Overview

Dataset statistics

Number of variables9
Number of observations168
Missing cells56
Missing cells (%)3.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory73.8 B

Variable types

Categorical2
Text5
DateTime1
Numeric1

Dataset

Description충청남도 청양군 담배소매업 현황으로 사업장명, 인허가일자, 영업상태명, 소재지전화, 지번주소등으로 데이터를 나타내고 있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=430&beforeMenuCd=DOM_000000201001001000&publicdatapk=15029936

Alerts

서비스구분 has constant value ""Constant
영업상태명 has constant value ""Constant
소재지전화 has 26 (15.5%) missing valuesMissing
지번주소 has 13 (7.7%) missing valuesMissing
도로명주소 has 16 (9.5%) missing valuesMissing

Reproduction

Analysis started2024-01-09 21:22:26.158417
Analysis finished2024-01-09 21:22:26.835684
Duration0.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

서비스구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
담배소매업
168 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
담배소매업 168
100.0%

Length

2024-01-10T06:22:26.885008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:22:26.961422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
담배소매업 168
100.0%

사업장명
Text

Distinct145
Distinct (%)86.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-10T06:22:27.128150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length13
Mean length5.5119048
Min length2

Characters and Unicode

Total characters926
Distinct characters229
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

Unique140 ?
Unique (%)83.3%

Sample

1st row잡화
2nd row정유소
3rd row잡화
4th row대림슈퍼
5th row없음
ValueCountFrequency (%)
잡화 18
 
9.3%
없음 5
 
2.6%
씨유 4
 
2.1%
휴게소 3
 
1.6%
편의점 3
 
1.6%
세븐일레븐 2
 
1.0%
미래마트 2
 
1.0%
비봉주유소 2
 
1.0%
gs25 2
 
1.0%
사)한국고속도로휴게시설협회 2
 
1.0%
Other values (149) 150
77.7%
2024-01-10T06:22:27.411952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
퍼 28
 
3.0%
슈 27
 
2.9%
청 26
 
2.8%
점 26
 
2.8%
25
 
2.7%
화 24
 
2.6%
양 23
 
2.5%
소 21
 
2.3%
상 19
 
2.1%
마 19
 
2.1%
Other values (219) 688
74.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 860
92.9%
Space Separator 25
 
2.7%
Uppercase Letter 17
 
1.8%
Close Punctuation 8
 
0.9%
Open Punctuation 8
 
0.9%
Decimal Number 7
 
0.8%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
퍼 28
 
3.3%
슈 27
 
3.1%
청 26
 
3.0%
점 26
 
3.0%
화 24
 
2.8%
양 23
 
2.7%
소 21
 
2.4%
상 19
 
2.2%
마 19
 
2.2%
잡 19
 
2.2%
Other values (201) 628
73.0%
Uppercase Letter
ValueCountFrequency (%)
G 3
17.6%
S 3
17.6%
E 2
11.8%
U 2
11.8%
C 2
11.8%
O 2
11.8%
K 1
 
5.9%
A 1
 
5.9%
L 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
5 2
28.6%
2 2
28.6%
9 1
14.3%
3 1
14.3%
7 1
14.3%
Space Separator
ValueCountFrequency (%)
25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 860
92.9%
Common 49
 
5.3%
Latin 17
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
퍼 28
 
3.3%
슈 27
 
3.1%
청 26
 
3.0%
점 26
 
3.0%
화 24
 
2.8%
양 23
 
2.7%
소 21
 
2.4%
상 19
 
2.2%
마 19
 
2.2%
잡 19
 
2.2%
Other values (201) 628
73.0%
Common
ValueCountFrequency (%)
25
51.0%
) 8
 
16.3%
( 8
 
16.3%
5 2
 
4.1%
2 2
 
4.1%
9 1
 
2.0%
3 1
 
2.0%
- 1
 
2.0%
7 1
 
2.0%
Latin
ValueCountFrequency (%)
G 3
17.6%
S 3
17.6%
E 2
11.8%
U 2
11.8%
C 2
11.8%
O 2
11.8%
K 1
 
5.9%
A 1
 
5.9%
L 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 860
92.9%
ASCII 66
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
퍼 28
 
3.3%
슈 27
 
3.1%
청 26
 
3.0%
점 26
 
3.0%
화 24
 
2.8%
양 23
 
2.7%
소 21
 
2.4%
상 19
 
2.2%
마 19
 
2.2%
잡 19
 
2.2%
Other values (201) 628
73.0%
ASCII
ValueCountFrequency (%)
25
37.9%
) 8
 
12.1%
( 8
 
12.1%
G 3
 
4.5%
S 3
 
4.5%
E 2
 
3.0%
5 2
 
3.0%
2 2
 
3.0%
U 2
 
3.0%
C 2
 
3.0%
Other values (8) 9
 
13.6%

인허가일자
Date

Distinct143
Distinct (%)85.6%
Missing1
Missing (%)0.6%
Memory size1.4 KiB
Minimum1984-08-24 00:00:00
Maximum2020-05-26 00:00:00
2024-01-10T06:22:27.520513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:22:27.621343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
영업/정상
168 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 168
100.0%

Length

2024-01-10T06:22:27.715885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:22:27.792825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 168
100.0%

소재지전화
Text

MISSING 

Distinct135
Distinct (%)95.1%
Missing26
Missing (%)15.5%
Memory size1.4 KiB
2024-01-10T06:22:27.975940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.535211
Min length1

Characters and Unicode

Total characters1638
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique132 ?
Unique (%)93.0%

Sample

1st row041-942-8912
2nd row041-942-5413
3rd row041-942-5114
4th row041-943-3909
5th row042-942-7019
ValueCountFrequency (%)
02-2055-1951 2
 
1.5%
041-943-2826 2
 
1.5%
041-943-4467 1
 
0.7%
041-943-2896 1
 
0.7%
041-943-8884 1
 
0.7%
041-943-2627 1
 
0.7%
041-942-9999 1
 
0.7%
041-943-5681 1
 
0.7%
041-943-1465 1
 
0.7%
041-943-5587 1
 
0.7%
Other values (124) 124
91.2%
2024-01-10T06:22:28.273066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 341
20.8%
- 272
16.6%
0 206
12.6%
1 200
12.2%
9 181
11.1%
2 129
 
7.9%
3 99
 
6.0%
8 69
 
4.2%
5 47
 
2.9%
7 45
 
2.7%
Other values (2) 49
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1360
83.0%
Dash Punctuation 272
 
16.6%
Space Separator 6
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 341
25.1%
0 206
15.1%
1 200
14.7%
9 181
13.3%
2 129
 
9.5%
3 99
 
7.3%
8 69
 
5.1%
5 47
 
3.5%
7 45
 
3.3%
6 43
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 272
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1638
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 341
20.8%
- 272
16.6%
0 206
12.6%
1 200
12.2%
9 181
11.1%
2 129
 
7.9%
3 99
 
6.0%
8 69
 
4.2%
5 47
 
2.9%
7 45
 
2.7%
Other values (2) 49
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1638
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 341
20.8%
- 272
16.6%
0 206
12.6%
1 200
12.2%
9 181
11.1%
2 129
 
7.9%
3 99
 
6.0%
8 69
 
4.2%
5 47
 
2.9%
7 45
 
2.7%
Other values (2) 49
 
3.0%

지번주소
Text

MISSING 

Distinct154
Distinct (%)99.4%
Missing13
Missing (%)7.7%
Memory size1.4 KiB
2024-01-10T06:22:28.522738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length25.612903
Min length19

Characters and Unicode

Total characters3970
Distinct characters128
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)98.7%

Sample

1st row충청남도 청양군 운곡면 후덕리 373번지
2nd row충청남도 청양군 비봉면 용천리 21호
3rd row충청남도 청양군 비봉면 강정리 108호
4th row충청남도 청양군 청양읍 읍내리 116번지 9호
5th row충청남도 청양군 청양읍 읍내리 196-1번지
ValueCountFrequency (%)
충청남도 155
 
16.8%
청양군 155
 
16.8%
청양읍 66
 
7.2%
읍내리 48
 
5.2%
호 31
 
3.4%
정산면 17
 
1.8%
1호 13
 
1.4%
대치면 12
 
1.3%
장평면 11
 
1.2%
비봉면 11
 
1.2%
Other values (247) 403
43.7%
2024-01-10T06:22:28.892133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
929
23.4%
청 387
 
9.7%
양 230
 
5.8%
남 172
 
4.3%
충 156
 
3.9%
도 156
 
3.9%
군 156
 
3.9%
리 153
 
3.9%
지 138
 
3.5%
번 133
 
3.4%
Other values (118) 1360
34.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2443
61.5%
Space Separator 929
 
23.4%
Decimal Number 586
 
14.8%
Dash Punctuation 9
 
0.2%
Uppercase Letter 2
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 387
15.8%
양 230
 
9.4%
남 172
 
7.0%
충 156
 
6.4%
도 156
 
6.4%
군 156
 
6.4%
리 153
 
6.3%
지 138
 
5.6%
번 133
 
5.4%
호 121
 
5.0%
Other values (103) 641
26.2%
Decimal Number
ValueCountFrequency (%)
1 120
20.5%
2 85
14.5%
3 68
11.6%
7 56
9.6%
6 51
8.7%
4 51
8.7%
5 46
 
7.8%
0 42
 
7.2%
9 38
 
6.5%
8 29
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
929
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2443
61.5%
Common 1525
38.4%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 387
15.8%
양 230
 
9.4%
남 172
 
7.0%
충 156
 
6.4%
도 156
 
6.4%
군 156
 
6.4%
리 153
 
6.3%
지 138
 
5.6%
번 133
 
5.4%
호 121
 
5.0%
Other values (103) 641
26.2%
Common
ValueCountFrequency (%)
929
60.9%
1 120
 
7.9%
2 85
 
5.6%
3 68
 
4.5%
7 56
 
3.7%
6 51
 
3.3%
4 51
 
3.3%
5 46
 
3.0%
0 42
 
2.8%
9 38
 
2.5%
Other values (3) 39
 
2.6%
Latin
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2443
61.5%
ASCII 1527
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
929
60.8%
1 120
 
7.9%
2 85
 
5.6%
3 68
 
4.5%
7 56
 
3.7%
6 51
 
3.3%
4 51
 
3.3%
5 46
 
3.0%
0 42
 
2.8%
9 38
 
2.5%
Other values (5) 41
 
2.7%
Hangul
ValueCountFrequency (%)
청 387
15.8%
양 230
 
9.4%
남 172
 
7.0%
충 156
 
6.4%
도 156
 
6.4%
군 156
 
6.4%
리 153
 
6.3%
지 138
 
5.6%
번 133
 
5.4%
호 121
 
5.0%
Other values (103) 641
26.2%

도로명주소
Text

MISSING 

Distinct149
Distinct (%)98.0%
Missing16
Missing (%)9.5%
Memory size1.4 KiB
2024-01-10T06:22:29.169173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length21.934211
Min length18

Characters and Unicode

Total characters3334
Distinct characters139
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

Unique146 ?
Unique (%)96.1%

Sample

1st row충청남도 청양군 운곡면 청신로 579
2nd row충청남도 청양군 청양읍 중앙로열길 22
3rd row충청남도 청양군 청양읍 칠갑산로 225
4th row충청남도 청양군 장평면 미당큰길 54-1
5th row충청남도 청양군 청양읍 중앙로13길 9
ValueCountFrequency (%)
충청남도 152
19.5%
청양군 152
19.5%
청양읍 72
 
9.2%
정산면 19
 
2.4%
칠갑산로 15
 
1.9%
중앙로 13
 
1.7%
장평면 11
 
1.4%
충절로 10
 
1.3%
운곡면 9
 
1.2%
대치면 8
 
1.0%
Other values (210) 318
40.8%
2024-01-10T06:22:29.743155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
629
18.9%
청 397
 
11.9%
양 231
 
6.9%
충 169
 
5.1%
남 166
 
5.0%
도 155
 
4.6%
군 153
 
4.6%
1 121
 
3.6%
로 101
 
3.0%
면 80
 
2.4%
Other values (129) 1132
34.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2158
64.7%
Space Separator 629
 
18.9%
Decimal Number 482
 
14.5%
Dash Punctuation 45
 
1.3%
Other Punctuation 10
 
0.3%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 397
18.4%
양 231
10.7%
충 169
 
7.8%
남 166
 
7.7%
도 155
 
7.2%
군 153
 
7.1%
로 101
 
4.7%
면 80
 
3.7%
길 75
 
3.5%
읍 72
 
3.3%
Other values (112) 559
25.9%
Decimal Number
ValueCountFrequency (%)
1 121
25.1%
2 64
13.3%
7 47
 
9.8%
3 46
 
9.5%
5 44
 
9.1%
6 39
 
8.1%
4 33
 
6.8%
9 31
 
6.4%
0 30
 
6.2%
8 27
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
629
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 45
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2158
64.7%
Common 1174
35.2%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 397
18.4%
양 231
10.7%
충 169
 
7.8%
남 166
 
7.7%
도 155
 
7.2%
군 153
 
7.1%
로 101
 
4.7%
면 80
 
3.7%
길 75
 
3.5%
읍 72
 
3.3%
Other values (112) 559
25.9%
Common
ValueCountFrequency (%)
629
53.6%
1 121
 
10.3%
2 64
 
5.5%
7 47
 
4.0%
3 46
 
3.9%
- 45
 
3.8%
5 44
 
3.7%
6 39
 
3.3%
4 33
 
2.8%
9 31
 
2.6%
Other values (5) 75
 
6.4%
Latin
ValueCountFrequency (%)
G 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2158
64.7%
ASCII 1176
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
629
53.5%
1 121
 
10.3%
2 64
 
5.4%
7 47
 
4.0%
3 46
 
3.9%
- 45
 
3.8%
5 44
 
3.7%
6 39
 
3.3%
4 33
 
2.8%
9 31
 
2.6%
Other values (7) 77
 
6.5%
Hangul
ValueCountFrequency (%)
청 397
18.4%
양 231
10.7%
충 169
 
7.8%
남 166
 
7.7%
도 155
 
7.2%
군 153
 
7.1%
로 101
 
4.7%
면 80
 
3.7%
길 75
 
3.5%
읍 72
 
3.3%
Other values (112) 559
25.9%

위도
Text

Distinct165
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-10T06:22:29.966302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.744048
Min length9

Characters and Unicode

Total characters1805
Distinct characters12
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

Unique162 ?
Unique (%)96.4%

Sample

1st row36.49866922
2nd row36.48342298
3rd row36.51339655
4th row36.45155166
5th row36.45122223
ValueCountFrequency (%)
36.45186616 2
 
1.2%
36.44536678 2
 
1.2%
36.45032174 2
 
1.2%
36.34125366 1
 
0.6%
36.41167971 1
 
0.6%
36.50736374 1
 
0.6%
36.41172399 1
 
0.6%
36.49866922 1
 
0.6%
36.45029021 1
 
0.6%
36.44733187 1
 
0.6%
Other values (155) 155
92.3%
2024-01-10T06:22:30.309956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 323
17.9%
6 275
15.2%
4 243
13.5%
. 168
9.3%
5 154
8.5%
1 132
7.3%
2 114
 
6.3%
9 104
 
5.8%
7 102
 
5.7%
8 97
 
5.4%
Other values (2) 93
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1636
90.6%
Other Punctuation 169
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 323
19.7%
6 275
16.8%
4 243
14.9%
5 154
9.4%
1 132
8.1%
2 114
 
7.0%
9 104
 
6.4%
7 102
 
6.2%
8 97
 
5.9%
0 92
 
5.6%
Other Punctuation
ValueCountFrequency (%)
. 168
99.4%
, 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1805
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 323
17.9%
6 275
15.2%
4 243
13.5%
. 168
9.3%
5 154
8.5%
1 132
7.3%
2 114
 
6.3%
9 104
 
5.8%
7 102
 
5.7%
8 97
 
5.4%
Other values (2) 93
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1805
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 323
17.9%
6 275
15.2%
4 243
13.5%
. 168
9.3%
5 154
8.5%
1 132
7.3%
2 114
 
6.3%
9 104
 
5.8%
7 102
 
5.7%
8 97
 
5.4%
Other values (2) 93
 
5.2%

경도
Real number (ℝ)

Distinct165
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.84204
Minimum126.70184
Maximum127.01945
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-10T06:22:30.423813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.70184
5-th percentile126.76508
Q1126.8011
median126.80466
Q3126.89318
95-th percentile126.96079
Maximum127.01945
Range0.317612
Interquartile range (IQR)0.092082375

Descriptive statistics

Standard deviation0.07040121
Coefficient of variation (CV)0.00055503057
Kurtosis-0.36624173
Mean126.84204
Median Absolute Deviation (MAD)0.02662815
Skewness0.72783402
Sum21309.463
Variance0.0049563303
MonotonicityNot monotonic
2024-01-10T06:22:30.534829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8029749 2
 
1.2%
126.8027957 2
 
1.2%
126.8044376 2
 
1.2%
126.8334757 1
 
0.6%
126.8010478 1
 
0.6%
126.8050395 1
 
0.6%
126.8023415 1
 
0.6%
126.7997942 1
 
0.6%
126.8020003 1
 
0.6%
126.9503746 1
 
0.6%
Other values (155) 155
92.3%
ValueCountFrequency (%)
126.701836 1
0.6%
126.7049174 1
0.6%
126.7148649 1
0.6%
126.7152248 1
0.6%
126.7214854 1
0.6%
126.7355361 1
0.6%
126.7366184 1
0.6%
126.7553567 1
0.6%
126.762028 1
0.6%
126.7707518 1
0.6%
ValueCountFrequency (%)
127.019448 1
0.6%
127.0083918 1
0.6%
127.0081651 1
0.6%
127.0021842 1
0.6%
126.9927387 1
0.6%
126.987627 1
0.6%
126.9831037 1
0.6%
126.9769444 1
0.6%
126.9636416 1
0.6%
126.9554942 1
0.6%

Interactions

2024-01-10T06:22:26.496313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-01-10T06:22:26.590319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:22:26.704465image/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.
2024-01-10T06:22:26.789217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

서비스구분사업장명인허가일자영업상태명소재지전화지번주소도로명주소위도경도
0담배소매업잡화1985-06-30영업/정상041-942-8912충청남도 청양군 운곡면 후덕리 373번지충청남도 청양군 운곡면 청신로 57936.49866922126.833476
1담배소매업정유소1985-06-30영업/정상041-942-5413충청남도 청양군 비봉면 용천리 21호<NA>36.48342298126.770752
2담배소매업잡화1985-06-30영업/정상041-942-5114충청남도 청양군 비봉면 강정리 108호<NA>36.51339655126.777803
3담배소매업대림슈퍼1985-08-27영업/정상041-943-3909충청남도 청양군 청양읍 읍내리 116번지 9호충청남도 청양군 청양읍 중앙로열길 2236.45155166126.805768
4담배소매업없음2002-04-17영업/정상<NA>충청남도 청양군 청양읍 읍내리 196-1번지충청남도 청양군 청양읍 칠갑산로 22536.45122223126.801668
5담배소매업미당우슈퍼2002-12-17영업/정상042-942-7019충청남도 청양군 장평면 미당리 25번지 1호충청남도 청양군 장평면 미당큰길 54-136.37243194126.934164
6담배소매업성보OA상사2003-01-24영업/정상041-943-7171충청남도 청양군 청양읍 읍내리 220-19번지충청남도 청양군 청양읍 중앙로13길 936.45321926126.802207
7담배소매업CU청양점2014-11-25영업/정상<NA><NA>충청남도 청양군 청양읍 칠갑산로 21736.451677126.800699
8담배소매업미당휴게소2015-05-06영업/정상<NA>충청남도 청양군 장평면 미당리 15번지 1호충청남도 청양군 장평면 충의로 91736.37211648126.936185
9담배소매업하머니마트2015-05-13영업/정상041-943-9858충청남도 청양군 정산면 서정리 547번지 5호충청남도 청양군 정산면 정현길 7236.41071857126.949797
서비스구분사업장명인허가일자영업상태명소재지전화지번주소도로명주소위도경도
158담배소매업잡화1998-10-16영업/정상041-943-7688충청남도 청양군 청양읍 읍내리 124호충청남도 청양군 청양읍 칠갑산로9길 2136.45258031126.805898
159담배소매업대치농협협동조합1998-11-07영업/정상041-943-3610충청남도 청양군 대치면 주정리 286번지 2 호<NA>36.44632834126.827979
160담배소매업정산농협목면지소1998-12-02영업/정상041-942-9681충청남도 청양군 목면 안심리 262번지충청남도 청양군 목면 안심길 16236.42271831127.008392
161담배소매업천강슈퍼1998-12-04영업/정상041-944-0252충청남도 청양군 청양읍 읍내리 377번지 5호충청남도 청양군 청양읍 청산로 2936.44536678126.802796
162담배소매업일광슈퍼1987-03-19영업/정상041-943-2982충청남도 청양군 청양읍 읍내리 271번지 5호 2통충청남도 청양군 청양읍 중앙로 18036.45565196126.803954
163담배소매업정산농협연쇄점1998-04-13영업/정상041-942-0034충청남도 청양군 정산면 서정리 156번지 14 호충청남도 청양군 정산면 정현길 5536.41167971126.948413
164담배소매업정산농협장평지소1998-06-23영업/정상041-942-6681충청남도 청양군 장평면 분향리 397번지 4호충청남도 청양군 장평면 닭우리고개길 30-736.34125366126.893873
165담배소매업청남정류소2009-12-23영업/정상041-942-7072충청남도 청양군 청남면 청소리 208번지 4호충청남도 청양군 청남면 명덕로 19536.35355885126.952347
166담배소매업농암슈퍼2010-03-08영업/정상041-942-4141충청남도 청양군 화성면 농암리 38번지<NA>36.44102794126.721485
167담배소매업현대예식장2003-04-09영업/정상041-943-5345충청남도 청양군 청양읍 읍내리 170번지 4 호충청남도 청양군 청양읍 중앙로6길 1136.44982371126.8042