Overview

Dataset statistics

Number of variables6
Number of observations1294
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory60.8 KiB
Average record size in memory48.1 B

Variable types

Categorical3
Text2
DateTime1

Dataset

Description인천광역시 관광사업체 현황(분류/구분/업체명/지역/소재지/등록일) 데이터 입니다. * 인천광역시 관광사업체통계시스템 데이터
Author인천광역시
URLhttps://www.data.go.kr/data/15066564/fileData.do

Alerts

분류 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 분류High correlation

Reproduction

Analysis started2023-12-12 10:31:33.281775
Analysis finished2023-12-12 10:31:34.235302
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
여행업
618 
숙박업
171 
유원시설업
155 
관광식당업
91 
야영장업
91 
Other values (13)
168 

Length

Max length10
Median length3
Mean length4.0401855
Min length3

Unique

Unique3 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
여행업 618
47.8%
숙박업 171
 
13.2%
유원시설업 155
 
12.0%
관광식당업 91
 
7.0%
야영장업 91
 
7.0%
외국인관광도시민박업 73
 
5.6%
관광팬션업 26
 
2.0%
국제회의업 18
 
1.4%
한옥체험업 12
 
0.9%
관광극장유흥업 11
 
0.9%
Other values (8) 28
 
2.2%

Length

2023-12-12T19:31:34.333886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여행업 618
47.8%
숙박업 171
 
13.2%
유원시설업 155
 
12.0%
관광식당업 91
 
7.0%
야영장업 91
 
7.0%
외국인관광도시민박업 73
 
5.6%
관광팬션업 26
 
2.0%
국제회의업 18
 
1.4%
한옥체험업 12
 
0.9%
관광극장유흥업 11
 
0.9%
Other values (8) 28
 
2.2%

구분
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
국내외여행업
237 
종합여행업
224 
국내여행업
157 
기타유원시설업
136 
관광식당업
91 
Other values (23)
449 

Length

Max length12
Median length10
Mean length5.8114374
Min length4

Unique

Unique6 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
국내외여행업 237
18.3%
종합여행업 224
17.3%
국내여행업 157
12.1%
기타유원시설업 136
10.5%
관광식당업 91
 
7.0%
호스텔업 85
 
6.6%
관광호텔업 80
 
6.2%
일반야영장업 74
 
5.7%
외국인관광도시민박업 73
 
5.6%
관광펜션업 26
 
2.0%
Other values (18) 111
8.6%

Length

2023-12-12T19:31:34.516955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국내외여행업 237
18.3%
종합여행업 224
17.3%
국내여행업 157
12.1%
기타유원시설업 136
10.5%
관광식당업 91
 
7.0%
호스텔업 85
 
6.6%
관광호텔업 80
 
6.2%
일반야영장업 74
 
5.7%
외국인관광도시민박업 73
 
5.6%
관광펜션업 26
 
2.0%
Other values (19) 113
8.7%

업체명
Text

Distinct1194
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
2023-12-12T19:31:34.906951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length7.1978362
Min length2

Characters and Unicode

Total characters9314
Distinct characters595
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1096 ?
Unique (%)84.7%

Sample

1st row범한세계여행사
2nd row㈜현대투어
3rd row한스투어
4th row㈜투어랜드
5th row주식회사 씨엘국제
ValueCountFrequency (%)
호스텔 30
 
1.8%
주식회사 29
 
1.8%
여행사 11
 
0.7%
호텔 11
 
0.7%
게스트하우스 11
 
0.7%
관광호텔 8
 
0.5%
키즈카페 8
 
0.5%
노리파크 7
 
0.4%
투어 6
 
0.4%
캠핑장 5
 
0.3%
Other values (1357) 1530
92.4%
2023-12-12T19:31:35.443619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
363
 
3.9%
스 316
 
3.4%
㈜ 309
 
3.3%
이 231
 
2.5%
사 226
 
2.4%
어 206
 
2.2%
행 199
 
2.1%
여 194
 
2.1%
투 167
 
1.8%
리 150
 
1.6%
Other values (585) 6953
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7711
82.8%
Space Separator 363
 
3.9%
Lowercase Letter 343
 
3.7%
Other Symbol 309
 
3.3%
Uppercase Letter 260
 
2.8%
Open Punctuation 130
 
1.4%
Close Punctuation 128
 
1.4%
Decimal Number 36
 
0.4%
Other Punctuation 25
 
0.3%
Dash Punctuation 7
 
0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 316
 
4.1%
이 231
 
3.0%
사 226
 
2.9%
어 206
 
2.7%
행 199
 
2.6%
여 194
 
2.5%
투 167
 
2.2%
리 150
 
1.9%
호 149
 
1.9%
텔 141
 
1.8%
Other values (513) 5732
74.3%
Uppercase Letter
ValueCountFrequency (%)
T 31
 
11.9%
O 21
 
8.1%
S 20
 
7.7%
A 20
 
7.7%
E 17
 
6.5%
C 15
 
5.8%
R 14
 
5.4%
B 14
 
5.4%
H 13
 
5.0%
G 11
 
4.2%
Other values (15) 84
32.3%
Lowercase Letter
ValueCountFrequency (%)
e 52
15.2%
o 34
9.9%
a 31
 
9.0%
t 28
 
8.2%
s 26
 
7.6%
r 25
 
7.3%
u 19
 
5.5%
p 17
 
5.0%
i 16
 
4.7%
m 14
 
4.1%
Other values (14) 81
23.6%
Decimal Number
ValueCountFrequency (%)
2 8
22.2%
1 7
19.4%
4 6
16.7%
9 4
11.1%
0 3
 
8.3%
7 3
 
8.3%
3 3
 
8.3%
6 1
 
2.8%
8 1
 
2.8%
Other Punctuation
ValueCountFrequency (%)
& 11
44.0%
; 10
40.0%
. 2
 
8.0%
, 1
 
4.0%
' 1
 
4.0%
Open Punctuation
ValueCountFrequency (%)
( 128
98.5%
[ 2
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 126
98.4%
] 2
 
1.6%
Space Separator
ValueCountFrequency (%)
363
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 309
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8020
86.1%
Common 691
 
7.4%
Latin 603
 
6.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 316
 
3.9%
㈜ 309
 
3.9%
이 231
 
2.9%
사 226
 
2.8%
어 206
 
2.6%
행 199
 
2.5%
여 194
 
2.4%
투 167
 
2.1%
리 150
 
1.9%
호 149
 
1.9%
Other values (514) 5873
73.2%
Latin
ValueCountFrequency (%)
e 52
 
8.6%
o 34
 
5.6%
T 31
 
5.1%
a 31
 
5.1%
t 28
 
4.6%
s 26
 
4.3%
r 25
 
4.1%
O 21
 
3.5%
S 20
 
3.3%
A 20
 
3.3%
Other values (39) 315
52.2%
Common
ValueCountFrequency (%)
363
52.5%
( 128
 
18.5%
) 126
 
18.2%
& 11
 
1.6%
; 10
 
1.4%
2 8
 
1.2%
1 7
 
1.0%
- 7
 
1.0%
4 6
 
0.9%
9 4
 
0.6%
Other values (12) 21
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7711
82.8%
ASCII 1293
 
13.9%
None 309
 
3.3%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
363
28.1%
( 128
 
9.9%
) 126
 
9.7%
e 52
 
4.0%
o 34
 
2.6%
T 31
 
2.4%
a 31
 
2.4%
t 28
 
2.2%
s 26
 
2.0%
r 25
 
1.9%
Other values (60) 449
34.7%
Hangul
ValueCountFrequency (%)
스 316
 
4.1%
이 231
 
3.0%
사 226
 
2.9%
어 206
 
2.7%
행 199
 
2.6%
여 194
 
2.5%
투 167
 
2.2%
리 150
 
1.9%
호 149
 
1.9%
텔 141
 
1.8%
Other values (513) 5732
74.3%
None
ValueCountFrequency (%)
㈜ 309
100.0%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

지역
Categorical

Distinct10
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
중구
352 
연수구
178 
서구
161 
남동구
155 
부평구
131 
Other values (5)
317 

Length

Max length4
Median length3
Mean length2.6669243
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미추홀구
2nd row중구
3rd row중구
4th row계양구
5th row중구

Common Values

ValueCountFrequency (%)
중구 352
27.2%
연수구 178
13.8%
서구 161
12.4%
남동구 155
12.0%
부평구 131
 
10.1%
강화군 99
 
7.7%
미추홀구 97
 
7.5%
계양구 57
 
4.4%
옹진군 49
 
3.8%
동구 15
 
1.2%

Length

2023-12-12T19:31:35.613362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:31:35.758820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 352
27.2%
연수구 178
13.8%
서구 161
12.4%
남동구 155
12.0%
부평구 131
 
10.1%
강화군 99
 
7.7%
미추홀구 97
 
7.5%
계양구 57
 
4.4%
옹진군 49
 
3.8%
동구 15
 
1.2%

소재지
Text

Distinct1210
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
2023-12-12T19:31:36.121680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length40
Mean length25.122875
Min length8

Characters and Unicode

Total characters32509
Distinct characters427
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1128 ?
Unique (%)87.2%

Sample

1st row미추홀구 경인로321, 수림빌딩 4층(도화동)
2nd row인천광역시 중구 자연대로40, 801호(중산동, 비젼프라자2)
3rd row중구 신포로46번길 5, 102호(내동)
4th row계양구 경명대로1029번길 5-4, 202호(계산동)
5th row인천광역시 중구 신도시남로142번길 17, 305호(운서동)
ValueCountFrequency (%)
중구 345
 
5.7%
연수구 176
 
2.9%
인천광역시 163
 
2.7%
서구 157
 
2.6%
남동구 153
 
2.5%
부평구 131
 
2.2%
인천 99
 
1.6%
미추홀구 96
 
1.6%
강화군 95
 
1.6%
계양구 55
 
0.9%
Other values (2428) 4580
75.7%
2023-12-12T19:31:36.662526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4787
 
14.7%
1 1480
 
4.6%
구 1213
 
3.7%
동 1212
 
3.7%
로 1195
 
3.7%
2 1140
 
3.5%
, 1044
 
3.2%
0 822
 
2.5%
3 816
 
2.5%
( 809
 
2.5%
Other values (417) 17991
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17236
53.0%
Decimal Number 7238
22.3%
Space Separator 4788
 
14.7%
Other Punctuation 1054
 
3.2%
Open Punctuation 809
 
2.5%
Close Punctuation 808
 
2.5%
Dash Punctuation 390
 
1.2%
Uppercase Letter 159
 
0.5%
Math Symbol 16
 
< 0.1%
Lowercase Letter 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1213
 
7.0%
동 1212
 
7.0%
로 1195
 
6.9%
호 537
 
3.1%
길 525
 
3.0%
번 479
 
2.8%
중 413
 
2.4%
인 399
 
2.3%
천 364
 
2.1%
층 328
 
1.9%
Other values (367) 10571
61.3%
Uppercase Letter
ValueCountFrequency (%)
B 52
32.7%
I 18
 
11.3%
A 16
 
10.1%
C 13
 
8.2%
S 13
 
8.2%
D 12
 
7.5%
E 5
 
3.1%
T 5
 
3.1%
H 4
 
2.5%
N 3
 
1.9%
Other values (11) 18
 
11.3%
Decimal Number
ValueCountFrequency (%)
1 1480
20.4%
2 1140
15.8%
0 822
11.4%
3 816
11.3%
4 672
9.3%
6 533
 
7.4%
5 521
 
7.2%
7 463
 
6.4%
8 441
 
6.1%
9 350
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
i 2
22.2%
u 1
11.1%
e 1
11.1%
o 1
11.1%
t 1
11.1%
r 1
11.1%
v 1
11.1%
c 1
11.1%
Other Punctuation
ValueCountFrequency (%)
, 1044
99.1%
. 8
 
0.8%
: 1
 
0.1%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
4787
> 99.9%
　 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 809
100.0%
Close Punctuation
ValueCountFrequency (%)
) 808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 390
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17236
53.0%
Common 15105
46.5%
Latin 168
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1213
 
7.0%
동 1212
 
7.0%
로 1195
 
6.9%
호 537
 
3.1%
길 525
 
3.0%
번 479
 
2.8%
중 413
 
2.4%
인 399
 
2.3%
천 364
 
2.1%
층 328
 
1.9%
Other values (367) 10571
61.3%
Latin
ValueCountFrequency (%)
B 52
31.0%
I 18
 
10.7%
A 16
 
9.5%
C 13
 
7.7%
S 13
 
7.7%
D 12
 
7.1%
E 5
 
3.0%
T 5
 
3.0%
H 4
 
2.4%
N 3
 
1.8%
Other values (19) 27
16.1%
Common
ValueCountFrequency (%)
4787
31.7%
1 1480
 
9.8%
2 1140
 
7.5%
, 1044
 
6.9%
0 822
 
5.4%
3 816
 
5.4%
( 809
 
5.4%
) 808
 
5.3%
4 672
 
4.4%
6 533
 
3.5%
Other values (11) 2194
14.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17236
53.0%
ASCII 15270
47.0%
CJK Compat 2
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4787
31.3%
1 1480
 
9.7%
2 1140
 
7.5%
, 1044
 
6.8%
0 822
 
5.4%
3 816
 
5.3%
( 809
 
5.3%
) 808
 
5.3%
4 672
 
4.4%
6 533
 
3.5%
Other values (38) 2359
15.4%
Hangul
ValueCountFrequency (%)
구 1213
 
7.0%
동 1212
 
7.0%
로 1195
 
6.9%
호 537
 
3.1%
길 525
 
3.0%
번 479
 
2.8%
중 413
 
2.4%
인 399
 
2.3%
천 364
 
2.1%
층 328
 
1.9%
Other values (367) 10571
61.3%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%
None
ValueCountFrequency (%)
　 1
100.0%

등록일
Date

Distinct352
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Memory size10.2 KiB
Minimum2017-12-06 00:00:00
Maximum2022-09-01 00:00:00
2023-12-12T19:31:36.799389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:31:36.945772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Correlations

2023-12-12T19:31:37.030638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류구분지역
분류1.0001.0000.652
구분1.0001.0000.685
지역0.6520.6851.000
2023-12-12T19:31:37.106866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류구분
지역1.0000.3150.321
분류0.3151.0000.996
구분0.3210.9961.000
2023-12-12T19:31:37.193531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류구분지역
분류1.0000.9960.315
구분0.9961.0000.321
지역0.3150.3211.000

Missing values

2023-12-12T19:31:34.038676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:31:34.180536image/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

분류구분업체명지역소재지등록일
0여행업종합여행업범한세계여행사미추홀구미추홀구 경인로321, 수림빌딩 4층(도화동)2017-12-06
1여행업종합여행업㈜현대투어중구인천광역시 중구 자연대로40, 801호(중산동, 비젼프라자2)2017-12-06
2여행업종합여행업한스투어중구중구 신포로46번길 5, 102호(내동)2017-12-06
3여행업종합여행업㈜투어랜드계양구계양구 경명대로1029번길 5-4, 202호(계산동)2017-12-06
4여행업종합여행업주식회사 씨엘국제중구인천광역시 중구 신도시남로142번길 17, 305호(운서동)2017-12-06
5여행업종합여행업㈜타이한 투어연수구연수구 함박로8번길 58, 102호(연수동)2017-12-06
6여행업종합여행업한중국제여행사부평구부평구 배곶북로 14-1(십정동)2017-12-06
7여행업종합여행업㈜현대에이엠씨남동구남동구 소래로646, 3층(만수동)2017-12-06
8여행업종합여행업㈜조은투어중구중구 신포로27번길 632017-12-06
9여행업종합여행업㈜투어플러스연수구연수구 송도국제대로165, 지하1층(송도동,홈플러스송도점)2017-12-06
분류구분업체명지역소재지등록일
1284관광극장유흥업관광극장유흥업코리아관광나이트미추홀구미추홀구 경인로 392(주안동)2017-12-06
1285관광극장유흥업관광극장유흥업동경중년관광나이트미추홀구미추홀구 주안로 1162017-12-06
1286관광극장유흥업관광극장유흥업백악관관광나이트미추홀구미추홀구 주안동로 4 (주안동)2017-12-06
1287관광극장유흥업관광극장유흥업뉴월드관광나이트클럽미추홀구미추홀구 주안로 136, 3층 (주안동)2017-12-06
1288관광극장유흥업관광극장유흥업뉴 잠보관광나이트 크럽연수구인천광역시 연수구 벚꽃로 114 (연수동,9층)2017-12-06
1289관광극장유흥업관광극장유흥업아라비안관광나이트계양구인천광역시 계양구 도두리로 14 (작전동) 4~7층2017-12-06
1290관광극장유흥업관광극장유흥업호박관광나이트클럽서구인천광역시 서구 가정로 270(석남동)2017-12-06
1291관광극장유흥업관광극장유흥업국빈관서구서구 길주로 87(석남동)2017-12-06
1292관광극장유흥업관광극장유흥업징기스칸 관광나이트클럽서구서구 길주로 79(석남동)2017-12-06
1293관광극장유흥업관광극장유흥업크로마중구중구 영종해안남로 321번길 1862018-08-10