Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells2
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory46.5 B

Variable types

Unsupported2
Text2
Numeric1

Dataset

Description대전광역시에 등록되어 있는 특수여객(장의) 운송사업 현황 자료로 상호, 설립날짜, 주사무소, 보유대수의 정보가 포함되어 있습니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15077204/fileData.do

Alerts

상     호 has 1 (4.2%) missing valuesMissing
주 사 무 소 has 1 (4.2%) missing valuesMissing
연번 is an unsupported type, check if it needs cleaning or further analysisUnsupported
설립날짜 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 13:00:15.528824
Analysis finished2023-12-12 13:00:16.102677
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size324.0 B

상     호
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing1
Missing (%)4.2%
Memory size324.0 B
2023-12-12T22:00:16.248118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.9130435
Min length4

Characters and Unicode

Total characters159
Distinct characters68
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)100.0%

Sample

1st row(자)동원특수여객
2nd row대전캐딜락
3rd row동남기업
4th row청원특수여객
5th row보람정보산업(주)(영업소)
ValueCountFrequency (%)
화 2
 
6.9%
자)동원특수여객 1
 
3.4%
대진특수여객 1
 
3.4%
인 1
 
3.4%
늘 1
 
3.4%
하 1
 
3.4%
㈜ 1
 
3.4%
금 1
 
3.4%
우리특수이송 1
 
3.4%
오성장례서비스 1
 
3.4%
Other values (18) 18
62.1%
2023-12-12T22:00:16.629441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
11.9%
수 10
 
6.3%
특 10
 
6.3%
객 8
 
5.0%
여 8
 
5.0%
대 4
 
2.5%
( 4
 
2.5%
) 4
 
2.5%
원 3
 
1.9%
진 3
 
1.9%
Other values (58) 86
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
77.4%
Space Separator 19
 
11.9%
Open Punctuation 4
 
2.5%
Close Punctuation 4
 
2.5%
Other Symbol 3
 
1.9%
Decimal Number 3
 
1.9%
Uppercase Letter 2
 
1.3%
Lowercase Letter 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 10
 
8.1%
특 10
 
8.1%
객 8
 
6.5%
여 8
 
6.5%
대 4
 
3.3%
원 3
 
2.4%
진 3
 
2.4%
리 3
 
2.4%
딜 3
 
2.4%
락 3
 
2.4%
Other values (49) 68
55.3%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
D 1
50.0%
F 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 126
79.2%
Common 30
 
18.9%
Latin 3
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 10
 
7.9%
특 10
 
7.9%
객 8
 
6.3%
여 8
 
6.3%
대 4
 
3.2%
원 3
 
2.4%
진 3
 
2.4%
리 3
 
2.4%
딜 3
 
2.4%
락 3
 
2.4%
Other values (50) 71
56.3%
Common
ValueCountFrequency (%)
19
63.3%
( 4
 
13.3%
) 4
 
13.3%
1 2
 
6.7%
9 1
 
3.3%
Latin
ValueCountFrequency (%)
e 1
33.3%
D 1
33.3%
F 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
77.4%
ASCII 33
 
20.8%
None 3
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
57.6%
( 4
 
12.1%
) 4
 
12.1%
1 2
 
6.1%
e 1
 
3.0%
9 1
 
3.0%
D 1
 
3.0%
F 1
 
3.0%
Hangul
ValueCountFrequency (%)
수 10
 
8.1%
특 10
 
8.1%
객 8
 
6.5%
여 8
 
6.5%
대 4
 
3.3%
원 3
 
2.4%
진 3
 
2.4%
리 3
 
2.4%
딜 3
 
2.4%
락 3
 
2.4%
Other values (49) 68
55.3%
None
ValueCountFrequency (%)
㈜ 3
100.0%

설립날짜
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size324.0 B

주 사 무 소
Text

MISSING 

Distinct17
Distinct (%)73.9%
Missing1
Missing (%)4.2%
Memory size324.0 B
2023-12-12T22:00:16.834774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length12.695652
Min length9

Characters and Unicode

Total characters292
Distinct characters45
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

Unique12 ?
Unique (%)52.2%

Sample

1st row서구 정림서로 189
2nd row서구 도솔로 141-6
3rd row동구 산서로1604번길 8
4th row중구 대전천서로 745
5th row중구 동서대로 1297
ValueCountFrequency (%)
중구 10
 
14.5%
동구 7
 
10.1%
산내로1299번길 5
 
7.2%
서구 4
 
5.8%
45 3
 
4.3%
46 2
 
2.9%
대전천서로 2
 
2.9%
745 2
 
2.9%
55 2
 
2.9%
중촌동 2
 
2.9%
Other values (27) 30
43.5%
2023-12-12T22:00:17.213908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
15.8%
구 23
 
7.9%
로 20
 
6.8%
1 19
 
6.5%
중 15
 
5.1%
9 15
 
5.1%
5 14
 
4.8%
길 11
 
3.8%
4 11
 
3.8%
동 11
 
3.8%
Other values (35) 107
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 152
52.1%
Decimal Number 91
31.2%
Space Separator 46
 
15.8%
Dash Punctuation 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 23
15.1%
로 20
13.2%
중 15
9.9%
길 11
 
7.2%
동 11
 
7.2%
번 11
 
7.2%
서 10
 
6.6%
대 7
 
4.6%
산 7
 
4.6%
내 5
 
3.3%
Other values (23) 32
21.1%
Decimal Number
ValueCountFrequency (%)
1 19
20.9%
9 15
16.5%
5 14
15.4%
4 11
12.1%
2 9
9.9%
6 7
 
7.7%
7 7
 
7.7%
8 5
 
5.5%
3 2
 
2.2%
0 2
 
2.2%
Space Separator
ValueCountFrequency (%)
46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 152
52.1%
Common 140
47.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 23
15.1%
로 20
13.2%
중 15
9.9%
길 11
 
7.2%
동 11
 
7.2%
번 11
 
7.2%
서 10
 
6.6%
대 7
 
4.6%
산 7
 
4.6%
내 5
 
3.3%
Other values (23) 32
21.1%
Common
ValueCountFrequency (%)
46
32.9%
1 19
13.6%
9 15
 
10.7%
5 14
 
10.0%
4 11
 
7.9%
2 9
 
6.4%
6 7
 
5.0%
7 7
 
5.0%
8 5
 
3.6%
- 3
 
2.1%
Other values (2) 4
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 152
52.1%
ASCII 140
47.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
32.9%
1 19
13.6%
9 15
 
10.7%
5 14
 
10.0%
4 11
 
7.9%
2 9
 
6.4%
6 7
 
5.0%
7 7
 
5.0%
8 5
 
3.6%
- 3
 
2.1%
Other values (2) 4
 
2.9%
Hangul
ValueCountFrequency (%)
구 23
15.1%
로 20
13.2%
중 15
9.9%
길 11
 
7.2%
동 11
 
7.2%
번 11
 
7.2%
서 10
 
6.6%
대 7
 
4.6%
산 7
 
4.6%
내 5
 
3.3%
Other values (23) 32
21.1%

계
Real number (ℝ)

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.6666667
Minimum1
Maximum116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T22:00:17.358986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37.5
95-th percentile13.7
Maximum116
Range115
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation22.971943
Coefficient of variation (CV)2.3764079
Kurtosis22.49646
Mean9.6666667
Median Absolute Deviation (MAD)3
Skewness4.6809096
Sum232
Variance527.71014
MonotonicityNot monotonic
2023-12-12T22:00:17.482163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 5
20.8%
1 4
16.7%
7 3
12.5%
3 2
 
8.3%
4 2
 
8.3%
116 1
 
4.2%
12 1
 
4.2%
6 1
 
4.2%
11 1
 
4.2%
9 1
 
4.2%
Other values (3) 3
12.5%
ValueCountFrequency (%)
1 4
16.7%
2 5
20.8%
3 2
 
8.3%
4 2
 
8.3%
5 1
 
4.2%
6 1
 
4.2%
7 3
12.5%
9 1
 
4.2%
10 1
 
4.2%
11 1
 
4.2%
ValueCountFrequency (%)
116 1
 
4.2%
14 1
 
4.2%
12 1
 
4.2%
11 1
 
4.2%
10 1
 
4.2%
9 1
 
4.2%
7 3
12.5%
6 1
 
4.2%
5 1
 
4.2%
4 2
8.3%

Interactions

2023-12-12T22:00:15.677657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:00:17.575550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상     호주 사 무 소계
상     호1.0001.0001.000
주 사 무 소1.0001.0001.000
계1.0001.0001.000

Missing values

2023-12-12T22:00:15.823651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:00:15.937701image/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.
2023-12-12T22:00:16.051333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번상     호설립날짜주 사 무 소계
0계<NA>23<NA>116
11(자)동원특수여객1963.06.12서구 정림서로 1897
22대전캐딜락1969.06.05서구 도솔로 141-612
33동남기업2000.08.07동구 산서로1604번길 83
44청원특수여객2003.11.01중구 대전천서로 7451
55보람정보산업(주)(영업소)2005.06.30중구 동서대로 12972
66(재)대전교구천주교회재단2006.01.03중구 대흥로 642
77㈜해참특수2007.06.05대덕구 신탄진로218번길 626
88이 화2008.03.20서구 가수원중로57번길 554
99태경특수여객2009.02.04중구 중촌동 19511
연번상     호설립날짜주 사 무 소계
1414FD장례2012.04.13중구 선화로12번길 510
1515대진특수여객2012.06.04중구 문화로 71-13
1616영생캐딜락2014.07.08.동구 산내로1299번길 455
1717명진리무진2015.06.19동구 대별동 844
1818e 이화2016.01.26서구 가수원중로57번길 557
1919오성장례서비스2016.08.04중구 보문산로 110-11
2020우리특수이송2018.12.05동구 산내로1299번길 461
2121금 화2017.05.16동구 산내로1299번길 462
2222㈜ 하 늘 인2017.08.09중구 중촌동 1957
2323㈜119특수여객충효2018.06.21대덕구 중리서로 92