Overview

Dataset statistics

Number of variables7
Number of observations37
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory60.6 B

Variable types

Numeric1
Categorical2
Text4

Dataset

Description대구광역시 8개구군에 인허가받은 배출가스 전문정비 사업자 37개소에 대한 등록현황(상호, 대표자, 소재지, 전화번호, 측정항목)에 대한 데이터임
Author대구광역시
URLhttps://www.data.go.kr/data/15022053/fileData.do

Alerts

연번 is highly overall correlated with 지역High correlation
지역 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:35:22.817118
Analysis finished2023-12-12 05:35:23.687773
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19
Minimum1
Maximum37
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size465.0 B
2023-12-12T14:35:23.839447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.8
Q110
median19
Q328
95-th percentile35.2
Maximum37
Range36
Interquartile range (IQR)18

Descriptive statistics

Standard deviation10.824355
Coefficient of variation (CV)0.56970291
Kurtosis-1.2
Mean19
Median Absolute Deviation (MAD)9
Skewness0
Sum703
Variance117.16667
MonotonicityStrictly increasing
2023-12-12T14:35:23.978768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
1 1
 
2.7%
29 1
 
2.7%
22 1
 
2.7%
23 1
 
2.7%
24 1
 
2.7%
25 1
 
2.7%
26 1
 
2.7%
27 1
 
2.7%
28 1
 
2.7%
30 1
 
2.7%
Other values (27) 27
73.0%
ValueCountFrequency (%)
1 1
2.7%
2 1
2.7%
3 1
2.7%
4 1
2.7%
5 1
2.7%
6 1
2.7%
7 1
2.7%
8 1
2.7%
9 1
2.7%
10 1
2.7%
ValueCountFrequency (%)
37 1
2.7%
36 1
2.7%
35 1
2.7%
34 1
2.7%
33 1
2.7%
32 1
2.7%
31 1
2.7%
30 1
2.7%
29 1
2.7%
28 1
2.7%

지역
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)18.9%
Missing0
Missing (%)0.0%
Memory size428.0 B
대구시 달서구
15 
대구시 서구
8 
대구시 북구
4 
대구시 달성군
4 
대구시 동구
3 
Other values (2)
3 

Length

Max length7
Median length7
Mean length6.5675676
Min length6

Unique

Unique1 ?
Unique (%)2.7%

Sample

1st row대구시 동구
2nd row대구시 동구
3rd row대구시 동구
4th row대구시 서구
5th row대구시 서구

Common Values

ValueCountFrequency (%)
대구시 달서구 15
40.5%
대구시 서구 8
21.6%
대구시 북구 4
 
10.8%
대구시 달성군 4
 
10.8%
대구시 동구 3
 
8.1%
대구시 수성구 2
 
5.4%
대구시 남구 1
 
2.7%

Length

2023-12-12T14:35:24.126854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:24.282547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구시 37
50.0%
달서구 15
20.3%
서구 8
 
10.8%
북구 4
 
5.4%
달성군 4
 
5.4%
동구 3
 
4.1%
수성구 2
 
2.7%
남구 1
 
1.4%

업소명
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T14:35:24.565837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.972973
Min length4

Characters and Unicode

Total characters295
Distinct characters109
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row반야월자동차정비공장
2nd row스피드1급카센터
3rd row자동차도우미
4th row르노삼성자동차㈜대구사업소
5th row삼천리보림부란자
ValueCountFrequency (%)
오토1급 2
 
4.7%
대구서비스센터 2
 
4.7%
반야월자동차정비공장 1
 
2.3%
청구1급카써비스 1
 
2.3%
호림자동차검사정비 1
 
2.3%
공임나라 1
 
2.3%
성서공단점 1
 
2.3%
범양카tbo플러스 1
 
2.3%
명륜카센터 1
 
2.3%
대곡종합카센타 1
 
2.3%
Other values (31) 31
72.1%
2023-12-12T14:35:25.013810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 16
 
5.4%
스 16
 
5.4%
자 12
 
4.1%
동 12
 
4.1%
카 12
 
4.1%
대 11
 
3.7%
터 11
 
3.7%
차 11
 
3.7%
정 9
 
3.1%
센 9
 
3.1%
Other values (99) 176
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 276
93.6%
Decimal Number 6
 
2.0%
Space Separator 6
 
2.0%
Other Symbol 4
 
1.4%
Uppercase Letter 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 16
 
5.8%
스 16
 
5.8%
자 12
 
4.3%
동 12
 
4.3%
카 12
 
4.3%
대 11
 
4.0%
터 11
 
4.0%
차 11
 
4.0%
정 9
 
3.3%
센 9
 
3.3%
Other values (93) 157
56.9%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
T 1
33.3%
O 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 280
94.9%
Common 12
 
4.1%
Latin 3
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 16
 
5.7%
스 16
 
5.7%
자 12
 
4.3%
동 12
 
4.3%
카 12
 
4.3%
대 11
 
3.9%
터 11
 
3.9%
차 11
 
3.9%
정 9
 
3.2%
센 9
 
3.2%
Other values (94) 161
57.5%
Latin
ValueCountFrequency (%)
B 1
33.3%
T 1
33.3%
O 1
33.3%
Common
ValueCountFrequency (%)
1 6
50.0%
6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 276
93.6%
ASCII 15
 
5.1%
None 4
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 16
 
5.8%
스 16
 
5.8%
자 12
 
4.3%
동 12
 
4.3%
카 12
 
4.3%
대 11
 
4.0%
터 11
 
4.0%
차 11
 
4.0%
정 9
 
3.3%
센 9
 
3.3%
Other values (93) 157
56.9%
ASCII
ValueCountFrequency (%)
1 6
40.0%
6
40.0%
B 1
 
6.7%
T 1
 
6.7%
O 1
 
6.7%
None
ValueCountFrequency (%)
㈜ 4
100.0%

대표자
Text

Distinct34
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T14:35:25.301221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4594595
Min length3

Characters and Unicode

Total characters128
Distinct characters65
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

Unique32 ?
Unique (%)86.5%

Sample

1st row박종근
2nd row전병효
3rd row이성철
4th row대표이사
5th row이철호
ValueCountFrequency (%)
대표이사 3
 
7.3%
외 2
 
4.9%
박일랑 2
 
4.9%
이상일 1
 
2.4%
한정혁 1
 
2.4%
1명 1
 
2.4%
김미옥 1
 
2.4%
윤경화 1
 
2.4%
박상영 1
 
2.4%
윤만식 1
 
2.4%
Other values (27) 27
65.9%
2023-12-12T14:35:25.740475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 9
 
7.0%
박 9
 
7.0%
일 5
 
3.9%
호 4
 
3.1%
4
 
3.1%
윤 4
 
3.1%
정 4
 
3.1%
김 4
 
3.1%
대 3
 
2.3%
표 3
 
2.3%
Other values (55) 79
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121
94.5%
Space Separator 4
 
3.1%
Decimal Number 2
 
1.6%
Other Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 9
 
7.4%
박 9
 
7.4%
일 5
 
4.1%
호 4
 
3.3%
윤 4
 
3.3%
정 4
 
3.3%
김 4
 
3.3%
대 3
 
2.5%
표 3
 
2.5%
만 3
 
2.5%
Other values (51) 73
60.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
94.5%
Common 7
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 9
 
7.4%
박 9
 
7.4%
일 5
 
4.1%
호 4
 
3.3%
윤 4
 
3.3%
정 4
 
3.3%
김 4
 
3.3%
대 3
 
2.5%
표 3
 
2.5%
만 3
 
2.5%
Other values (51) 73
60.3%
Common
ValueCountFrequency (%)
4
57.1%
1 1
 
14.3%
2 1
 
14.3%
/ 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121
94.5%
ASCII 7
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 9
 
7.4%
박 9
 
7.4%
일 5
 
4.1%
호 4
 
3.3%
윤 4
 
3.3%
정 4
 
3.3%
김 4
 
3.3%
대 3
 
2.5%
표 3
 
2.5%
만 3
 
2.5%
Other values (51) 73
60.3%
ASCII
ValueCountFrequency (%)
4
57.1%
1 1
 
14.3%
2 1
 
14.3%
/ 1
 
14.3%

소재지
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T14:35:26.095816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length17.162162
Min length9

Characters and Unicode

Total characters635
Distinct characters89
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

Unique37 ?
Unique (%)100.0%

Sample

1st row동구 안심로 55길 52 (동호동)
2nd row동구 송라로 34
3rd row동구 공항로 135(불로동)
4th row서구 와룡로 392(중리동)
5th row서구 와룡로87길 68(이현동)
ValueCountFrequency (%)
달서구 15
 
11.7%
서구 8
 
6.2%
달성군 4
 
3.1%
북구 4
 
3.1%
동구 3
 
2.3%
와룡로 3
 
2.3%
성서공단로11길 2
 
1.6%
팔달로 2
 
1.6%
수성구 2
 
1.6%
진천동 2
 
1.6%
Other values (79) 83
64.8%
2023-12-12T14:35:26.618104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
14.3%
로 37
 
5.8%
동 35
 
5.5%
구 34
 
5.4%
서 34
 
5.4%
( 32
 
5.0%
) 32
 
5.0%
1 24
 
3.8%
달 22
 
3.5%
3 18
 
2.8%
Other values (79) 276
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 361
56.9%
Decimal Number 116
 
18.3%
Space Separator 91
 
14.3%
Open Punctuation 32
 
5.0%
Close Punctuation 32
 
5.0%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 37
 
10.2%
동 35
 
9.7%
구 34
 
9.4%
서 34
 
9.4%
달 22
 
6.1%
성 15
 
4.2%
길 13
 
3.6%
공 8
 
2.2%
북 7
 
1.9%
원 7
 
1.9%
Other values (65) 149
41.3%
Decimal Number
ValueCountFrequency (%)
1 24
20.7%
3 18
15.5%
4 15
12.9%
5 11
9.5%
7 11
9.5%
9 10
8.6%
2 9
 
7.8%
6 9
 
7.8%
8 6
 
5.2%
0 3
 
2.6%
Space Separator
ValueCountFrequency (%)
91
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 361
56.9%
Common 274
43.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 37
 
10.2%
동 35
 
9.7%
구 34
 
9.4%
서 34
 
9.4%
달 22
 
6.1%
성 15
 
4.2%
길 13
 
3.6%
공 8
 
2.2%
북 7
 
1.9%
원 7
 
1.9%
Other values (65) 149
41.3%
Common
ValueCountFrequency (%)
91
33.2%
( 32
 
11.7%
) 32
 
11.7%
1 24
 
8.8%
3 18
 
6.6%
4 15
 
5.5%
5 11
 
4.0%
7 11
 
4.0%
9 10
 
3.6%
2 9
 
3.3%
Other values (4) 21
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 361
56.9%
ASCII 274
43.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
33.2%
( 32
 
11.7%
) 32
 
11.7%
1 24
 
8.8%
3 18
 
6.6%
4 15
 
5.5%
5 11
 
4.0%
7 11
 
4.0%
9 10
 
3.6%
2 9
 
3.3%
Other values (4) 21
 
7.7%
Hangul
ValueCountFrequency (%)
로 37
 
10.2%
동 35
 
9.7%
구 34
 
9.4%
서 34
 
9.4%
달 22
 
6.1%
성 15
 
4.2%
길 13
 
3.6%
공 8
 
2.2%
북 7
 
1.9%
원 7
 
1.9%
Other values (65) 149
41.3%

전화번호
Text

UNIQUE 

Distinct37
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size428.0 B
2023-12-12T14:35:26.917339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters444
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row053)964-0964
2nd row053)754-1006
3rd row053)382-5582
4th row053)563-3333
5th row053)563-0636
ValueCountFrequency (%)
053)964-0964 1
 
2.7%
053)585-7744 1
 
2.7%
053)593-0025 1
 
2.7%
053)583-1156 1
 
2.7%
053)639-1222 1
 
2.7%
053)651-0802 1
 
2.7%
053)636-2580 1
 
2.7%
053)583-7364 1
 
2.7%
053)633-0877 1
 
2.7%
053)587-5109 1
 
2.7%
Other values (27) 27
73.0%
2023-12-12T14:35:27.363761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 89
20.0%
3 63
14.2%
0 57
12.8%
) 37
8.3%
- 37
8.3%
6 31
 
7.0%
4 27
 
6.1%
1 27
 
6.1%
8 26
 
5.9%
7 22
 
5.0%
Other values (2) 28
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 370
83.3%
Close Punctuation 37
 
8.3%
Dash Punctuation 37
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 89
24.1%
3 63
17.0%
0 57
15.4%
6 31
 
8.4%
4 27
 
7.3%
1 27
 
7.3%
8 26
 
7.0%
7 22
 
5.9%
2 17
 
4.6%
9 11
 
3.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 444
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 89
20.0%
3 63
14.2%
0 57
12.8%
) 37
8.3%
- 37
8.3%
6 31
 
7.0%
4 27
 
6.1%
1 27
 
6.1%
8 26
 
5.9%
7 22
 
5.0%
Other values (2) 28
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 89
20.0%
3 63
14.2%
0 57
12.8%
) 37
8.3%
- 37
8.3%
6 31
 
7.0%
4 27
 
6.1%
1 27
 
6.1%
8 26
 
5.9%
7 22
 
5.0%
Other values (2) 28
 
6.3%

측정항목
Categorical

Distinct2
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size428.0 B
CO/HC/λ/Nox/매연
20 
매연
17 

Length

Max length14
Median length14
Mean length8.4864865
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCO/HC/λ/Nox/매연
2nd row매연
3rd row매연
4th rowCO/HC/λ/Nox/매연
5th row매연

Common Values

ValueCountFrequency (%)
CO/HC/λ/Nox/매연 20
54.1%
매연 17
45.9%

Length

2023-12-12T14:35:27.576388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:35:27.704864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
co/hc/λ/nox/매연 20
54.1%
매연 17
45.9%

Interactions

2023-12-12T14:35:23.234523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:35:27.798515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역업소명대표자소재지전화번호측정항목
연번1.0000.9131.0000.9151.0001.0000.000
지역0.9131.0001.0000.9171.0001.0000.000
업소명1.0001.0001.0001.0001.0001.0001.000
대표자0.9150.9171.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
측정항목0.0000.0001.0001.0001.0001.0001.000
2023-12-12T14:35:27.919392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역측정항목
지역1.0000.000
측정항목0.0001.000
2023-12-12T14:35:28.020474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역측정항목
연번1.0000.7040.000
지역0.7041.0000.000
측정항목0.0000.0001.000

Missing values

2023-12-12T14:35:23.443761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:35:23.626200image/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

연번지역업소명대표자소재지전화번호측정항목
01대구시 동구반야월자동차정비공장박종근동구 안심로 55길 52 (동호동)053)964-0964CO/HC/λ/Nox/매연
12대구시 동구스피드1급카센터전병효동구 송라로 34053)754-1006매연
23대구시 동구자동차도우미이성철동구 공항로 135(불로동)053)382-5582매연
34대구시 서구르노삼성자동차㈜대구사업소대표이사서구 와룡로 392(중리동)053)563-3333CO/HC/λ/Nox/매연
45대구시 서구삼천리보림부란자이철호서구 와룡로87길 68(이현동)053)563-0636매연
56대구시 서구오토1급 카센터박일랑서구 서대구로 225(평리동)053)566-4470CO/HC/λ/Nox/매연
67대구시 서구경북1급종합정비곽동윤서구 북비산로 17길 12(이현동)053)526-8155매연
78대구시 서구청구자동차 전문정비석용우서구 국채보상로 196(평리동)053)551-9737CO/HC/λ/Nox/매연
89대구시 서구동양카센타정점태서구 문화로 327(비산동)053)571-7200CO/HC/λ/Nox/매연
910대구시 서구㈜한독모터스서대구중앙서비스센터박신광서구 와룡로 425(이현동)053)655-7301CO/HC/λ/Nox/매연
연번지역업소명대표자소재지전화번호측정항목
2728대구시 달서구청구1급카써비스박영배달서구 진천로 14 (진천동)053)633-0877CO/HC/λ/Nox/매연
2829대구시 달서구카매니져이상일달서구 성서4차첨단로 169(월암동)053)587-5109매연
2930대구시 달서구진모터스배성호달서구 성서서로 36길 3(갈산동)053)591-1026매연
3031대구시 달서구골든오토이정호달서구 성서4차첨단로111(대천동)053)581-0014매연
3132대구시 달서구영남카정비김현섭달서구 성서공단로11길 6-7 (호림동)053)552-9844CO/HC/λ/Nox/매연
3233대구시 달서구오토1급 카센터용산점박일랑달서구 평리로 68 (용산동)053)566-6644CO/HC/λ/Nox/매연
3334대구시 달성군창림종합정비공장김종만달성군 논공읍 비슬로 1947053)615-4747CO/HC/λ/Nox/매연
3435대구시 달성군애니카랜드다사점이후근달성군 다사읍 대실역북로 90053)563-9551매연
3536대구시 달성군오토파크윤만식달성군 현풍읍 테크노상업로2길 16-14053)611-7136매연
3637대구시 달성군태원모터스임창규달성군 논공읍 논공중앙로34길 10(북리)053)617-8888매연