Overview

Dataset statistics

Number of variables23
Number of observations55
Missing cells270
Missing cells (%)21.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.0 KiB
Average record size in memory186.4 B

Variable types

Categorical5
Text18

Dataset

Description2020년 건축허가 통계 자료입니다.(시군별, 건축종별(신축,증축·개축·이전·대수선,용도변경), 면적, 건 수, 동 수)
Author경상남도
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15050512

Alerts

신축.1 has 18 (32.7%) missing valuesMissing
신축.2 has 18 (32.7%) missing valuesMissing
신축.3 has 18 (32.7%) missing valuesMissing
신축.4 has 18 (32.7%) missing valuesMissing
신축.5 has 18 (32.7%) missing valuesMissing
신축.6 has 18 (32.7%) missing valuesMissing
증축/개축/이전/대수선.1 has 18 (32.7%) missing valuesMissing
증축/개축/이전/대수선.2 has 18 (32.7%) missing valuesMissing
증축/개축/이전/대수선.3 has 18 (32.7%) missing valuesMissing
증축/개축/이전/대수선.5 has 18 (32.7%) missing valuesMissing
증축/개축/이전/대수선.6 has 18 (32.7%) missing valuesMissing
용도변경.1 has 18 (32.7%) missing valuesMissing
용도변경.2 has 18 (32.7%) missing valuesMissing
용도변경.3 has 18 (32.7%) missing valuesMissing
용도변경.5 has 18 (32.7%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:21:16.872925
Analysis finished2023-12-11 00:21:17.364294
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct19
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Memory size572.0 B
의령군
 
3
창원시
 
3
진주시
 
3
통영시
 
3
사천시
 
3
Other values (14)
40 

Length

Max length3
Median length3
Mean length2.9818182
Min length2

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row지역
2nd row창원시
3rd row창원시
4th row창원시
5th row진주시

Common Values

ValueCountFrequency (%)
의령군 3
 
5.5%
창원시 3
 
5.5%
진주시 3
 
5.5%
통영시 3
 
5.5%
사천시 3
 
5.5%
김해시 3
 
5.5%
밀양시 3
 
5.5%
거제시 3
 
5.5%
양산시 3
 
5.5%
합천군 3
 
5.5%
Other values (9) 25
45.5%

Length

2023-12-11T09:21:17.419749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의령군 3
 
5.5%
함안군 3
 
5.5%
거창군 3
 
5.5%
함양군 3
 
5.5%
산청군 3
 
5.5%
하동군 3
 
5.5%
남해군 3
 
5.5%
고성군 3
 
5.5%
창녕군 3
 
5.5%
합천군 3
 
5.5%
Other values (9) 25
45.5%

구분
Categorical

Distinct4
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size572.0 B
건수
18 
동수
18 
연면적
18 
구분
 
1

Length

Max length3
Median length2
Mean length2.3272727
Min length2

Unique

Unique1 ?
Unique (%)1.8%

Sample

1st row구분
2nd row건수
3rd row동수
4th row연면적
5th row건수

Common Values

ValueCountFrequency (%)
건수 18
32.7%
동수 18
32.7%
연면적 18
32.7%
구분 1
 
1.8%

Length

2023-12-11T09:21:17.526553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:21:17.613046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건수 18
32.7%
동수 18
32.7%
연면적 18
32.7%
구분 1
 
1.8%

신축
Text

Distinct54
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T09:21:17.777554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length4
Mean length5.2
Min length1

Characters and Unicode

Total characters286
Distinct characters13
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

Unique53 ?
Unique (%)96.4%

Sample

1st row계
2nd row563
3rd row743
4th row628,474
5th row391
ValueCountFrequency (%)
391 2
 
3.6%
153,829 1
 
1.8%
610 1
 
1.8%
413 1
 
1.8%
78,631 1
 
1.8%
377 1
 
1.8%
568 1
 
1.8%
133,324 1
 
1.8%
400 1
 
1.8%
676 1
 
1.8%
Other values (44) 44
80.0%
2023-12-11T09:21:18.062302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
18.9%
1 29
10.1%
3 26
9.1%
4 25
8.7%
6 23
8.0%
9 21
 
7.3%
8 21
 
7.3%
5 20
 
7.0%
, 19
 
6.6%
7 17
 
5.9%
Other values (3) 31
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 212
74.1%
Space Separator 54
 
18.9%
Other Punctuation 19
 
6.6%
Other Letter 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
13.7%
3 26
12.3%
4 25
11.8%
6 23
10.8%
9 21
9.9%
8 21
9.9%
5 20
9.4%
7 17
8.0%
0 16
7.5%
2 14
6.6%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Other Letter
ValueCountFrequency (%)
계 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 285
99.7%
Hangul 1
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
54
18.9%
1 29
10.2%
3 26
9.1%
4 25
8.8%
6 23
8.1%
9 21
 
7.4%
8 21
 
7.4%
5 20
 
7.0%
, 19
 
6.7%
7 17
 
6.0%
Other values (2) 30
10.5%
Hangul
ValueCountFrequency (%)
계 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 285
99.7%
Hangul 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
18.9%
1 29
10.2%
3 26
9.1%
4 25
8.8%
6 23
8.1%
9 21
 
7.4%
8 21
 
7.4%
5 20
 
7.0%
, 19
 
6.7%
7 17
 
6.0%
Other values (2) 30
10.5%
Hangul
ValueCountFrequency (%)
계 1
100.0%

신축.1
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:18.257756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length5.5945946
Min length3

Characters and Unicode

Total characters207
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

Unique37 ?
Unique (%)100.0%

Sample

1st row철근콘크리트
2nd row329
3rd row485,984
4th row192
5th row95,156
ValueCountFrequency (%)
140 1
 
2.7%
61 1
 
2.7%
91 1
 
2.7%
15,659 1
 
2.7%
62 1
 
2.7%
20,523 1
 
2.7%
203 1
 
2.7%
107,570 1
 
2.7%
219 1
 
2.7%
121,885 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T09:21:18.638978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
17.4%
1 25
12.1%
, 19
9.2%
2 18
8.7%
9 17
8.2%
5 16
7.7%
8 14
 
6.8%
4 14
 
6.8%
0 13
 
6.3%
6 12
 
5.8%
Other values (8) 23
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 146
70.5%
Space Separator 36
 
17.4%
Other Punctuation 19
 
9.2%
Other Letter 6
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
17.1%
2 18
12.3%
9 17
11.6%
5 16
11.0%
8 14
9.6%
4 14
9.6%
0 13
8.9%
6 12
8.2%
3 9
 
6.2%
7 8
 
5.5%
Other Letter
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 201
97.1%
Hangul 6
 
2.9%

Most frequent character per script

Common
ValueCountFrequency (%)
36
17.9%
1 25
12.4%
, 19
9.5%
2 18
9.0%
9 17
8.5%
5 16
8.0%
8 14
 
7.0%
4 14
 
7.0%
0 13
 
6.5%
6 12
 
6.0%
Other values (2) 17
8.5%
Hangul
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 201
97.1%
Hangul 6
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
17.9%
1 25
12.4%
, 19
9.5%
2 18
9.0%
9 17
8.5%
5 16
8.0%
8 14
 
7.0%
4 14
 
7.0%
0 13
 
6.5%
6 12
 
6.0%
Other values (2) 17
8.5%
Hangul
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%

신축.2
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:18.892094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.5405405
Min length2

Characters and Unicode

Total characters205
Distinct characters14
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

Unique37 ?
Unique (%)100.0%

Sample

1st row철골
2nd row369
3rd row89,495
4th row294
5th row117,225
ValueCountFrequency (%)
331 1
 
2.7%
278 1
 
2.7%
265 1
 
2.7%
60,369 1
 
2.7%
467 1
 
2.7%
109,904 1
 
2.7%
394 1
 
2.7%
50,302 1
 
2.7%
232 1
 
2.7%
26,470 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T09:21:19.222998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
17.6%
2 20
9.8%
3 19
9.3%
4 18
8.8%
, 18
8.8%
1 16
7.8%
9 16
7.8%
0 14
 
6.8%
7 13
 
6.3%
5 13
 
6.3%
Other values (4) 22
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 149
72.7%
Space Separator 36
 
17.6%
Other Punctuation 18
 
8.8%
Other Letter 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 20
13.4%
3 19
12.8%
4 18
12.1%
1 16
10.7%
9 16
10.7%
0 14
9.4%
7 13
8.7%
5 13
8.7%
6 11
7.4%
8 9
6.0%
Other Letter
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 203
99.0%
Hangul 2
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
36
17.7%
2 20
9.9%
3 19
9.4%
4 18
8.9%
, 18
8.9%
1 16
7.9%
9 16
7.9%
0 14
 
6.9%
7 13
 
6.4%
5 13
 
6.4%
Other values (2) 20
9.9%
Hangul
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 203
99.0%
Hangul 2
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
17.7%
2 20
9.9%
3 19
9.4%
4 18
8.9%
, 18
8.9%
1 16
7.9%
9 16
7.9%
0 14
 
6.9%
7 13
 
6.4%
5 13
 
6.4%
Other values (2) 20
9.9%
Hangul
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%

신축.3
Text

MISSING 

Distinct25
Distinct (%)67.6%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:19.384769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.8108108
Min length2

Characters and Unicode

Total characters104
Distinct characters12
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

Unique18 ?
Unique (%)48.6%

Sample

1st row조적
2nd row3
3rd row169
4th row1
5th row81
ValueCountFrequency (%)
1 5
 
13.5%
2 4
 
10.8%
5 2
 
5.4%
3 2
 
5.4%
49 2
 
5.4%
6 2
 
5.4%
4 2
 
5.4%
조적 1
 
2.7%
120 1
 
2.7%
861 1
 
2.7%
Other values (15) 15
40.5%
2023-12-11T09:21:19.684274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
34.6%
1 21
20.2%
2 9
 
8.7%
9 7
 
6.7%
3 6
 
5.8%
5 5
 
4.8%
4 5
 
4.8%
6 5
 
4.8%
8 5
 
4.8%
0 3
 
2.9%
Other values (2) 2
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
63.5%
Space Separator 36
34.6%
Other Letter 2
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
31.8%
2 9
13.6%
9 7
 
10.6%
3 6
 
9.1%
5 5
 
7.6%
4 5
 
7.6%
6 5
 
7.6%
8 5
 
7.6%
0 3
 
4.5%
Other Letter
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102
98.1%
Hangul 2
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
36
35.3%
1 21
20.6%
2 9
 
8.8%
9 7
 
6.9%
3 6
 
5.9%
5 5
 
4.9%
4 5
 
4.9%
6 5
 
4.9%
8 5
 
4.9%
0 3
 
2.9%
Hangul
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102
98.1%
Hangul 2
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
35.3%
1 21
20.6%
2 9
 
8.8%
9 7
 
6.9%
3 6
 
5.9%
5 5
 
4.9%
4 5
 
4.9%
6 5
 
4.9%
8 5
 
4.9%
0 3
 
2.9%
Hangul
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%

신축.4
Text

MISSING 

Distinct19
Distinct (%)51.4%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:19.822494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length2
Mean length3.1081081
Min length2

Characters and Unicode

Total characters115
Distinct characters15
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

Unique16 ?
Unique (%)43.2%

Sample

1st row철골철근
2nd row7
3rd row49,986
4th row0
5th row319
ValueCountFrequency (%)
0 13
35.1%
1 6
16.2%
7 2
 
5.4%
5,672 1
 
2.7%
철골철근 1
 
2.7%
2 1
 
2.7%
91 1
 
2.7%
139 1
 
2.7%
8,759 1
 
2.7%
5 1
 
2.7%
Other values (9) 9
24.3%
2023-12-11T09:21:20.080746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
31.3%
0 14
 
12.2%
1 13
 
11.3%
9 10
 
8.7%
, 7
 
6.1%
7 6
 
5.2%
3 5
 
4.3%
8 5
 
4.3%
2 5
 
4.3%
5 5
 
4.3%
Other values (5) 9
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
59.1%
Space Separator 36
31.3%
Other Punctuation 7
 
6.1%
Other Letter 4
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.6%
1 13
19.1%
9 10
14.7%
7 6
8.8%
3 5
 
7.4%
8 5
 
7.4%
2 5
 
7.4%
5 5
 
7.4%
6 4
 
5.9%
4 1
 
1.5%
Other Letter
ValueCountFrequency (%)
철 2
50.0%
골 1
25.0%
근 1
25.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 111
96.5%
Hangul 4
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
36
32.4%
0 14
 
12.6%
1 13
 
11.7%
9 10
 
9.0%
, 7
 
6.3%
7 6
 
5.4%
3 5
 
4.5%
8 5
 
4.5%
2 5
 
4.5%
5 5
 
4.5%
Other values (2) 5
 
4.5%
Hangul
ValueCountFrequency (%)
철 2
50.0%
골 1
25.0%
근 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 111
96.5%
Hangul 4
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
32.4%
0 14
 
12.6%
1 13
 
11.7%
9 10
 
9.0%
, 7
 
6.3%
7 6
 
5.4%
3 5
 
4.5%
8 5
 
4.5%
2 5
 
4.5%
5 5
 
4.5%
Other values (2) 5
 
4.5%
Hangul
ValueCountFrequency (%)
철 2
50.0%
골 1
25.0%
근 1
25.0%

신축.5
Text

MISSING 

Distinct35
Distinct (%)94.6%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:20.300211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.2702703
Min length2

Characters and Unicode

Total characters158
Distinct characters14
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

Unique33 ?
Unique (%)89.2%

Sample

1st row나무
2nd row24
3rd row2,528
4th row34
5th row3,489
ValueCountFrequency (%)
17 2
 
5.4%
34 2
 
5.4%
3,794 1
 
2.7%
2,582 1
 
2.7%
42 1
 
2.7%
3,808 1
 
2.7%
45 1
 
2.7%
4,079 1
 
2.7%
35 1
 
2.7%
5,855 1
 
2.7%
Other values (25) 25
67.6%
2023-12-11T09:21:20.655406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
22.8%
, 16
10.1%
4 15
9.5%
3 12
 
7.6%
2 12
 
7.6%
7 11
 
7.0%
5 11
 
7.0%
9 11
 
7.0%
1 10
 
6.3%
8 10
 
6.3%
Other values (4) 14
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 104
65.8%
Space Separator 36
 
22.8%
Other Punctuation 16
 
10.1%
Other Letter 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 15
14.4%
3 12
11.5%
2 12
11.5%
7 11
10.6%
5 11
10.6%
9 11
10.6%
1 10
9.6%
8 10
9.6%
6 8
7.7%
0 4
 
3.8%
Other Letter
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 156
98.7%
Hangul 2
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
36
23.1%
, 16
10.3%
4 15
9.6%
3 12
 
7.7%
2 12
 
7.7%
7 11
 
7.1%
5 11
 
7.1%
9 11
 
7.1%
1 10
 
6.4%
8 10
 
6.4%
Other values (2) 12
 
7.7%
Hangul
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 156
98.7%
Hangul 2
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
23.1%
, 16
10.3%
4 15
9.6%
3 12
 
7.7%
2 12
 
7.7%
7 11
 
7.1%
5 11
 
7.1%
9 11
 
7.1%
1 10
 
6.4%
8 10
 
6.4%
Other values (2) 12
 
7.7%
Hangul
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%

신축.6
Text

MISSING 

Distinct33
Distinct (%)89.2%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:20.818918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.6756757
Min length2

Characters and Unicode

Total characters136
Distinct characters14
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

Unique30 ?
Unique (%)81.1%

Sample

1st row기타
2nd row11
3rd row312
4th row22
5th row628
ValueCountFrequency (%)
7 3
 
8.1%
15 2
 
5.4%
9 2
 
5.4%
1,115 1
 
2.7%
697 1
 
2.7%
147 1
 
2.7%
35 1
 
2.7%
1,677 1
 
2.7%
16 1
 
2.7%
기타 1
 
2.7%
Other values (23) 23
62.2%
2023-12-11T09:21:21.084035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
26.5%
1 24
17.6%
6 12
 
8.8%
2 11
 
8.1%
5 10
 
7.4%
7 8
 
5.9%
9 7
 
5.1%
3 7
 
5.1%
, 7
 
5.1%
4 5
 
3.7%
Other values (4) 9
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
66.9%
Space Separator 36
 
26.5%
Other Punctuation 7
 
5.1%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
26.4%
6 12
13.2%
2 11
12.1%
5 10
11.0%
7 8
 
8.8%
9 7
 
7.7%
3 7
 
7.7%
4 5
 
5.5%
0 4
 
4.4%
8 3
 
3.3%
Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 134
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
36
26.9%
1 24
17.9%
6 12
 
9.0%
2 11
 
8.2%
5 10
 
7.5%
7 8
 
6.0%
9 7
 
5.2%
3 7
 
5.2%
, 7
 
5.2%
4 5
 
3.7%
Other values (2) 7
 
5.2%
Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 134
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
26.9%
1 24
17.9%
6 12
 
9.0%
2 11
 
8.2%
5 10
 
7.5%
7 8
 
6.0%
9 7
 
5.2%
3 7
 
5.2%
, 7
 
5.2%
4 5
 
3.7%
Other values (2) 7
 
5.2%
Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

증축/개축/이전/대수선
Text

Distinct54
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T09:21:21.287329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length4
Mean length4.9818182
Min length1

Characters and Unicode

Total characters274
Distinct characters13
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

Unique53 ?
Unique (%)96.4%

Sample

1st row계
2nd row370
3rd row562
4th row207,055
5th row230
ValueCountFrequency (%)
136 2
 
3.6%
21,113 1
 
1.8%
886 1
 
1.8%
158 1
 
1.8%
81,669 1
 
1.8%
169 1
 
1.8%
419 1
 
1.8%
60,430 1
 
1.8%
205 1
 
1.8%
386 1
 
1.8%
Other values (44) 44
80.0%
2023-12-11T09:21:21.719301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
19.7%
1 37
13.5%
3 30
10.9%
6 21
 
7.7%
2 20
 
7.3%
8 19
 
6.9%
, 18
 
6.6%
0 17
 
6.2%
5 16
 
5.8%
4 15
 
5.5%
Other values (3) 27
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 201
73.4%
Space Separator 54
 
19.7%
Other Punctuation 18
 
6.6%
Other Letter 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 37
18.4%
3 30
14.9%
6 21
10.4%
2 20
10.0%
8 19
9.5%
0 17
8.5%
5 16
8.0%
4 15
7.5%
7 14
 
7.0%
9 12
 
6.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Other Letter
ValueCountFrequency (%)
계 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 273
99.6%
Hangul 1
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
54
19.8%
1 37
13.6%
3 30
11.0%
6 21
 
7.7%
2 20
 
7.3%
8 19
 
7.0%
, 18
 
6.6%
0 17
 
6.2%
5 16
 
5.9%
4 15
 
5.5%
Other values (2) 26
9.5%
Hangul
ValueCountFrequency (%)
계 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 273
99.6%
Hangul 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
19.8%
1 37
13.6%
3 30
11.0%
6 21
 
7.7%
2 20
 
7.3%
8 19
 
7.0%
, 18
 
6.6%
0 17
 
6.2%
5 16
 
5.9%
4 15
 
5.5%
Other values (2) 26
9.5%
Hangul
ValueCountFrequency (%)
계 1
100.0%

증축/개축/이전/대수선.1
Text

MISSING 

Distinct36
Distinct (%)97.3%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:21.917277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.8108108
Min length3

Characters and Unicode

Total characters178
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

Unique35 ?
Unique (%)94.6%

Sample

1st row철근콘크리트
2nd row148
3rd row94,656
4th row88
5th row43,742
ValueCountFrequency (%)
51 2
 
5.4%
52 1
 
2.7%
60 1
 
2.7%
4,734 1
 
2.7%
17,373 1
 
2.7%
33 1
 
2.7%
1,401 1
 
2.7%
40 1
 
2.7%
3,922 1
 
2.7%
철근콘크리트 1
 
2.7%
Other values (26) 26
70.3%
2023-12-11T09:21:22.282663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
20.2%
1 21
11.8%
, 18
10.1%
2 15
8.4%
3 13
 
7.3%
4 12
 
6.7%
5 12
 
6.7%
9 12
 
6.7%
6 10
 
5.6%
7 9
 
5.1%
Other values (8) 20
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118
66.3%
Space Separator 36
 
20.2%
Other Punctuation 18
 
10.1%
Other Letter 6
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
17.8%
2 15
12.7%
3 13
11.0%
4 12
10.2%
5 12
10.2%
9 12
10.2%
6 10
8.5%
7 9
7.6%
0 9
7.6%
8 5
 
4.2%
Other Letter
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 172
96.6%
Hangul 6
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
36
20.9%
1 21
12.2%
, 18
10.5%
2 15
8.7%
3 13
 
7.6%
4 12
 
7.0%
5 12
 
7.0%
9 12
 
7.0%
6 10
 
5.8%
7 9
 
5.2%
Other values (2) 14
 
8.1%
Hangul
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 172
96.6%
Hangul 6
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
20.9%
1 21
12.2%
, 18
10.5%
2 15
8.7%
3 13
 
7.6%
4 12
 
7.0%
5 12
 
7.0%
9 12
 
7.0%
6 10
 
5.8%
7 9
 
5.2%
Other values (2) 14
 
8.1%
Hangul
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%

증축/개축/이전/대수선.2
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:22.515590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.3783784
Min length2

Characters and Unicode

Total characters199
Distinct characters14
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

Unique37 ?
Unique (%)100.0%

Sample

1st row철골
2nd row349
3rd row76,856
4th row224
5th row48,548
ValueCountFrequency (%)
229 1
 
2.7%
257 1
 
2.7%
250 1
 
2.7%
63,092 1
 
2.7%
339 1
 
2.7%
57,190 1
 
2.7%
294 1
 
2.7%
52,219 1
 
2.7%
128 1
 
2.7%
13,500 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T09:21:22.876969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
18.1%
2 18
9.0%
, 18
9.0%
3 17
8.5%
9 15
7.5%
1 15
7.5%
6 14
 
7.0%
5 14
 
7.0%
4 13
 
6.5%
8 13
 
6.5%
Other values (4) 26
13.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 143
71.9%
Space Separator 36
 
18.1%
Other Punctuation 18
 
9.0%
Other Letter 2
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 18
12.6%
3 17
11.9%
9 15
10.5%
1 15
10.5%
6 14
9.8%
5 14
9.8%
4 13
9.1%
8 13
9.1%
7 12
8.4%
0 12
8.4%
Other Letter
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 197
99.0%
Hangul 2
 
1.0%

Most frequent character per script

Common
ValueCountFrequency (%)
36
18.3%
2 18
9.1%
, 18
9.1%
3 17
8.6%
9 15
7.6%
1 15
7.6%
6 14
 
7.1%
5 14
 
7.1%
4 13
 
6.6%
8 13
 
6.6%
Other values (2) 24
12.2%
Hangul
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 197
99.0%
Hangul 2
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
18.3%
2 18
9.1%
, 18
9.1%
3 17
8.6%
9 15
7.6%
1 15
7.6%
6 14
 
7.1%
5 14
 
7.1%
4 13
 
6.6%
8 13
 
6.6%
Other values (2) 24
12.2%
Hangul
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%

증축/개축/이전/대수선.3
Text

MISSING 

Distinct33
Distinct (%)89.2%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:23.071424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.6486486
Min length2

Characters and Unicode

Total characters135
Distinct characters15
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

Unique29 ?
Unique (%)78.4%

Sample

1st row조적
2nd row32
3rd row1,531
4th row12
5th row964
ValueCountFrequency (%)
57 2
 
5.4%
15 2
 
5.4%
18 2
 
5.4%
12 2
 
5.4%
546 1
 
2.7%
14 1
 
2.7%
1,348 1
 
2.7%
38 1
 
2.7%
6 1
 
2.7%
254 1
 
2.7%
Other values (23) 23
62.2%
2023-12-11T09:21:23.443760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
26.7%
1 21
15.6%
2 15
11.1%
5 13
 
9.6%
3 10
 
7.4%
8 8
 
5.9%
4 8
 
5.9%
6 6
 
4.4%
7 5
 
3.7%
, 5
 
3.7%
Other values (5) 8
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
67.4%
Space Separator 36
 
26.7%
Other Punctuation 5
 
3.7%
Other Letter 2
 
1.5%
Dash Punctuation 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
23.1%
2 15
16.5%
5 13
14.3%
3 10
11.0%
8 8
 
8.8%
4 8
 
8.8%
6 6
 
6.6%
7 5
 
5.5%
9 4
 
4.4%
0 1
 
1.1%
Other Letter
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 133
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
36
27.1%
1 21
15.8%
2 15
11.3%
5 13
 
9.8%
3 10
 
7.5%
8 8
 
6.0%
4 8
 
6.0%
6 6
 
4.5%
7 5
 
3.8%
, 5
 
3.8%
Other values (3) 6
 
4.5%
Hangul
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
27.1%
1 21
15.8%
2 15
11.3%
5 13
 
9.8%
3 10
 
7.5%
8 8
 
6.0%
4 8
 
6.0%
6 6
 
4.5%
7 5
 
3.8%
, 5
 
3.8%
Other values (3) 6
 
4.5%
Hangul
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%

증축/개축/이전/대수선.4
Categorical

Distinct17
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size572.0 B
<NA>
18 
0
14 
1
4 
3
3 
2
3 
Other values (12)
13 

Length

Max length7
Median length6
Mean length3.1818182
Min length2

Unique

Unique11 ?
Unique (%)20.0%

Sample

1st row철골철근
2nd row<NA>
3rd row4
4th row33,810
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
32.7%
0 14
25.5%
1 4
 
7.3%
3 3
 
5.5%
2 3
 
5.5%
4 2
 
3.6%
99 1
 
1.8%
33,810 1
 
1.8%
5,682 1
 
1.8%
3,088 1
 
1.8%
Other values (7) 7
 
12.7%

Length

2023-12-11T09:21:23.585096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 18
32.7%
0 14
25.5%
1 4
 
7.3%
3 3
 
5.5%
2 3
 
5.5%
4 2
 
3.6%
48 1
 
1.8%
철골철근 1
 
1.8%
18 1
 
1.8%
1,613 1
 
1.8%
Other values (7) 7
 
12.7%

증축/개축/이전/대수선.5
Text

MISSING 

Distinct33
Distinct (%)89.2%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:23.765028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.4054054
Min length2

Characters and Unicode

Total characters126
Distinct characters15
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

Unique29 ?
Unique (%)78.4%

Sample

1st row나무
2nd row8
3rd row-333
4th row10
5th row1,424
ValueCountFrequency (%)
990 2
 
5.4%
20 2
 
5.4%
5 2
 
5.4%
16 2
 
5.4%
331 1
 
2.7%
119 1
 
2.7%
13 1
 
2.7%
32 1
 
2.7%
11 1
 
2.7%
1,180 1
 
2.7%
Other values (23) 23
62.2%
2023-12-11T09:21:24.147926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
28.6%
1 16
12.7%
3 14
 
11.1%
9 10
 
7.9%
0 9
 
7.1%
2 9
 
7.1%
6 8
 
6.3%
5 8
 
6.3%
7 4
 
3.2%
8 4
 
3.2%
Other values (5) 8
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 85
67.5%
Space Separator 36
28.6%
Other Punctuation 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
18.8%
3 14
16.5%
9 10
11.8%
0 9
10.6%
2 9
10.6%
6 8
9.4%
5 8
9.4%
7 4
 
4.7%
8 4
 
4.7%
4 3
 
3.5%
Other Letter
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
36
29.0%
1 16
12.9%
3 14
 
11.3%
9 10
 
8.1%
0 9
 
7.3%
2 9
 
7.3%
6 8
 
6.5%
5 8
 
6.5%
7 4
 
3.2%
8 4
 
3.2%
Other values (3) 6
 
4.8%
Hangul
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
29.0%
1 16
12.9%
3 14
 
11.3%
9 10
 
8.1%
0 9
 
7.3%
2 9
 
7.3%
6 8
 
6.5%
5 8
 
6.5%
7 4
 
3.2%
8 4
 
3.2%
Other values (3) 6
 
4.8%
Hangul
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%

증축/개축/이전/대수선.6
Text

MISSING 

Distinct33
Distinct (%)89.2%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:24.352747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.4054054
Min length2

Characters and Unicode

Total characters126
Distinct characters14
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

Unique29 ?
Unique (%)78.4%

Sample

1st row기타
2nd row21
3rd row535
4th row5
5th row1,821
ValueCountFrequency (%)
21 2
 
5.4%
13 2
 
5.4%
12 2
 
5.4%
5 2
 
5.4%
222 1
 
2.7%
415 1
 
2.7%
17 1
 
2.7%
103 1
 
2.7%
47 1
 
2.7%
491 1
 
2.7%
Other values (23) 23
62.2%
2023-12-11T09:21:24.753434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
28.6%
1 20
15.9%
2 15
11.9%
7 9
 
7.1%
6 8
 
6.3%
5 7
 
5.6%
3 7
 
5.6%
8 6
 
4.8%
4 6
 
4.8%
9 5
 
4.0%
Other values (4) 7
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 86
68.3%
Space Separator 36
28.6%
Other Punctuation 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
23.3%
2 15
17.4%
7 9
10.5%
6 8
 
9.3%
5 7
 
8.1%
3 7
 
8.1%
8 6
 
7.0%
4 6
 
7.0%
9 5
 
5.8%
0 3
 
3.5%
Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
36
29.0%
1 20
16.1%
2 15
12.1%
7 9
 
7.3%
6 8
 
6.5%
5 7
 
5.6%
3 7
 
5.6%
8 6
 
4.8%
4 6
 
4.8%
9 5
 
4.0%
Other values (2) 5
 
4.0%
Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
29.0%
1 20
16.1%
2 15
12.1%
7 9
 
7.3%
6 8
 
6.5%
5 7
 
5.6%
3 7
 
5.6%
8 6
 
4.8%
4 6
 
4.8%
9 5
 
4.0%
Other values (2) 5
 
4.0%
Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

용도변경
Text

Distinct48
Distinct (%)87.3%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-11T09:21:24.972998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.2
Min length1

Characters and Unicode

Total characters231
Distinct characters13
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

Unique41 ?
Unique (%)74.5%

Sample

1st row계
2nd row400
3rd row411
4th row95,769
5th row103
ValueCountFrequency (%)
22 2
 
3.6%
33 2
 
3.6%
9 2
 
3.6%
16 2
 
3.6%
18 2
 
3.6%
25 2
 
3.6%
103 2
 
3.6%
32 1
 
1.8%
400 1
 
1.8%
21 1
 
1.8%
Other values (38) 38
69.1%
2023-12-11T09:21:25.276586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54
23.4%
2 25
10.8%
1 25
10.8%
3 20
 
8.7%
, 18
 
7.8%
0 17
 
7.4%
9 13
 
5.6%
7 13
 
5.6%
6 12
 
5.2%
5 12
 
5.2%
Other values (3) 22
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 158
68.4%
Space Separator 54
 
23.4%
Other Punctuation 18
 
7.8%
Other Letter 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 25
15.8%
1 25
15.8%
3 20
12.7%
0 17
10.8%
9 13
8.2%
7 13
8.2%
6 12
7.6%
5 12
7.6%
4 11
7.0%
8 10
 
6.3%
Space Separator
ValueCountFrequency (%)
54
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Other Letter
ValueCountFrequency (%)
계 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 230
99.6%
Hangul 1
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
54
23.5%
2 25
10.9%
1 25
10.9%
3 20
 
8.7%
, 18
 
7.8%
0 17
 
7.4%
9 13
 
5.7%
7 13
 
5.7%
6 12
 
5.2%
5 12
 
5.2%
Other values (2) 21
 
9.1%
Hangul
ValueCountFrequency (%)
계 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 230
99.6%
Hangul 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54
23.5%
2 25
10.9%
1 25
10.9%
3 20
 
8.7%
, 18
 
7.8%
0 17
 
7.4%
9 13
 
5.7%
7 13
 
5.7%
6 12
 
5.2%
5 12
 
5.2%
Other values (2) 21
 
9.1%
Hangul
ValueCountFrequency (%)
계 1
100.0%

용도변경.1
Text

MISSING 

Distinct36
Distinct (%)97.3%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:25.470966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length4.4864865
Min length2

Characters and Unicode

Total characters166
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

Unique35 ?
Unique (%)94.6%

Sample

1st row철근콘크리트
2nd row241
3rd row61,914
4th row61
5th row15,262
ValueCountFrequency (%)
13 2
 
5.4%
18,357 1
 
2.7%
637 1
 
2.7%
1,308 1
 
2.7%
10 1
 
2.7%
3,238 1
 
2.7%
8 1
 
2.7%
2,593 1
 
2.7%
3 1
 
2.7%
9 1
 
2.7%
Other values (26) 26
70.3%
2023-12-11T09:21:25.790498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
21.7%
1 23
13.9%
, 16
9.6%
2 16
9.6%
3 13
 
7.8%
6 10
 
6.0%
4 10
 
6.0%
8 9
 
5.4%
7 8
 
4.8%
9 7
 
4.2%
Other values (8) 18
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
65.1%
Space Separator 36
 
21.7%
Other Punctuation 16
 
9.6%
Other Letter 6
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
21.3%
2 16
14.8%
3 13
12.0%
6 10
9.3%
4 10
9.3%
8 9
 
8.3%
7 8
 
7.4%
9 7
 
6.5%
0 7
 
6.5%
5 5
 
4.6%
Other Letter
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 160
96.4%
Hangul 6
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
36
22.5%
1 23
14.4%
, 16
10.0%
2 16
10.0%
3 13
 
8.1%
6 10
 
6.2%
4 10
 
6.2%
8 9
 
5.6%
7 8
 
5.0%
9 7
 
4.4%
Other values (2) 12
 
7.5%
Hangul
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 160
96.4%
Hangul 6
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
22.5%
1 23
14.4%
, 16
10.0%
2 16
10.0%
3 13
 
8.1%
6 10
 
6.2%
4 10
 
6.2%
8 9
 
5.6%
7 8
 
5.0%
9 7
 
4.4%
Other values (2) 12
 
7.5%
Hangul
ValueCountFrequency (%)
철 1
16.7%
근 1
16.7%
콘 1
16.7%
크 1
16.7%
리 1
16.7%
트 1
16.7%

용도변경.2
Text

MISSING 

Distinct34
Distinct (%)91.9%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:25.971824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.027027
Min length2

Characters and Unicode

Total characters149
Distinct characters14
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

Unique31 ?
Unique (%)83.8%

Sample

1st row철골
2nd row41
3rd row9,291
4th row26
5th row3,605
ValueCountFrequency (%)
22 2
 
5.4%
9 2
 
5.4%
13 2
 
5.4%
66 1
 
2.7%
3,177 1
 
2.7%
5,494 1
 
2.7%
8 1
 
2.7%
3,567 1
 
2.7%
2 1
 
2.7%
1,716 1
 
2.7%
Other values (24) 24
64.9%
2023-12-11T09:21:26.275265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
24.2%
2 14
 
9.4%
, 14
 
9.4%
1 12
 
8.1%
3 12
 
8.1%
6 12
 
8.1%
9 10
 
6.7%
4 9
 
6.0%
5 8
 
5.4%
8 8
 
5.4%
Other values (4) 14
 
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97
65.1%
Space Separator 36
 
24.2%
Other Punctuation 14
 
9.4%
Other Letter 2
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
14.4%
1 12
12.4%
3 12
12.4%
6 12
12.4%
9 10
10.3%
4 9
9.3%
5 8
8.2%
8 8
8.2%
7 8
8.2%
0 4
 
4.1%
Other Letter
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 147
98.7%
Hangul 2
 
1.3%

Most frequent character per script

Common
ValueCountFrequency (%)
36
24.5%
2 14
 
9.5%
, 14
 
9.5%
1 12
 
8.2%
3 12
 
8.2%
6 12
 
8.2%
9 10
 
6.8%
4 9
 
6.1%
5 8
 
5.4%
8 8
 
5.4%
Other values (2) 12
 
8.2%
Hangul
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147
98.7%
Hangul 2
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
24.5%
2 14
 
9.5%
, 14
 
9.5%
1 12
 
8.2%
3 12
 
8.2%
6 12
 
8.2%
9 10
 
6.8%
4 9
 
6.1%
5 8
 
5.4%
8 8
 
5.4%
Other values (2) 12
 
8.2%
Hangul
ValueCountFrequency (%)
철 1
50.0%
골 1
50.0%

용도변경.3
Text

MISSING 

Distinct31
Distinct (%)83.8%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:26.425444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length3.4324324
Min length2

Characters and Unicode

Total characters127
Distinct characters14
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

Unique26 ?
Unique (%)70.3%

Sample

1st row조적
2nd row97
3rd row9,793
4th row18
5th row1,323
ValueCountFrequency (%)
5 3
 
8.1%
7 2
 
5.4%
3 2
 
5.4%
2 2
 
5.4%
1 2
 
5.4%
604 1
 
2.7%
295 1
 
2.7%
408 1
 
2.7%
400 1
 
2.7%
319 1
 
2.7%
Other values (21) 21
56.8%
2023-12-11T09:21:26.719009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
28.3%
1 21
16.5%
3 12
 
9.4%
9 11
 
8.7%
2 10
 
7.9%
0 8
 
6.3%
, 6
 
4.7%
4 6
 
4.7%
5 5
 
3.9%
7 5
 
3.9%
Other values (4) 7
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83
65.4%
Space Separator 36
28.3%
Other Punctuation 6
 
4.7%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
25.3%
3 12
14.5%
9 11
13.3%
2 10
12.0%
0 8
 
9.6%
4 6
 
7.2%
5 5
 
6.0%
7 5
 
6.0%
8 3
 
3.6%
6 2
 
2.4%
Other Letter
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 125
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
36
28.8%
1 21
16.8%
3 12
 
9.6%
9 11
 
8.8%
2 10
 
8.0%
0 8
 
6.4%
, 6
 
4.8%
4 6
 
4.8%
5 5
 
4.0%
7 5
 
4.0%
Other values (2) 5
 
4.0%
Hangul
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 125
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
28.8%
1 21
16.8%
3 12
 
9.6%
9 11
 
8.8%
2 10
 
8.0%
0 8
 
6.4%
, 6
 
4.8%
4 6
 
4.8%
5 5
 
4.0%
7 5
 
4.0%
Other values (2) 5
 
4.0%
Hangul
ValueCountFrequency (%)
조 1
50.0%
적 1
50.0%

용도변경.4
Categorical

Distinct12
Distinct (%)21.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
0
25 
<NA>
18 
1
3 
철골철근
 
1
22
 
1
Other values (7)
7 

Length

Max length7
Median length2
Mean length3.0727273
Min length2

Unique

Unique9 ?
Unique (%)16.4%

Sample

1st row철골철근
2nd row<NA>
3rd row22
4th row14,247
5th row<NA>

Common Values

ValueCountFrequency (%)
0 25
45.5%
<NA> 18
32.7%
1 3
 
5.5%
철골철근 1
 
1.8%
22 1
 
1.8%
14,247 1
 
1.8%
1,119 1
 
1.8%
10 1
 
1.8%
5,465 1
 
1.8%
6 1
 
1.8%
Other values (2) 2
 
3.6%

Length

2023-12-11T09:21:26.833492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 25
45.5%
na 18
32.7%
1 3
 
5.5%
철골철근 1
 
1.8%
22 1
 
1.8%
14,247 1
 
1.8%
1,119 1
 
1.8%
10 1
 
1.8%
5,465 1
 
1.8%
6 1
 
1.8%
Other values (2) 2
 
3.6%

용도변경.5
Text

MISSING 

Distinct23
Distinct (%)62.2%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-11T09:21:26.941293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.7837838
Min length2

Characters and Unicode

Total characters103
Distinct characters13
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 (%)45.9%

Sample

1st row나무
2nd row10
3rd row495
4th row3
5th row102
ValueCountFrequency (%)
0 8
21.6%
3 4
 
10.8%
6 2
 
5.4%
4 2
 
5.4%
102 2
 
5.4%
2 2
 
5.4%
308 1
 
2.7%
261 1
 
2.7%
258 1
 
2.7%
1 1
 
2.7%
Other values (13) 13
35.1%
2023-12-11T09:21:27.211742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
36
35.0%
0 14
 
13.6%
2 11
 
10.7%
3 7
 
6.8%
1 7
 
6.8%
6 6
 
5.8%
4 6
 
5.8%
8 5
 
4.9%
5 5
 
4.9%
7 3
 
2.9%
Other values (3) 3
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
63.1%
Space Separator 36
35.0%
Other Letter 2
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
21.5%
2 11
16.9%
3 7
10.8%
1 7
10.8%
6 6
9.2%
4 6
9.2%
8 5
 
7.7%
5 5
 
7.7%
7 3
 
4.6%
9 1
 
1.5%
Other Letter
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%
Space Separator
ValueCountFrequency (%)
36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101
98.1%
Hangul 2
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
36
35.6%
0 14
 
13.9%
2 11
 
10.9%
3 7
 
6.9%
1 7
 
6.9%
6 6
 
5.9%
4 6
 
5.9%
8 5
 
5.0%
5 5
 
5.0%
7 3
 
3.0%
Hangul
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 101
98.1%
Hangul 2
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
36
35.6%
0 14
 
13.9%
2 11
 
10.9%
3 7
 
6.9%
1 7
 
6.9%
6 6
 
5.9%
4 6
 
5.9%
8 5
 
5.0%
5 5
 
5.0%
7 3
 
3.0%
Hangul
ValueCountFrequency (%)
나 1
50.0%
무 1
50.0%

용도변경.6
Categorical

Distinct9
Distinct (%)16.4%
Missing0
Missing (%)0.0%
Memory size572.0 B
0
29 
<NA>
18 
2
 
2
기타
 
1
29
 
1
Other values (4)
4 

Length

Max length4
Median length2
Mean length2.7090909
Min length2

Unique

Unique6 ?
Unique (%)10.9%

Sample

1st row기타
2nd row<NA>
3rd row0
4th row29
5th row<NA>

Common Values

ValueCountFrequency (%)
0 29
52.7%
<NA> 18
32.7%
2 2
 
3.6%
기타 1
 
1.8%
29 1
 
1.8%
1 1
 
1.8%
82 1
 
1.8%
52 1
 
1.8%
9 1
 
1.8%

Length

2023-12-11T09:21:27.616495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:21:27.739251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 29
52.7%
na 18
32.7%
2 2
 
3.6%
기타 1
 
1.8%
29 1
 
1.8%
1 1
 
1.8%
82 1
 
1.8%
52 1
 
1.8%
9 1
 
1.8%

Sample

지역구분신축신축.1신축.2신축.3신축.4신축.5신축.6증축/개축/이전/대수선증축/개축/이전/대수선.1증축/개축/이전/대수선.2증축/개축/이전/대수선.3증축/개축/이전/대수선.4증축/개축/이전/대수선.5증축/개축/이전/대수선.6용도변경용도변경.1용도변경.2용도변경.3용도변경.4용도변경.5용도변경.6
0지역구분계철근콘크리트철골조적철골철근나무기타계철근콘크리트철골조적철골철근나무기타계철근콘크리트철골조적철골철근나무기타
1창원시건수563<NA><NA><NA><NA><NA><NA>370<NA><NA><NA><NA><NA><NA>400<NA><NA><NA><NA><NA><NA>
2창원시동수743329369372411562148349324821411241419722100
3창원시연면적628,474485,98489,49516949,9862,528312207,05594,65676,8561,53133,810-33353595,76961,9149,2919,79314,24749529
4진주시건수391<NA><NA><NA><NA><NA><NA>230<NA><NA><NA><NA><NA><NA>103<NA><NA><NA><NA><NA><NA>
5진주시동수54319229410342234188224122105109612618031
6진주시연면적216,89895,156117,225813193,489628102,18143,74248,5489645,6821,4241,82120,37415,2623,6051,323010282
7통영시건수215<NA><NA><NA><NA><NA><NA>114<NA><NA><NA><NA><NA><NA>56<NA><NA><NA><NA><NA><NA>
8통영시동수28312713911961836190812215737107120
9통영시연면적184,472164,86716,147492,67554818619,5169,5926,0893163,08810732415,77012,7335761,2361,1191060
지역구분신축신축.1신축.2신축.3신축.4신축.5신축.6증축/개축/이전/대수선증축/개축/이전/대수선.1증축/개축/이전/대수선.2증축/개축/이전/대수선.3증축/개축/이전/대수선.4증축/개축/이전/대수선.5증축/개축/이전/대수선.6용도변경용도변경.1용도변경.2용도변경.3용도변경.4용도변경.5용도변경.6
45산청군연면적69,57614,11549,2021011395,85516426,6086,72918,8043809904710,9767,2243,29621002460
46함양군건수314<NA><NA><NA><NA><NA><NA>136<NA><NA><NA><NA><NA><NA>9<NA><NA><NA><NA><NA><NA>
47함양군동수41575312001992572718118019129431010
48함양군연면적68,94615,68949,3284901,7472,13335,1142,19530,8991,34805691031,73988964510301020
49거창군건수391<NA><NA><NA><NA><NA><NA>166<NA><NA><NA><NA><NA><NA>23<NA><NA><NA><NA><NA><NA>
50거창군동수504121319613324403313211402017261363040
51거창군연면적219,904128,37287,053861912,2661,26171,3836,61063,03913901,1804159,0856,9201,71619102580
52합천군건수443<NA><NA><NA><NA><NA><NA>292<NA><NA><NA><NA><NA><NA>10<NA><NA><NA><NA><NA><NA>
53합천군동수6109847751141588651677572326716191140
54합천군연면적119,86824,04092,578283991,6731,19583,3113,51773,8683,27406032,0492,3471,1376939504220