Overview

Dataset statistics

Number of variables6
Number of observations119
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description부산광역시 강서구내 건설기계사업자 현황 정보 입니다. 건설기계에 사용하는 중장비대여업 정보이며 제공하는 정보는 다음과 같습니다.(상호(명칭), 사업유형, 등록종별, 주소 등)
URLhttps://www.data.go.kr/data/15006101/fileData.do

Alerts

등록종별 is highly overall correlated with 사업유형High correlation
사업유형 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 is highly overall correlated with 사업유형High correlation
상태 is highly imbalanced (75.3%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:29:15.286486
Analysis finished2023-12-12 08:29:16.097197
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct119
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60
Minimum1
Maximum119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T17:29:16.180368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.9
Q130.5
median60
Q389.5
95-th percentile113.1
Maximum119
Range118
Interquartile range (IQR)59

Descriptive statistics

Standard deviation34.496377
Coefficient of variation (CV)0.57493961
Kurtosis-1.2
Mean60
Median Absolute Deviation (MAD)30
Skewness0
Sum7140
Variance1190
MonotonicityStrictly increasing
2023-12-12T17:29:16.360707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.8%
2 1
 
0.8%
89 1
 
0.8%
88 1
 
0.8%
87 1
 
0.8%
86 1
 
0.8%
85 1
 
0.8%
84 1
 
0.8%
83 1
 
0.8%
82 1
 
0.8%
Other values (109) 109
91.6%
ValueCountFrequency (%)
1 1
0.8%
2 1
0.8%
3 1
0.8%
4 1
0.8%
5 1
0.8%
6 1
0.8%
7 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
ValueCountFrequency (%)
119 1
0.8%
118 1
0.8%
117 1
0.8%
116 1
0.8%
115 1
0.8%
114 1
0.8%
113 1
0.8%
112 1
0.8%
111 1
0.8%
110 1
0.8%

상태
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
영업
111 
<NA>
 
7
재개업
 
1

Length

Max length4
Median length2
Mean length2.1260504
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
영업 111
93.3%
<NA> 7
 
5.9%
재개업 1
 
0.8%

Length

2023-12-12T17:29:16.562414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:16.679946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 111
93.3%
na 7
 
5.9%
재개업 1
 
0.8%

상호(명칭)
Text

Distinct105
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:29:16.960047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length11
Mean length7.4621849
Min length3

Characters and Unicode

Total characters888
Distinct characters146
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

Unique93 ?
Unique (%)78.2%

Sample

1st row(주)북부녹산폐차장
2nd row(주)현진아이엘
3rd row부산종합중기정비공장
4th row두산종합정비
5th row렌텍(주)
ValueCountFrequency (%)
주식회사 4
 
3.2%
렌텍(주 3
 
2.4%
주)현진아이엘 3
 
2.4%
주)현대지게차판매 2
 
1.6%
클라크지게차영남총판 2
 
1.6%
연일(주 2
 
1.6%
두산종합정비 2
 
1.6%
서부산지게차마트 2
 
1.6%
클라크지게차부산(주 2
 
1.6%
신창건기 2
 
1.6%
Other values (99) 102
81.0%
2023-12-12T17:29:17.396682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 55
 
6.2%
( 52
 
5.9%
) 52
 
5.9%
기 42
 
4.7%
중 28
 
3.2%
산 23
 
2.6%
비 23
 
2.6%
건 21
 
2.4%
합 21
 
2.4%
지 21
 
2.4%
Other values (136) 550
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 773
87.0%
Open Punctuation 52
 
5.9%
Close Punctuation 52
 
5.9%
Space Separator 7
 
0.8%
Uppercase Letter 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 55
 
7.1%
기 42
 
5.4%
중 28
 
3.6%
산 23
 
3.0%
비 23
 
3.0%
건 21
 
2.7%
합 21
 
2.7%
지 21
 
2.7%
차 21
 
2.7%
정 20
 
2.6%
Other values (129) 498
64.4%
Uppercase Letter
ValueCountFrequency (%)
V 1
25.0%
T 1
25.0%
B 1
25.0%
K 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 773
87.0%
Common 111
 
12.5%
Latin 4
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 55
 
7.1%
기 42
 
5.4%
중 28
 
3.6%
산 23
 
3.0%
비 23
 
3.0%
건 21
 
2.7%
합 21
 
2.7%
지 21
 
2.7%
차 21
 
2.7%
정 20
 
2.6%
Other values (129) 498
64.4%
Latin
ValueCountFrequency (%)
V 1
25.0%
T 1
25.0%
B 1
25.0%
K 1
25.0%
Common
ValueCountFrequency (%)
( 52
46.8%
) 52
46.8%
7
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 773
87.0%
ASCII 115
 
13.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 55
 
7.1%
기 42
 
5.4%
중 28
 
3.6%
산 23
 
3.0%
비 23
 
3.0%
건 21
 
2.7%
합 21
 
2.7%
지 21
 
2.7%
차 21
 
2.7%
정 20
 
2.6%
Other values (129) 498
64.4%
ASCII
ValueCountFrequency (%)
( 52
45.2%
) 52
45.2%
7
 
6.1%
V 1
 
0.9%
T 1
 
0.9%
B 1
 
0.9%
K 1
 
0.9%

사업유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
대여업
59 
매매업
30 
정비업
29 
해체재활용업
 
1

Length

Max length6
Median length3
Mean length3.0252101
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
대여업 59
49.6%
매매업 30
25.2%
정비업 29
24.4%
해체재활용업 1
 
0.8%

Length

2023-12-12T17:29:17.578578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:17.725657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대여업 59
49.6%
매매업 30
25.2%
정비업 29
24.4%
해체재활용업 1
 
0.8%

등록종별
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
일반
44 
<NA>
31 
개별
15 
종합(덤프 및 믹서트럭)
13 
종합(지게차)
7 
Other values (4)
9 

Length

Max length13
Median length12
Mean length4.4789916
Min length2

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st row<NA>
2nd row종합(지게차)
3rd row종합(전기종)
4th row부분(타이어식은 종합)
5th row전문(유압)

Common Values

ValueCountFrequency (%)
일반 44
37.0%
<NA> 31
26.1%
개별 15
 
12.6%
종합(덤프 및 믹서트럭) 13
 
10.9%
종합(지게차) 7
 
5.9%
부분(타이어식은 종합) 3
 
2.5%
전문(유압) 3
 
2.5%
부분(일반) 2
 
1.7%
종합(전기종) 1
 
0.8%

Length

2023-12-12T17:29:17.877148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:29:18.041784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 44
29.7%
na 31
20.9%
개별 15
 
10.1%
종합(덤프 13
 
8.8%
및 13
 
8.8%
믹서트럭 13
 
8.8%
종합(지게차 7
 
4.7%
부분(타이어식은 3
 
2.0%
종합 3
 
2.0%
전문(유압 3
 
2.0%
Other values (2) 3
 
2.0%

주소
Text

Distinct94
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T17:29:18.383316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length29.168067
Min length21

Characters and Unicode

Total characters3471
Distinct characters102
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)64.7%

Sample

1st row부산광역시 강서구 녹산산업북로193번길 14(송정동)
2nd row부산광역시 강서구 가리새2로 37(범방동)
3rd row부산광역시 강서구 녹산산업북로193번길 7(송정동)
4th row부산광역시 강서구 녹산산업북로 189(송정동)
5th row부산광역시 강서구 녹산산업북로 161-10(송정동)
ValueCountFrequency (%)
부산광역시 119
21.9%
강서구 119
21.9%
녹산산업북로 15
 
2.8%
유통단지1로 13
 
2.4%
41 12
 
2.2%
부산티플렉스 10
 
1.8%
녹산산업북로193번길 7
 
1.3%
미음산단로295번길 5
 
0.9%
과학산단2로43번길 5
 
0.9%
15(미음동 5
 
0.9%
Other values (172) 233
42.9%
2023-12-12T17:29:18.921814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
424
 
12.2%
산 203
 
5.8%
1 198
 
5.7%
동 149
 
4.3%
부 130
 
3.7%
강 126
 
3.6%
2 126
 
3.6%
서 125
 
3.6%
시 121
 
3.5%
광 119
 
3.4%
Other values (92) 1750
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2092
60.3%
Decimal Number 650
 
18.7%
Space Separator 424
 
12.2%
Close Punctuation 117
 
3.4%
Open Punctuation 117
 
3.4%
Other Punctuation 47
 
1.4%
Dash Punctuation 22
 
0.6%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 203
 
9.7%
동 149
 
7.1%
부 130
 
6.2%
강 126
 
6.0%
서 125
 
6.0%
시 121
 
5.8%
광 119
 
5.7%
역 119
 
5.7%
구 119
 
5.7%
로 109
 
5.2%
Other values (75) 772
36.9%
Decimal Number
ValueCountFrequency (%)
1 198
30.5%
2 126
19.4%
3 57
 
8.8%
0 54
 
8.3%
5 51
 
7.8%
4 46
 
7.1%
9 37
 
5.7%
6 33
 
5.1%
7 27
 
4.2%
8 21
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
424
100.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Other Punctuation
ValueCountFrequency (%)
, 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2092
60.3%
Common 1377
39.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 203
 
9.7%
동 149
 
7.1%
부 130
 
6.2%
강 126
 
6.0%
서 125
 
6.0%
시 121
 
5.8%
광 119
 
5.7%
역 119
 
5.7%
구 119
 
5.7%
로 109
 
5.2%
Other values (75) 772
36.9%
Common
ValueCountFrequency (%)
424
30.8%
1 198
14.4%
2 126
 
9.2%
) 117
 
8.5%
( 117
 
8.5%
3 57
 
4.1%
0 54
 
3.9%
5 51
 
3.7%
, 47
 
3.4%
4 46
 
3.3%
Other values (5) 140
 
10.2%
Latin
ValueCountFrequency (%)
C 1
50.0%
B 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2092
60.3%
ASCII 1379
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
424
30.7%
1 198
14.4%
2 126
 
9.1%
) 117
 
8.5%
( 117
 
8.5%
3 57
 
4.1%
0 54
 
3.9%
5 51
 
3.7%
, 47
 
3.4%
4 46
 
3.3%
Other values (7) 142
 
10.3%
Hangul
ValueCountFrequency (%)
산 203
 
9.7%
동 149
 
7.1%
부 130
 
6.2%
강 126
 
6.0%
서 125
 
6.0%
시 121
 
5.8%
광 119
 
5.7%
역 119
 
5.7%
구 119
 
5.7%
로 109
 
5.2%
Other values (75) 772
36.9%

Interactions

2023-12-12T17:29:15.766378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:29:19.033540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상태사업유형등록종별주소
순번1.0000.0000.8570.5800.689
상태0.0001.0000.0000.0001.000
사업유형0.8570.0001.0001.0000.783
등록종별0.5800.0001.0001.0000.689
주소0.6891.0000.7830.6891.000
2023-12-12T17:29:19.125394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상태등록종별사업유형
상태1.0000.0000.000
등록종별0.0001.0000.964
사업유형0.0000.9641.000
2023-12-12T17:29:19.213664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상태사업유형등록종별
순번1.0000.0000.6900.329
상태0.0001.0000.0000.000
사업유형0.6900.0001.0000.964
등록종별0.3290.0000.9641.000

Missing values

2023-12-12T17:29:15.908572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:29:16.035617image/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
01영업(주)북부녹산폐차장해체재활용업<NA>부산광역시 강서구 녹산산업북로193번길 14(송정동)
12영업(주)현진아이엘정비업종합(지게차)부산광역시 강서구 가리새2로 37(범방동)
23영업부산종합중기정비공장정비업종합(전기종)부산광역시 강서구 녹산산업북로193번길 7(송정동)
34영업두산종합정비정비업부분(타이어식은 종합)부산광역시 강서구 녹산산업북로 189(송정동)
45영업렌텍(주)정비업전문(유압)부산광역시 강서구 녹산산업북로 161-10(송정동)
56영업종합지게차정비(주)정비업부분(타이어식은 종합)부산광역시 강서구 녹산산업북로313번길 66(송정동)
67영업(주)신항자동차정비업종합(덤프 및 믹서트럭)부산광역시 강서구 녹산산업북로 183(송정동)
78영업대우종합정비정비업종합(덤프 및 믹서트럭)부산광역시 강서구 녹산산업북로193번길 23(송정동)
89영업(주)VT신항종합정비정비업종합(덤프 및 믹서트럭)부산광역시 강서구 녹산산업북로 161-13(송정동)
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