Overview

Dataset statistics

Number of variables7
Number of observations55
Missing cells45
Missing cells (%)11.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.2 KiB
Average record size in memory59.4 B

Variable types

Numeric1
Text5
DateTime1

Dataset

Description충청북도 충주시 건축사 사무소 현황에 대한 데이터 제공(대표자, 연락처, 연락처2(선택), 주소, 데이터 기준일자)
Author충청북도 충주시
URLhttps://www.data.go.kr/data/15034744/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연락처2 has 45 (81.8%) missing valuesMissing
구분 has unique valuesUnique
대표자 has unique valuesUnique
건축사사무소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:39:35.953675
Analysis finished2023-12-12 05:39:36.798343
Duration0.84 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size627.0 B
2023-12-12T14:39:36.917930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.7
Q114.5
median28
Q341.5
95-th percentile52.3
Maximum55
Range54
Interquartile range (IQR)27

Descriptive statistics

Standard deviation16.02082
Coefficient of variation (CV)0.57217214
Kurtosis-1.2
Mean28
Median Absolute Deviation (MAD)14
Skewness0
Sum1540
Variance256.66667
MonotonicityStrictly increasing
2023-12-12T14:39:37.106123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.8%
2 1
 
1.8%
31 1
 
1.8%
32 1
 
1.8%
33 1
 
1.8%
34 1
 
1.8%
35 1
 
1.8%
36 1
 
1.8%
37 1
 
1.8%
38 1
 
1.8%
Other values (45) 45
81.8%
ValueCountFrequency (%)
1 1
1.8%
2 1
1.8%
3 1
1.8%
4 1
1.8%
5 1
1.8%
6 1
1.8%
7 1
1.8%
8 1
1.8%
9 1
1.8%
10 1
1.8%
ValueCountFrequency (%)
55 1
1.8%
54 1
1.8%
53 1
1.8%
52 1
1.8%
51 1
1.8%
50 1
1.8%
49 1
1.8%
48 1
1.8%
47 1
1.8%
46 1
1.8%

대표자
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-12T14:39:37.424699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9818182
Min length2

Characters and Unicode

Total characters164
Distinct characters84
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

Unique55 ?
Unique (%)100.0%

Sample

1st row강선미
2nd row김계영
3rd row김광수
4th row김바울
5th row김상엽
ValueCountFrequency (%)
강선미 1
 
1.8%
장병율 1
 
1.8%
정선웅 1
 
1.8%
정세영 1
 
1.8%
조관형 1
 
1.8%
조임원 1
 
1.8%
채희천 1
 
1.8%
최고은 1
 
1.8%
최선 1
 
1.8%
최영배 1
 
1.8%
Other values (45) 45
81.8%
2023-12-12T14:39:37.902976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 13
 
7.9%
이 6
 
3.7%
영 5
 
3.0%
기 5
 
3.0%
최 4
 
2.4%
연 4
 
2.4%
승 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
희 4
 
2.4%
Other values (74) 111
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 13
 
7.9%
이 6
 
3.7%
영 5
 
3.0%
기 5
 
3.0%
최 4
 
2.4%
연 4
 
2.4%
승 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
희 4
 
2.4%
Other values (74) 111
67.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 13
 
7.9%
이 6
 
3.7%
영 5
 
3.0%
기 5
 
3.0%
최 4
 
2.4%
연 4
 
2.4%
승 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
희 4
 
2.4%
Other values (74) 111
67.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 13
 
7.9%
이 6
 
3.7%
영 5
 
3.0%
기 5
 
3.0%
최 4
 
2.4%
연 4
 
2.4%
승 4
 
2.4%
상 4
 
2.4%
정 4
 
2.4%
희 4
 
2.4%
Other values (74) 111
67.7%

건축사사무소명
Text

UNIQUE 

Distinct55
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-12T14:39:38.208958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.0909091
Min length7

Characters and Unicode

Total characters500
Distinct characters90
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

Unique55 ?
Unique (%)100.0%

Sample

1st row시와플랜건축사사무소
2nd row나우건축사사무소
3rd row종합건축사사무소 단 건축
4th row바른건축사사무소
5th row온건축사사무소
ValueCountFrequency (%)
종합건축사사무소 6
 
9.0%
건축사사무소 4
 
6.0%
주)건축사사무소 1
 
1.5%
건문 1
 
1.5%
사이 1
 
1.5%
건축동인 1
 
1.5%
화담건축사사무소 1
 
1.5%
㈜예원건축사사무소 1
 
1.5%
한알건축 1
 
1.5%
고은 1
 
1.5%
Other values (49) 49
73.1%
2023-12-12T14:39:38.662576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 111
22.2%
건 62
12.4%
축 60
12.0%
무 55
11.0%
소 55
11.0%
12
 
2.4%
종 9
 
1.8%
합 9
 
1.8%
우 5
 
1.0%
리 5
 
1.0%
Other values (80) 117
23.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 484
96.8%
Space Separator 12
 
2.4%
Close Punctuation 2
 
0.4%
Other Symbol 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 111
22.9%
건 62
12.8%
축 60
12.4%
무 55
11.4%
소 55
11.4%
종 9
 
1.9%
합 9
 
1.9%
우 5
 
1.0%
리 5
 
1.0%
담 4
 
0.8%
Other values (76) 109
22.5%
Space Separator
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 485
97.0%
Common 15
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 111
22.9%
건 62
12.8%
축 60
12.4%
무 55
11.3%
소 55
11.3%
종 9
 
1.9%
합 9
 
1.9%
우 5
 
1.0%
리 5
 
1.0%
담 4
 
0.8%
Other values (77) 110
22.7%
Common
ValueCountFrequency (%)
12
80.0%
) 2
 
13.3%
( 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 484
96.8%
ASCII 15
 
3.0%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 111
22.9%
건 62
12.8%
축 60
12.4%
무 55
11.4%
소 55
11.4%
종 9
 
1.9%
합 9
 
1.9%
우 5
 
1.0%
리 5
 
1.0%
담 4
 
0.8%
Other values (76) 109
22.5%
ASCII
ValueCountFrequency (%)
12
80.0%
) 2
 
13.3%
( 1
 
6.7%
None
ValueCountFrequency (%)
㈜ 1
100.0%

연락처
Text

Distinct54
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-12T14:39:38.927594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters660
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

Unique53 ?
Unique (%)96.4%

Sample

1st row043-847-4100
2nd row043-855-0411
3rd row043-857-7890
4th row043-846-4232
5th row043-852-1900
ValueCountFrequency (%)
043-847-4100 2
 
3.6%
043-845-0235 1
 
1.8%
043-847-7765 1
 
1.8%
043-852-0933 1
 
1.8%
043-851-1586 1
 
1.8%
043-845-1453 1
 
1.8%
043-842-3400 1
 
1.8%
043-846-3450 1
 
1.8%
043-854-0290 1
 
1.8%
043-856-8456 1
 
1.8%
Other values (44) 44
80.0%
2023-12-12T14:39:39.323323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 110
16.7%
- 110
16.7%
0 99
15.0%
8 81
12.3%
3 79
12.0%
5 50
7.6%
2 36
 
5.5%
1 33
 
5.0%
6 30
 
4.5%
7 18
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 550
83.3%
Dash Punctuation 110
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 110
20.0%
0 99
18.0%
8 81
14.7%
3 79
14.4%
5 50
9.1%
2 36
 
6.5%
1 33
 
6.0%
6 30
 
5.5%
7 18
 
3.3%
9 14
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 110
16.7%
- 110
16.7%
0 99
15.0%
8 81
12.3%
3 79
12.0%
5 50
7.6%
2 36
 
5.5%
1 33
 
5.0%
6 30
 
4.5%
7 18
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 110
16.7%
- 110
16.7%
0 99
15.0%
8 81
12.3%
3 79
12.0%
5 50
7.6%
2 36
 
5.5%
1 33
 
5.0%
6 30
 
4.5%
7 18
 
2.7%

연락처2
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing45
Missing (%)81.8%
Memory size572.0 B
2023-12-12T14:39:39.514787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters120
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

Unique10 ?
Unique (%)100.0%

Sample

1st row043-855-0412
2nd row043-857-7891
3rd row043-847-5842
4th row043-842-0232
5th row043-851-2884
ValueCountFrequency (%)
043-855-0412 1
10.0%
043-857-7891 1
10.0%
043-847-5842 1
10.0%
043-842-0232 1
10.0%
043-851-2884 1
10.0%
043-856-8009 1
10.0%
043-857-0332 1
10.0%
043-851-1587 1
10.0%
043-847-3400 1
10.0%
043-848-3450 1
10.0%
2023-12-12T14:39:39.796562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 20
16.7%
4 19
15.8%
0 18
15.0%
8 17
14.2%
3 15
12.5%
5 10
8.3%
2 7
 
5.8%
7 6
 
5.0%
1 5
 
4.2%
9 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100
83.3%
Dash Punctuation 20
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 19
19.0%
0 18
18.0%
8 17
17.0%
3 15
15.0%
5 10
10.0%
2 7
 
7.0%
7 6
 
6.0%
1 5
 
5.0%
9 2
 
2.0%
6 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 20
16.7%
4 19
15.8%
0 18
15.0%
8 17
14.2%
3 15
12.5%
5 10
8.3%
2 7
 
5.8%
7 6
 
5.0%
1 5
 
4.2%
9 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 20
16.7%
4 19
15.8%
0 18
15.0%
8 17
14.2%
3 15
12.5%
5 10
8.3%
2 7
 
5.8%
7 6
 
5.0%
1 5
 
4.2%
9 2
 
1.7%

주소
Text

Distinct51
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size572.0 B
2023-12-12T14:39:40.053069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length27
Mean length21.6
Min length14

Characters and Unicode

Total characters1188
Distinct characters77
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)87.3%

Sample

1st row충청북도 충주시 금제2길1
2nd row충청북도 충주시 금제13길 8(금릉동)
3rd row충청북도 충주시 으뜸로 38(금릉동)
4th row충청북도 충주시 으뜸로 5(금릉동)
5th row충청북도 충주시 금제8길19(1층)
ValueCountFrequency (%)
충주시 56
23.9%
충청북도 55
23.5%
금봉대로 7
 
3.0%
금제9길 6
 
2.6%
으뜸로 5
 
2.1%
2층 4
 
1.7%
금제3길 4
 
1.7%
838 3
 
1.3%
팽고리산길 3
 
1.3%
2층(금릉동 3
 
1.3%
Other values (77) 88
37.6%
2023-12-12T14:39:40.448632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
 
15.1%
충 111
 
9.3%
시 58
 
4.9%
청 57
 
4.8%
주 56
 
4.7%
북 55
 
4.6%
도 55
 
4.6%
금 54
 
4.5%
( 46
 
3.9%
) 45
 
3.8%
Other values (67) 472
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 707
59.5%
Decimal Number 189
 
15.9%
Space Separator 179
 
15.1%
Open Punctuation 46
 
3.9%
Close Punctuation 45
 
3.8%
Dash Punctuation 12
 
1.0%
Other Punctuation 10
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 111
15.7%
시 58
 
8.2%
청 57
 
8.1%
주 56
 
7.9%
북 55
 
7.8%
도 55
 
7.8%
금 54
 
7.6%
길 34
 
4.8%
동 29
 
4.1%
층 26
 
3.7%
Other values (51) 172
24.3%
Decimal Number
ValueCountFrequency (%)
1 41
21.7%
2 32
16.9%
4 21
11.1%
8 20
10.6%
3 19
10.1%
0 15
 
7.9%
7 15
 
7.9%
9 11
 
5.8%
6 10
 
5.3%
5 5
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 8
80.0%
. 2
 
20.0%
Space Separator
ValueCountFrequency (%)
179
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 707
59.5%
Common 481
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 111
15.7%
시 58
 
8.2%
청 57
 
8.1%
주 56
 
7.9%
북 55
 
7.8%
도 55
 
7.8%
금 54
 
7.6%
길 34
 
4.8%
동 29
 
4.1%
층 26
 
3.7%
Other values (51) 172
24.3%
Common
ValueCountFrequency (%)
179
37.2%
( 46
 
9.6%
) 45
 
9.4%
1 41
 
8.5%
2 32
 
6.7%
4 21
 
4.4%
8 20
 
4.2%
3 19
 
4.0%
0 15
 
3.1%
7 15
 
3.1%
Other values (6) 48
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 707
59.5%
ASCII 481
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
37.2%
( 46
 
9.6%
) 45
 
9.4%
1 41
 
8.5%
2 32
 
6.7%
4 21
 
4.4%
8 20
 
4.2%
3 19
 
4.0%
0 15
 
3.1%
7 15
 
3.1%
Other values (6) 48
 
10.0%
Hangul
ValueCountFrequency (%)
충 111
15.7%
시 58
 
8.2%
청 57
 
8.1%
주 56
 
7.9%
북 55
 
7.8%
도 55
 
7.8%
금 54
 
7.6%
길 34
 
4.8%
동 29
 
4.1%
층 26
 
3.7%
Other values (51) 172
24.3%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
Minimum2023-09-30 00:00:00
Maximum2023-09-30 00:00:00
2023-12-12T14:39:40.864461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:39:40.974335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T14:39:36.386811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:39:41.089583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분대표자건축사사무소명연락처연락처2주소
구분1.0001.0001.0000.9451.0000.704
대표자1.0001.0001.0001.0001.0001.000
건축사사무소명1.0001.0001.0001.0001.0001.000
연락처0.9451.0001.0001.0001.0001.000
연락처21.0001.0001.0001.0001.0001.000
주소0.7041.0001.0001.0001.0001.000

Missing values

2023-12-12T14:39:36.559376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:39:36.732823image/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

구분대표자건축사사무소명연락처연락처2주소데이터기준일자
01강선미시와플랜건축사사무소043-847-4100<NA>충청북도 충주시 금제2길12023-09-30
12김계영나우건축사사무소043-855-0411043-855-0412충청북도 충주시 금제13길 8(금릉동)2023-09-30
23김광수종합건축사사무소 단 건축043-857-7890043-857-7891충청북도 충주시 으뜸로 38(금릉동)2023-09-30
34김바울바른건축사사무소043-846-4232<NA>충청북도 충주시 으뜸로 5(금릉동)2023-09-30
45김상엽온건축사사무소043-852-1900<NA>충청북도 충주시 금제8길19(1층)2023-09-30
56김승길하나종합건축사사무소043-843-2229<NA>충청북도 충주시 금제9길 14(금릉동)2023-09-30
67김지연연건축사사무소043-848-6801<NA>충청북도 충주시 금봉대로 838 (2층)2023-09-30
78김진규어울림건축사사무소043-846-5842043-847-5842충청북도 충주시 금제6길 7(금릉동)2023-09-30
89김창식우리종합건축사사무소043-842-0231043-842-0232충청북도 충주시 금제9길 6(금릉동)2023-09-30
910김천기팀스건축사사무소043-851-1212<NA>충청북도 충주시 금제9길4 2층(금릉동)2023-09-30
구분대표자건축사사무소명연락처연락처2주소데이터기준일자
4546김현주두리건축사사무소043-852-7296<NA>충청북도 충주시 팽고리산길 77-12(2층)2023-09-30
4647채형기종합건축사사무소 채움건축043-846-5090<NA>충청북도 충주시 팽고리산길 77-4(2층)2023-09-30
4748최호연모아건축사사무소043-845-8457<NA>충청북도 충주시 금봉대로 532(연수동)2023-09-30
4849이홍근희원건축사사무소043-911-1617<NA>충청북도 충주시 충주시 예성로 70 2층(지현동)2023-09-30
4950황기숙건축사사무소 공유043-848-0404<NA>충청북도 충주시 금제 9길 6(1층)2023-09-30
5051김연호우주건축사사무소043-845-0318<NA>충청북도 충주시 으뜸로 38 3층 303호(금릉동, 금능빌딩)2023-09-30
5152박명호명부건축사사무소043-846-6658<NA>충청북도 충주시 금제 7길 6-1, 1층(금릉동)2023-09-30
5253안기완누리건축사사무소043-851-2021<NA>충청북도 충주시 금봉대로 840, 201호2023-09-30
5354길학영가람종합건축사사무소043-847-7765<NA>충청북도 충주시 금제3길 8, 2층(금릉동)2023-09-30
5455한상민한마루건축사사무소043-855-4246<NA>충청북도 충주시 금제3길 4, 101호2023-09-30