Overview

Dataset statistics

Number of variables5
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory44.7 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description용인시 전세버스, 특수여객 업체 현황
Author경기도 용인시
URLhttps://www.data.go.kr/data/15044267/fileData.do

Alerts

보유대수 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 보유대수High correlation
업체명 has unique valuesUnique
소재지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:07:09.466083
Analysis finished2023-12-12 16:07:09.994786
Duration0.53 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
전세버스
26 
특수여객
10 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전세버스 26
72.2%
특수여객 10
 
27.8%

Length

2023-12-13T01:07:10.074272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:07:10.180161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전세버스 26
72.2%
특수여객 10
 
27.8%

업체명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T01:07:10.385056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length6.3333333
Min length2

Characters and Unicode

Total characters228
Distinct characters97
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

Unique36 ?
Unique (%)100.0%

Sample

1st row(합명)용성고속관광
2nd row㈜홍인관광여행사
3rd row에버모터스㈜
4th row㈜길벗여행사
5th row㈜월명관광여행사
ValueCountFrequency (%)
합명)용성고속관광 1
 
2.8%
㈜홍인관광여행사 1
 
2.8%
신갈아주특수캐딜락 1
 
2.8%
㈜뉴신명관광 1
 
2.8%
㈜리무진클럽여행사 1
 
2.8%
한맥관광㈜ 1
 
2.8%
주)조은투어 1
 
2.8%
㈜오렌지버스투어 1
 
2.8%
엠제이시티㈜ 1
 
2.8%
㈜매방 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T01:07:10.756559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 26
 
11.4%
관 11
 
4.8%
광 11
 
4.8%
여 10
 
4.4%
스 9
 
3.9%
행 8
 
3.5%
사 8
 
3.5%
투 7
 
3.1%
어 7
 
3.1%
장 5
 
2.2%
Other values (87) 126
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 198
86.8%
Other Symbol 26
 
11.4%
Open Punctuation 2
 
0.9%
Close Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 11
 
5.6%
광 11
 
5.6%
여 10
 
5.1%
스 9
 
4.5%
행 8
 
4.0%
사 8
 
4.0%
투 7
 
3.5%
어 7
 
3.5%
장 5
 
2.5%
신 4
 
2.0%
Other values (84) 118
59.6%
Other Symbol
ValueCountFrequency (%)
㈜ 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 224
98.2%
Common 4
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 26
 
11.6%
관 11
 
4.9%
광 11
 
4.9%
여 10
 
4.5%
스 9
 
4.0%
행 8
 
3.6%
사 8
 
3.6%
투 7
 
3.1%
어 7
 
3.1%
장 5
 
2.2%
Other values (85) 122
54.5%
Common
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 198
86.8%
None 26
 
11.4%
ASCII 4
 
1.8%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 26
100.0%
Hangul
ValueCountFrequency (%)
관 11
 
5.6%
광 11
 
5.6%
여 10
 
5.1%
스 9
 
4.5%
행 8
 
4.0%
사 8
 
4.0%
투 7
 
3.5%
어 7
 
3.5%
장 5
 
2.5%
신 4
 
2.0%
Other values (84) 118
59.6%
ASCII
ValueCountFrequency (%)
( 2
50.0%
) 2
50.0%

소재지
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T01:07:11.061620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length20.472222
Min length11

Characters and Unicode

Total characters737
Distinct characters112
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

Unique36 ?
Unique (%)100.0%

Sample

1st row처인구 금령로 75 (김량장동)
2nd row처인구 남동 473-1
3rd row처인구 포곡읍 전대리 95-3
4th row수지구 달맞이로 36(죽전동, 현대프라자 204호)
5th row처인구 신송로 129 (마평동)
ValueCountFrequency (%)
기흥구 17
 
11.4%
처인구 16
 
10.7%
용인시 7
 
4.7%
구갈동 3
 
2.0%
김량장동 2
 
1.3%
남동 2
 
1.3%
기흥로 2
 
1.3%
남사면 2
 
1.3%
수지구 2
 
1.3%
죽전로 2
 
1.3%
Other values (92) 94
63.1%
2023-12-13T01:07:11.456377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
15.3%
구 45
 
6.1%
동 30
 
4.1%
1 27
 
3.7%
로 25
 
3.4%
인 23
 
3.1%
2 22
 
3.0%
흥 20
 
2.7%
기 20
 
2.7%
( 19
 
2.6%
Other values (102) 393
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 404
54.8%
Decimal Number 153
 
20.8%
Space Separator 113
 
15.3%
Open Punctuation 19
 
2.6%
Close Punctuation 19
 
2.6%
Other Punctuation 16
 
2.2%
Dash Punctuation 13
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 45
 
11.1%
동 30
 
7.4%
로 25
 
6.2%
인 23
 
5.7%
흥 20
 
5.0%
기 20
 
5.0%
처 16
 
4.0%
갈 11
 
2.7%
호 10
 
2.5%
용 8
 
2.0%
Other values (87) 196
48.5%
Decimal Number
ValueCountFrequency (%)
1 27
17.6%
2 22
14.4%
0 18
11.8%
3 17
11.1%
5 15
9.8%
4 15
9.8%
6 13
8.5%
8 11
7.2%
7 8
 
5.2%
9 7
 
4.6%
Space Separator
ValueCountFrequency (%)
113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 404
54.8%
Common 333
45.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 45
 
11.1%
동 30
 
7.4%
로 25
 
6.2%
인 23
 
5.7%
흥 20
 
5.0%
기 20
 
5.0%
처 16
 
4.0%
갈 11
 
2.7%
호 10
 
2.5%
용 8
 
2.0%
Other values (87) 196
48.5%
Common
ValueCountFrequency (%)
113
33.9%
1 27
 
8.1%
2 22
 
6.6%
( 19
 
5.7%
) 19
 
5.7%
0 18
 
5.4%
3 17
 
5.1%
, 16
 
4.8%
5 15
 
4.5%
4 15
 
4.5%
Other values (5) 52
15.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 404
54.8%
ASCII 333
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
33.9%
1 27
 
8.1%
2 22
 
6.6%
( 19
 
5.7%
) 19
 
5.7%
0 18
 
5.4%
3 17
 
5.1%
, 16
 
4.8%
5 15
 
4.5%
4 15
 
4.5%
Other values (5) 52
15.6%
Hangul
ValueCountFrequency (%)
구 45
 
11.1%
동 30
 
7.4%
로 25
 
6.2%
인 23
 
5.7%
흥 20
 
5.0%
기 20
 
5.0%
처 16
 
4.0%
갈 11
 
2.7%
호 10
 
2.5%
용 8
 
2.0%
Other values (87) 196
48.5%

보유대수
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.805556
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-13T01:07:11.586501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median17.5
Q334.25
95-th percentile59
Maximum93
Range92
Interquartile range (IQR)28.25

Descriptive statistics

Standard deviation21.84598
Coefficient of variation (CV)0.91768409
Kurtosis3.2980618
Mean23.805556
Median Absolute Deviation (MAD)15.5
Skewness1.5794783
Sum857
Variance477.24683
MonotonicityNot monotonic
2023-12-13T01:07:11.692507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 5
 
13.9%
16 3
 
8.3%
37 2
 
5.6%
17 2
 
5.6%
2 2
 
5.6%
6 2
 
5.6%
35 2
 
5.6%
34 2
 
5.6%
36 1
 
2.8%
18 1
 
2.8%
Other values (14) 14
38.9%
ValueCountFrequency (%)
1 5
13.9%
2 2
 
5.6%
3 1
 
2.8%
6 2
 
5.6%
11 1
 
2.8%
13 1
 
2.8%
14 1
 
2.8%
16 3
8.3%
17 2
 
5.6%
18 1
 
2.8%
ValueCountFrequency (%)
93 1
2.8%
89 1
2.8%
49 1
2.8%
48 1
2.8%
37 2
5.6%
36 1
2.8%
35 2
5.6%
34 2
5.6%
33 1
2.8%
31 1
2.8%

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-13T01:07:11.891082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.2777778
Min length8

Characters and Unicode

Total characters298
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

Unique36 ?
Unique (%)100.0%

Sample

1st row332-4445
2nd row321-5206
3rd row322-7733
4th row261-8009
5th row332-7778
ValueCountFrequency (%)
332-4445 1
 
2.8%
321-5206 1
 
2.8%
285-4444 1
 
2.8%
781-8088 1
 
2.8%
241-0034 1
 
2.8%
555-2886 1
 
2.8%
273-4488 1
 
2.8%
262-3210 1
 
2.8%
889-9784 1
 
2.8%
02-408-7205 1
 
2.8%
Other values (26) 26
72.2%
2023-12-13T01:07:12.242102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 44
14.8%
- 39
13.1%
0 35
11.7%
4 33
11.1%
3 31
10.4%
8 26
8.7%
5 22
7.4%
7 22
7.4%
1 16
 
5.4%
9 16
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 259
86.9%
Dash Punctuation 39
 
13.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 44
17.0%
0 35
13.5%
4 33
12.7%
3 31
12.0%
8 26
10.0%
5 22
8.5%
7 22
8.5%
1 16
 
6.2%
9 16
 
6.2%
6 14
 
5.4%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 298
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 44
14.8%
- 39
13.1%
0 35
11.7%
4 33
11.1%
3 31
10.4%
8 26
8.7%
5 22
7.4%
7 22
7.4%
1 16
 
5.4%
9 16
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 44
14.8%
- 39
13.1%
0 35
11.7%
4 33
11.1%
3 31
10.4%
8 26
8.7%
5 22
7.4%
7 22
7.4%
1 16
 
5.4%
9 16
 
5.4%

Interactions

2023-12-13T01:07:09.739269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:07:12.331868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분업체명소재지보유대수전화번호
구분1.0001.0001.0001.0001.000
업체명1.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.000
보유대수1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
2023-12-13T01:07:12.420332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보유대수구분
보유대수1.0000.939
구분0.9391.000

Missing values

2023-12-13T01:07:09.851480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:07:09.949128image/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

구분업체명소재지보유대수전화번호
0전세버스(합명)용성고속관광처인구 금령로 75 (김량장동)37332-4445
1전세버스㈜홍인관광여행사처인구 남동 473-129321-5206
2전세버스에버모터스㈜처인구 포곡읍 전대리 95-316322-7733
3전세버스㈜길벗여행사수지구 달맞이로 36(죽전동, 현대프라자 204호)89261-8009
4전세버스㈜월명관광여행사처인구 신송로 129 (마평동)25332-7778
5전세버스뉴현대관광㈜기흥구 구갈로60번길 9, 902호 (구갈동, 로얄프라자)34286-9779
6전세버스㈜에스엠여행사용인시 기흥구 삼성2로42번길 4 (농서동)36276-1441
7전세버스여산관광㈜용인시 기흥구 농서로 17(고매동)34275-1721
8전세버스새림투어닷컴㈜기흥구 덕영대로 1678(서천동)17204-2420
9전세버스㈜현대항공여행사기흥구 구갈로60번길 11-1(구갈동, 흥원빌딩401호)18285-6400
구분업체명소재지보유대수전화번호
26특수여객신갈아주특수캐딜락용인시 기흥구 상하동 135-36285-4444
27특수여객㈜매방용인시 처인구 남사면 완장전로 448-20, 2호602-408-7205
28특수여객제생처인구 이동면 천리 503-73703-4369
29특수여객샘물호스피스선교회백암면 고안리 5481329-2999
30특수여객신명가특수여객기흥구 구갈동 412-6 4층1282-0134
31특수여객용인장의차처인구 남동 26-31339-4300
32특수여객신용인장례식장처인구 역북동 4051337-3100
33특수여객영문장의버스처인구 김량장동 143-82323-4444
34특수여객장율처인구 이동면 평온의숲로 772329-5959
35특수여객㈜용인베스트처인구 양지면 남곡리 281-21338-9444