Overview

Dataset statistics

Number of variables7
Number of observations120
Missing cells382
Missing cells (%)45.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory60.1 B

Variable types

Categorical1
Text3
Unsupported3

Dataset

Description울산광역시 남구 여행업 현황에 대한 데이터로 업종(국내여행업, 국내외여행업, 종합여행업), 상호, 소재지(도로명), 전화번호 항목을 제공합니다.
Author울산광역시 남구
URLhttps://www.data.go.kr/data/15032280/fileData.do

Alerts

전화번호 has 22 (18.3%) missing valuesMissing
Unnamed: 4 has 120 (100.0%) missing valuesMissing
Unnamed: 5 has 120 (100.0%) missing valuesMissing
Unnamed: 6 has 120 (100.0%) missing valuesMissing
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 11:57:04.723074
Analysis finished2023-12-12 11:57:05.300684
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct3
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
국내외여행업
78 
종합여행업
29 
국내여행업
13 

Length

Max length6
Median length6
Mean length5.65
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 78
65.0%
종합여행업 29
 
24.2%
국내여행업 13
 
10.8%

Length

2023-12-12T20:57:05.390178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:57:05.542500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국내외여행업 78
65.0%
종합여행업 29
 
24.2%
국내여행업 13
 
10.8%

상호
Text

Distinct117
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T20:57:05.860029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length8.625
Min length4

Characters and Unicode

Total characters1035
Distinct characters197
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)95.0%

Sample

1st row(주)굿모닝해외여행사
2nd row프라임여행사
3rd row(주)동진관광
4th row가자고속투어 주식회사
5th row에코투어 태화강협동조합
ValueCountFrequency (%)
주식회사 21
 
12.3%
여행사 10
 
5.8%
주 5
 
2.9%
투어 4
 
2.3%
아이펙투어 2
 
1.2%
주)굿모닝해외여행사 2
 
1.2%
글로벌투어 2
 
1.2%
연수센타 2
 
1.2%
너랑나랑 1
 
0.6%
에이치투어(h-tour 1
 
0.6%
Other values (121) 121
70.8%
2023-12-12T20:57:06.389569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 72
 
7.0%
주 70
 
6.8%
행 57
 
5.5%
여 57
 
5.5%
51
 
4.9%
( 51
 
4.9%
) 51
 
4.9%
어 39
 
3.8%
투 35
 
3.4%
이 24
 
2.3%
Other values (187) 528
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 843
81.4%
Space Separator 51
 
4.9%
Open Punctuation 51
 
4.9%
Close Punctuation 51
 
4.9%
Uppercase Letter 25
 
2.4%
Lowercase Letter 13
 
1.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 72
 
8.5%
주 70
 
8.3%
행 57
 
6.8%
여 57
 
6.8%
어 39
 
4.6%
투 35
 
4.2%
이 24
 
2.8%
식 21
 
2.5%
회 21
 
2.5%
스 16
 
1.9%
Other values (163) 431
51.1%
Uppercase Letter
ValueCountFrequency (%)
U 4
16.0%
R 3
12.0%
O 3
12.0%
T 3
12.0%
L 3
12.0%
K 2
8.0%
A 2
8.0%
J 1
 
4.0%
H 1
 
4.0%
C 1
 
4.0%
Other values (2) 2
8.0%
Lowercase Letter
ValueCountFrequency (%)
c 2
15.4%
o 2
15.4%
m 2
15.4%
n 2
15.4%
i 2
15.4%
t 1
7.7%
a 1
7.7%
u 1
7.7%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 843
81.4%
Common 154
 
14.9%
Latin 38
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 72
 
8.5%
주 70
 
8.3%
행 57
 
6.8%
여 57
 
6.8%
어 39
 
4.6%
투 35
 
4.2%
이 24
 
2.8%
식 21
 
2.5%
회 21
 
2.5%
스 16
 
1.9%
Other values (163) 431
51.1%
Latin
ValueCountFrequency (%)
U 4
 
10.5%
R 3
 
7.9%
O 3
 
7.9%
T 3
 
7.9%
L 3
 
7.9%
K 2
 
5.3%
A 2
 
5.3%
c 2
 
5.3%
o 2
 
5.3%
m 2
 
5.3%
Other values (10) 12
31.6%
Common
ValueCountFrequency (%)
51
33.1%
( 51
33.1%
) 51
33.1%
- 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 843
81.4%
ASCII 192
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 72
 
8.5%
주 70
 
8.3%
행 57
 
6.8%
여 57
 
6.8%
어 39
 
4.6%
투 35
 
4.2%
이 24
 
2.8%
식 21
 
2.5%
회 21
 
2.5%
스 16
 
1.9%
Other values (163) 431
51.1%
ASCII
ValueCountFrequency (%)
51
26.6%
( 51
26.6%
) 51
26.6%
U 4
 
2.1%
R 3
 
1.6%
O 3
 
1.6%
T 3
 
1.6%
L 3
 
1.6%
K 2
 
1.0%
A 2
 
1.0%
Other values (14) 19
 
9.9%

소재지(도로명)
Text

Distinct117
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T20:57:06.873224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length42
Mean length29.2
Min length21

Characters and Unicode

Total characters3504
Distinct characters149
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

Unique114 ?
Unique (%)95.0%

Sample

1st row울산광역시 남구 중앙로 218 (신정동)
2nd row울산광역시 남구 팔등로41번길 39-1 (신정동)
3rd row울산광역시 남구 봉월로 176, 2층 (신정동)
4th row울산광역시 남구 화합로 214, 2층 (삼산동)
5th row울산광역시 남구 봉월로50번길 45, 2층 (신정동)
ValueCountFrequency (%)
울산광역시 120
 
16.2%
남구 120
 
16.2%
삼산동 31
 
4.2%
신정동 29
 
3.9%
달동 24
 
3.2%
2층 23
 
3.1%
1층 19
 
2.6%
돋질로 14
 
1.9%
3층 14
 
1.9%
무거동 11
 
1.5%
Other values (229) 337
45.4%
2023-12-12T20:57:07.604590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
623
 
17.8%
산 187
 
5.3%
동 135
 
3.9%
울 127
 
3.6%
1 126
 
3.6%
( 124
 
3.5%
) 124
 
3.5%
남 124
 
3.5%
구 123
 
3.5%
시 122
 
3.5%
Other values (139) 1689
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1946
55.5%
Space Separator 623
 
17.8%
Decimal Number 567
 
16.2%
Open Punctuation 124
 
3.5%
Close Punctuation 124
 
3.5%
Other Punctuation 107
 
3.1%
Dash Punctuation 9
 
0.3%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 187
 
9.6%
동 135
 
6.9%
울 127
 
6.5%
남 124
 
6.4%
구 123
 
6.3%
시 122
 
6.3%
로 121
 
6.2%
광 121
 
6.2%
역 120
 
6.2%
층 72
 
3.7%
Other values (122) 694
35.7%
Decimal Number
ValueCountFrequency (%)
1 126
22.2%
2 109
19.2%
3 75
13.2%
4 60
10.6%
0 57
10.1%
5 41
 
7.2%
9 27
 
4.8%
7 26
 
4.6%
6 25
 
4.4%
8 21
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
75.0%
F 1
 
25.0%
Space Separator
ValueCountFrequency (%)
623
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 124
100.0%
Other Punctuation
ValueCountFrequency (%)
, 107
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1946
55.5%
Common 1554
44.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 187
 
9.6%
동 135
 
6.9%
울 127
 
6.5%
남 124
 
6.4%
구 123
 
6.3%
시 122
 
6.3%
로 121
 
6.2%
광 121
 
6.2%
역 120
 
6.2%
층 72
 
3.7%
Other values (122) 694
35.7%
Common
ValueCountFrequency (%)
623
40.1%
1 126
 
8.1%
( 124
 
8.0%
) 124
 
8.0%
2 109
 
7.0%
, 107
 
6.9%
3 75
 
4.8%
4 60
 
3.9%
0 57
 
3.7%
5 41
 
2.6%
Other values (5) 108
 
6.9%
Latin
ValueCountFrequency (%)
B 3
75.0%
F 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1946
55.5%
ASCII 1558
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
623
40.0%
1 126
 
8.1%
( 124
 
8.0%
) 124
 
8.0%
2 109
 
7.0%
, 107
 
6.9%
3 75
 
4.8%
4 60
 
3.9%
0 57
 
3.7%
5 41
 
2.6%
Other values (7) 112
 
7.2%
Hangul
ValueCountFrequency (%)
산 187
 
9.6%
동 135
 
6.9%
울 127
 
6.5%
남 124
 
6.4%
구 123
 
6.3%
시 122
 
6.3%
로 121
 
6.2%
광 121
 
6.2%
역 120
 
6.2%
층 72
 
3.7%
Other values (122) 694
35.7%

전화번호
Text

MISSING 

Distinct93
Distinct (%)94.9%
Missing22
Missing (%)18.3%
Memory size1.1 KiB
2023-12-12T20:57:08.056692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010204
Min length9

Characters and Unicode

Total characters1177
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

Unique88 ?
Unique (%)89.8%

Sample

1st row052-267-9190
2nd row052-272-3572
3rd row052-272-5131
4th row052-225-2500
5th row052-911-6768
ValueCountFrequency (%)
052-225-2788 2
 
2.0%
052-277-2005 2
 
2.0%
052-266-4240 2
 
2.0%
052-267-9190 2
 
2.0%
052-917-8253 2
 
2.0%
052-235-1111 1
 
1.0%
052-903-9883 1
 
1.0%
052-283-0077 1
 
1.0%
052-260-5007 1
 
1.0%
052-700-4200 1
 
1.0%
Other values (83) 83
84.7%
2023-12-12T20:57:08.736758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 248
21.1%
0 203
17.2%
- 195
16.6%
5 156
13.3%
7 80
 
6.8%
6 62
 
5.3%
8 53
 
4.5%
1 52
 
4.4%
9 50
 
4.2%
3 40
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 982
83.4%
Dash Punctuation 195
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 248
25.3%
0 203
20.7%
5 156
15.9%
7 80
 
8.1%
6 62
 
6.3%
8 53
 
5.4%
1 52
 
5.3%
9 50
 
5.1%
3 40
 
4.1%
4 38
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 195
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1177
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 248
21.1%
0 203
17.2%
- 195
16.6%
5 156
13.3%
7 80
 
6.8%
6 62
 
5.3%
8 53
 
4.5%
1 52
 
4.4%
9 50
 
4.2%
3 40
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1177
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 248
21.1%
0 203
17.2%
- 195
16.6%
5 156
13.3%
7 80
 
6.8%
6 62
 
5.3%
8 53
 
4.5%
1 52
 
4.4%
9 50
 
4.2%
3 40
 
3.4%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing120
Missing (%)100.0%
Memory size1.2 KiB

Correlations

2023-12-12T20:57:08.886765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종전화번호
업종1.0000.699
전화번호0.6991.000

Missing values

2023-12-12T20:57:05.056085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:57:05.226842image/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

업종상호소재지(도로명)전화번호Unnamed: 4Unnamed: 5Unnamed: 6
0국내여행업(주)굿모닝해외여행사울산광역시 남구 중앙로 218 (신정동)052-267-9190<NA><NA><NA>
1국내여행업프라임여행사울산광역시 남구 팔등로41번길 39-1 (신정동)052-272-3572<NA><NA><NA>
2국내여행업(주)동진관광울산광역시 남구 봉월로 176, 2층 (신정동)052-272-5131<NA><NA><NA>
3국내여행업가자고속투어 주식회사울산광역시 남구 화합로 214, 2층 (삼산동)052-225-2500<NA><NA><NA>
4국내여행업에코투어 태화강협동조합울산광역시 남구 봉월로50번길 45, 2층 (신정동)052-911-6768<NA><NA><NA>
5국내여행업주식회사 글로벌투어울산광역시 남구 두왕로154번길 13 (선암동)052-225-2788<NA><NA><NA>
6국내여행업(주) 향산관광울산광역시 남구 삼산로199번길 36, 401호 (달동)<NA><NA><NA><NA>
7국내여행업(주)대현관광울산광역시 남구 번영로 179, 4층 (달동)052-227-3225<NA><NA><NA>
8국내여행업경동고속투어울산광역시 남구 남산로62번길 10-1 (무거동)052-286-1555<NA><NA><NA>
9국내여행업나들이 여행사울산광역시 남구 삼산로169번길 37, 201호 (달동)052-951-0849<NA><NA><NA>
업종상호소재지(도로명)전화번호Unnamed: 4Unnamed: 5Unnamed: 6
110종합여행업나비투어울산광역시 남구 산업로613번길 9, 3층 (삼산동)052-222-4193<NA><NA><NA>
111종합여행업주식회사 세계로여행사울산광역시 남구 수암로 207, 2층 (야음동)<NA><NA><NA><NA>
112종합여행업주식회사 엘리스울산광역시 남구 봉월로151번길 16, 미래빌딩 4층 (신정동)<NA><NA><NA><NA>
113종합여행업K코리아 여행사울산광역시 남구 삼산로355번길 20, 4층 (삼산동)<NA><NA><NA><NA>
114종합여행업유학플래너닷컴 울산대지사울산광역시 남구 대학로 93, 울산대학교 1층 (무거동)052-225-9990<NA><NA><NA>
115종합여행업신명여행사울산광역시 남구 삼산로155번길 11 (달동)<NA><NA><NA><NA>
116종합여행업(주)꿈에그린골프투어울산광역시 남구 중앙로 313, 1층 (신정동)052-266-4240<NA><NA><NA>
117종합여행업주식회사 핀투어울산광역시 남구 돋질로 234, 3층 (달동)052-277-2005<NA><NA><NA>
118종합여행업(주)글로벌여행서비스울산광역시 남구 삼산로 157, 2층 (달동)052-917-8253<NA><NA><NA>
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