Overview

Dataset statistics

Number of variables4
Number of observations555
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.5 KiB
Average record size in memory32.2 B

Variable types

Text3
Categorical1

Alerts

재산소재지 has unique valuesUnique

Reproduction

Analysis started2024-03-14 03:11:53.296673
Analysis finished2024-03-14 03:11:53.537302
Duration0.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Text

Distinct540
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-03-14T12:11:53.807023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.7513514
Min length1

Characters and Unicode

Total characters1527
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

Unique538 ?
Unique (%)96.9%

Sample

1st row-
2nd row-
3rd row1
4th row2
5th row3
ValueCountFrequency (%)
15
 
2.7%
348 2
 
0.4%
403 1
 
0.2%
371 1
 
0.2%
358 1
 
0.2%
359 1
 
0.2%
360 1
 
0.2%
361 1
 
0.2%
363 1
 
0.2%
355 1
 
0.2%
Other values (530) 530
95.5%
2024-03-14T12:11:54.243076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 215
14.1%
1 214
14.0%
2 214
14.0%
4 205
13.4%
5 144
9.4%
8 105
6.9%
6 104
6.8%
7 104
6.8%
9 104
6.8%
0 103
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1512
99.0%
Dash Punctuation 15
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 215
14.2%
1 214
14.2%
2 214
14.2%
4 205
13.6%
5 144
9.5%
8 105
6.9%
6 104
6.9%
7 104
6.9%
9 104
6.9%
0 103
6.8%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1527
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 215
14.1%
1 214
14.0%
2 214
14.0%
4 205
13.4%
5 144
9.4%
8 105
6.9%
6 104
6.8%
7 104
6.8%
9 104
6.8%
0 103
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1527
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 215
14.1%
1 214
14.0%
2 214
14.0%
4 205
13.4%
5 144
9.4%
8 105
6.9%
6 104
6.8%
7 104
6.8%
9 104
6.8%
0 103
6.7%

재산소재지
Text

UNIQUE 

Distinct555
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-03-14T12:11:54.432507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length16.145946
Min length10

Characters and Unicode

Total characters8961
Distinct characters176
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique555 ?
Unique (%)100.0%

Sample

1st row전라북도 계 : 540필지
2nd row전주시 계 : 83필지
3rd row 전주시 완산구 중앙동1가 7­3
4th row 전주시 완산구 풍남동1가 14­0
5th row 전주시 완산구 교동 50­8
ValueCountFrequency (%)
전주시 84
 
7.4%
고창군 75
 
6.6%
완산구 52
 
4.6%
부안면 31
 
2.7%
수앙리 31
 
2.7%
부안군 28
 
2.5%
고창읍 18
 
1.6%
계 15
 
1.3%
15
 
1.3%
임실군 12
 
1.1%
Other values (656) 770
68.1%
2024-03-14T12:11:54.751907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1123
 
12.5%
­ 540
 
6.0%
1 484
 
5.4%
리 419
 
4.7%
면 350
 
3.9%
시 299
 
3.3%
2 295
 
3.3%
군 284
 
3.2%
0 262
 
2.9%
산 252
 
2.8%
Other values (166) 4653
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4880
54.5%
Decimal Number 2403
26.8%
Space Separator 1123
 
12.5%
Format 540
 
6.0%
Other Punctuation 15
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 419
 
8.6%
면 350
 
7.2%
시 299
 
6.1%
군 284
 
5.8%
산 252
 
5.2%
주 160
 
3.3%
동 157
 
3.2%
고 127
 
2.6%
읍 125
 
2.6%
부 121
 
2.5%
Other values (153) 2586
53.0%
Decimal Number
ValueCountFrequency (%)
1 484
20.1%
2 295
12.3%
0 262
10.9%
3 246
10.2%
4 241
10.0%
9 229
9.5%
7 166
 
6.9%
6 164
 
6.8%
5 160
 
6.7%
8 156
 
6.5%
Space Separator
ValueCountFrequency (%)
1123
100.0%
Format
ValueCountFrequency (%)
­ 540
100.0%
Other Punctuation
ValueCountFrequency (%)
: 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4880
54.5%
Common 4081
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 419
 
8.6%
면 350
 
7.2%
시 299
 
6.1%
군 284
 
5.8%
산 252
 
5.2%
주 160
 
3.3%
동 157
 
3.2%
고 127
 
2.6%
읍 125
 
2.6%
부 121
 
2.5%
Other values (153) 2586
53.0%
Common
ValueCountFrequency (%)
1123
27.5%
­ 540
13.2%
1 484
11.9%
2 295
 
7.2%
0 262
 
6.4%
3 246
 
6.0%
4 241
 
5.9%
9 229
 
5.6%
7 166
 
4.1%
6 164
 
4.0%
Other values (3) 331
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4880
54.5%
ASCII 3541
39.5%
None 540
 
6.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1123
31.7%
1 484
13.7%
2 295
 
8.3%
0 262
 
7.4%
3 246
 
6.9%
4 241
 
6.8%
9 229
 
6.5%
7 166
 
4.7%
6 164
 
4.6%
5 160
 
4.5%
Other values (2) 171
 
4.8%
None
ValueCountFrequency (%)
­ 540
100.0%
Hangul
ValueCountFrequency (%)
리 419
 
8.6%
면 350
 
7.2%
시 299
 
6.1%
군 284
 
5.8%
산 252
 
5.2%
주 160
 
3.3%
동 157
 
3.2%
고 127
 
2.6%
읍 125
 
2.6%
부 121
 
2.5%
Other values (153) 2586
53.0%

지목
Categorical

Distinct18
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
답
190 
전
105 
대
70 
도로
63 
임야
48 
Other values (13)
79 

Length

Max length4
Median length1
Mean length1.427027
Min length1

Unique

Unique5 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
답 190
34.2%
전 105
18.9%
대 70
 
12.6%
도로 63
 
11.4%
임야 48
 
8.6%
잡종지 46
 
8.3%
- 15
 
2.7%
구거 3
 
0.5%
과수원 2
 
0.4%
묘지 2
 
0.4%
Other values (8) 11
 
2.0%

Length

2024-03-14T12:11:54.860429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
답 190
34.2%
전 105
18.9%
대 70
 
12.6%
도로 63
 
11.4%
임야 48
 
8.6%
잡종지 46
 
8.3%
15
 
2.7%
구거 3
 
0.5%
학교용지 2
 
0.4%
창고용지 2
 
0.4%
Other values (8) 11
 
2.0%

면적(㎡)
Text

Distinct407
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-03-14T12:11:55.178020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.1279279
Min length1

Characters and Unicode

Total characters1736
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

Unique310 ?
Unique (%)55.9%

Sample

1st row451,572
2nd row66,789
3rd row251
4th row10
5th row23
ValueCountFrequency (%)
23 9
 
1.6%
7 6
 
1.1%
122 5
 
0.9%
138 4
 
0.7%
3 4
 
0.7%
63 4
 
0.7%
235 4
 
0.7%
54 4
 
0.7%
40 4
 
0.7%
53 3
 
0.5%
Other values (397) 508
91.5%
2024-03-14T12:11:55.686768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 274
15.8%
2 212
12.2%
3 204
11.8%
4 143
8.2%
6 141
8.1%
5 141
8.1%
7 130
7.5%
0 127
7.3%
9 127
7.3%
8 119
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1618
93.2%
Other Punctuation 118
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 274
16.9%
2 212
13.1%
3 204
12.6%
4 143
8.8%
6 141
8.7%
5 141
8.7%
7 130
8.0%
0 127
7.8%
9 127
7.8%
8 119
7.4%
Other Punctuation
ValueCountFrequency (%)
, 118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1736
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 274
15.8%
2 212
12.2%
3 204
11.8%
4 143
8.2%
6 141
8.1%
5 141
8.1%
7 130
7.5%
0 127
7.3%
9 127
7.3%
8 119
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 274
15.8%
2 212
12.2%
3 204
11.8%
4 143
8.2%
6 141
8.1%
5 141
8.1%
7 130
7.5%
0 127
7.3%
9 127
7.3%
8 119
6.9%

Missing values

2024-03-14T12:11:53.447216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:11:53.510609image/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

순번재산소재지지목면적(㎡)
0-전라북도 계 : 540필지-451,572
1-전주시 계 : 83필지-66,789
21전주시 완산구 중앙동1가 7­3대251
32전주시 완산구 풍남동1가 14­0대10
43전주시 완산구 교동 50­8대23
54전주시 완산구 교동 50­9전10
65전주시 완산구 교동 981­4대96
76전주시 완산구 교동 981­8전30
87전주시 완산구 교동 981­11전66
98전주시 완산구 교동 989­2대82
순번재산소재지지목면적(㎡)
545530부안군 진서면 곰소리 428­0임야2,740
546531부안군 진서면 곰소리 467­0학교용지7
547532부안군 백산면 신평리 142­86대23
548533부안군 상서면 고잔리 52­19답127
549534부안군 상서면 고잔리 505­5답69
550535부안군 상서면 용서리 725­4답55
551536부안군 상서면 장동리 981­13답535
552537부안군 하서면 장신리 2086­0답216
553538부안군 줄포 면장동리 481­1답179
554539부안군 줄포면 장동리 696­1전409