Overview

Dataset statistics

Number of variables7
Number of observations31
Missing cells6
Missing cells (%)2.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory61.3 B

Variable types

Categorical1
Text4
Numeric1
DateTime1

Dataset

Description전라남도 보성군에 소속된 운송사업체 현황에 대한 공공데이터로 업체명, 연략처, 소재지, 업종,면허대수 등의 정보를 제공합니다.
Author전라남도 보성군
URLhttps://www.data.go.kr/data/3033597/fileData.do

Alerts

전화번호 has 6 (19.4%) missing valuesMissing
업 체 명 has unique valuesUnique
면허일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:11:04.756412
Analysis finished2023-12-12 10:11:05.627449
Duration0.87 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업 종
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
일반화물자동차
15 
일반택시
7 
특수여객
5 
전세버스
3 
농어촌버스
 
1

Length

Max length7
Median length5
Mean length5.483871
Min length4

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row농어촌버스
2nd row전세버스
3rd row전세버스
4th row전세버스
5th row특수여객

Common Values

ValueCountFrequency (%)
일반화물자동차 15
48.4%
일반택시 7
22.6%
특수여객 5
 
16.1%
전세버스 3
 
9.7%
농어촌버스 1
 
3.2%

Length

2023-12-12T19:11:05.741973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:05.920809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반화물자동차 15
48.4%
일반택시 7
22.6%
특수여객 5
 
16.1%
전세버스 3
 
9.7%
농어촌버스 1
 
3.2%

업 체 명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:11:06.216820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.9032258
Min length3

Characters and Unicode

Total characters183
Distinct characters73
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row(주)보성교통
2nd row(유)보라고속관광
3rd row(유)나라고속
4th row여로관광협동조합
5th row춘추장례식장
ValueCountFrequency (%)
주)보성교통 1
 
3.2%
유)보성운수 1
 
3.2%
㈜에이원 1
 
3.2%
㈜대광물류 1
 
3.2%
보성축산물류 1
 
3.2%
㈜벌교화물 1
 
3.2%
조성물류(오치윤 1
 
3.2%
유)백제특수 1
 
3.2%
보성왕겨덤프 1
 
3.2%
청하렉카 1
 
3.2%
Other values (21) 21
67.7%
2023-12-12T19:11:06.723951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 10
 
5.5%
) 10
 
5.5%
성 10
 
5.5%
보 9
 
4.9%
장 8
 
4.4%
물 7
 
3.8%
시 7
 
3.8%
택 7
 
3.8%
유 7
 
3.8%
광 5
 
2.7%
Other values (63) 103
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
87.4%
Open Punctuation 10
 
5.5%
Close Punctuation 10
 
5.5%
Other Symbol 3
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 10
 
6.2%
보 9
 
5.6%
장 8
 
5.0%
물 7
 
4.4%
시 7
 
4.4%
택 7
 
4.4%
유 7
 
4.4%
광 5
 
3.1%
교 5
 
3.1%
벌 4
 
2.5%
Other values (60) 91
56.9%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 163
89.1%
Common 20
 
10.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 10
 
6.1%
보 9
 
5.5%
장 8
 
4.9%
물 7
 
4.3%
시 7
 
4.3%
택 7
 
4.3%
유 7
 
4.3%
광 5
 
3.1%
교 5
 
3.1%
벌 4
 
2.5%
Other values (61) 94
57.7%
Common
ValueCountFrequency (%)
( 10
50.0%
) 10
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
87.4%
ASCII 20
 
10.9%
None 3
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 10
50.0%
) 10
50.0%
Hangul
ValueCountFrequency (%)
성 10
 
6.2%
보 9
 
5.6%
장 8
 
5.0%
물 7
 
4.4%
시 7
 
4.4%
택 7
 
4.4%
유 7
 
4.4%
광 5
 
3.1%
교 5
 
3.1%
벌 4
 
2.5%
Other values (60) 91
56.9%
None
ValueCountFrequency (%)
㈜ 3
100.0%

전화번호
Text

MISSING 

Distinct23
Distinct (%)92.0%
Missing6
Missing (%)19.4%
Memory size380.0 B
2023-12-12T19:11:06.988540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.96
Min length11

Characters and Unicode

Total characters299
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

Unique21 ?
Unique (%)84.0%

Sample

1st row061-857-7293
2nd row061-857-6565
3rd row062-526-7700
4th row061-858-0456
5th row061-858-4441
ValueCountFrequency (%)
061-852-2011 2
 
8.0%
061-857-2611 2
 
8.0%
061-857-0511 1
 
4.0%
061-857-7293 1
 
4.0%
061-857-6565 1
 
4.0%
061-858-2331 1
 
4.0%
061-857-1294 1
 
4.0%
02-529-0027 1
 
4.0%
061-857-0150 1
 
4.0%
061-852-7700 1
 
4.0%
Other values (13) 13
52.0%
2023-12-12T19:11:07.422553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 50
16.7%
0 47
15.7%
1 39
13.0%
5 35
11.7%
6 31
10.4%
8 29
9.7%
2 25
8.4%
7 16
 
5.4%
4 15
 
5.0%
3 7
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 249
83.3%
Dash Punctuation 50
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 47
18.9%
1 39
15.7%
5 35
14.1%
6 31
12.4%
8 29
11.6%
2 25
10.0%
7 16
 
6.4%
4 15
 
6.0%
3 7
 
2.8%
9 5
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 299
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 50
16.7%
0 47
15.7%
1 39
13.0%
5 35
11.7%
6 31
10.4%
8 29
9.7%
2 25
8.4%
7 16
 
5.4%
4 15
 
5.0%
3 7
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 299
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 50
16.7%
0 47
15.7%
1 39
13.0%
5 35
11.7%
6 31
10.4%
8 29
9.7%
2 25
8.4%
7 16
 
5.4%
4 15
 
5.0%
3 7
 
2.3%

대표자
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:11:07.694370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0322581
Min length3

Characters and Unicode

Total characters94
Distinct characters58
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)90.3%

Sample

1st row박재순
2nd row장복자
3rd row지상룡
4th row박우진
5th row반재훈
ValueCountFrequency (%)
주초호 3
 
9.7%
박재순 1
 
3.2%
최오봉 1
 
3.2%
이태오 1
 
3.2%
정경희 1
 
3.2%
오치윤 1
 
3.2%
김진혁 1
 
3.2%
김종현 1
 
3.2%
김청현 1
 
3.2%
이선호 1
 
3.2%
Other values (19) 19
61.3%
2023-12-12T19:11:08.073787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 6
 
6.4%
주 4
 
4.3%
호 4
 
4.3%
진 4
 
4.3%
박 3
 
3.2%
초 3
 
3.2%
순 3
 
3.2%
정 3
 
3.2%
오 3
 
3.2%
재 3
 
3.2%
Other values (48) 58
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 93
98.9%
Space Separator 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
6.5%
주 4
 
4.3%
호 4
 
4.3%
진 4
 
4.3%
박 3
 
3.2%
초 3
 
3.2%
순 3
 
3.2%
정 3
 
3.2%
오 3
 
3.2%
재 3
 
3.2%
Other values (47) 57
61.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 93
98.9%
Common 1
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 6
 
6.5%
주 4
 
4.3%
호 4
 
4.3%
진 4
 
4.3%
박 3
 
3.2%
초 3
 
3.2%
순 3
 
3.2%
정 3
 
3.2%
오 3
 
3.2%
재 3
 
3.2%
Other values (47) 57
61.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 93
98.9%
ASCII 1
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 6
 
6.5%
주 4
 
4.3%
호 4
 
4.3%
진 4
 
4.3%
박 3
 
3.2%
초 3
 
3.2%
순 3
 
3.2%
정 3
 
3.2%
오 3
 
3.2%
재 3
 
3.2%
Other values (47) 57
61.3%
ASCII
ValueCountFrequency (%)
1
100.0%

면허대수
Real number (ℝ)

Distinct17
Distinct (%)54.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.16129
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T19:11:08.257659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q316
95-th percentile46.5
Maximum52
Range51
Interquartile range (IQR)14

Descriptive statistics

Standard deviation15.624973
Coefficient of variation (CV)1.2848121
Kurtosis0.97223781
Mean12.16129
Median Absolute Deviation (MAD)4
Skewness1.4849172
Sum377
Variance244.13978
MonotonicityNot monotonic
2023-12-12T19:11:08.401079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2 7
22.6%
1 6
19.4%
5 3
9.7%
6 2
 
6.5%
30 1
 
3.2%
43 1
 
3.2%
35 1
 
3.2%
9 1
 
3.2%
34 1
 
3.2%
25 1
 
3.2%
Other values (7) 7
22.6%
ValueCountFrequency (%)
1 6
19.4%
2 7
22.6%
3 1
 
3.2%
5 3
9.7%
6 2
 
6.5%
7 1
 
3.2%
9 1
 
3.2%
10 1
 
3.2%
13 1
 
3.2%
19 1
 
3.2%
ValueCountFrequency (%)
52 1
3.2%
50 1
3.2%
43 1
3.2%
35 1
3.2%
34 1
3.2%
30 1
3.2%
25 1
3.2%
19 1
3.2%
13 1
3.2%
10 1
3.2%

소재지
Text

Distinct28
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T19:11:08.646829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length22
Mean length20.322581
Min length11

Characters and Unicode

Total characters630
Distinct characters75
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

Unique26 ?
Unique (%)83.9%

Sample

1st row전라남도 보성군 벌교읍 홍암로 277
2nd row전라남도 보성군 보성읍 흥성로 2665
3rd row본사)광주광역시 서구
4th row전라남도 보성군 벌교읍 채동선로 99
5th row전라남도 보성군 벌교읍 원동길 81
ValueCountFrequency (%)
전라남도 30
19.6%
보성군 30
19.6%
벌교읍 16
 
10.5%
보성읍 9
 
5.9%
채동선로 6
 
3.9%
현충로 4
 
2.6%
원동길 3
 
2.0%
송재로 3
 
2.0%
12 3
 
2.0%
171 3
 
2.0%
Other values (44) 46
30.1%
2023-12-12T19:11:09.095783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
19.4%
성 41
 
6.5%
보 39
 
6.2%
남 33
 
5.2%
전 30
 
4.8%
도 30
 
4.8%
군 30
 
4.8%
라 30
 
4.8%
읍 25
 
4.0%
1 22
 
3.5%
Other values (65) 228
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 409
64.9%
Space Separator 122
 
19.4%
Decimal Number 89
 
14.1%
Dash Punctuation 8
 
1.3%
Other Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
성 41
 
10.0%
보 39
 
9.5%
남 33
 
8.1%
전 30
 
7.3%
도 30
 
7.3%
군 30
 
7.3%
라 30
 
7.3%
읍 25
 
6.1%
로 19
 
4.6%
벌 16
 
3.9%
Other values (51) 116
28.4%
Decimal Number
ValueCountFrequency (%)
1 22
24.7%
2 14
15.7%
7 12
13.5%
8 7
 
7.9%
0 7
 
7.9%
9 7
 
7.9%
3 6
 
6.7%
4 5
 
5.6%
6 5
 
5.6%
5 4
 
4.5%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 409
64.9%
Common 221
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
성 41
 
10.0%
보 39
 
9.5%
남 33
 
8.1%
전 30
 
7.3%
도 30
 
7.3%
군 30
 
7.3%
라 30
 
7.3%
읍 25
 
6.1%
로 19
 
4.6%
벌 16
 
3.9%
Other values (51) 116
28.4%
Common
ValueCountFrequency (%)
122
55.2%
1 22
 
10.0%
2 14
 
6.3%
7 12
 
5.4%
- 8
 
3.6%
8 7
 
3.2%
0 7
 
3.2%
9 7
 
3.2%
3 6
 
2.7%
4 5
 
2.3%
Other values (4) 11
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 409
64.9%
ASCII 221
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
55.2%
1 22
 
10.0%
2 14
 
6.3%
7 12
 
5.4%
- 8
 
3.6%
8 7
 
3.2%
0 7
 
3.2%
9 7
 
3.2%
3 6
 
2.7%
4 5
 
2.3%
Other values (4) 11
 
5.0%
Hangul
ValueCountFrequency (%)
성 41
 
10.0%
보 39
 
9.5%
남 33
 
8.1%
전 30
 
7.3%
도 30
 
7.3%
군 30
 
7.3%
라 30
 
7.3%
읍 25
 
6.1%
로 19
 
4.6%
벌 16
 
3.9%
Other values (51) 116
28.4%

면허일자
Date

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
Minimum1956-06-07 00:00:00
Maximum2019-06-11 00:00:00
2023-12-12T19:11:09.236607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:11:09.401222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

Interactions

2023-12-12T19:11:05.188917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:11:09.519449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업 종업 체 명전화번호대표자면허대수소재지면허일자
업 종1.0001.0001.0001.0000.6921.0001.000
업 체 명1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0000.0001.0001.000
대표자1.0001.0001.0001.0000.0001.0001.000
면허대수0.6921.0000.0000.0001.0000.0001.000
소재지1.0001.0001.0001.0000.0001.0001.000
면허일자1.0001.0001.0001.0001.0001.0001.000
2023-12-12T19:11:09.637553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면허대수업 종
면허대수1.0000.444
업 종0.4441.000

Missing values

2023-12-12T19:11:05.368101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:11:05.556690image/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

업 종업 체 명전화번호대표자면허대수소재지면허일자
0농어촌버스(주)보성교통061-857-7293박재순30전라남도 보성군 벌교읍 홍암로 2771986-11-13
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