Overview

Dataset statistics

Number of variables5
Number of observations282
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.4 KiB
Average record size in memory41.5 B

Variable types

Categorical1
Text2
Numeric1
DateTime1

Dataset

Description인천광역시 소재 관광숙박업, 관광펜션업, 한옥체험업, 외국인 관광도시민박업 현황으로 업체명, 소재지, 객실수를 제공합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15091308&srcSe=7661IVAWM27C61E190

Reproduction

Analysis started2024-01-28 17:13:57.751795
Analysis finished2024-01-28 17:13:58.259424
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct9
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
호스텔업
85 
관광호텔업
80 
외국인관광도시민박업
73 
관광펜션업
26 
한옥체험업
12 
Other values (4)
 
6

Length

Max length10
Median length8
Mean length6.0177305
Min length4

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
호스텔업 85
30.1%
관광호텔업 80
28.4%
외국인관광도시민박업 73
25.9%
관광펜션업 26
 
9.2%
한옥체험업 12
 
4.3%
한국전통호텔업 2
 
0.7%
가족호텔업 2
 
0.7%
소형호텔업 1
 
0.4%
휴양콘도미니엄업 1
 
0.4%

Length

2024-01-29T02:13:58.316782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:13:58.420764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
호스텔업 85
30.1%
관광호텔업 80
28.4%
외국인관광도시민박업 73
25.9%
관광펜션업 26
 
9.2%
한옥체험업 12
 
4.3%
한국전통호텔업 2
 
0.7%
가족호텔업 2
 
0.7%
소형호텔업 1
 
0.4%
휴양콘도미니엄업 1
 
0.4%

업체명
Text

Distinct281
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-01-29T02:13:58.666622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length7.748227
Min length2

Characters and Unicode

Total characters2185
Distinct characters344
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique280 ?
Unique (%)99.3%

Sample

1st row나무와 숲 석모도점
2nd row하미양 관광펜션
3rd row수랜드
4th row한가라지
5th row관광펜션무무
ValueCountFrequency (%)
호스텔 30
 
7.2%
호텔 11
 
2.6%
게스트하우스 11
 
2.6%
관광호텔 8
 
1.9%
house 4
 
1.0%
월미도 3
 
0.7%
hotel 3
 
0.7%
하우스 3
 
0.7%
guesthouse 3
 
0.7%
베니키아 2
 
0.5%
Other values (331) 341
81.4%
2024-01-29T02:13:59.051774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 170
 
7.8%
텔 138
 
6.3%
호 137
 
6.3%
137
 
6.3%
하 60
 
2.7%
우 50
 
2.3%
트 47
 
2.2%
이 44
 
2.0%
관 35
 
1.6%
광 33
 
1.5%
Other values (334) 1334
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1705
78.0%
Lowercase Letter 148
 
6.8%
Space Separator 137
 
6.3%
Uppercase Letter 124
 
5.7%
Decimal Number 25
 
1.1%
Close Punctuation 17
 
0.8%
Open Punctuation 17
 
0.8%
Other Punctuation 7
 
0.3%
Dash Punctuation 4
 
0.2%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 170
 
10.0%
텔 138
 
8.1%
호 137
 
8.0%
하 60
 
3.5%
우 50
 
2.9%
트 47
 
2.8%
이 44
 
2.6%
관 35
 
2.1%
광 33
 
1.9%
리 32
 
1.9%
Other values (270) 959
56.2%
Lowercase Letter
ValueCountFrequency (%)
e 25
16.9%
s 19
12.8%
o 16
10.8%
u 13
8.8%
t 12
8.1%
a 10
 
6.8%
h 7
 
4.7%
i 7
 
4.7%
m 6
 
4.1%
y 5
 
3.4%
Other values (13) 28
18.9%
Uppercase Letter
ValueCountFrequency (%)
E 13
 
10.5%
O 12
 
9.7%
H 10
 
8.1%
S 10
 
8.1%
T 9
 
7.3%
G 8
 
6.5%
B 8
 
6.5%
A 7
 
5.6%
U 6
 
4.8%
R 5
 
4.0%
Other values (11) 36
29.0%
Decimal Number
ValueCountFrequency (%)
2 5
20.0%
1 4
16.0%
4 3
12.0%
7 3
12.0%
3 3
12.0%
9 3
12.0%
0 2
 
8.0%
8 1
 
4.0%
6 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
& 4
57.1%
; 1
 
14.3%
' 1
 
14.3%
. 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 15
88.2%
] 2
 
11.8%
Open Punctuation
ValueCountFrequency (%)
( 15
88.2%
[ 2
 
11.8%
Space Separator
ValueCountFrequency (%)
137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1705
78.0%
Latin 272
 
12.4%
Common 208
 
9.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 170
 
10.0%
텔 138
 
8.1%
호 137
 
8.0%
하 60
 
3.5%
우 50
 
2.9%
트 47
 
2.8%
이 44
 
2.6%
관 35
 
2.1%
광 33
 
1.9%
리 32
 
1.9%
Other values (270) 959
56.2%
Latin
ValueCountFrequency (%)
e 25
 
9.2%
s 19
 
7.0%
o 16
 
5.9%
E 13
 
4.8%
u 13
 
4.8%
O 12
 
4.4%
t 12
 
4.4%
H 10
 
3.7%
a 10
 
3.7%
S 10
 
3.7%
Other values (34) 132
48.5%
Common
ValueCountFrequency (%)
137
65.9%
) 15
 
7.2%
( 15
 
7.2%
2 5
 
2.4%
1 4
 
1.9%
- 4
 
1.9%
& 4
 
1.9%
4 3
 
1.4%
7 3
 
1.4%
3 3
 
1.4%
Other values (10) 15
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1705
78.0%
ASCII 479
 
21.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 170
 
10.0%
텔 138
 
8.1%
호 137
 
8.0%
하 60
 
3.5%
우 50
 
2.9%
트 47
 
2.8%
이 44
 
2.6%
관 35
 
2.1%
광 33
 
1.9%
리 32
 
1.9%
Other values (270) 959
56.2%
ASCII
ValueCountFrequency (%)
137
28.6%
e 25
 
5.2%
s 19
 
4.0%
o 16
 
3.3%
) 15
 
3.1%
( 15
 
3.1%
E 13
 
2.7%
u 13
 
2.7%
O 12
 
2.5%
t 12
 
2.5%
Other values (53) 202
42.2%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

소재지
Text

Distinct281
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
2024-01-29T02:13:59.311913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length38
Mean length21.021277
Min length8

Characters and Unicode

Total characters5928
Distinct characters227
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique280 ?
Unique (%)99.3%

Sample

1st row인천시 강화군 삼산면 어류정길 212번길 17
2nd row인천시 강화군 화도면 해안남로 1414-1
3rd row인천광역시 강화군 화도면 해안남로1502번길 11
4th row강화군 삼산면 삼산남로 1011
5th row강화군 화도면 해안남로 1066번길-12
ValueCountFrequency (%)
중구 175
 
15.4%
인천광역시 49
 
4.3%
서구 29
 
2.6%
강화군 25
 
2.2%
인천 15
 
1.3%
용유서로 13
 
1.1%
남동구 13
 
1.1%
을왕동 13
 
1.1%
화도면 13
 
1.1%
연수구 12
 
1.1%
Other values (564) 780
68.6%
2024-01-29T02:13:59.726755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
863
 
14.6%
1 303
 
5.1%
로 257
 
4.3%
구 247
 
4.2%
2 240
 
4.0%
중 188
 
3.2%
길 179
 
3.0%
동 175
 
3.0%
번 170
 
2.9%
3 158
 
2.7%
Other values (217) 3148
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3043
51.3%
Decimal Number 1563
26.4%
Space Separator 863
 
14.6%
Dash Punctuation 129
 
2.2%
Open Punctuation 126
 
2.1%
Close Punctuation 126
 
2.1%
Other Punctuation 77
 
1.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 257
 
8.4%
구 247
 
8.1%
중 188
 
6.2%
길 179
 
5.9%
동 175
 
5.8%
번 170
 
5.6%
서 93
 
3.1%
인 78
 
2.6%
왕 76
 
2.5%
천 74
 
2.4%
Other values (201) 1506
49.5%
Decimal Number
ValueCountFrequency (%)
1 303
19.4%
2 240
15.4%
3 158
10.1%
0 156
10.0%
4 143
9.1%
7 133
8.5%
5 129
8.3%
6 117
 
7.5%
8 107
 
6.8%
9 77
 
4.9%
Space Separator
ValueCountFrequency (%)
863
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Other Punctuation
ValueCountFrequency (%)
, 77
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3043
51.3%
Common 2885
48.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 257
 
8.4%
구 247
 
8.1%
중 188
 
6.2%
길 179
 
5.9%
동 175
 
5.8%
번 170
 
5.6%
서 93
 
3.1%
인 78
 
2.6%
왕 76
 
2.5%
천 74
 
2.4%
Other values (201) 1506
49.5%
Common
ValueCountFrequency (%)
863
29.9%
1 303
 
10.5%
2 240
 
8.3%
3 158
 
5.5%
0 156
 
5.4%
4 143
 
5.0%
7 133
 
4.6%
- 129
 
4.5%
5 129
 
4.5%
( 126
 
4.4%
Other values (6) 505
17.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3043
51.3%
ASCII 2885
48.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
863
29.9%
1 303
 
10.5%
2 240
 
8.3%
3 158
 
5.5%
0 156
 
5.4%
4 143
 
5.0%
7 133
 
4.6%
- 129
 
4.5%
5 129
 
4.5%
( 126
 
4.4%
Other values (6) 505
17.5%
Hangul
ValueCountFrequency (%)
로 257
 
8.4%
구 247
 
8.1%
중 188
 
6.2%
길 179
 
5.9%
동 175
 
5.8%
번 170
 
5.6%
서 93
 
3.1%
인 78
 
2.6%
왕 76
 
2.5%
천 74
 
2.4%
Other values (201) 1506
49.5%

객실수
Real number (ℝ)

Distinct83
Distinct (%)29.5%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean39.989324
Minimum1
Maximum769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.6 KiB
2024-01-29T02:13:59.872518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q342
95-th percentile184
Maximum769
Range768
Interquartile range (IQR)38

Descriptive statistics

Standard deviation87.965476
Coefficient of variation (CV)2.199724
Kurtosis26.71059
Mean39.989324
Median Absolute Deviation (MAD)6
Skewness4.6933374
Sum11237
Variance7737.9249
MonotonicityNot monotonic
2024-01-29T02:14:00.074874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 31
 
11.0%
1 22
 
7.8%
5 21
 
7.4%
4 20
 
7.1%
6 16
 
5.7%
3 15
 
5.3%
12 9
 
3.2%
8 9
 
3.2%
7 7
 
2.5%
15 6
 
2.1%
Other values (73) 125
44.3%
ValueCountFrequency (%)
1 22
7.8%
2 31
11.0%
3 15
5.3%
4 20
7.1%
5 21
7.4%
6 16
5.7%
7 7
 
2.5%
8 9
 
3.2%
9 3
 
1.1%
10 1
 
0.4%
ValueCountFrequency (%)
769 1
0.4%
523 1
0.4%
510 1
0.4%
501 1
0.4%
423 1
0.4%
370 1
0.4%
321 1
0.4%
305 1
0.4%
300 1
0.4%
275 1
0.4%

등록일
Date

Distinct99
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size2.3 KiB
Minimum2017-12-06 00:00:00
Maximum2022-08-24 00:00:00
2024-01-29T02:14:00.301778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:14:00.526819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-01-29T02:13:58.047588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:14:00.688281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분객실수등록일
구분1.0000.6050.000
객실수0.6051.0000.000
등록일0.0000.0001.000
2024-01-29T02:14:00.815927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
객실수구분
객실수1.0000.350
구분0.3501.000

Missing values

2024-01-29T02:13:58.151791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:13:58.228692image/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

구분업체명소재지객실수등록일
0관광펜션업나무와 숲 석모도점인천시 강화군 삼산면 어류정길 212번길 17122017-12-06
1관광펜션업하미양 관광펜션인천시 강화군 화도면 해안남로 1414-172017-12-06
2관광펜션업수랜드인천광역시 강화군 화도면 해안남로1502번길 11162017-12-06
3관광펜션업한가라지강화군 삼산면 삼산남로 1011182017-12-06
4관광펜션업관광펜션무무강화군 화도면 해안남로 1066번길-1252017-12-06
5관광펜션업라파엘강화군 화도면 해안남로164172017-12-06
6관광펜션업하와이비치인천시 옹진군 영흥면 영흥서로446번길 36172017-12-06
7관광펜션업랜드하우스강화군 화도면 해안남로 1669-1262017-12-06
8관광펜션업썬댄스펜션강화군 화도면 해안남로 1691번길 43-30112017-12-06
9관광펜션업퀸스비치인천시 옹진군 영흥면 선재로306번길 27-116212017-12-06
구분업체명소재지객실수등록일
272호스텔업에버뷰인천 중구 용유서로 348번길 16152021-06-21
273호스텔업어느 멋진날에1중구 늘목로22번길 57-712021-07-15
274호스텔업제이든 29-1중구 용유서로302번길 1542021-07-16
275호스텔업어느 멋진날에2중구 늘목로22번길 57-312021-07-16
276호스텔업하나호스텔인천 중구 용유서로 304번길 6(을왕동)102021-09-17
277호스텔업해처럼중구 왕산로7262021-10-29
278호스텔업꿈호스텔중구 용유서로 380-1852021-11-03
279호스텔업원더풀호스텔중구 왕산로 68-1652021-11-03
280호스텔업레드호스텔중구 왕산로7132022-08-24
281휴양콘도미니엄업TheWeek&amp (더위크앤 리조트)중구 용유서로 379(을왕동 773)1842017-12-06