Overview

Dataset statistics

Number of variables6
Number of observations132
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory49.0 B

Variable types

Categorical2
DateTime1
Text3

Dataset

Description충청남도 논산시 숙박업소현황에 대한 데이터로 업종구분, 업소명, 행정구역, 주소, 전화번호 정보를 제공하고있습니다.
Author충청남도 논산시
URLhttps://www.data.go.kr/data/15067288/fileData.do

Alerts

업종구분 is highly imbalanced (80.4%)Imbalance

Reproduction

Analysis started2023-12-12 03:10:06.578342
Analysis finished2023-12-12 03:10:07.237870
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
숙박업(일반)
128 
숙박업(생활)
 
4

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) 128
97.0%
숙박업(생활) 4
 
3.0%

Length

2023-12-12T12:10:07.359248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:10:07.511969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숙박업(일반 128
97.0%
숙박업(생활 4
 
3.0%

신고일자
Date

Distinct119
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1971-07-07 00:00:00
Maximum2021-07-09 00:00:00
2023-12-12T12:10:07.682736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T12:10:07.899004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T12:10:08.376121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length4.9015152
Min length2

Characters and Unicode

Total characters647
Distinct characters180
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)98.5%

Sample

1st row오로라
2nd row향란여인숙
3rd row조화여인숙
4th row삼남여인숙
5th row청양여인숙
ValueCountFrequency (%)
스테이인터뷰강경구락부 2
 
1.5%
피크닉 2
 
1.5%
미라클모텔 1
 
0.7%
월 1
 
0.7%
호텔 1
 
0.7%
뉴파크장 1
 
0.7%
모텔알프스 1
 
0.7%
타이타닉 1
 
0.7%
커플리아 1
 
0.7%
조선호텔 1
 
0.7%
Other values (123) 123
91.1%
2023-12-12T12:10:09.018966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
텔 63
 
9.7%
모 48
 
7.4%
여 34
 
5.3%
인 33
 
5.1%
숙 18
 
2.8%
스 16
 
2.5%
무 16
 
2.5%
장 15
 
2.3%
관 15
 
2.3%
크 14
 
2.2%
Other values (170) 375
58.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 619
95.7%
Uppercase Letter 13
 
2.0%
Decimal Number 7
 
1.1%
Space Separator 3
 
0.5%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
텔 63
 
10.2%
모 48
 
7.8%
여 34
 
5.5%
인 33
 
5.3%
숙 18
 
2.9%
스 16
 
2.6%
무 16
 
2.6%
장 15
 
2.4%
관 15
 
2.4%
크 14
 
2.3%
Other values (157) 347
56.1%
Uppercase Letter
ValueCountFrequency (%)
A 4
30.8%
B 4
30.8%
K 2
15.4%
O 2
15.4%
G 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
0 2
28.6%
2 2
28.6%
7 2
28.6%
1 1
14.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 619
95.7%
Common 15
 
2.3%
Latin 13
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
텔 63
 
10.2%
모 48
 
7.8%
여 34
 
5.5%
인 33
 
5.3%
숙 18
 
2.9%
스 16
 
2.6%
무 16
 
2.6%
장 15
 
2.4%
관 15
 
2.4%
크 14
 
2.3%
Other values (157) 347
56.1%
Common
ValueCountFrequency (%)
3
20.0%
0 2
13.3%
) 2
13.3%
( 2
13.3%
2 2
13.3%
7 2
13.3%
. 1
 
6.7%
1 1
 
6.7%
Latin
ValueCountFrequency (%)
A 4
30.8%
B 4
30.8%
K 2
15.4%
O 2
15.4%
G 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 619
95.7%
ASCII 28
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
텔 63
 
10.2%
모 48
 
7.8%
여 34
 
5.5%
인 33
 
5.3%
숙 18
 
2.9%
스 16
 
2.6%
무 16
 
2.6%
장 15
 
2.4%
관 15
 
2.4%
크 14
 
2.3%
Other values (157) 347
56.1%
ASCII
ValueCountFrequency (%)
A 4
14.3%
B 4
14.3%
3
10.7%
0 2
7.1%
) 2
7.1%
( 2
7.1%
K 2
7.1%
O 2
7.1%
2 2
7.1%
7 2
7.1%
Other values (3) 3
10.7%

행정동명
Categorical

Distinct13
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
취암동
32 
강경읍
29 
연무읍
23 
연산면
19 
벌곡면
7 
Other values (8)
22 

Length

Max length4
Median length3
Mean length3.0378788
Min length3

Unique

Unique3 ?
Unique (%)2.3%

Sample

1st row강경읍
2nd row강경읍
3rd row취암동
4th row취암동
5th row취암동

Common Values

ValueCountFrequency (%)
취암동 32
24.2%
강경읍 29
22.0%
연무읍 23
17.4%
연산면 19
14.4%
벌곡면 7
 
5.3%
은진면 5
 
3.8%
가야곡면 5
 
3.8%
부창동 4
 
3.0%
부적면 3
 
2.3%
성동면 2
 
1.5%
Other values (3) 3
 
2.3%

Length

2023-12-12T12:10:09.263406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
취암동 32
24.2%
강경읍 29
22.0%
연무읍 23
17.4%
연산면 19
14.4%
벌곡면 7
 
5.3%
은진면 5
 
3.8%
가야곡면 5
 
3.8%
부창동 4
 
3.0%
부적면 3
 
2.3%
성동면 2
 
1.5%
Other values (3) 3
 
2.3%

주소
Text

Distinct131
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T12:10:09.508542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length28
Mean length23.772727
Min length18

Characters and Unicode

Total characters3138
Distinct characters104
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique130 ?
Unique (%)98.5%

Sample

1st row충청남도 논산시 강경읍 계백로133번길 3-33
2nd row충청남도 논산시 강경읍 계백로133번길 3-27
3rd row충청남도 논산시 해월로125번길 19-2 (반월동)
4th row충청남도 논산시 해월로211번길 8-26 (화지동)
5th row충청남도 논산시 해월로211번길 8-28 (화지동)
ValueCountFrequency (%)
충청남도 132
19.7%
논산시 132
19.7%
강경읍 29
 
4.3%
연무읍 23
 
3.4%
계백로133번길 23
 
3.4%
연산면 19
 
2.8%
취암동 13
 
1.9%
계백로 11
 
1.6%
화지동 9
 
1.3%
해월로 8
 
1.2%
Other values (190) 271
40.4%
2023-12-12T12:10:09.990291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
538
 
17.1%
산 153
 
4.9%
시 134
 
4.3%
충 132
 
4.2%
남 132
 
4.2%
도 132
 
4.2%
논 132
 
4.2%
청 132
 
4.2%
1 130
 
4.1%
로 113
 
3.6%
Other values (94) 1410
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1870
59.6%
Decimal Number 575
 
18.3%
Space Separator 538
 
17.1%
Dash Punctuation 66
 
2.1%
Open Punctuation 37
 
1.2%
Close Punctuation 37
 
1.2%
Other Punctuation 12
 
0.4%
Uppercase Letter 2
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 153
 
8.2%
시 134
 
7.2%
충 132
 
7.1%
남 132
 
7.1%
도 132
 
7.1%
논 132
 
7.1%
청 132
 
7.1%
로 113
 
6.0%
길 69
 
3.7%
읍 52
 
2.8%
Other values (75) 689
36.8%
Decimal Number
ValueCountFrequency (%)
1 130
22.6%
3 101
17.6%
2 82
14.3%
4 45
 
7.8%
5 44
 
7.7%
8 40
 
7.0%
9 38
 
6.6%
6 36
 
6.3%
7 31
 
5.4%
0 28
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 8
66.7%
· 4
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
538
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1870
59.6%
Common 1266
40.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 153
 
8.2%
시 134
 
7.2%
충 132
 
7.1%
남 132
 
7.1%
도 132
 
7.1%
논 132
 
7.1%
청 132
 
7.1%
로 113
 
6.0%
길 69
 
3.7%
읍 52
 
2.8%
Other values (75) 689
36.8%
Common
ValueCountFrequency (%)
538
42.5%
1 130
 
10.3%
3 101
 
8.0%
2 82
 
6.5%
- 66
 
5.2%
4 45
 
3.6%
5 44
 
3.5%
8 40
 
3.2%
9 38
 
3.0%
( 37
 
2.9%
Other values (7) 145
 
11.5%
Latin
ValueCountFrequency (%)
B 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1870
59.6%
ASCII 1264
40.3%
None 4
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
538
42.6%
1 130
 
10.3%
3 101
 
8.0%
2 82
 
6.5%
- 66
 
5.2%
4 45
 
3.6%
5 44
 
3.5%
8 40
 
3.2%
9 38
 
3.0%
( 37
 
2.9%
Other values (8) 143
 
11.3%
Hangul
ValueCountFrequency (%)
산 153
 
8.2%
시 134
 
7.2%
충 132
 
7.1%
남 132
 
7.1%
도 132
 
7.1%
논 132
 
7.1%
청 132
 
7.1%
로 113
 
6.0%
길 69
 
3.7%
읍 52
 
2.8%
Other values (75) 689
36.8%
None
ValueCountFrequency (%)
· 4
100.0%

전화번호
Text

Distinct104
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T12:10:10.415902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.060606
Min length7

Characters and Unicode

Total characters1460
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique99 ?
Unique (%)75.0%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row041-735-2829
4th row041-735-3712
5th row041-733-3409
ValueCountFrequency (%)
데이터 25
 
15.9%
미집계 25
 
15.9%
041-732-3032 2
 
1.3%
041-735-9080 2
 
1.3%
041-736-0501 2
 
1.3%
041-742-8787 2
 
1.3%
041-736-8702 1
 
0.6%
041-742-5111 1
 
0.6%
041-741-5250 1
 
0.6%
041-736-8251 1
 
0.6%
Other values (95) 95
60.5%
2023-12-12T12:10:10.985009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 214
14.7%
4 182
12.5%
0 176
12.1%
7 163
11.2%
1 156
10.7%
3 116
7.9%
5 78
 
5.3%
2 76
 
5.2%
8 53
 
3.6%
6 43
 
2.9%
Other values (8) 203
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1071
73.4%
Dash Punctuation 214
 
14.7%
Other Letter 150
 
10.3%
Space Separator 25
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 182
17.0%
0 176
16.4%
7 163
15.2%
1 156
14.6%
3 116
10.8%
5 78
7.3%
2 76
7.1%
8 53
 
4.9%
6 43
 
4.0%
9 28
 
2.6%
Other Letter
ValueCountFrequency (%)
이 25
16.7%
계 25
16.7%
집 25
16.7%
미 25
16.7%
터 25
16.7%
데 25
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 214
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1310
89.7%
Hangul 150
 
10.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 214
16.3%
4 182
13.9%
0 176
13.4%
7 163
12.4%
1 156
11.9%
3 116
8.9%
5 78
 
6.0%
2 76
 
5.8%
8 53
 
4.0%
6 43
 
3.3%
Other values (2) 53
 
4.0%
Hangul
ValueCountFrequency (%)
이 25
16.7%
계 25
16.7%
집 25
16.7%
미 25
16.7%
터 25
16.7%
데 25
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1310
89.7%
Hangul 150
 
10.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 214
16.3%
4 182
13.9%
0 176
13.4%
7 163
12.4%
1 156
11.9%
3 116
8.9%
5 78
 
6.0%
2 76
 
5.8%
8 53
 
4.0%
6 43
 
3.3%
Other values (2) 53
 
4.0%
Hangul
ValueCountFrequency (%)
이 25
16.7%
계 25
16.7%
집 25
16.7%
미 25
16.7%
터 25
16.7%
데 25
16.7%

Correlations

2023-12-12T12:10:11.136062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분행정동명
업종구분1.0000.141
행정동명0.1411.000
2023-12-12T12:10:11.238726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분행정동명
업종구분1.0000.122
행정동명0.1221.000
2023-12-12T12:10:11.343749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종구분행정동명
업종구분1.0000.122
행정동명0.1221.000

Missing values

2023-12-12T12:10:07.010322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:10:07.165124image/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

업종구분신고일자업소명행정동명주소전화번호
0숙박업(일반)1971-07-07오로라강경읍충청남도 논산시 강경읍 계백로133번길 3-33데이터 미집계
1숙박업(일반)1973-07-23향란여인숙강경읍충청남도 논산시 강경읍 계백로133번길 3-27데이터 미집계
2숙박업(일반)1973-11-03조화여인숙취암동충청남도 논산시 해월로125번길 19-2 (반월동)041-735-2829
3숙박업(일반)1974-02-14삼남여인숙취암동충청남도 논산시 해월로211번길 8-26 (화지동)041-735-3712
4숙박업(일반)1974-03-20청양여인숙취암동충청남도 논산시 해월로211번길 8-28 (화지동)041-733-3409
5숙박업(일반)1975-12-17목화장모텔취암동충청남도 논산시 해월로179번길 21-5 (화지동)데이터 미집계
6숙박업(일반)1977-08-04에덴여인숙강경읍충청남도 논산시 강경읍 계백로133번길 9-1데이터 미집계
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128숙박업(생활)2000-09-08잉스힐벌곡면충청남도 논산시 벌곡면 수락계곡2길 63-3041-733-2639
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