Overview

Dataset statistics

Number of variables5
Number of observations44
Missing cells18
Missing cells (%)8.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory43.9 B

Variable types

Categorical1
Text3
Numeric1

Dataset

Description관광사업등록 중 여행업에 대한 정보입니다.가. 국내여행업: 국내를 여행하는 내국인을 대상으로 하는 여행업나. 국내외여행업: 국내외를 여행하는 내국인을 대상으로 하는 여행업다. 종합여행업: 국내외를 여행하는 내/외국인을 대상으로 하는 여행업
Author부산광역시 강서구
URLhttps://www.data.go.kr/data/15026342/fileData.do

Alerts

전화번호 has 18 (40.9%) missing valuesMissing

Reproduction

Analysis started2024-03-14 17:09:58.598060
Analysis finished2024-03-14 17:09:59.651716
Duration1.05 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct7
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size480.0 B
국내외여행업
16 
종합여행업
12 
국내여행업
10 
외국인관광 도시민박업
2 
국제회의기획업
2 
Other values (2)
2 

Length

Max length11
Median length9
Mean length5.7954545
Min length5

Unique

Unique2 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 16
36.4%
종합여행업 12
27.3%
국내여행업 10
22.7%
외국인관광 도시민박업 2
 
4.5%
국제회의기획업 2
 
4.5%
일반야영장업 1
 
2.3%
자동차야영장업 1
 
2.3%

Length

2024-03-15T02:09:59.888321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T02:10:00.199601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 16
34.8%
종합여행업 12
26.1%
국내여행업 10
21.7%
외국인관광 2
 
4.3%
도시민박업 2
 
4.3%
국제회의기획업 2
 
4.3%
일반야영장업 1
 
2.2%
자동차야영장업 1
 
2.2%

상호
Text

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T02:10:01.017607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.1818182
Min length2

Characters and Unicode

Total characters316
Distinct characters122
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)95.5%

Sample

1st row(주)부산트랩
2nd row댕큐블랙
3rd row삼부자 여행사
4th row(주)유림이엔티
5th row주식회사 응카
ValueCountFrequency (%)
주식회사 6
 
10.9%
주)부산여행사 2
 
3.6%
여행사 2
 
3.6%
주)트윈스라이팅 1
 
1.8%
나나투어 1
 
1.8%
스타엘 1
 
1.8%
주)삼천리투어 1
 
1.8%
영한여행사 1
 
1.8%
samsung 1
 
1.8%
tour 1
 
1.8%
Other values (38) 38
69.1%
2024-03-15T02:10:02.032436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 24
 
7.6%
( 17
 
5.4%
) 17
 
5.4%
사 12
 
3.8%
어 12
 
3.8%
11
 
3.5%
이 10
 
3.2%
투 10
 
3.2%
행 9
 
2.8%
여 9
 
2.8%
Other values (112) 185
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
81.6%
Open Punctuation 17
 
5.4%
Close Punctuation 17
 
5.4%
Space Separator 11
 
3.5%
Uppercase Letter 11
 
3.5%
Other Symbol 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 24
 
9.3%
사 12
 
4.7%
어 12
 
4.7%
이 10
 
3.9%
투 10
 
3.9%
행 9
 
3.5%
여 9
 
3.5%
스 7
 
2.7%
리 6
 
2.3%
식 6
 
2.3%
Other values (99) 153
59.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
18.2%
U 2
18.2%
G 1
9.1%
N 1
9.1%
M 1
9.1%
R 1
9.1%
T 1
9.1%
O 1
9.1%
A 1
9.1%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 260
82.3%
Common 45
 
14.2%
Latin 11
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 24
 
9.2%
사 12
 
4.6%
어 12
 
4.6%
이 10
 
3.8%
투 10
 
3.8%
행 9
 
3.5%
여 9
 
3.5%
스 7
 
2.7%
리 6
 
2.3%
식 6
 
2.3%
Other values (100) 155
59.6%
Latin
ValueCountFrequency (%)
S 2
18.2%
U 2
18.2%
G 1
9.1%
N 1
9.1%
M 1
9.1%
R 1
9.1%
T 1
9.1%
O 1
9.1%
A 1
9.1%
Common
ValueCountFrequency (%)
( 17
37.8%
) 17
37.8%
11
24.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
81.6%
ASCII 56
 
17.7%
None 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 24
 
9.3%
사 12
 
4.7%
어 12
 
4.7%
이 10
 
3.9%
투 10
 
3.9%
행 9
 
3.5%
여 9
 
3.5%
스 7
 
2.7%
리 6
 
2.3%
식 6
 
2.3%
Other values (99) 153
59.3%
ASCII
ValueCountFrequency (%)
( 17
30.4%
) 17
30.4%
11
19.6%
S 2
 
3.6%
U 2
 
3.6%
G 1
 
1.8%
N 1
 
1.8%
M 1
 
1.8%
R 1
 
1.8%
T 1
 
1.8%
Other values (2) 2
 
3.6%
None
ValueCountFrequency (%)
㈜ 2
100.0%

우편번호
Real number (ℝ)

Distinct17
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean46724.909
Minimum46700
Maximum46773
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size524.0 B
2024-03-15T02:10:02.404823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46700
5-th percentile46700
Q146714.5
median46721
Q346726
95-th percentile46763.7
Maximum46773
Range73
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation20.747449
Coefficient of variation (CV)0.00044403403
Kurtosis0.18883708
Mean46724.909
Median Absolute Deviation (MAD)5
Skewness0.98635514
Sum2055896
Variance430.45666
MonotonicityNot monotonic
2024-03-15T02:10:02.716725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
46721 8
18.2%
46726 7
15.9%
46720 5
11.4%
46700 5
11.4%
46702 3
 
6.8%
46762 3
 
6.8%
46727 2
 
4.5%
46705 2
 
4.5%
46722 1
 
2.3%
46771 1
 
2.3%
Other values (7) 7
15.9%
ValueCountFrequency (%)
46700 5
11.4%
46702 3
 
6.8%
46705 2
 
4.5%
46707 1
 
2.3%
46717 1
 
2.3%
46719 1
 
2.3%
46720 5
11.4%
46721 8
18.2%
46722 1
 
2.3%
46726 7
15.9%
ValueCountFrequency (%)
46773 1
 
2.3%
46771 1
 
2.3%
46764 1
 
2.3%
46762 3
 
6.8%
46760 1
 
2.3%
46757 1
 
2.3%
46727 2
 
4.5%
46726 7
15.9%
46722 1
 
2.3%
46721 8
18.2%

소재지(도로명)
Text

Distinct42
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size480.0 B
2024-03-15T02:10:03.772751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length44
Mean length35.681818
Min length21

Characters and Unicode

Total characters1570
Distinct characters129
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)90.9%

Sample

1st row부산광역시 강서구 공항로743번길 2-1 (대저2동)
2nd row부산광역시 강서구 식만로 2 (죽림동)
3rd row부산광역시 강서구 범방3로72번길 14 (범방동)
4th row부산광역시 강서구 낙동북로73번길 15, 1층 (강동동)
5th row부산광역시 강서구 대저중앙로394번길 32 (대저1동)
ValueCountFrequency (%)
부산광역시 44
 
15.0%
강서구 44
 
15.0%
대저2동 15
 
5.1%
명지동 13
 
4.4%
1층 8
 
2.7%
대저1동 8
 
2.7%
유통단지1로 8
 
2.7%
50 6
 
2.0%
41 5
 
1.7%
부산티플렉스 5
 
1.7%
Other values (115) 138
46.9%
2024-03-15T02:10:05.399754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
250
 
15.9%
1 69
 
4.4%
동 62
 
3.9%
2 57
 
3.6%
산 54
 
3.4%
시 51
 
3.2%
부 49
 
3.1%
강 46
 
2.9%
서 45
 
2.9%
역 44
 
2.8%
Other values (119) 843
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 901
57.4%
Decimal Number 291
 
18.5%
Space Separator 250
 
15.9%
Close Punctuation 44
 
2.8%
Open Punctuation 44
 
2.8%
Other Punctuation 31
 
2.0%
Dash Punctuation 6
 
0.4%
Uppercase Letter 2
 
0.1%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 62
 
6.9%
산 54
 
6.0%
시 51
 
5.7%
부 49
 
5.4%
강 46
 
5.1%
서 45
 
5.0%
역 44
 
4.9%
구 44
 
4.9%
광 44
 
4.9%
로 40
 
4.4%
Other values (101) 422
46.8%
Decimal Number
ValueCountFrequency (%)
1 69
23.7%
2 57
19.6%
0 32
11.0%
3 30
10.3%
4 22
 
7.6%
5 21
 
7.2%
9 18
 
6.2%
6 15
 
5.2%
8 14
 
4.8%
7 13
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
B 1
50.0%
Space Separator
ValueCountFrequency (%)
250
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Open Punctuation
ValueCountFrequency (%)
( 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 31
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 901
57.4%
Common 666
42.4%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 62
 
6.9%
산 54
 
6.0%
시 51
 
5.7%
부 49
 
5.4%
강 46
 
5.1%
서 45
 
5.0%
역 44
 
4.9%
구 44
 
4.9%
광 44
 
4.9%
로 40
 
4.4%
Other values (101) 422
46.8%
Common
ValueCountFrequency (%)
250
37.5%
1 69
 
10.4%
2 57
 
8.6%
) 44
 
6.6%
( 44
 
6.6%
0 32
 
4.8%
, 31
 
4.7%
3 30
 
4.5%
4 22
 
3.3%
5 21
 
3.2%
Other values (5) 66
 
9.9%
Latin
ValueCountFrequency (%)
K 1
33.3%
B 1
33.3%
e 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 901
57.4%
ASCII 669
42.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
250
37.4%
1 69
 
10.3%
2 57
 
8.5%
) 44
 
6.6%
( 44
 
6.6%
0 32
 
4.8%
, 31
 
4.6%
3 30
 
4.5%
4 22
 
3.3%
5 21
 
3.1%
Other values (8) 69
 
10.3%
Hangul
ValueCountFrequency (%)
동 62
 
6.9%
산 54
 
6.0%
시 51
 
5.7%
부 49
 
5.4%
강 46
 
5.1%
서 45
 
5.0%
역 44
 
4.9%
구 44
 
4.9%
광 44
 
4.9%
로 40
 
4.4%
Other values (101) 422
46.8%

전화번호
Text

MISSING 

Distinct24
Distinct (%)92.3%
Missing18
Missing (%)40.9%
Memory size480.0 B
2024-03-15T02:10:06.074760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.076923
Min length12

Characters and Unicode

Total characters314
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

Unique22 ?
Unique (%)84.6%

Sample

1st row051-912-3377
2nd row051-941-5802
3rd row051-941-9082
4th row051-941-1801
5th row051-832-0093
ValueCountFrequency (%)
051-808-1011 2
 
7.7%
051-310-6034 2
 
7.7%
051-912-3377 1
 
3.8%
051-744-7177 1
 
3.8%
051-463-4144 1
 
3.8%
051-201-4960 1
 
3.8%
070-4149-0071 1
 
3.8%
051-442-0755 1
 
3.8%
051-831-5555 1
 
3.8%
051-972-5648 1
 
3.8%
Other values (14) 14
53.8%
2024-03-15T02:10:07.050686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
19.4%
- 52
16.6%
1 48
15.3%
5 36
11.5%
4 23
 
7.3%
7 22
 
7.0%
2 16
 
5.1%
8 15
 
4.8%
3 15
 
4.8%
9 15
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 262
83.4%
Dash Punctuation 52
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
23.3%
1 48
18.3%
5 36
13.7%
4 23
 
8.8%
7 22
 
8.4%
2 16
 
6.1%
8 15
 
5.7%
3 15
 
5.7%
9 15
 
5.7%
6 11
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 314
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
19.4%
- 52
16.6%
1 48
15.3%
5 36
11.5%
4 23
 
7.3%
7 22
 
7.0%
2 16
 
5.1%
8 15
 
4.8%
3 15
 
4.8%
9 15
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 314
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
19.4%
- 52
16.6%
1 48
15.3%
5 36
11.5%
4 23
 
7.3%
7 22
 
7.0%
2 16
 
5.1%
8 15
 
4.8%
3 15
 
4.8%
9 15
 
4.8%

Interactions

2024-03-15T02:09:59.020413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T02:10:07.214183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종상호우편번호소재지(도로명)전화번호
업종1.0000.9720.1230.9940.000
상호0.9721.0001.0001.0001.000
우편번호0.1231.0001.0001.0001.000
소재지(도로명)0.9941.0001.0001.0001.000
전화번호0.0001.0001.0001.0001.000
2024-03-15T02:10:07.463688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호업종
우편번호1.0000.000
업종0.0001.000

Missing values

2024-03-15T02:09:59.388151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T02:09:59.558688image/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

업종상호우편번호소재지(도로명)전화번호
0국내여행업(주)부산트랩46720부산광역시 강서구 공항로743번길 2-1 (대저2동)051-912-3377
1국내여행업댕큐블랙46707부산광역시 강서구 식만로 2 (죽림동)051-941-5802
2국내여행업삼부자 여행사46727부산광역시 강서구 범방3로72번길 14 (범방동)051-941-9082
3국내여행업(주)유림이엔티46705부산광역시 강서구 낙동북로73번길 15, 1층 (강동동)051-941-1801
4국내여행업주식회사 응카46702부산광역시 강서구 대저중앙로394번길 32 (대저1동)051-832-0093
5국내여행업(주)부산여행사46726부산광역시 강서구 명지국제6로 21, 플러스시티 605호 (명지동)051-808-1011
6국내여행업(주)로메인인터네셔널46721부산광역시 강서구 유통단지1로 50, 부산티플렉스 217동 1층 105호 (대저2동)<NA>
7국내여행업우짜46717부산광역시 강서구 에코델타스마트로 39, 어반테크하우스 산학연계지원공간 3동 1호 (명지동)<NA>
8국내여행업탑리무진투어46720부산광역시 강서구 공항로743번길 2-1 (대저2동)<NA>
9국내여행업빌리밀리46762부산광역시 강서구 명지오션시티9로 50, 102동 1901호 (명지동)<NA>
업종상호우편번호소재지(도로명)전화번호
34종합여행업메디핑크46721부산광역시 강서구 유통단지1로 41, 부산티플렉스 115동 208호 (대저2동)<NA>
35종합여행업(주)티제이투어46762부산광역시 강서구 명지오션시티9로 50, 삼정그린코아 웨스트 2층 202호 (명지동)<NA>
36종합여행업(주)포커스투어46720부산광역시 강서구 공항앞길163번길 99-2 (대저2동)051-463-4144
37종합여행업㈜이음컴퍼니46727부산광역시 강서구 범방3로64번길 42, 1층 (범방동)<NA>
38일반야영장업대저생태공원캠핑장46700부산광역시 강서구 대저로 3, 대저캠핑장 (대저1동)051-310-6034
39자동차야영장업대저생태공원 캠핑장46700부산광역시 강서구 대저로 3 (대저1동)051-310-6034
40외국인관광 도시민박업스카이필드46722부산광역시 강서구 금호순서길89번가길 48, 스카이필드 (대저2동)<NA>
41외국인관광 도시민박업부산 백패커46720부산광역시 강서구 공항앞길187번길 20 (대저2동)<NA>
42국제회의기획업(주)트윈스라이팅46702부산광역시 강서구 공항로1309번길 95-5 (대저1동)051-314-4607
43국제회의기획업주식회사 유림이엔티46705부산광역시 강서구 낙동북로73번길 15 (강동동)<NA>