Overview

Dataset statistics

Number of variables8
Number of observations63
Missing cells24
Missing cells (%)4.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory67.1 B

Variable types

Numeric1
Categorical1
Text4
DateTime2

Dataset

Description인천광역시 서구 여행업 현황에 대한 데이터셋입니다. 인천광역시 서구 여행업 업종, 상호명, 등록일자, 소재지, 전화번호에 대한 정보를 포함하고 있습니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15039934&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
전화번호 has 24 (38.1%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 15:31:30.849011
Analysis finished2024-01-28 15:31:31.593445
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct63
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32
Minimum1
Maximum63
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size699.0 B
2024-01-29T00:31:31.650389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.1
Q116.5
median32
Q347.5
95-th percentile59.9
Maximum63
Range62
Interquartile range (IQR)31

Descriptive statistics

Standard deviation18.330303
Coefficient of variation (CV)0.57282196
Kurtosis-1.2
Mean32
Median Absolute Deviation (MAD)16
Skewness0
Sum2016
Variance336
MonotonicityStrictly increasing
2024-01-29T00:31:31.762038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
2 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
42 1
 
1.6%
Other values (53) 53
84.1%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
63 1
1.6%
62 1
1.6%
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%

업종
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
종합여행업
29 
국내외여행업
22 
국내여행업
12 

Length

Max length6
Median length5
Mean length5.3492063
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종합여행업 29
46.0%
국내외여행업 22
34.9%
국내여행업 12
19.0%

Length

2024-01-29T00:31:31.865353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:31:31.948488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합여행업 29
46.0%
국내외여행업 22
34.9%
국내여행업 12
19.0%

상호명
Text

Distinct57
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-01-29T00:31:32.125021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length8.0793651
Min length2

Characters and Unicode

Total characters509
Distinct characters141
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)81.0%

Sample

1st row삼화관광(합자)
2nd row(주)메이트항공여행사
3rd row(주)신화이앤씨
4th row(주)하누리
5th row(주)새론여행사
ValueCountFrequency (%)
주식회사 9
 
10.6%
삼화관광(합자 2
 
2.4%
투어 2
 
2.4%
tour 2
 
2.4%
주 2
 
2.4%
주)새론여행사 2
 
2.4%
여행사 2
 
2.4%
주)신화이앤씨 2
 
2.4%
정투어 2
 
2.4%
주)한빛여행사 2
 
2.4%
Other values (57) 58
68.2%
2024-01-29T00:31:32.436615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 39
 
7.7%
( 34
 
6.7%
) 34
 
6.7%
사 26
 
5.1%
어 23
 
4.5%
22
 
4.3%
투 22
 
4.3%
여 18
 
3.5%
행 17
 
3.3%
이 12
 
2.4%
Other values (131) 262
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 388
76.2%
Open Punctuation 34
 
6.7%
Close Punctuation 34
 
6.7%
Space Separator 22
 
4.3%
Lowercase Letter 19
 
3.7%
Uppercase Letter 12
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 39
 
10.1%
사 26
 
6.7%
어 23
 
5.9%
투 22
 
5.7%
여 18
 
4.6%
행 17
 
4.4%
이 12
 
3.1%
회 10
 
2.6%
광 9
 
2.3%
식 9
 
2.3%
Other values (107) 203
52.3%
Lowercase Letter
ValueCountFrequency (%)
r 4
21.1%
o 3
15.8%
e 3
15.8%
a 2
10.5%
i 1
 
5.3%
c 1
 
5.3%
t 1
 
5.3%
y 1
 
5.3%
v 1
 
5.3%
l 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
T 3
25.0%
V 1
 
8.3%
W 1
 
8.3%
U 1
 
8.3%
O 1
 
8.3%
D 1
 
8.3%
G 1
 
8.3%
R 1
 
8.3%
H 1
 
8.3%
K 1
 
8.3%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 388
76.2%
Common 90
 
17.7%
Latin 31
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 39
 
10.1%
사 26
 
6.7%
어 23
 
5.9%
투 22
 
5.7%
여 18
 
4.6%
행 17
 
4.4%
이 12
 
3.1%
회 10
 
2.6%
광 9
 
2.3%
식 9
 
2.3%
Other values (107) 203
52.3%
Latin
ValueCountFrequency (%)
r 4
 
12.9%
T 3
 
9.7%
o 3
 
9.7%
e 3
 
9.7%
a 2
 
6.5%
V 1
 
3.2%
i 1
 
3.2%
c 1
 
3.2%
t 1
 
3.2%
y 1
 
3.2%
Other values (11) 11
35.5%
Common
ValueCountFrequency (%)
( 34
37.8%
) 34
37.8%
22
24.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 388
76.2%
ASCII 121
 
23.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 39
 
10.1%
사 26
 
6.7%
어 23
 
5.9%
투 22
 
5.7%
여 18
 
4.6%
행 17
 
4.4%
이 12
 
3.1%
회 10
 
2.6%
광 9
 
2.3%
식 9
 
2.3%
Other values (107) 203
52.3%
ASCII
ValueCountFrequency (%)
( 34
28.1%
) 34
28.1%
22
18.2%
r 4
 
3.3%
T 3
 
2.5%
o 3
 
2.5%
e 3
 
2.5%
a 2
 
1.7%
V 1
 
0.8%
i 1
 
0.8%
Other values (14) 14
11.6%

등록일자
Date

Distinct56
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum1995-03-01 00:00:00
Maximum2022-08-08 00:00:00
2024-01-29T00:31:32.545851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:31:32.659879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지(도로명)
Text

Distinct49
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-01-29T00:31:32.831015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length32
Mean length24.650794
Min length19

Characters and Unicode

Total characters1553
Distinct characters110
Distinct categories5 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)61.9%

Sample

1st row인천광역시 서구 마전동 911-8
2nd row인천광역시 서구 가좌동 81-61 범양아파트
3rd row인천광역시 서구 원당동 825-15 아침愛캐슬
4th row인천광역시 서구 심곡동 245-5 네오프라자 606호
5th row인천광역시 서구 가좌동 114-62 창대빌딩 1층
ValueCountFrequency (%)
인천광역시 63
19.9%
서구 63
19.9%
가좌동 15
 
4.7%
가정동 9
 
2.8%
원창동 6
 
1.9%
심곡동 6
 
1.9%
마전동 6
 
1.9%
화방주차타워 6
 
1.9%
616-3 6
 
1.9%
석남동 5
 
1.6%
Other values (94) 131
41.5%
2024-01-29T00:31:33.128952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
309
19.9%
1 78
 
5.0%
동 66
 
4.2%
인 65
 
4.2%
서 65
 
4.2%
천 65
 
4.2%
시 64
 
4.1%
광 63
 
4.1%
역 63
 
4.1%
구 63
 
4.1%
Other values (100) 652
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 868
55.9%
Decimal Number 318
 
20.5%
Space Separator 309
 
19.9%
Dash Punctuation 57
 
3.7%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
 
7.6%
인 65
 
7.5%
서 65
 
7.5%
천 65
 
7.5%
시 64
 
7.4%
광 63
 
7.3%
역 63
 
7.3%
구 63
 
7.3%
가 28
 
3.2%
좌 17
 
2.0%
Other values (87) 309
35.6%
Decimal Number
ValueCountFrequency (%)
1 78
24.5%
6 39
12.3%
3 37
11.6%
2 37
11.6%
4 30
 
9.4%
0 27
 
8.5%
5 21
 
6.6%
8 21
 
6.6%
9 16
 
5.0%
7 12
 
3.8%
Space Separator
ValueCountFrequency (%)
309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 866
55.8%
Common 684
44.0%
Han 2
 
0.1%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
 
7.6%
인 65
 
7.5%
서 65
 
7.5%
천 65
 
7.5%
시 64
 
7.4%
광 63
 
7.3%
역 63
 
7.3%
구 63
 
7.3%
가 28
 
3.2%
좌 17
 
2.0%
Other values (86) 307
35.5%
Common
ValueCountFrequency (%)
309
45.2%
1 78
 
11.4%
- 57
 
8.3%
6 39
 
5.7%
3 37
 
5.4%
2 37
 
5.4%
4 30
 
4.4%
0 27
 
3.9%
5 21
 
3.1%
8 21
 
3.1%
Other values (2) 28
 
4.1%
Han
ValueCountFrequency (%)
愛 2
100.0%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 866
55.8%
ASCII 685
44.1%
CJK 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
309
45.1%
1 78
 
11.4%
- 57
 
8.3%
6 39
 
5.7%
3 37
 
5.4%
2 37
 
5.4%
4 30
 
4.4%
0 27
 
3.9%
5 21
 
3.1%
8 21
 
3.1%
Other values (3) 29
 
4.2%
Hangul
ValueCountFrequency (%)
동 66
 
7.6%
인 65
 
7.5%
서 65
 
7.5%
천 65
 
7.5%
시 64
 
7.4%
광 63
 
7.3%
역 63
 
7.3%
구 63
 
7.3%
가 28
 
3.2%
좌 17
 
2.0%
Other values (86) 307
35.5%
CJK
ValueCountFrequency (%)
愛 2
100.0%

소재지(지번)
Text

Distinct56
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Memory size636.0 B
2024-01-29T00:31:33.348124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length44
Mean length32.904762
Min length22

Characters and Unicode

Total characters2073
Distinct characters135
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

Unique49 ?
Unique (%)77.8%

Sample

1st row인천광역시 서구 검단로487번길 3 (마전동)
2nd row인천광역시 서구 건지로 411, 범양아파트 상가동 2층 8-3호 (가좌동)
3rd row인천광역시 서구 고산후로121번안길 22, 510호 (원당동)
4th row인천광역시 서구 탁옥로51번길 11, 606호 (심곡동,네오프라자)
5th row인천광역시 서구 가정로 142 (가좌동,창대빌딩 1층)
ValueCountFrequency (%)
인천광역시 63
 
15.1%
서구 63
 
15.1%
가좌동 13
 
3.1%
가정동 9
 
2.2%
2층 9
 
2.2%
원창동 6
 
1.4%
마전동 6
 
1.4%
봉오재3로 6
 
1.4%
115 6
 
1.4%
승학로 5
 
1.2%
Other values (157) 230
55.3%
2024-01-29T00:31:33.670265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
353
 
17.0%
1 84
 
4.1%
동 73
 
3.5%
, 70
 
3.4%
서 68
 
3.3%
인 65
 
3.1%
천 65
 
3.1%
시 64
 
3.1%
( 63
 
3.0%
광 63
 
3.0%
Other values (125) 1105
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1137
54.8%
Decimal Number 377
 
18.2%
Space Separator 353
 
17.0%
Other Punctuation 70
 
3.4%
Open Punctuation 63
 
3.0%
Close Punctuation 63
 
3.0%
Dash Punctuation 8
 
0.4%
Math Symbol 1
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 73
 
6.4%
서 68
 
6.0%
인 65
 
5.7%
천 65
 
5.7%
시 64
 
5.6%
광 63
 
5.5%
역 63
 
5.5%
구 63
 
5.5%
로 63
 
5.5%
가 38
 
3.3%
Other values (108) 512
45.0%
Decimal Number
ValueCountFrequency (%)
1 84
22.3%
2 60
15.9%
3 43
11.4%
4 42
11.1%
0 36
9.5%
5 29
 
7.7%
8 25
 
6.6%
7 24
 
6.4%
6 18
 
4.8%
9 16
 
4.2%
Space Separator
ValueCountFrequency (%)
353
100.0%
Other Punctuation
ValueCountFrequency (%)
, 70
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1137
54.8%
Common 935
45.1%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 73
 
6.4%
서 68
 
6.0%
인 65
 
5.7%
천 65
 
5.7%
시 64
 
5.6%
광 63
 
5.5%
역 63
 
5.5%
구 63
 
5.5%
로 63
 
5.5%
가 38
 
3.3%
Other values (108) 512
45.0%
Common
ValueCountFrequency (%)
353
37.8%
1 84
 
9.0%
, 70
 
7.5%
( 63
 
6.7%
) 63
 
6.7%
2 60
 
6.4%
3 43
 
4.6%
4 42
 
4.5%
0 36
 
3.9%
5 29
 
3.1%
Other values (6) 92
 
9.8%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1137
54.8%
ASCII 936
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
353
37.7%
1 84
 
9.0%
, 70
 
7.5%
( 63
 
6.7%
) 63
 
6.7%
2 60
 
6.4%
3 43
 
4.6%
4 42
 
4.5%
0 36
 
3.8%
5 29
 
3.1%
Other values (7) 93
 
9.9%
Hangul
ValueCountFrequency (%)
동 73
 
6.4%
서 68
 
6.0%
인 65
 
5.7%
천 65
 
5.7%
시 64
 
5.6%
광 63
 
5.5%
역 63
 
5.5%
구 63
 
5.5%
로 63
 
5.5%
가 38
 
3.3%
Other values (108) 512
45.0%

전화번호
Text

MISSING 

Distinct35
Distinct (%)89.7%
Missing24
Missing (%)38.1%
Memory size636.0 B
2024-01-29T00:31:33.846353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.974359
Min length9

Characters and Unicode

Total characters467
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

Unique31 ?
Unique (%)79.5%

Sample

1st row032-566-6666
2nd row032-202-7171
3rd row032-554-0662
4th row032-277-0001
5th row032-582-0020
ValueCountFrequency (%)
032-202-7171 2
 
5.1%
032-777-0555 2
 
5.1%
032-554-0662 2
 
5.1%
032-582-0020 2
 
5.1%
032-567-8641 1
 
2.6%
032-572-0927 1
 
2.6%
032-567-9937 1
 
2.6%
032-567-9962 1
 
2.6%
032-567-7744 1
 
2.6%
032-567-9953 1
 
2.6%
Other values (25) 25
64.1%
2024-01-29T00:31:34.131083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 77
16.5%
0 72
15.4%
2 63
13.5%
3 49
10.5%
5 48
10.3%
7 43
9.2%
6 39
8.4%
8 21
 
4.5%
1 20
 
4.3%
9 19
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 390
83.5%
Dash Punctuation 77
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 72
18.5%
2 63
16.2%
3 49
12.6%
5 48
12.3%
7 43
11.0%
6 39
10.0%
8 21
 
5.4%
1 20
 
5.1%
9 19
 
4.9%
4 16
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 77
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 467
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 77
16.5%
0 72
15.4%
2 63
13.5%
3 49
10.5%
5 48
10.3%
7 43
9.2%
6 39
8.4%
8 21
 
4.5%
1 20
 
4.3%
9 19
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 77
16.5%
0 72
15.4%
2 63
13.5%
3 49
10.5%
5 48
10.3%
7 43
9.2%
6 39
8.4%
8 21
 
4.5%
1 20
 
4.3%
9 19
 
4.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size636.0 B
Minimum2022-08-31 00:00:00
Maximum2022-08-31 00:00:00
2024-01-29T00:31:34.222847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:31:34.296161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-29T00:31:31.354734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:31:34.359743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종상호명등록일자소재지(도로명)소재지(지번)전화번호
연번1.0000.9410.5480.8950.8720.4670.000
업종0.9411.0000.0000.0000.4250.0000.000
상호명0.5480.0001.0000.9931.0001.0000.999
등록일자0.8950.0000.9931.0000.9960.9980.999
소재지(도로명)0.8720.4251.0000.9961.0001.0001.000
소재지(지번)0.4670.0001.0000.9981.0001.0001.000
전화번호0.0000.0000.9990.9991.0001.0001.000
2024-01-29T00:31:34.445484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.879
업종0.8791.000

Missing values

2024-01-29T00:31:31.447604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:31:31.551246image/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

연번업종상호명등록일자소재지(도로명)소재지(지번)전화번호데이터기준일자
01국내여행업삼화관광(합자)1995-03-01인천광역시 서구 마전동 911-8인천광역시 서구 검단로487번길 3 (마전동)032-566-66662022-08-31
12국내여행업(주)메이트항공여행사2008-04-01인천광역시 서구 가좌동 81-61 범양아파트인천광역시 서구 건지로 411, 범양아파트 상가동 2층 8-3호 (가좌동)032-202-71712022-08-31
23국내여행업(주)신화이앤씨2010-05-03인천광역시 서구 원당동 825-15 아침愛캐슬인천광역시 서구 고산후로121번안길 22, 510호 (원당동)032-554-06622022-08-31
34국내여행업(주)하누리2011-06-08인천광역시 서구 심곡동 245-5 네오프라자 606호인천광역시 서구 탁옥로51번길 11, 606호 (심곡동,네오프라자)032-277-00012022-08-31
45국내여행업(주)새론여행사2011-07-05인천광역시 서구 가좌동 114-62 창대빌딩 1층인천광역시 서구 가정로 142 (가좌동,창대빌딩 1층)032-582-00202022-08-31
56국내여행업라라투어2012-10-08인천광역시 서구 가좌동 308 외 1필지 주공아파트상가 104호인천광역시 서구 장고개로 336, 104호 (가좌동, 주공아파트상가)<NA>2022-08-31
67국내여행업(주) 인천두레관광2017-08-29인천광역시 서구 가좌동 468-1인천광역시 서구 가좌로83번길 22 (가좌동)1899-03442022-08-31
78국내여행업(주)한빛여행사1999-07-22인천광역시 서구 심곡동 334-13 신안주택 12동 102호인천광역시 서구 승학로 237-12, 12동 102호 (심곡동, 신안주택)032-777-05552022-08-31
89국내여행업정투어2018-08-27인천광역시 서구 당하동 1065-1 당하 이마트인천광역시 서구 서곶로 754, 이마트 검단점 3층 (당하동)032-562-88552022-08-31
910국내여행업(주)금강고속관광2021-04-09인천광역시 서구 경서동 249-36인천광역시 서구 경명대로 463, 2층 (경서동)032-761-30002022-08-31
연번업종상호명등록일자소재지(도로명)소재지(지번)전화번호데이터기준일자
5354종합여행업주식회사 신라이여행사2015-12-22인천광역시 서구 가정동 616-3 화방주차타워인천광역시 서구 봉오재3로 115, 화방주차타워 120호 (가정동)<NA>2022-08-31
5455종합여행업(주)우리글로벌코리아2021-02-15인천광역시 서구 원창동 393-123인천광역시 서구 북항로177번길 42 (원창동)032-572-09272022-08-31
5556종합여행업주식회사 광해홀딩스2021-05-12인천광역시 서구 원창동 391-111인천광역시 서구 북항로120번길 77, 401호 (원창동)<NA>2022-08-31
5657종합여행업(주)솔로몬투어2021-06-28인천광역시 서구 심곡동 247-7인천광역시 서구 서곶로 295, 3층 (심곡동)<NA>2022-08-31
5758종합여행업(주)우리투어2019-03-08인천광역시 서구 당하동 1100-6 하이드파크인천광역시 서구 청마로148번길 49, 101동 502호 (당하동, 하이드파크)<NA>2022-08-31
5859종합여행업(주)제나웰니스2021-02-15인천광역시 서구 왕길동 638-4 제이원검단메디컬프라자인천광역시 서구 완정로 179, 제이원검단메디컬프라자 6층 (왕길동)<NA>2022-08-31
5960종합여행업(주)동감투어2021-11-12인천광역시 서구 가좌동 541-11인천광역시 서구 가재울로 43-7, 2층 (가좌동)032-710-34352022-08-31
6061종합여행업웨이브투어(주)2021-12-09인천광역시 서구 왕길동 662-9 이레메디칼센타인천광역시 서구 완정로 153, 이레메디칼센타 813호 (왕길동)<NA>2022-08-31
6162종합여행업주식회사 다나라트레이딩2022-05-27인천광역시 서구 가정동 602-11인천광역시 서구 염곡로498번길 15-1, 1층 (가정동)070-4153-82812022-08-31
6263종합여행업위투어코리아(We Tour Korea)2022-08-08인천광역시 서구 원창동 382-113인천광역시 서구 중봉대로376번길 4, 3층 (원창동)<NA>2022-08-31