 183
 
5.5%
Other values (5) 146
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2762
83.1%
Other Punctuation 558
 
16.8%
Other Letter 4
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 558
20.2%
1 472
17.1%
2 319
11.5%
5 301
10.9%
3 218
 
7.9%
7 191
 
6.9%
6 191
 
6.9%
4 187
 
6.8%
8 183
 
6.6%
9 142
 
5.1%
Other Letter
ValueCountFrequency (%)
집 1
25.0%
행 1
25.0%
면 1
25.0%
적 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 558
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3320
99.9%
Hangul 4
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 558
16.8%
, 558
16.8%
1 472
14.2%
2 319
9.6%
5 301
9.1%
3 218
 
6.6%
7 191
 
5.8%
6 191
 
5.8%
4 187
 
5.6%
8 183
 
5.5%
Hangul
ValueCountFrequency (%)
집 1
25.0%
행 1
25.0%
면 1
25.0%
적 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3320
99.9%
Hangul 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 558
16.8%
, 558
16.8%
1 472
14.2%
2 319
9.6%
5 301
9.1%
3 218
 
6.6%
7 191
 
5.8%
6 191
 
5.8%
4 187
 
5.6%
8 183
 
5.5%
Hangul
ValueCountFrequency (%)
집 1
25.0%
행 1
25.0%
면 1
25.0%
적 1
25.0%

Unnamed: 20
Text

Distinct105
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:33.161069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.464191
Min length1

Characters and Unicode

Total characters1104
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)11.4%

Sample

1st row보상비
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 598
79.3%
62 16
 
2.1%
112 12
 
1.6%
60 8
 
1.1%
150 4
 
0.5%
65 3
 
0.4%
80 3
 
0.4%
185 2
 
0.3%
75 2
 
0.3%
164 2
 
0.3%
Other values (95) 104
 
13.8%
2024-03-14T09:40:33.529434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 679
61.5%
1 84
 
7.6%
2 65
 
5.9%
6 63
 
5.7%
, 39
 
3.5%
3 32
 
2.9%
4 32
 
2.9%
5 31
 
2.8%
7 30
 
2.7%
8 27
 
2.4%
Other values (4) 22
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1062
96.2%
Other Punctuation 39
 
3.5%
Other Letter 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 679
63.9%
1 84
 
7.9%
2 65
 
6.1%
6 63
 
5.9%
3 32
 
3.0%
4 32
 
3.0%
5 31
 
2.9%
7 30
 
2.8%
8 27
 
2.5%
9 19
 
1.8%
Other Letter
ValueCountFrequency (%)
보 1
33.3%
상 1
33.3%
비 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1101
99.7%
Hangul 3
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 679
61.7%
1 84
 
7.6%
2 65
 
5.9%
6 63
 
5.7%
, 39
 
3.5%
3 32
 
2.9%
4 32
 
2.9%
5 31
 
2.8%
7 30
 
2.7%
8 27
 
2.5%
Hangul
ValueCountFrequency (%)
보 1
33.3%
상 1
33.3%
비 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1101
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 679
61.7%
1 84
 
7.6%
2 65
 
5.9%
6 63
 
5.7%
, 39
 
3.5%
3 32
 
2.9%
4 32
 
2.9%
5 31
 
2.8%
7 30
 
2.7%
8 27
 
2.5%
Hangul
ValueCountFrequency (%)
보 1
33.3%
상 1
33.3%
비 1
33.3%

Unnamed: 21
Text

Distinct120
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:33.734567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.4893899
Min length1

Characters and Unicode

Total characters1123
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)13.9%

Sample

1st row사업비
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 577
76.5%
23 16
 
2.1%
42 12
 
1.6%
22 11
 
1.5%
150 6
 
0.8%
24 5
 
0.7%
27 4
 
0.5%
3,000 3
 
0.4%
174 3
 
0.4%
30 2
 
0.3%
Other values (110) 115
 
15.3%
2024-03-14T09:40:34.058541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 643
57.3%
2 97
 
8.6%
1 71
 
6.3%
3 61
 
5.4%
4 50
 
4.5%
5 47
 
4.2%
, 41
 
3.7%
7 29
 
2.6%
6 29
 
2.6%
8 29
 
2.6%
Other values (4) 26
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1079
96.1%
Other Punctuation 41
 
3.7%
Other Letter 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 643
59.6%
2 97
 
9.0%
1 71
 
6.6%
3 61
 
5.7%
4 50
 
4.6%
5 47
 
4.4%
7 29
 
2.7%
6 29
 
2.7%
8 29
 
2.7%
9 23
 
2.1%
Other Letter
ValueCountFrequency (%)
사 1
33.3%
업 1
33.3%
비 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1120
99.7%
Hangul 3
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 643
57.4%
2 97
 
8.7%
1 71
 
6.3%
3 61
 
5.4%
4 50
 
4.5%
5 47
 
4.2%
, 41
 
3.7%
7 29
 
2.6%
6 29
 
2.6%
8 29
 
2.6%
Hangul
ValueCountFrequency (%)
사 1
33.3%
업 1
33.3%
비 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1120
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 643
57.4%
2 97
 
8.7%
1 71
 
6.3%
3 61
 
5.4%
4 50
 
4.5%
5 47
 
4.2%
, 41
 
3.7%
7 29
 
2.6%
6 29
 
2.6%
8 29
 
2.6%
Hangul
ValueCountFrequency (%)
사 1
33.3%
업 1
33.3%
비 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)66.7%
Missing718
Missing (%)95.2%
Memory size6.0 KiB
2024-03-14T09:40:34.232511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8055556
Min length3

Characters and Unicode

Total characters353
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)47.2%

Sample

1st row착공일
2nd row2013-03-22
3rd row2013-03-22
4th row2013-03-22
5th row2013-03-22
ValueCountFrequency (%)
1991-05-03 4
 
11.1%
2013-03-22 4
 
11.1%
2000-06-01 3
 
8.3%
1990-06-12 2
 
5.6%
2008-09-17 2
 
5.6%
2009-02-01 2
 
5.6%
2010-09-01 2
 
5.6%
1985-07-01 1
 
2.8%
착공일 1
 
2.8%
2013-01-11 1
 
2.8%
Other values (14) 14
38.9%
2024-03-14T09:40:34.497430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 102
28.9%
- 70
19.8%
1 53
15.0%
2 40
 
11.3%
9 30
 
8.5%
3 18
 
5.1%
7 10
 
2.8%
6 9
 
2.5%
5 8
 
2.3%
8 5
 
1.4%
Other values (4) 8
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 280
79.3%
Dash Punctuation 70
 
19.8%
Other Letter 3
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 102
36.4%
1 53
18.9%
2 40
 
14.3%
9 30
 
10.7%
3 18
 
6.4%
7 10
 
3.6%
6 9
 
3.2%
5 8
 
2.9%
8 5
 
1.8%
4 5
 
1.8%
Other Letter
ValueCountFrequency (%)
착 1
33.3%
공 1
33.3%
일 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 350
99.2%
Hangul 3
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 102
29.1%
- 70
20.0%
1 53
15.1%
2 40
 
11.4%
9 30
 
8.6%
3 18
 
5.1%
7 10
 
2.9%
6 9
 
2.6%
5 8
 
2.3%
8 5
 
1.4%
Hangul
ValueCountFrequency (%)
착 1
33.3%
공 1
33.3%
일 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 350
99.2%
Hangul 3
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 102
29.1%
- 70
20.0%
1 53
15.1%
2 40
 
11.4%
9 30
 
8.6%
3 18
 
5.1%
7 10
 
2.9%
6 9
 
2.6%
5 8
 
2.3%
8 5
 
1.4%
Hangul
ValueCountFrequency (%)
착 1
33.3%
공 1
33.3%
일 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct25
Distinct (%)65.8%
Missing716
Missing (%)95.0%
Memory size6.0 KiB
2024-03-14T09:40:34.648202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.8157895
Min length3

Characters and Unicode

Total characters373
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)44.7%

Sample

1st row준공일
2nd row2014-03-31
3rd row2014-12-31
4th row2014-12-31
5th row2014-12-31
ValueCountFrequency (%)
2015-12-31 4
 
10.5%
1994-01-26 4
 
10.5%
2014-12-31 3
 
7.9%
2011-07-06 2
 
5.3%
2013-12-31 2
 
5.3%
2001-10-01 2
 
5.3%
1993-12-11 2
 
5.3%
1987-08-08 2
 
5.3%
1984-08-01 1
 
2.6%
준공일 1
 
2.6%
Other values (15) 15
39.5%
2024-03-14T09:40:34.914123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 89
23.9%
- 74
19.8%
0 69
18.5%
2 49
13.1%
3 26
 
7.0%
9 21
 
5.6%
4 13
 
3.5%
6 10
 
2.7%
8 8
 
2.1%
5 7
 
1.9%
Other values (4) 7
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 296
79.4%
Dash Punctuation 74
 
19.8%
Other Letter 3
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 89
30.1%
0 69
23.3%
2 49
16.6%
3 26
 
8.8%
9 21
 
7.1%
4 13
 
4.4%
6 10
 
3.4%
8 8
 
2.7%
5 7
 
2.4%
7 4
 
1.4%
Other Letter
ValueCountFrequency (%)
준 1
33.3%
공 1
33.3%
일 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 370
99.2%
Hangul 3
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 89
24.1%
- 74
20.0%
0 69
18.6%
2 49
13.2%
3 26
 
7.0%
9 21
 
5.7%
4 13
 
3.5%
6 10
 
2.7%
8 8
 
2.2%
5 7
 
1.9%
Hangul
ValueCountFrequency (%)
준 1
33.3%
공 1
33.3%
일 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 370
99.2%
Hangul 3
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 89
24.1%
- 74
20.0%
0 69
18.6%
2 49
13.2%
3 26
 
7.0%
9 21
 
5.7%
4 13
 
3.5%
6 10
 
2.7%
8 8
 
2.2%
5 7
 
1.9%
Hangul
ValueCountFrequency (%)
준 1
33.3%
공 1
33.3%
일 1
33.3%

최초결정일
Date

MISSING 

Distinct257
Distinct (%)35.0%
Missing19
Missing (%)2.5%
Memory size6.0 KiB
Minimum1938-05-08 00:00:00
Maximum2015-11-27 00:00:00
2024-03-14T09:40:35.046381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:40:35.188146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

미집행면적
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
753 
미집행연장
 
1

Length

Max length5
Median length1
Mean length1.005305
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row미집행연장
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 753
99.9%
미집행연장 1
 
0.1%

Length

2024-03-14T09:40:35.333310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:40:35.462438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 753
99.9%
미집행연장 1
 
0.1%

Unnamed: 26
Text

Distinct132
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:35.717651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.7506631
Min length1

Characters and Unicode

Total characters1320
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique124 ?
Unique (%)16.4%

Sample

1st row국공유지
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 615
81.6%
3,000 3
 
0.4%
500 2
 
0.3%
68 2
 
0.3%
765 2
 
0.3%
5 2
 
0.3%
10,000 2
 
0.3%
28 2
 
0.3%
10,977 1
 
0.1%
4,459 1
 
0.1%
Other values (122) 122
 
16.2%
2024-03-14T09:40:36.070722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 689
52.2%
, 114
 
8.6%
1 75
 
5.7%
2 71
 
5.4%
3 66
 
5.0%
5 60
 
4.5%
8 55
 
4.2%
6 50
 
3.8%
4 48
 
3.6%
7 46
 
3.5%
Other values (5) 46
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1202
91.1%
Other Punctuation 114
 
8.6%
Other Letter 4
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 689
57.3%
1 75
 
6.2%
2 71
 
5.9%
3 66
 
5.5%
5 60
 
5.0%
8 55
 
4.6%
6 50
 
4.2%
4 48
 
4.0%
7 46
 
3.8%
9 42
 
3.5%
Other Letter
ValueCountFrequency (%)
국 1
25.0%
공 1
25.0%
유 1
25.0%
지 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1316
99.7%
Hangul 4
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 689
52.4%
, 114
 
8.7%
1 75
 
5.7%
2 71
 
5.4%
3 66
 
5.0%
5 60
 
4.6%
8 55
 
4.2%
6 50
 
3.8%
4 48
 
3.6%
7 46
 
3.5%
Hangul
ValueCountFrequency (%)
국 1
25.0%
공 1
25.0%
유 1
25.0%
지 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1316
99.7%
Hangul 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 689
52.4%
, 114
 
8.7%
1 75
 
5.7%
2 71
 
5.4%
3 66
 
5.0%
5 60
 
4.6%
8 55
 
4.2%
6 50
 
3.8%
4 48
 
3.6%
7 46
 
3.5%
Hangul
ValueCountFrequency (%)
국 1
25.0%
공 1
25.0%
유 1
25.0%
지 1
25.0%

Unnamed: 27
Text

Distinct171
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:36.347164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length1
Mean length2.0915119
Min length1

Characters and Unicode

Total characters1577
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)22.1%

Sample

1st row사유지
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 579
76.8%
1,550 3
 
0.4%
1,500 3
 
0.4%
1,510 2
 
0.3%
168 1
 
0.1%
18,212 1
 
0.1%
436 1
 
0.1%
1,570 1
 
0.1%
1,650 1
 
0.1%
834 1
 
0.1%
Other values (161) 161
 
21.4%
2024-03-14T09:40:36.709552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 674
42.7%
, 161
 
10.2%
1 121
 
7.7%
2 98
 
6.2%
5 96
 
6.1%
9 82
 
5.2%
3 79
 
5.0%
6 73
 
4.6%
7 67
 
4.2%
4 65
 
4.1%
Other values (4) 61
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1413
89.6%
Other Punctuation 161
 
10.2%
Other Letter 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 674
47.7%
1 121
 
8.6%
2 98
 
6.9%
5 96
 
6.8%
9 82
 
5.8%
3 79
 
5.6%
6 73
 
5.2%
7 67
 
4.7%
4 65
 
4.6%
8 58
 
4.1%
Other Letter
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 161
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1574
99.8%
Hangul 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 674
42.8%
, 161
 
10.2%
1 121
 
7.7%
2 98
 
6.2%
5 96
 
6.1%
9 82
 
5.2%
3 79
 
5.0%
6 73
 
4.6%
7 67
 
4.3%
4 65
 
4.1%
Hangul
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1574
99.8%
Hangul 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 674
42.8%
, 161
 
10.2%
1 121
 
7.7%
2 98
 
6.2%
5 96
 
6.1%
9 82
 
5.2%
3 79
 
5.0%
6 73
 
4.6%
7 67
 
4.3%
4 65
 
4.1%
Hangul
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%

Unnamed: 28
Categorical

IMBALANCE 

Distinct26
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
729 
국공유대지
 
1
390
 
1
5
 
1
561
 
1
Other values (21)
 
21

Length

Max length6
Median length1
Mean length1.0755968
Min length1

Unique

Unique25 ?
Unique (%)3.3%

Sample

1st row국공유대지
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 729
96.7%
국공유대지 1
 
0.1%
390 1
 
0.1%
5 1
 
0.1%
561 1
 
0.1%
402 1
 
0.1%
337 1
 
0.1%
68 1
 
0.1%
301 1
 
0.1%
267 1
 
0.1%
Other values (16) 16
 
2.1%

Length

2024-03-14T09:40:36.840842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 729
96.7%
국공유대지 1
 
0.1%
357 1
 
0.1%
60 1
 
0.1%
354 1
 
0.1%
897 1
 
0.1%
483 1
 
0.1%
6,755 1
 
0.1%
821 1
 
0.1%
2,202 1
 
0.1%
Other values (16) 16
 
2.1%

Unnamed: 29
Text

Distinct106
Distinct (%)14.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:37.028215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.4323607
Min length1

Characters and Unicode

Total characters1080
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)13.5%

Sample

1st row사유대지
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 646
85.7%
75 2
 
0.3%
1,540 2
 
0.3%
684 2
 
0.3%
2,977 1
 
0.1%
1,815 1
 
0.1%
882 1
 
0.1%
701 1
 
0.1%
4,731 1
 
0.1%
4,139 1
 
0.1%
Other values (96) 96
 
12.7%
2024-03-14T09:40:37.358750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 675
62.5%
1 66
 
6.1%
, 53
 
4.9%
2 44
 
4.1%
7 43
 
4.0%
5 40
 
3.7%
4 34
 
3.1%
8 33
 
3.1%
3 33
 
3.1%
6 32
 
3.0%
Other values (5) 27
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1023
94.7%
Other Punctuation 53
 
4.9%
Other Letter 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 675
66.0%
1 66
 
6.5%
2 44
 
4.3%
7 43
 
4.2%
5 40
 
3.9%
4 34
 
3.3%
8 33
 
3.2%
3 33
 
3.2%
6 32
 
3.1%
9 23
 
2.2%
Other Letter
ValueCountFrequency (%)
사 1
25.0%
유 1
25.0%
대 1
25.0%
지 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1076
99.6%
Hangul 4
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 675
62.7%
1 66
 
6.1%
, 53
 
4.9%
2 44
 
4.1%
7 43
 
4.0%
5 40
 
3.7%
4 34
 
3.2%
8 33
 
3.1%
3 33
 
3.1%
6 32
 
3.0%
Hangul
ValueCountFrequency (%)
사 1
25.0%
유 1
25.0%
대 1
25.0%
지 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1076
99.6%
Hangul 4
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 675
62.7%
1 66
 
6.1%
, 53
 
4.9%
2 44
 
4.1%
7 43
 
4.0%
5 40
 
3.7%
4 34
 
3.2%
8 33
 
3.1%
3 33
 
3.1%
6 32
 
3.0%
Hangul
ValueCountFrequency (%)
사 1
25.0%
유 1
25.0%
대 1
25.0%
지 1
25.0%

미집행 사업비(보상비 및 공사비)
Text

Distinct152
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:37.645830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.6034483
Min length1

Characters and Unicode

Total characters1209
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)19.5%

Sample

1st row사유지
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 598
79.3%
83 3
 
0.4%
86 2
 
0.3%
429 2
 
0.3%
79 2
 
0.3%
134 1
 
0.1%
99 1
 
0.1%
사유지 1
 
0.1%
75 1
 
0.1%
1,794 1
 
0.1%
Other values (142) 142
 
18.8%
2024-03-14T09:40:38.081089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 648
53.6%
1 78
 
6.5%
2 71
 
5.9%
, 71
 
5.9%
3 56
 
4.6%
4 53
 
4.4%
8 49
 
4.1%
9 49
 
4.1%
5 49
 
4.1%
7 44
 
3.6%
Other values (4) 41
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1135
93.9%
Other Punctuation 71
 
5.9%
Other Letter 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 648
57.1%
1 78
 
6.9%
2 71
 
6.3%
3 56
 
4.9%
4 53
 
4.7%
8 49
 
4.3%
9 49
 
4.3%
5 49
 
4.3%
7 44
 
3.9%
6 38
 
3.3%
Other Letter
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1206
99.8%
Hangul 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 648
53.7%
1 78
 
6.5%
2 71
 
5.9%
, 71
 
5.9%
3 56
 
4.6%
4 53
 
4.4%
8 49
 
4.1%
9 49
 
4.1%
5 49
 
4.1%
7 44
 
3.6%
Hangul
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1206
99.8%
Hangul 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 648
53.7%
1 78
 
6.5%
2 71
 
5.9%
, 71
 
5.9%
3 56
 
4.6%
4 53
 
4.4%
8 49
 
4.1%
9 49
 
4.1%
5 49
 
4.1%
7 44
 
3.6%
Hangul
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%

Unnamed: 31
Text

Distinct81
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:38.266122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.2334218
Min length1

Characters and Unicode

Total characters930
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)9.3%

Sample

1st row사유대지
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 658
87.3%
3 3
 
0.4%
2 3
 
0.4%
13 3
 
0.4%
12 3
 
0.4%
7 3
 
0.4%
4 3
 
0.4%
11 2
 
0.3%
1 2
 
0.3%
16 2
 
0.3%
Other values (71) 72
 
9.5%
2024-03-14T09:40:38.549263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 675
72.6%
1 51
 
5.5%
2 33
 
3.5%
3 32
 
3.4%
6 26
 
2.8%
5 22
 
2.4%
4 21
 
2.3%
, 19
 
2.0%
7 18
 
1.9%
9 17
 
1.8%
Other values (5) 16
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 907
97.5%
Other Punctuation 19
 
2.0%
Other Letter 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 675
74.4%
1 51
 
5.6%
2 33
 
3.6%
3 32
 
3.5%
6 26
 
2.9%
5 22
 
2.4%
4 21
 
2.3%
7 18
 
2.0%
9 17
 
1.9%
8 12
 
1.3%
Other Letter
ValueCountFrequency (%)
사 1
25.0%
유 1
25.0%
대 1
25.0%
지 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 926
99.6%
Hangul 4
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 675
72.9%
1 51
 
5.5%
2 33
 
3.6%
3 32
 
3.5%
6 26
 
2.8%
5 22
 
2.4%
4 21
 
2.3%
, 19
 
2.1%
7 18
 
1.9%
9 17
 
1.8%
Hangul
ValueCountFrequency (%)
사 1
25.0%
유 1
25.0%
대 1
25.0%
지 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 926
99.6%
Hangul 4
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 675
72.9%
1 51
 
5.5%
2 33
 
3.6%
3 32
 
3.5%
6 26
 
2.8%
5 22
 
2.4%
4 21
 
2.3%
, 19
 
2.1%
7 18
 
1.9%
9 17
 
1.8%
Hangul
ValueCountFrequency (%)
사 1
25.0%
유 1
25.0%
대 1
25.0%
지 1
25.0%

Unnamed: 32
Text

Distinct146
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:38.781926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length1
Mean length1.6061008
Min length1

Characters and Unicode

Total characters1211
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)18.2%

Sample

1st row공사비
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 598
79.3%
135 4
 
0.5%
123 3
 
0.4%
412 2
 
0.3%
52 2
 
0.3%
141 2
 
0.3%
121 2
 
0.3%
57 2
 
0.3%
251 2
 
0.3%
3,847 1
 
0.1%
Other values (136) 136
 
18.0%
2024-03-14T09:40:39.155182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 651
53.8%
1 96
 
7.9%
2 71
 
5.9%
, 70
 
5.8%
3 55
 
4.5%
5 52
 
4.3%
7 44
 
3.6%
8 44
 
3.6%
4 43
 
3.6%
9 41
 
3.4%
Other values (4) 44
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1138
94.0%
Other Punctuation 70
 
5.8%
Other Letter 3
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 651
57.2%
1 96
 
8.4%
2 71
 
6.2%
3 55
 
4.8%
5 52
 
4.6%
7 44
 
3.9%
8 44
 
3.9%
4 43
 
3.8%
9 41
 
3.6%
6 41
 
3.6%
Other Letter
ValueCountFrequency (%)
공 1
33.3%
사 1
33.3%
비 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1208
99.8%
Hangul 3
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 651
53.9%
1 96
 
7.9%
2 71
 
5.9%
, 70
 
5.8%
3 55
 
4.6%
5 52
 
4.3%
7 44
 
3.6%
8 44
 
3.6%
4 43
 
3.6%
9 41
 
3.4%
Hangul
ValueCountFrequency (%)
공 1
33.3%
사 1
33.3%
비 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1208
99.8%
Hangul 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 651
53.9%
1 96
 
7.9%
2 71
 
5.9%
, 70
 
5.8%
3 55
 
4.6%
5 52
 
4.3%
7 44
 
3.6%
8 44
 
3.6%
4 43
 
3.6%
9 41
 
3.4%
Hangul
ValueCountFrequency (%)
공 1
33.3%
사 1
33.3%
비 1
33.3%

미집행 필지수
Categorical

IMBALANCE 

Distinct46
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
651 
1
 
13
3
 
10
2
 
8
9
 
4
Other values (41)
68 

Length

Max length5
Median length1
Mean length1.0981432
Min length1

Unique

Unique26 ?
Unique (%)3.4%

Sample

1st row국공유지
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 651
86.3%
1 13
 
1.7%
3 10
 
1.3%
2 8
 
1.1%
9 4
 
0.5%
18 4
 
0.5%
11 4
 
0.5%
7 4
 
0.5%
15 3
 
0.4%
21 3
 
0.4%
Other values (36) 50
 
6.6%

Length

2024-03-14T09:40:39.304127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 651
86.3%
1 13
 
1.7%
3 10
 
1.3%
2 8
 
1.1%
9 4
 
0.5%
18 4
 
0.5%
11 4
 
0.5%
7 4
 
0.5%
10 3
 
0.4%
8 3
 
0.4%
Other values (36) 50
 
6.6%

Unnamed: 34
Text

Distinct83
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2024-03-14T09:40:39.479672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.2108753
Min length1

Characters and Unicode

Total characters913
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)6.2%

Sample

1st row사유지
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 589
78.1%
2 10
 
1.3%
1 9
 
1.2%
4 7
 
0.9%
6 7
 
0.9%
5 7
 
0.9%
3 6
 
0.8%
8 6
 
0.8%
16 4
 
0.5%
21 4
 
0.5%
Other values (73) 105
 
13.9%
2024-03-14T09:40:40.116286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 609
66.7%
1 60
 
6.6%
2 46
 
5.0%
4 34
 
3.7%
3 34
 
3.7%
5 32
 
3.5%
6 31
 
3.4%
8 23
 
2.5%
9 19
 
2.1%
7 14
 
1.5%
Other values (4) 11
 
1.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 902
98.8%
Other Punctuation 8
 
0.9%
Other Letter 3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 609
67.5%
1 60
 
6.7%
2 46
 
5.1%
4 34
 
3.8%
3 34
 
3.8%
5 32
 
3.5%
6 31
 
3.4%
8 23
 
2.5%
9 19
 
2.1%
7 14
 
1.6%
Other Letter
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 910
99.7%
Hangul 3
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 609
66.9%
1 60
 
6.6%
2 46
 
5.1%
4 34
 
3.7%
3 34
 
3.7%
5 32
 
3.5%
6 31
 
3.4%
8 23
 
2.5%
9 19
 
2.1%
7 14
 
1.5%
Hangul
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 910
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 609
66.9%
1 60
 
6.6%
2 46
 
5.1%
4 34
 
3.7%
3 34
 
3.7%
5 32
 
3.5%
6 31
 
3.4%
8 23
 
2.5%
9 19
 
2.1%
7 14
 
1.5%
Hangul
ValueCountFrequency (%)
사 1
33.3%
유 1
33.3%
지 1
33.3%

Unnamed: 35
Categorical

IMBALANCE 

Distinct33
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
649 
1
 
19
2
 
16
3
 
8
6
 
8
Other values (28)
 
54

Length

Max length5
Median length1
Mean length1.0557029
Min length1

Unique

Unique18 ?
Unique (%)2.4%

Sample

1st row사유대지
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 649
86.1%
1 19
 
2.5%
2 16
 
2.1%
3 8
 
1.1%
6 8
 
1.1%
7 7
 
0.9%
4 5
 
0.7%
5 5
 
0.7%
11 5
 
0.7%
13 4
 
0.5%
Other values (23) 28
 
3.7%

Length

2024-03-14T09:40:40.279484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 649
86.1%
1 19
 
2.5%
2 16
 
2.1%
3 8
 
1.1%
6 8
 
1.1%
7 7
 
0.9%
4 5
 
0.7%
5 5
 
0.7%
11 5
 
0.7%
13 4
 
0.5%
Other values (23) 28
 
3.7%

Sample

시도시군구대분류중분류세분류시설명최종변경일최초고시번호최종변경고시번호대표지번Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14위치결정연장결정면적집행Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23최초결정일미집행면적Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29미집행 사업비(보상비 및 공사비)Unnamed: 31Unnamed: 32미집행 필지수Unnamed: 34Unnamed: 35
0<NA><NA><NA><NA><NA><NA><NA><NA><NA>시군구읍면동리산본부<NA><NA><NA>집행연장집행면적보상비사업비착공일준공일<NA>미집행연장국공유지사유지국공유대지사유대지사유지사유대지공사비국공유지사유지사유대지
1전라북도전주시공원근린공원<NA>1호근린공원 1882015-11-18전주시고시 제2012-67호전주시고시 제2015-172호전주시 덕진구팔복동2가<NA><NA>505<NA>팔복동2가 505대(팔복지구근린공원)010,788010,78800<NA><NA>2012-06-2500000000000
2전라북도전주시공원근린공원<NA>가련산공원 32015-08-28건설교통부고시 제2188호전주시고시 제2015-112호전주시 덕진구덕진동2가<NA>산27<NA>덕진동2가 산 27-1 일원(가련산공원)0324,5600324,56000<NA><NA>1966-02-1000000000000
3전라북도전주시공원근린공원<NA>거마공원 141986-05-08건설부고시 제206호-전주시 완산구삼천동1가<NA><NA>707<NA>삼천동1가 707공(거마공원)09,92609,92600<NA><NA>1986-05-0800000000000
4전라북도전주시공원근린공원<NA>공원 1 만성지구2011-12-29전주시고시 제2008-108호-전주시 덕진구만성동<NA><NA>458<NA>만성동 458답 일원(만성1공원)058,582058,58200<NA><NA>2009-12-1200000000000
5전라북도전주시공원근린공원<NA>공원 1 하가지구2009-11-09전라북도고시 제2005-193호-전주시 덕진구덕진동2가<NA><NA>682<NA>덕진동2가 682일원(하늘공원)025,864025,86400<NA><NA>2005-08-0500000000000
6전라북도전주시공원근린공원<NA>공원 1 혁신도시2014-02-03건설교통부고시 제2008-91호국토교통부공고 제2014-72호전주시 덕진구장동<NA><NA>1073<NA>장동 1073-1(엽순공원)[232-3전]089,303089,30300<NA><NA>2008-03-0400000000000
7전라북도전주시공원근린공원<NA>공원 2 만성지구2011-12-29전주시고시 제2008-108호-전주시 덕진구만성동<NA><NA>962<NA>만성동 962전 일원(만성2공원)016,604016,60400<NA><NA>2009-12-1200000000000
8전라북도전주시공원근린공원<NA>공원 2 혁신도시2014-02-03건설교통부고시 제2008-91호국토교통부공고 제2014-72호전주시 덕진구장동<NA><NA>1065<NA>장동 1065(원장동공원)[산 189-2임]013,448013,44800<NA><NA>2008-03-0400000000000
9전라북도전주시공원근린공원<NA>공원 4 혁신도시2015-05-01건설교통부고시 제2008-91호국토교통부공고 제2015-544호전주시 완산구중동<NA><NA>832<NA>중동 832(정문공원)[276답]015,287015,28700<NA><NA>2008-03-0400000000000
시도시군구대분류중분류세분류시설명최종변경일최초고시번호최종변경고시번호대표지번Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14위치결정연장결정면적집행Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23최초결정일미집행면적Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29미집행 사업비(보상비 및 공사비)Unnamed: 31Unnamed: 32미집행 필지수Unnamed: 34Unnamed: 35
744전라북도부안군공원근린공원<NA>근린공원602(원장공원)2013-01-041994-03-12부안군고시 제2013-1호부안군상서면장동리<NA>406<NA>줄포면 장동리 406-41임053,9590000<NA><NA>1994-03-1205,17748,7820351473300512
745전라북도부안군공원근린공원<NA>근린공원7(수문공원)2013-01-04전북고시 제79호부안군고시 제2013-1호부안군계화면창북리<NA>336<NA>계화면 창북리 336-4임025,1370000<NA><NA>1977-04-280025,13700457000250
746전라북도부안군공원근린공원<NA>근린공원8(화상공원)2013-01-04전북고시 제79호부안군고시 제2013-1호부안군계화면창북리<NA>410<NA>계화면 창북리 410묘015,7650000<NA><NA>1977-04-2802,29513,47000273000140
747전라북도부안군공원근린공원<NA>근린공원9(중앙공원)2013-01-04전북고시 제79호부안군고시 제2013-1호부안군계화면창북리<NA>484<NA>계화면 창북리 484대07,3100000<NA><NA>1977-04-2801,7185,59209267290081
748전라북도부안군공원체육공원<NA>백련공원 3032013-01-04전북고시 제2008-332호부안군고시 제2013-1호부안군하서면백련리<NA>1113<NA>하서면 백련리 1113-2번지 일원010,200010,20000<NA><NA>2008-11-1400000000000
749전라북도부안군공원소공원<NA>소공원1150(진서공원)2013-09-06전북고시 제2005-86호전북고시 제2013-217호부안군진서면곰소리<NA>883<NA>진서면 곰소리 883공05,4400000<NA><NA>2005-04-2205,44000000390100
750전라북도부안군공원문화공원<NA>문화공원11(부안공원)2013-09-06전북고시 제2013-217호전북고시 제2013-217호부안군부안읍동중리<NA>239<NA>부안읍 동중리 239-2번지 일원014,8750000<NA><NA>2013-09-06014,77010501035800021
751전라북도부안군공원문화공원<NA>문화공원14(제3농공단지)2014-03-26부안군부안군부안군행안면역리<NA>123<NA>행안면 역리 123-3대 일원01,7480000<NA><NA>2014-03-26001,748006500010
752전라북도부안군공원문화공원<NA>문화공원4(매창공원)2013-01-04전북고시 제99-1호부안군고시 제2013-1호부안군부안읍서외리<NA>455<NA>부안읍 서외리 455-83번지 일원040,880016,58500<NA><NA>1999-01-060024,29504021,6631600241
753조회건수 : 752<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>049,790,888018,599,242231,706364,931<NA><NA><NA>05,672,33925,519,30717,256370,8161,591,524195,1751,013,7444,80824,9802,220