Overview

Dataset statistics

Number of variables5
Number of observations206
Missing cells17
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 KiB
Average record size in memory41.6 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description충청남도 아산시 숙박업소 현황으로 업소명, 업종명, 주소, 업소현황 등의 정보를 제공합니다----------------------------------
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=416&beforeMenuCd=DOM_000000201001001000&publicdatapk=15055142

Alerts

번호 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 번호High correlation
업종명 is highly imbalanced (76.3%)Imbalance
소재지전화 has 17 (8.3%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 22:27:58.218608
Analysis finished2024-01-09 22:27:58.709751
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct206
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.5
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-01-10T07:27:58.770226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.25
Q152.25
median103.5
Q3154.75
95-th percentile195.75
Maximum206
Range205
Interquartile range (IQR)102.5

Descriptive statistics

Standard deviation59.611241
Coefficient of variation (CV)0.57595401
Kurtosis-1.2
Mean103.5
Median Absolute Deviation (MAD)51.5
Skewness0
Sum21321
Variance3553.5
MonotonicityStrictly increasing
2024-01-10T07:27:58.872958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
143 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
Other values (196) 196
95.1%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%

업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
숙박업(일반)
198 
숙박업(생활)
 
8

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박업(일반)
2nd row숙박업(일반)
3rd row숙박업(일반)
4th row숙박업(일반)
5th row숙박업(일반)

Common Values

ValueCountFrequency (%)
숙박업(일반) 198
96.1%
숙박업(생활) 8
 
3.9%

Length

2024-01-10T07:27:58.968757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:27:59.042087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 198
96.1%
숙박업(생활 8
 
3.9%

업소명
Text

Distinct204
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-01-10T07:27:59.221810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length5.5825243
Min length2

Characters and Unicode

Total characters1150
Distinct characters254
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

Unique202 ?
Unique (%)98.1%

Sample

1st row온양여인숙
2nd row세종장여관
3rd row아이엔지모텔
4th row광천여인숙
5th row선화여인숙
ValueCountFrequency (%)
모텔 8
 
3.3%
여관 4
 
1.7%
호텔 3
 
1.3%
꿈의궁전 2
 
0.8%
주)이랜드파크 2
 
0.8%
집 2
 
0.8%
스파피아 2
 
0.8%
아산터미널점 2
 
0.8%
더블류무인텔 2
 
0.8%
도고 2
 
0.8%
Other values (208) 210
87.9%
2024-01-10T07:27:59.549896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 116
 
10.1%
모 69
 
6.0%
50
 
4.3%
스 45
 
3.9%
호 41
 
3.6%
여 37
 
3.2%
관 29
 
2.5%
인 28
 
2.4%
장 25
 
2.2%
파 22
 
1.9%
Other values (244) 688
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1031
89.7%
Space Separator 50
 
4.3%
Uppercase Letter 30
 
2.6%
Open Punctuation 12
 
1.0%
Close Punctuation 12
 
1.0%
Lowercase Letter 6
 
0.5%
Decimal Number 5
 
0.4%
Other Punctuation 3
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 116
 
11.3%
모 69
 
6.7%
스 45
 
4.4%
호 41
 
4.0%
여 37
 
3.6%
관 29
 
2.8%
인 28
 
2.7%
장 25
 
2.4%
파 22
 
2.1%
이 21
 
2.0%
Other values (218) 598
58.0%
Uppercase Letter
ValueCountFrequency (%)
A 6
20.0%
S 4
13.3%
T 4
13.3%
O 3
10.0%
H 3
10.0%
E 3
10.0%
L 2
 
6.7%
K 1
 
3.3%
C 1
 
3.3%
G 1
 
3.3%
Other values (2) 2
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 1
16.7%
t 1
16.7%
l 1
16.7%
e 1
16.7%
a 1
16.7%
g 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
2 2
40.0%
5 1
20.0%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1031
89.7%
Common 83
 
7.2%
Latin 36
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 116
 
11.3%
모 69
 
6.7%
스 45
 
4.4%
호 41
 
4.0%
여 37
 
3.6%
관 29
 
2.8%
인 28
 
2.7%
장 25
 
2.4%
파 22
 
2.1%
이 21
 
2.0%
Other values (218) 598
58.0%
Latin
ValueCountFrequency (%)
A 6
16.7%
S 4
11.1%
T 4
11.1%
O 3
 
8.3%
H 3
 
8.3%
E 3
 
8.3%
L 2
 
5.6%
o 1
 
2.8%
t 1
 
2.8%
K 1
 
2.8%
Other values (8) 8
22.2%
Common
ValueCountFrequency (%)
50
60.2%
( 12
 
14.5%
) 12
 
14.5%
. 3
 
3.6%
1 2
 
2.4%
2 2
 
2.4%
- 1
 
1.2%
5 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1031
89.7%
ASCII 119
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 116
 
11.3%
모 69
 
6.7%
스 45
 
4.4%
호 41
 
4.0%
여 37
 
3.6%
관 29
 
2.8%
인 28
 
2.7%
장 25
 
2.4%
파 22
 
2.1%
이 21
 
2.0%
Other values (218) 598
58.0%
ASCII
ValueCountFrequency (%)
50
42.0%
( 12
 
10.1%
) 12
 
10.1%
A 6
 
5.0%
S 4
 
3.4%
T 4
 
3.4%
O 3
 
2.5%
H 3
 
2.5%
E 3
 
2.5%
. 3
 
2.5%
Other values (16) 19
 
16.0%

영업소 주소(도로명)
Text

Distinct204
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-01-10T07:27:59.720708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length37
Mean length25.582524
Min length19

Characters and Unicode

Total characters5270
Distinct characters98
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

Unique202 ?
Unique (%)98.1%

Sample

1st row충청남도 아산시 온천대로 1510-10 (온천동)
2nd row충청남도 아산시 청운로84번길 23 (온천동)
3rd row충청남도 아산시 충무로8번길 17 (온천동)
4th row충청남도 아산시 시민로409번길 8, 광천여인숙 (온천동)
5th row충청남도 아산시 시민로409번길 10-4 (온천동)
ValueCountFrequency (%)
충청남도 206
19.6%
아산시 206
19.6%
온천동 79
 
7.5%
음봉면 41
 
3.9%
아산온천로157번길 21
 
2.0%
아산온천로243번길 18
 
1.7%
도고면 17
 
1.6%
모종동 17
 
1.6%
온천대로 17
 
1.6%
배방읍 10
 
1.0%
Other values (268) 419
39.9%
2024-01-10T07:28:00.216689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
845
 
16.0%
산 273
 
5.2%
아 259
 
4.9%
도 229
 
4.3%
시 228
 
4.3%
충 219
 
4.2%
1 218
 
4.1%
남 217
 
4.1%
청 214
 
4.1%
로 196
 
3.7%
Other values (88) 2372
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3118
59.2%
Decimal Number 940
 
17.8%
Space Separator 845
 
16.0%
Open Punctuation 114
 
2.2%
Close Punctuation 114
 
2.2%
Dash Punctuation 97
 
1.8%
Other Punctuation 35
 
0.7%
Math Symbol 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 273
 
8.8%
아 259
 
8.3%
도 229
 
7.3%
시 228
 
7.3%
충 219
 
7.0%
남 217
 
7.0%
청 214
 
6.9%
로 196
 
6.3%
온 152
 
4.9%
천 148
 
4.7%
Other values (72) 983
31.5%
Decimal Number
ValueCountFrequency (%)
1 218
23.2%
2 133
14.1%
5 97
10.3%
3 95
10.1%
4 92
9.8%
7 81
 
8.6%
6 69
 
7.3%
8 57
 
6.1%
0 50
 
5.3%
9 48
 
5.1%
Space Separator
ValueCountFrequency (%)
845
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%
Math Symbol
ValueCountFrequency (%)
~ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3118
59.2%
Common 2152
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 273
 
8.8%
아 259
 
8.3%
도 229
 
7.3%
시 228
 
7.3%
충 219
 
7.0%
남 217
 
7.0%
청 214
 
6.9%
로 196
 
6.3%
온 152
 
4.9%
천 148
 
4.7%
Other values (72) 983
31.5%
Common
ValueCountFrequency (%)
845
39.3%
1 218
 
10.1%
2 133
 
6.2%
( 114
 
5.3%
) 114
 
5.3%
5 97
 
4.5%
- 97
 
4.5%
3 95
 
4.4%
4 92
 
4.3%
7 81
 
3.8%
Other values (6) 266
 
12.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3118
59.2%
ASCII 2152
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
845
39.3%
1 218
 
10.1%
2 133
 
6.2%
( 114
 
5.3%
) 114
 
5.3%
5 97
 
4.5%
- 97
 
4.5%
3 95
 
4.4%
4 92
 
4.3%
7 81
 
3.8%
Other values (6) 266
 
12.4%
Hangul
ValueCountFrequency (%)
산 273
 
8.8%
아 259
 
8.3%
도 229
 
7.3%
시 228
 
7.3%
충 219
 
7.0%
남 217
 
7.0%
청 214
 
6.9%
로 196
 
6.3%
온 152
 
4.9%
천 148
 
4.7%
Other values (72) 983
31.5%

소재지전화
Text

MISSING 

Distinct188
Distinct (%)99.5%
Missing17
Missing (%)8.3%
Memory size1.7 KiB
2024-01-10T07:28:00.421483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2268
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

Unique187 ?
Unique (%)98.9%

Sample

1st row041-546-9372
2nd row041-545-2150
3rd row041-542-3313
4th row041-545-3076
5th row041-545-4136
ValueCountFrequency (%)
041-542-3101 2
 
1.1%
041-541-1288 1
 
0.5%
041-534-6330 1
 
0.5%
041-549-6262 1
 
0.5%
041-549-4415 1
 
0.5%
041-532-5001 1
 
0.5%
041-541-5477 1
 
0.5%
041-545-7080 1
 
0.5%
041-549-1211 1
 
0.5%
041-541-1223 1
 
0.5%
Other values (178) 178
94.2%
2024-01-10T07:28:00.730457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 422
18.6%
- 378
16.7%
1 328
14.5%
0 307
13.5%
5 301
13.3%
3 130
 
5.7%
2 98
 
4.3%
6 88
 
3.9%
8 77
 
3.4%
7 71
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1890
83.3%
Dash Punctuation 378
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 422
22.3%
1 328
17.4%
0 307
16.2%
5 301
15.9%
3 130
 
6.9%
2 98
 
5.2%
6 88
 
4.7%
8 77
 
4.1%
7 71
 
3.8%
9 68
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 378
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2268
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 422
18.6%
- 378
16.7%
1 328
14.5%
0 307
13.5%
5 301
13.3%
3 130
 
5.7%
2 98
 
4.3%
6 88
 
3.9%
8 77
 
3.4%
7 71
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2268
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 422
18.6%
- 378
16.7%
1 328
14.5%
0 307
13.5%
5 301
13.3%
3 130
 
5.7%
2 98
 
4.3%
6 88
 
3.9%
8 77
 
3.4%
7 71
 
3.1%

Interactions

2024-01-10T07:27:58.485787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:28:00.809705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종명
번호1.0000.729
업종명0.7291.000
2024-01-10T07:28:00.875758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종명
번호1.0000.560
업종명0.5601.000

Missing values

2024-01-10T07:27:58.584739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:27:58.676074image/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

번호업종명업소명영업소 주소(도로명)소재지전화
01숙박업(일반)온양여인숙충청남도 아산시 온천대로 1510-10 (온천동)041-546-9372
12숙박업(일반)세종장여관충청남도 아산시 청운로84번길 23 (온천동)041-545-2150
23숙박업(일반)아이엔지모텔충청남도 아산시 충무로8번길 17 (온천동)041-542-3313
34숙박업(일반)광천여인숙충청남도 아산시 시민로409번길 8, 광천여인숙 (온천동)041-545-3076
45숙박업(일반)선화여인숙충청남도 아산시 시민로409번길 10-4 (온천동)041-545-4136
56숙박업(일반)목화여인숙충청남도 아산시 충무로 34-6 (온천동)041-545-1790
67숙박업(일반)덕성여인숙충청남도 아산시 시민로393번길 6-15 (온천동)041-545-4015
78숙박업(일반)호텔 라그라스충청남도 아산시 충무로8번길 22 (온천동)041-545-5191
89숙박업(일반)신원장여관충청남도 아산시 충무로8번길 18-1 (온천동)041-545-4741
910숙박업(일반)달성장여관충청남도 아산시 온천대로 1531 (온천동)041-545-5141
번호업종명업소명영업소 주소(도로명)소재지전화
196197숙박업(일반)도고원탕충청남도 아산시 도고면 기곡로62번길 25-1, 2,4층<NA>
197198숙박업(일반)수 모텔충청남도 아산시 번영로 184-18, 1~3층 (권곡동)041-534-5333
198199숙박업(생활)(주)이랜드파크 한국콘도 도고충청남도 아산시 선장면 도고온천로 178041-534-8101
199200숙박업(생활)토비스콘도미니엄충청남도 아산시 도고면 기곡로77번길 39041-541-5432
200201숙박업(생활)도고토비스콘도미니엄충청남도 아산시 도고면 기곡로77번길 39041-541-6391
201202숙박업(생활)(주)이랜드파크 켄싱턴리조트 도고충청남도 아산시 도고면 도고온천로 124-23041-541-7100
202203숙박업(생활)게스트하우스충청남도 아산시 도고면 기곡로62번길 21-10<NA>
203204숙박업(생활)(주)더위트충청남도 아산시 도고면 기곡로62번길 6-8, 1층(일부),2층~15층,16층(일부),17층041-541-7734
204205숙박업(생활)가온누리홈타운충청남도 아산시 인주면 현대로 1299-3<NA>
205206숙박업(생활)SG아름다운골프앤리조트충청남도 아산시 영인면 영인산로 440-9 (주)에스지아름다운골프앤리조트041-536-8132