Overview

Dataset statistics

Number of variables3
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory756.0 B
Average record size in memory29.1 B

Variable types

Categorical1
Text2

Dataset

Description서울특별시 광진구 관광객에 대한 데이터로 관광객의 이용시설업 업종, 상호, 소재지(도로명)에 대한 항목을 제공합니다.
Author서울특별시 광진구
URLhttps://www.data.go.kr/data/15094364/fileData.do

Alerts

업종 is highly imbalanced (76.5%)Imbalance
상호 has unique valuesUnique
소재지(도로명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:40:21.202792
Analysis finished2023-12-12 07:40:21.504367
Duration0.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

IMBALANCE 

Distinct2
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size340.0 B
외국인관광 도시민박업
25 
한옥체험업
 
1

Length

Max length11
Median length11
Mean length10.769231
Min length5

Unique

Unique1 ?
Unique (%)3.8%

Sample

1st row외국인관광 도시민박업
2nd row외국인관광 도시민박업
3rd row외국인관광 도시민박업
4th row외국인관광 도시민박업
5th row외국인관광 도시민박업

Common Values

ValueCountFrequency (%)
외국인관광 도시민박업 25
96.2%
한옥체험업 1
 
3.8%

Length

2023-12-12T16:40:21.583939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:40:21.686020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인관광 25
49.0%
도시민박업 25
49.0%
한옥체험업 1
 
2.0%

상호
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T16:40:21.942490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length15.5
Mean length9.8461538
Min length3

Characters and Unicode

Total characters256
Distinct characters100
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

Unique26 ?
Unique (%)100.0%

Sample

1st row친친스테이(Chinchin Stay)
2nd rowRiver Side
3rd row아늑공간
4th row자양토박이네(Jayang Tobak's House)
5th rowKonkuk univ cozy house
ValueCountFrequency (%)
house 4
 
8.9%
게스트하우스 4
 
8.9%
stay 2
 
4.4%
릴릴레지던스 2
 
4.4%
친친스테이(chinchin 1
 
2.2%
한강에어비엔비 1
 
2.2%
love 1
 
2.2%
라온 1
 
2.2%
포레스트 1
 
2.2%
서호빌리지 1
 
2.2%
Other values (27) 27
60.0%
2023-12-12T16:40:22.349335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
7.4%
스 18
 
7.0%
o 9
 
3.5%
이 9
 
3.5%
e 9
 
3.5%
하 7
 
2.7%
우 7
 
2.7%
u 7
 
2.7%
트 6
 
2.3%
i 6
 
2.3%
Other values (90) 159
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
54.3%
Lowercase Letter 75
29.3%
Space Separator 19
 
7.4%
Uppercase Letter 13
 
5.1%
Open Punctuation 3
 
1.2%
Close Punctuation 3
 
1.2%
Decimal Number 3
 
1.2%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 18
 
12.9%
이 9
 
6.5%
하 7
 
5.0%
우 7
 
5.0%
트 6
 
4.3%
게 4
 
2.9%
릴 4
 
2.9%
레 4
 
2.9%
지 3
 
2.2%
테 3
 
2.2%
Other values (55) 74
53.2%
Lowercase Letter
ValueCountFrequency (%)
o 9
12.0%
e 9
12.0%
u 7
9.3%
i 6
 
8.0%
n 6
 
8.0%
a 5
 
6.7%
s 5
 
6.7%
h 4
 
5.3%
y 4
 
5.3%
k 3
 
4.0%
Other values (9) 17
22.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
23.1%
H 2
15.4%
J 2
15.4%
R 1
 
7.7%
C 1
 
7.7%
T 1
 
7.7%
B 1
 
7.7%
L 1
 
7.7%
K 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
2 1
33.3%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 139
54.3%
Latin 88
34.4%
Common 29
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 18
 
12.9%
이 9
 
6.5%
하 7
 
5.0%
우 7
 
5.0%
트 6
 
4.3%
게 4
 
2.9%
릴 4
 
2.9%
레 4
 
2.9%
지 3
 
2.2%
테 3
 
2.2%
Other values (55) 74
53.2%
Latin
ValueCountFrequency (%)
o 9
 
10.2%
e 9
 
10.2%
u 7
 
8.0%
i 6
 
6.8%
n 6
 
6.8%
a 5
 
5.7%
s 5
 
5.7%
h 4
 
4.5%
y 4
 
4.5%
k 3
 
3.4%
Other values (18) 30
34.1%
Common
ValueCountFrequency (%)
19
65.5%
( 3
 
10.3%
) 3
 
10.3%
' 1
 
3.4%
1 1
 
3.4%
2 1
 
3.4%
3 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
54.3%
ASCII 117
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
16.2%
o 9
 
7.7%
e 9
 
7.7%
u 7
 
6.0%
i 6
 
5.1%
n 6
 
5.1%
a 5
 
4.3%
s 5
 
4.3%
h 4
 
3.4%
y 4
 
3.4%
Other values (25) 43
36.8%
Hangul
ValueCountFrequency (%)
스 18
 
12.9%
이 9
 
6.5%
하 7
 
5.0%
우 7
 
5.0%
트 6
 
4.3%
게 4
 
2.9%
릴 4
 
2.9%
레 4
 
2.9%
지 3
 
2.2%
테 3
 
2.2%
Other values (55) 74
53.2%

소재지(도로명)
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-12T16:40:22.679507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length27
Mean length22
Min length14

Characters and Unicode

Total characters572
Distinct characters65
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row자양번영로5길 37-1 (자양동)
2nd row뚝섬로 702-4 (자양동)
3rd row자양로44나길 17, 지층 (구의동, 솔라빌리지)
4th row자양번영로7길 16-7 (자양동)
5th row아차산로26길 17-6, 202호 (자양동, 트윈빌)
ValueCountFrequency (%)
자양동 7
 
7.1%
화양동 5
 
5.1%
102호 5
 
5.1%
구의동 5
 
5.1%
202호 4
 
4.0%
아차산로21길 2
 
2.0%
201호 2
 
2.0%
30 2
 
2.0%
용마산로 2
 
2.0%
6-10 2
 
2.0%
Other values (59) 63
63.6%
2023-12-12T16:40:23.181966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
73
 
12.8%
1 38
 
6.6%
0 31
 
5.4%
동 29
 
5.1%
2 28
 
4.9%
로 26
 
4.5%
( 23
 
4.0%
양 23
 
4.0%
) 23
 
4.0%
, 22
 
3.8%
Other values (55) 256
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 252
44.1%
Decimal Number 164
28.7%
Space Separator 73
 
12.8%
Open Punctuation 23
 
4.0%
Close Punctuation 23
 
4.0%
Other Punctuation 22
 
3.8%
Dash Punctuation 15
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
 
11.5%
로 26
 
10.3%
양 23
 
9.1%
길 22
 
8.7%
자 17
 
6.7%
호 17
 
6.7%
구 8
 
3.2%
산 8
 
3.2%
아 7
 
2.8%
의 7
 
2.8%
Other values (40) 88
34.9%
Decimal Number
ValueCountFrequency (%)
1 38
23.2%
0 31
18.9%
2 28
17.1%
4 17
10.4%
3 13
 
7.9%
7 12
 
7.3%
6 12
 
7.3%
5 9
 
5.5%
8 3
 
1.8%
9 1
 
0.6%
Space Separator
ValueCountFrequency (%)
73
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320
55.9%
Hangul 252
44.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
 
11.5%
로 26
 
10.3%
양 23
 
9.1%
길 22
 
8.7%
자 17
 
6.7%
호 17
 
6.7%
구 8
 
3.2%
산 8
 
3.2%
아 7
 
2.8%
의 7
 
2.8%
Other values (40) 88
34.9%
Common
ValueCountFrequency (%)
73
22.8%
1 38
11.9%
0 31
9.7%
2 28
 
8.8%
( 23
 
7.2%
) 23
 
7.2%
, 22
 
6.9%
4 17
 
5.3%
- 15
 
4.7%
3 13
 
4.1%
Other values (5) 37
11.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320
55.9%
Hangul 252
44.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
73
22.8%
1 38
11.9%
0 31
9.7%
2 28
 
8.8%
( 23
 
7.2%
) 23
 
7.2%
, 22
 
6.9%
4 17
 
5.3%
- 15
 
4.7%
3 13
 
4.1%
Other values (5) 37
11.6%
Hangul
ValueCountFrequency (%)
동 29
 
11.5%
로 26
 
10.3%
양 23
 
9.1%
길 22
 
8.7%
자 17
 
6.7%
호 17
 
6.7%
구 8
 
3.2%
산 8
 
3.2%
아 7
 
2.8%
의 7
 
2.8%
Other values (40) 88
34.9%

Correlations

2023-12-12T16:40:23.287944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종상호소재지(도로명)
업종1.0001.0001.000
상호1.0001.0001.000
소재지(도로명)1.0001.0001.000

Missing values

2023-12-12T16:40:21.389605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:40:21.469195image/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)
0외국인관광 도시민박업친친스테이(Chinchin Stay)자양번영로5길 37-1 (자양동)
1외국인관광 도시민박업River Side뚝섬로 702-4 (자양동)
2외국인관광 도시민박업아늑공간자양로44나길 17, 지층 (구의동, 솔라빌리지)
3외국인관광 도시민박업자양토박이네(Jayang Tobak's House)자양번영로7길 16-7 (자양동)
4외국인관광 도시민박업Konkuk univ cozy house아차산로26길 17-6, 202호 (자양동, 트윈빌)
5외국인관광 도시민박업파랑새 하우스(Bluebird house)동일로26길 33, 102호 (화양동)
6외국인관광 도시민박업게스트하우스 브릭핸즈능동로16길 50-7, 401호(화양동)
7외국인관광 도시민박업이모네하우스자양로15길 108,400호(자양동)
8외국인관광 도시민박업Joeng Stay자양번영로1길 31-10, 스튜디오 안 501호(자양동)
9외국인관광 도시민박업릴릴레지던스 1용마산로 6-10 102호
업종상호소재지(도로명)
16외국인관광 도시민박업포레스트능동로24길 60-10, 1층 (능동)
17외국인관광 도시민박업서호빌리지아차산로21길 30, 201호 (화양동)
18외국인관광 도시민박업한강에어비엔비뚝섬로30가길 22, 2층 (자양동)
19외국인관광 도시민박업연화하우스아차산로31길 42-1, 202호 (화양동)
20외국인관광 도시민박업오프워크스테이아차산로21길 30, 202호 (화양동)
21외국인관광 도시민박업오프워크센터아차산로25길 57-1, 102호 (화양동)
22외국인관광 도시민박업제이와이 게스트하우스능동로3라길 6-3, 201호 (자양동)
23외국인관광 도시민박업웜플레이스자양로30길 64-13, 102호 (구의동)
24외국인관광 도시민박업새한아파트 홈스테이자양로26길 71, 101동 102호 (구의동, 구의동새한아파트)
25한옥체험업육영재단 어린이회관서울특별시 광진구 광나루로 441 (능동)