Overview

Dataset statistics

Number of variables6
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory53.3 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description대구광역시 서구 건설기계사업자 현황 데이터 입니다. 현재 영업상태, 상호명칭, 사업유형, 등록종별, 주소 등을 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15091965/fileData.do

Alerts

상태 has constant value ""Constant
순번 is highly overall correlated with 사업유형High correlation
사업유형 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
등록종별 is highly overall correlated with 사업유형High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:17:00.501117
Analysis finished2023-12-12 00:17:00.994902
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T09:17:01.061687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2023-12-12T09:17:01.186747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

상태
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
영업
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업
2nd row영업
3rd row영업
4th row영업
5th row영업

Common Values

ValueCountFrequency (%)
영업 31
100.0%

Length

2023-12-12T09:17:01.316597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:01.429849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 31
100.0%

상호(명칭)
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T09:17:01.636933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length8.1290323
Min length4

Characters and Unicode

Total characters252
Distinct characters71
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)87.1%

Sample

1st row달구벌자동차종합정비공장
2nd row대우자동차정비공장
3rd row보성종합정비(주)
4th row(주)정안
5th row두산FLS
ValueCountFrequency (%)
주)현대건설기계정비 2
 
6.2%
진보중기(주 2
 
6.2%
달구벌자동차종합정비공장 1
 
3.1%
모든종합중기(주 1
 
3.1%
나래중기매매상사 1
 
3.1%
대박상사 1
 
3.1%
기린지게차 1
 
3.1%
주식회사 1
 
3.1%
쌍용자동차대구사업소 1
 
3.1%
신대우종합정비(주 1
 
3.1%
Other values (20) 20
62.5%
2023-12-12T09:17:01.977248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 17
 
6.7%
주 15
 
6.0%
( 14
 
5.6%
) 14
 
5.6%
대 12
 
4.8%
정 10
 
4.0%
합 10
 
4.0%
종 10
 
4.0%
중 10
 
4.0%
비 9
 
3.6%
Other values (61) 131
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 220
87.3%
Open Punctuation 14
 
5.6%
Close Punctuation 14
 
5.6%
Uppercase Letter 3
 
1.2%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 17
 
7.7%
주 15
 
6.8%
대 12
 
5.5%
정 10
 
4.5%
합 10
 
4.5%
종 10
 
4.5%
중 10
 
4.5%
비 9
 
4.1%
매 7
 
3.2%
차 7
 
3.2%
Other values (55) 113
51.4%
Uppercase Letter
ValueCountFrequency (%)
F 1
33.3%
L 1
33.3%
S 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 220
87.3%
Common 29
 
11.5%
Latin 3
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 17
 
7.7%
주 15
 
6.8%
대 12
 
5.5%
정 10
 
4.5%
합 10
 
4.5%
종 10
 
4.5%
중 10
 
4.5%
비 9
 
4.1%
매 7
 
3.2%
차 7
 
3.2%
Other values (55) 113
51.4%
Common
ValueCountFrequency (%)
( 14
48.3%
) 14
48.3%
1
 
3.4%
Latin
ValueCountFrequency (%)
F 1
33.3%
L 1
33.3%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 220
87.3%
ASCII 32
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 17
 
7.7%
주 15
 
6.8%
대 12
 
5.5%
정 10
 
4.5%
합 10
 
4.5%
종 10
 
4.5%
중 10
 
4.5%
비 9
 
4.1%
매 7
 
3.2%
차 7
 
3.2%
Other values (55) 113
51.4%
ASCII
ValueCountFrequency (%)
( 14
43.8%
) 14
43.8%
1
 
3.1%
F 1
 
3.1%
L 1
 
3.1%
S 1
 
3.1%

사업유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
정비업
13 
대여업
10 
매매업
7 
해체재활용업
 
1

Length

Max length6
Median length3
Mean length3.0967742
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row정비업
2nd row정비업
3rd row정비업
4th row정비업
5th row정비업

Common Values

ValueCountFrequency (%)
정비업 13
41.9%
대여업 10
32.3%
매매업 7
22.6%
해체재활용업 1
 
3.2%

Length

2023-12-12T09:17:02.138442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:02.244342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정비업 13
41.9%
대여업 10
32.3%
매매업 7
22.6%
해체재활용업 1
 
3.2%

등록종별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
8 
일반
7 
종합(덤프 및 믹서트럭)
5 
부분(일반)
4 
개별
3 
Other values (4)
4 

Length

Max length13
Median length7
Mean length5.4193548
Min length2

Unique

Unique4 ?
Unique (%)12.9%

Sample

1st row종합(덤프 및 믹서트럭)
2nd row부분(일반)
3rd row종합(전기종)
4th row종합(덤프 및 믹서트럭)
5th row부분(일반)

Common Values

ValueCountFrequency (%)
<NA> 8
25.8%
일반 7
22.6%
종합(덤프 및 믹서트럭) 5
16.1%
부분(일반) 4
12.9%
개별 3
 
9.7%
종합(전기종) 1
 
3.2%
전문(유압) 1
 
3.2%
종합(굴착기) 1
 
3.2%
종합(지게차) 1
 
3.2%

Length

2023-12-12T09:17:02.358699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:17:02.477057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8
19.5%
일반 7
17.1%
종합(덤프 5
12.2%
및 5
12.2%
믹서트럭 5
12.2%
부분(일반 4
9.8%
개별 3
 
7.3%
종합(전기종 1
 
2.4%
전문(유압 1
 
2.4%
종합(굴착기 1
 
2.4%

주소
Text

Distinct26
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T09:17:02.702201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length28
Mean length23.741935
Min length20

Characters and Unicode

Total characters736
Distinct characters62
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

Unique23 ?
Unique (%)74.2%

Sample

1st row대구광역시 서구 와룡로 319(중리동)
2nd row대구광역시 서구 염색공단천로8길 16-2(비산동)
3rd row대구광역시 서구 북비산로 87(이현동)
4th row대구광역시 서구 팔달로18길 20-3(비산동)
5th row대구광역시 서구 와룡로 393, ,71번지
ValueCountFrequency (%)
대구광역시 31
23.5%
서구 31
23.5%
와룡로 7
 
5.3%
가르뱅이로 5
 
3.8%
79-15(상리동 4
 
3.0%
서대구로 4
 
3.0%
25(내당동 2
 
1.5%
염색공단천로14길 2
 
1.5%
서대구로7길 2
 
1.5%
78(평리동 2
 
1.5%
Other values (42) 42
31.8%
2023-12-12T09:17:03.064048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
13.7%
구 68
 
9.2%
대 39
 
5.3%
서 38
 
5.2%
광 31
 
4.2%
역 31
 
4.2%
시 31
 
4.2%
로 30
 
4.1%
동 29
 
3.9%
) 27
 
3.7%
Other values (52) 311
42.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 445
60.5%
Decimal Number 116
 
15.8%
Space Separator 101
 
13.7%
Close Punctuation 27
 
3.7%
Open Punctuation 27
 
3.7%
Dash Punctuation 12
 
1.6%
Other Punctuation 8
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 68
15.3%
대 39
 
8.8%
서 38
 
8.5%
광 31
 
7.0%
역 31
 
7.0%
시 31
 
7.0%
로 30
 
6.7%
동 29
 
6.5%
리 13
 
2.9%
이 11
 
2.5%
Other values (37) 124
27.9%
Decimal Number
ValueCountFrequency (%)
1 23
19.8%
7 13
11.2%
4 13
11.2%
9 12
10.3%
3 12
10.3%
5 11
9.5%
2 11
9.5%
6 9
 
7.8%
8 7
 
6.0%
0 5
 
4.3%
Space Separator
ValueCountFrequency (%)
101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 445
60.5%
Common 291
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 68
15.3%
대 39
 
8.8%
서 38
 
8.5%
광 31
 
7.0%
역 31
 
7.0%
시 31
 
7.0%
로 30
 
6.7%
동 29
 
6.5%
리 13
 
2.9%
이 11
 
2.5%
Other values (37) 124
27.9%
Common
ValueCountFrequency (%)
101
34.7%
) 27
 
9.3%
( 27
 
9.3%
1 23
 
7.9%
7 13
 
4.5%
4 13
 
4.5%
- 12
 
4.1%
9 12
 
4.1%
3 12
 
4.1%
5 11
 
3.8%
Other values (5) 40
 
13.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 445
60.5%
ASCII 291
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
34.7%
) 27
 
9.3%
( 27
 
9.3%
1 23
 
7.9%
7 13
 
4.5%
4 13
 
4.5%
- 12
 
4.1%
9 12
 
4.1%
3 12
 
4.1%
5 11
 
3.8%
Other values (5) 40
 
13.7%
Hangul
ValueCountFrequency (%)
구 68
15.3%
대 39
 
8.8%
서 38
 
8.5%
광 31
 
7.0%
역 31
 
7.0%
시 31
 
7.0%
로 30
 
6.7%
동 29
 
6.5%
리 13
 
2.9%
이 11
 
2.5%
Other values (37) 124
27.9%

Interactions

2023-12-12T09:17:00.736514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:17:03.164086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상호(명칭)사업유형등록종별주소
순번1.0000.8650.7800.3390.678
상호(명칭)0.8651.0000.7051.0001.000
사업유형0.7800.7051.0001.0000.897
등록종별0.3391.0001.0001.0001.000
주소0.6781.0000.8971.0001.000
2023-12-12T09:17:03.253307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록종별사업유형
등록종별1.0000.845
사업유형0.8451.000
2023-12-12T09:17:03.328049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번사업유형등록종별
순번1.0000.5090.452
사업유형0.5091.0000.845
등록종별0.4520.8451.000

Missing values

2023-12-12T09:17:00.863086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:17:00.954074image/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

순번상태상호(명칭)사업유형등록종별주소
01영업달구벌자동차종합정비공장정비업종합(덤프 및 믹서트럭)대구광역시 서구 와룡로 319(중리동)
12영업대우자동차정비공장정비업부분(일반)대구광역시 서구 염색공단천로8길 16-2(비산동)
23영업보성종합정비(주)정비업종합(전기종)대구광역시 서구 북비산로 87(이현동)
34영업(주)정안정비업종합(덤프 및 믹서트럭)대구광역시 서구 팔달로18길 20-3(비산동)
45영업두산FLS정비업부분(일반)대구광역시 서구 와룡로 393, ,71번지
56영업두산중기정비정비업전문(유압)대구광역시 서구 와룡로 439-8(이현동)
67영업두산지게차대구판매(주)정비업부분(일반)대구광역시 서구 와룡로 447(이현동)
78영업건륭종합정비공장정비업종합(덤프 및 믹서트럭)대구광역시 서구 염색공단천로14길 9-10, ,17
89영업진성지게차매매상사매매업<NA>대구광역시 서구 염색공단천로 26-1(비산동)
910영업대국건설기계매매업<NA>대구광역시 서구 가르뱅이로 79-15(상리동)
순번상태상호(명칭)사업유형등록종별주소
2122영업(주)현대건설기계정비정비업종합(굴착기)대구광역시 서구 가르뱅이로 79-15(상리동)
2223영업제일종합정비정비업종합(덤프 및 믹서트럭)대구광역시 서구 염색공단천로14길 6(비산동)
2324영업신대우종합정비(주)정비업종합(덤프 및 믹서트럭)대구광역시 서구 팔달로2길 34(비산동)
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