Overview

Dataset statistics

Number of variables5
Number of observations160
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory41.8 B

Variable types

Numeric1
Text2
DateTime1
Categorical1

Dataset

Description경기도 포천시에서 제공하는 화물운송주선업현황(순번, 상호업체명, 주사무소도로명주소, 허가연월일, 영업상태)데이터 입니다.
Author경기도 포천시
URLhttps://www.data.go.kr/data/15101904/fileData.do

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:04:37.401464
Analysis finished2023-12-12 20:04:38.007869
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct160
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.5
Minimum1
Maximum160
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-13T05:04:38.098382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.95
Q140.75
median80.5
Q3120.25
95-th percentile152.05
Maximum160
Range159
Interquartile range (IQR)79.5

Descriptive statistics

Standard deviation46.332134
Coefficient of variation (CV)0.57555446
Kurtosis-1.2
Mean80.5
Median Absolute Deviation (MAD)40
Skewness0
Sum12880
Variance2146.6667
MonotonicityStrictly increasing
2023-12-13T05:04:38.289880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
82 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
Other values (150) 150
93.8%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%

상호(업체명)
Text

Distinct134
Distinct (%)83.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T05:04:38.628909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length13
Mean length6.3625
Min length4

Characters and Unicode

Total characters1018
Distinct characters182
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)70.0%

Sample

1st row동서고속화물
2nd row(주)동원고속물류
3rd row(주)오피뉴
4th row신용운수
5th row북도퀵화물(정상민)
ValueCountFrequency (%)
나라퀵화물 4
 
2.4%
포천화물 3
 
1.8%
장현화물터미널 3
 
1.8%
mk화물 2
 
1.2%
logistics 2
 
1.2%
삼성화물퀵 2
 
1.2%
대성화물 2
 
1.2%
금화화물 2
 
1.2%
용정종합화물 2
 
1.2%
전국특송 2
 
1.2%
Other values (131) 145
85.8%
2023-12-13T05:04:39.100702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
물 102
 
10.0%
화 87
 
8.5%
( 33
 
3.2%
) 33
 
3.2%
스 32
 
3.1%
퀵 32
 
3.1%
주 27
 
2.7%
고 18
 
1.8%
운 18
 
1.8%
류 18
 
1.8%
Other values (172) 618
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 900
88.4%
Open Punctuation 33
 
3.2%
Close Punctuation 33
 
3.2%
Lowercase Letter 23
 
2.3%
Uppercase Letter 15
 
1.5%
Space Separator 9
 
0.9%
Decimal Number 3
 
0.3%
Other Punctuation 1
 
0.1%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 102
 
11.3%
화 87
 
9.7%
스 32
 
3.6%
퀵 32
 
3.6%
주 27
 
3.0%
고 18
 
2.0%
운 18
 
2.0%
류 18
 
2.0%
성 18
 
2.0%
송 17
 
1.9%
Other values (145) 531
59.0%
Lowercase Letter
ValueCountFrequency (%)
s 4
17.4%
i 4
17.4%
o 2
8.7%
k 2
8.7%
g 2
8.7%
m 2
8.7%
t 2
8.7%
c 2
8.7%
r 1
 
4.3%
w 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
O 4
26.7%
C 2
13.3%
L 2
13.3%
K 2
13.3%
G 2
13.3%
N 1
 
6.7%
W 1
 
6.7%
R 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
2 1
33.3%
4 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 901
88.5%
Common 79
 
7.8%
Latin 38
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 102
 
11.3%
화 87
 
9.7%
스 32
 
3.6%
퀵 32
 
3.6%
주 27
 
3.0%
고 18
 
2.0%
운 18
 
2.0%
류 18
 
2.0%
성 18
 
2.0%
송 17
 
1.9%
Other values (146) 532
59.0%
Latin
ValueCountFrequency (%)
s 4
 
10.5%
i 4
 
10.5%
O 4
 
10.5%
C 2
 
5.3%
L 2
 
5.3%
o 2
 
5.3%
k 2
 
5.3%
g 2
 
5.3%
m 2
 
5.3%
t 2
 
5.3%
Other values (9) 12
31.6%
Common
ValueCountFrequency (%)
( 33
41.8%
) 33
41.8%
9
 
11.4%
3 1
 
1.3%
2 1
 
1.3%
& 1
 
1.3%
4 1
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 900
88.4%
ASCII 117
 
11.5%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
물 102
 
11.3%
화 87
 
9.7%
스 32
 
3.6%
퀵 32
 
3.6%
주 27
 
3.0%
고 18
 
2.0%
운 18
 
2.0%
류 18
 
2.0%
성 18
 
2.0%
송 17
 
1.9%
Other values (145) 531
59.0%
ASCII
ValueCountFrequency (%)
( 33
28.2%
) 33
28.2%
9
 
7.7%
s 4
 
3.4%
i 4
 
3.4%
O 4
 
3.4%
C 2
 
1.7%
L 2
 
1.7%
o 2
 
1.7%
k 2
 
1.7%
Other values (16) 22
18.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주사무소도로명주소
Text

Distinct118
Distinct (%)73.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2023-12-13T05:04:39.468557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length21.44375
Min length15

Characters and Unicode

Total characters3431
Distinct characters125
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

Unique91 ?
Unique (%)56.9%

Sample

1st row경기도 포천시 소흘읍 태봉로 28, 2층
2nd row경기도 포천시 내촌면 포천로 38, 2층
3rd row경기도 포천시 내촌면 부마로282번길 102
4th row경기도 포천시 송선로 464 (선단동)
5th row경기도 포천시 소흘읍 송우로 172, 1층
ValueCountFrequency (%)
경기도 158
19.1%
포천시 152
18.4%
가산면 38
 
4.6%
소흘읍 37
 
4.5%
포천로 23
 
2.8%
내촌면 20
 
2.4%
호국로 19
 
2.3%
영중면 13
 
1.6%
군내면 11
 
1.3%
가산로 11
 
1.3%
Other values (202) 346
41.8%
2023-12-13T05:04:39.988266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
669
19.5%
포 177
 
5.2%
천 176
 
5.1%
도 161
 
4.7%
경 160
 
4.7%
기 158
 
4.6%
시 158
 
4.6%
로 141
 
4.1%
1 138
 
4.0%
2 105
 
3.1%
Other values (115) 1388
40.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2069
60.3%
Space Separator 669
 
19.5%
Decimal Number 595
 
17.3%
Open Punctuation 25
 
0.7%
Close Punctuation 25
 
0.7%
Dash Punctuation 24
 
0.7%
Other Punctuation 22
 
0.6%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
포 177
 
8.6%
천 176
 
8.5%
도 161
 
7.8%
경 160
 
7.7%
기 158
 
7.6%
시 158
 
7.6%
로 141
 
6.8%
면 94
 
4.5%
산 65
 
3.1%
가 60
 
2.9%
Other values (99) 719
34.8%
Decimal Number
ValueCountFrequency (%)
1 138
23.2%
2 105
17.6%
3 61
10.3%
0 56
9.4%
4 51
 
8.6%
9 48
 
8.1%
8 40
 
6.7%
5 38
 
6.4%
6 35
 
5.9%
7 23
 
3.9%
Space Separator
ValueCountFrequency (%)
669
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2069
60.3%
Common 1360
39.6%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
포 177
 
8.6%
천 176
 
8.5%
도 161
 
7.8%
경 160
 
7.7%
기 158
 
7.6%
시 158
 
7.6%
로 141
 
6.8%
면 94
 
4.5%
산 65
 
3.1%
가 60
 
2.9%
Other values (99) 719
34.8%
Common
ValueCountFrequency (%)
669
49.2%
1 138
 
10.1%
2 105
 
7.7%
3 61
 
4.5%
0 56
 
4.1%
4 51
 
3.8%
9 48
 
3.5%
8 40
 
2.9%
5 38
 
2.8%
6 35
 
2.6%
Other values (5) 119
 
8.8%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2069
60.3%
ASCII 1362
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
669
49.1%
1 138
 
10.1%
2 105
 
7.7%
3 61
 
4.5%
0 56
 
4.1%
4 51
 
3.7%
9 48
 
3.5%
8 40
 
2.9%
5 38
 
2.8%
6 35
 
2.6%
Other values (6) 121
 
8.9%
Hangul
ValueCountFrequency (%)
포 177
 
8.6%
천 176
 
8.5%
도 161
 
7.8%
경 160
 
7.7%
기 158
 
7.6%
시 158
 
7.6%
로 141
 
6.8%
면 94
 
4.5%
산 65
 
3.1%
가 60
 
2.9%
Other values (99) 719
34.8%

허가연월일
Date

Distinct119
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum1984-05-29 00:00:00
Maximum2022-03-17 00:00:00
2023-12-13T05:04:40.155679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:04:40.353185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태
Categorical

Distinct3
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
폐지
84 
신규
75 
전출
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
폐지 84
52.5%
신규 75
46.9%
전출 1
 
0.6%

Length

2023-12-13T05:04:40.485324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:04:40.621653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐지 84
52.5%
신규 75
46.9%
전출 1
 
0.6%

Interactions

2023-12-13T05:04:37.696942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:04:40.703125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번영업상태
순번1.0000.000
영업상태0.0001.000
2023-12-13T05:04:40.813300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번영업상태
순번1.0000.000
영업상태0.0001.000

Missing values

2023-12-13T05:04:37.849153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:04:37.967858image/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

순번상호(업체명)주사무소도로명주소허가연월일영업상태
01동서고속화물경기도 포천시 소흘읍 태봉로 28, 2층2022-03-17신규
12(주)동원고속물류경기도 포천시 내촌면 포천로 38, 2층2003-08-18신규
23(주)오피뉴경기도 포천시 내촌면 부마로282번길 1021998-09-05신규
34신용운수경기도 포천시 송선로 464 (선단동)1995-01-17신규
45북도퀵화물(정상민)경기도 포천시 소흘읍 송우로 172, 1층2003-03-11신규
56한백퀵화물경기도 남양주시 진접읍 진벌로 151, 1층2001-11-08폐지
67(주)경기상사경기도 포천시 내촌면 포천로 4232015-09-18신규
78상무익스프레스경기도 포천시 신북면 호국로 20992003-10-15폐지
89진영특송화물경기도 포천시 내촌면 포천로 182015-08-18신규
910전국토탈익스프레스경기도 포천시 가산면 가산로348번길 502006-04-28폐지
순번상호(업체명)주사무소도로명주소허가연월일영업상태
150151나라퀵화물경기도 포천시 소흘읍 죽엽산로 191993-05-04폐지
151152삼보물류경기도 포천시 영중면 금화봉길 326-11993-07-12신규
152153나라퀵화물경기도 포천시 소흘읍 죽엽산로 191993-05-04폐지
153154나라퀵화물경기도 포천시 소흘읍 죽엽산로 191993-05-04폐지
154155북부퀵공동화물경기도 포천시 호국로1025번길 25-20 (선단동)1993-12-17폐지
155156종합화물경기도 포천시 군내면 포천로 10521993-08-14폐지
156157가양주차장경기도 포천시 창수면 가영로150번길 92-151993-06-09폐지
157158빙고특송24경기도 포천시 소흘읍 호국로 410, 에코아울렛 나동 102호1992-11-13신규
158159천리마특송경기도 포천시 가산면 가산로 2091989-07-29신규
159160북부퀵공동화물경기도 포천시 호국로1025번길 25-20 (선단동)1984-05-29폐지