Overview

Dataset statistics

Number of variables12
Number of observations21
Missing cells22
Missing cells (%)8.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory106.3 B

Variable types

Categorical3
Numeric4
Text5

Dataset

Description김해시 기타위생용품제조업 현황 자료로 업종명,사업장명,소재지전화,도로명전체주소,지번전체주소 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15033391

Alerts

업종명 has constant value ""Constant
상태 has constant value ""Constant
소재지전화 has 11 (52.4%) missing valuesMissing
영업자 has 3 (14.3%) missing valuesMissing
영업장면적 has 8 (38.1%) missing valuesMissing
인허가번호 has unique valuesUnique
사업장명 has unique valuesUnique
소재지전체주소 has unique valuesUnique
도로명전체주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
영업장면적 has 2 (9.5%) zerosZeros

Reproduction

Analysis started2023-12-10 23:02:38.770033
Analysis finished2023-12-10 23:02:41.236452
Duration2.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
위생용품제조업
21 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
위생용품제조업 21
100.0%

Length

2023-12-11T08:02:41.313098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:41.427497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위생용품제조업 21
100.0%

인허가번호
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0107702 × 1010
Minimum1.9829607 × 1010
Maximum2.0209607 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T08:02:41.555174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9829607 × 1010
5-th percentile1.9939607 × 1010
Q12.0019607 × 1010
median2.0159607 × 1010
Q32.0199607 × 1010
95-th percentile2.0209607 × 1010
Maximum2.0209607 × 1010
Range3.8 × 108
Interquartile range (IQR)1.8 × 108

Descriptive statistics

Standard deviation1.1120337 × 108
Coefficient of variation (CV)0.005530387
Kurtosis0.24869832
Mean2.0107702 × 1010
Median Absolute Deviation (MAD)50000000
Skewness-1.0486536
Sum4.2226175 × 1011
Variance1.236619 × 1016
MonotonicityNot monotonic
2023-12-11T08:02:41.678857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
19829607001 1
 
4.8%
20019607002 1
 
4.8%
19939607002 1
 
4.8%
20009607001 1
 
4.8%
20109607003 1
 
4.8%
20189607001 1
 
4.8%
20189607002 1
 
4.8%
20039607001 1
 
4.8%
19939607003 1
 
4.8%
20209607001 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
19829607001 1
4.8%
19939607002 1
4.8%
19939607003 1
4.8%
20009607001 1
4.8%
20019607002 1
4.8%
20019607004 1
4.8%
20039607001 1
4.8%
20099607001 1
4.8%
20109607003 1
4.8%
20129607001 1
4.8%
ValueCountFrequency (%)
20209607003 1
4.8%
20209607002 1
4.8%
20209607001 1
4.8%
20199607003 1
4.8%
20199607002 1
4.8%
20199607001 1
4.8%
20189607003 1
4.8%
20189607002 1
4.8%
20189607001 1
4.8%
20169607001 1
4.8%

사업장명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T08:02:41.871510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6
Min length2

Characters and Unicode

Total characters126
Distinct characters69
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

Unique21 ?
Unique (%)100.0%

Sample

1st row동림산업
2nd rowS. G(에스.지)
3rd row유광
4th row팔도산업
5th row주식회사 홍여사세정제
ValueCountFrequency (%)
주식회사 2
 
8.3%
동림산업 1
 
4.2%
경성크린텍 1
 
4.2%
그린풀 1
 
4.2%
유림코리아 1
 
4.2%
주)창전산업 1
 
4.2%
주)백양산업 1
 
4.2%
에버그린 1
 
4.2%
세광지기산업 1
 
4.2%
동심 1
 
4.2%
Other values (13) 13
54.2%
2023-12-11T08:02:42.207057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 7
 
5.6%
업 7
 
5.6%
주 5
 
4.0%
) 5
 
4.0%
( 5
 
4.0%
사 4
 
3.2%
아 4
 
3.2%
지 4
 
3.2%
이 3
 
2.4%
세 3
 
2.4%
Other values (59) 79
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
86.5%
Close Punctuation 5
 
4.0%
Open Punctuation 5
 
4.0%
Space Separator 3
 
2.4%
Other Punctuation 2
 
1.6%
Uppercase Letter 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 7
 
6.4%
업 7
 
6.4%
주 5
 
4.6%
사 4
 
3.7%
아 4
 
3.7%
지 4
 
3.7%
이 3
 
2.8%
세 3
 
2.8%
성 3
 
2.8%
회 3
 
2.8%
Other values (53) 66
60.6%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
86.5%
Common 15
 
11.9%
Latin 2
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 7
 
6.4%
업 7
 
6.4%
주 5
 
4.6%
사 4
 
3.7%
아 4
 
3.7%
지 4
 
3.7%
이 3
 
2.8%
세 3
 
2.8%
성 3
 
2.8%
회 3
 
2.8%
Other values (53) 66
60.6%
Common
ValueCountFrequency (%)
) 5
33.3%
( 5
33.3%
3
20.0%
. 2
 
13.3%
Latin
ValueCountFrequency (%)
S 1
50.0%
G 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
86.5%
ASCII 17
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 7
 
6.4%
업 7
 
6.4%
주 5
 
4.6%
사 4
 
3.7%
아 4
 
3.7%
지 4
 
3.7%
이 3
 
2.8%
세 3
 
2.8%
성 3
 
2.8%
회 3
 
2.8%
Other values (53) 66
60.6%
ASCII
ValueCountFrequency (%)
) 5
29.4%
( 5
29.4%
3
17.6%
. 2
 
11.8%
S 1
 
5.9%
G 1
 
5.9%

소재지전화
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing11
Missing (%)52.4%
Memory size300.0 B
2023-12-11T08:02:42.399317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.1
Min length12

Characters and Unicode

Total characters121
Distinct characters10
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

Unique10 ?
Unique (%)100.0%

Sample

1st row055-343-0407
2nd row055-323-8480
3rd row055-343-2211
4th row055-331-0008
5th row055-322-8730
ValueCountFrequency (%)
055-343-0407 1
10.0%
055-323-8480 1
10.0%
055-343-2211 1
10.0%
055-331-0008 1
10.0%
055-322-8730 1
10.0%
055-325-2223 1
10.0%
055-346-5308 1
10.0%
070-4352-6582 1
10.0%
055-337-0201 1
10.0%
055-328-1428 1
10.0%
2023-12-11T08:02:42.730592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 22
18.2%
0 21
17.4%
- 20
16.5%
3 18
14.9%
2 14
11.6%
8 8
 
6.6%
4 7
 
5.8%
1 5
 
4.1%
7 4
 
3.3%
6 2
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
83.5%
Dash Punctuation 20
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 22
21.8%
0 21
20.8%
3 18
17.8%
2 14
13.9%
8 8
 
7.9%
4 7
 
6.9%
1 5
 
5.0%
7 4
 
4.0%
6 2
 
2.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 121
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 22
18.2%
0 21
17.4%
- 20
16.5%
3 18
14.9%
2 14
11.6%
8 8
 
6.6%
4 7
 
5.8%
1 5
 
4.1%
7 4
 
3.3%
6 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 121
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 22
18.2%
0 21
17.4%
- 20
16.5%
3 18
14.9%
2 14
11.6%
8 8
 
6.6%
4 7
 
5.8%
1 5
 
4.1%
7 4
 
3.3%
6 2
 
1.7%

영업자
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing3
Missing (%)14.3%
Memory size300.0 B
2023-12-11T08:02:42.956059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters54
Distinct characters39
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row손봉길
2nd row김준기
3rd row고영란
4th row유청연
5th row조윤기
ValueCountFrequency (%)
김준기 1
 
5.6%
고영란 1
 
5.6%
엄*숙 1
 
5.6%
정*현 1
 
5.6%
김*창 1
 
5.6%
장*영 1
 
5.6%
장선훈 1
 
5.6%
박해경 1
 
5.6%
이신자 1
 
5.6%
손봉길 1
 
5.6%
Other values (8) 8
44.4%
2023-12-11T08:02:43.288528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 5
 
9.3%
김 3
 
5.6%
연 2
 
3.7%
정 2
 
3.7%
숙 2
 
3.7%
경 2
 
3.7%
이 2
 
3.7%
장 2
 
3.7%
신 2
 
3.7%
영 2
 
3.7%
Other values (29) 30
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49
90.7%
Other Punctuation 5
 
9.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 3
 
6.1%
연 2
 
4.1%
정 2
 
4.1%
숙 2
 
4.1%
경 2
 
4.1%
이 2
 
4.1%
장 2
 
4.1%
신 2
 
4.1%
영 2
 
4.1%
기 2
 
4.1%
Other values (28) 28
57.1%
Other Punctuation
ValueCountFrequency (%)
* 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49
90.7%
Common 5
 
9.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 3
 
6.1%
연 2
 
4.1%
정 2
 
4.1%
숙 2
 
4.1%
경 2
 
4.1%
이 2
 
4.1%
장 2
 
4.1%
신 2
 
4.1%
영 2
 
4.1%
기 2
 
4.1%
Other values (28) 28
57.1%
Common
ValueCountFrequency (%)
* 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49
90.7%
ASCII 5
 
9.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 5
100.0%
Hangul
ValueCountFrequency (%)
김 3
 
6.1%
연 2
 
4.1%
정 2
 
4.1%
숙 2
 
4.1%
경 2
 
4.1%
이 2
 
4.1%
장 2
 
4.1%
신 2
 
4.1%
영 2
 
4.1%
기 2
 
4.1%
Other values (28) 28
57.1%

소재지전체주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T08:02:43.526686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length22
Min length18

Characters and Unicode

Total characters462
Distinct characters58
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

Unique21 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 한림면 신천리 195-7
2nd row경상남도 김해시 주촌면 내삼리 985-21, A동
3rd row경상남도 김해시 진영읍 의전리 344-9
4th row경상남도 김해시 진영읍 내룡리 328
5th row경상남도 김해시 삼문동 572-6 1층
ValueCountFrequency (%)
경상남도 21
19.4%
김해시 21
19.4%
1층 7
 
6.5%
진영읍 5
 
4.6%
주촌면 3
 
2.8%
상동면 2
 
1.9%
한림면 2
 
1.9%
부곡동 2
 
1.9%
a동 2
 
1.9%
어방동 1
 
0.9%
Other values (42) 42
38.9%
2023-12-11T08:02:43.884842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
18.8%
1 24
 
5.2%
상 23
 
5.0%
경 21
 
4.5%
남 21
 
4.5%
도 21
 
4.5%
김 21
 
4.5%
해 21
 
4.5%
시 21
 
4.5%
- 17
 
3.7%
Other values (48) 185
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 258
55.8%
Decimal Number 96
 
20.8%
Space Separator 87
 
18.8%
Dash Punctuation 17
 
3.7%
Other Punctuation 2
 
0.4%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 23
 
8.9%
경 21
 
8.1%
남 21
 
8.1%
도 21
 
8.1%
김 21
 
8.1%
해 21
 
8.1%
시 21
 
8.1%
동 14
 
5.4%
리 13
 
5.0%
면 8
 
3.1%
Other values (34) 74
28.7%
Decimal Number
ValueCountFrequency (%)
1 24
25.0%
2 12
12.5%
6 11
11.5%
4 8
 
8.3%
9 8
 
8.3%
0 8
 
8.3%
5 7
 
7.3%
7 7
 
7.3%
3 7
 
7.3%
8 4
 
4.2%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 258
55.8%
Common 202
43.7%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 23
 
8.9%
경 21
 
8.1%
남 21
 
8.1%
도 21
 
8.1%
김 21
 
8.1%
해 21
 
8.1%
시 21
 
8.1%
동 14
 
5.4%
리 13
 
5.0%
면 8
 
3.1%
Other values (34) 74
28.7%
Common
ValueCountFrequency (%)
87
43.1%
1 24
 
11.9%
- 17
 
8.4%
2 12
 
5.9%
6 11
 
5.4%
4 8
 
4.0%
9 8
 
4.0%
0 8
 
4.0%
5 7
 
3.5%
7 7
 
3.5%
Other values (3) 13
 
6.4%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 258
55.8%
ASCII 204
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
42.6%
1 24
 
11.8%
- 17
 
8.3%
2 12
 
5.9%
6 11
 
5.4%
4 8
 
3.9%
9 8
 
3.9%
0 8
 
3.9%
5 7
 
3.4%
7 7
 
3.4%
Other values (4) 15
 
7.4%
Hangul
ValueCountFrequency (%)
상 23
 
8.9%
경 21
 
8.1%
남 21
 
8.1%
도 21
 
8.1%
김 21
 
8.1%
해 21
 
8.1%
시 21
 
8.1%
동 14
 
5.4%
리 13
 
5.0%
면 8
 
3.1%
Other values (34) 74
28.7%

도로명전체주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T08:02:44.121025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length26.666667
Min length20

Characters and Unicode

Total characters560
Distinct characters60
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

Unique21 ?
Unique (%)100.0%

Sample

1st row경상남도 김해시 한림면 김해대로1559번길 22
2nd row경상남도 김해시 주촌면 서부로1541번길 87-1, A동
3rd row경상남도 김해시 진영읍 서부로396번길 20-19
4th row경상남도 김해시 진영읍 진영로454번길 85
5th row경상남도 김해시 삼문로43번길 4-18, 1층 (삼문동)
ValueCountFrequency (%)
경상남도 21
18.8%
김해시 21
18.8%
1층 6
 
5.4%
진영읍 5
 
4.5%
주촌면 3
 
2.7%
장유로149번길 2
 
1.8%
상동면 2
 
1.8%
a동 2
 
1.8%
한림면 2
 
1.8%
22 2
 
1.8%
Other values (46) 46
41.1%
2023-12-11T08:02:44.487453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
16.2%
1 32
 
5.7%
김 23
 
4.1%
해 23
 
4.1%
상 23
 
4.1%
경 21
 
3.8%
남 21
 
3.8%
도 21
 
3.8%
시 21
 
3.8%
로 21
 
3.8%
Other values (50) 263
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
55.2%
Decimal Number 127
22.7%
Space Separator 91
 
16.2%
Dash Punctuation 12
 
2.1%
Other Punctuation 9
 
1.6%
Open Punctuation 5
 
0.9%
Close Punctuation 5
 
0.9%
Uppercase Letter 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 23
 
7.4%
해 23
 
7.4%
상 23
 
7.4%
경 21
 
6.8%
남 21
 
6.8%
도 21
 
6.8%
시 21
 
6.8%
로 21
 
6.8%
번 16
 
5.2%
길 16
 
5.2%
Other values (34) 103
33.3%
Decimal Number
ValueCountFrequency (%)
1 32
25.2%
2 19
15.0%
3 17
13.4%
4 15
11.8%
5 11
 
8.7%
8 10
 
7.9%
9 9
 
7.1%
7 7
 
5.5%
6 5
 
3.9%
0 2
 
1.6%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
55.2%
Common 249
44.5%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 23
 
7.4%
해 23
 
7.4%
상 23
 
7.4%
경 21
 
6.8%
남 21
 
6.8%
도 21
 
6.8%
시 21
 
6.8%
로 21
 
6.8%
번 16
 
5.2%
길 16
 
5.2%
Other values (34) 103
33.3%
Common
ValueCountFrequency (%)
91
36.5%
1 32
 
12.9%
2 19
 
7.6%
3 17
 
6.8%
4 15
 
6.0%
- 12
 
4.8%
5 11
 
4.4%
8 10
 
4.0%
, 9
 
3.6%
9 9
 
3.6%
Other values (5) 24
 
9.6%
Latin
ValueCountFrequency (%)
A 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
55.2%
ASCII 251
44.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
36.3%
1 32
 
12.7%
2 19
 
7.6%
3 17
 
6.8%
4 15
 
6.0%
- 12
 
4.8%
5 11
 
4.4%
8 10
 
4.0%
, 9
 
3.6%
9 9
 
3.6%
Other values (6) 26
 
10.4%
Hangul
ValueCountFrequency (%)
김 23
 
7.4%
해 23
 
7.4%
상 23
 
7.4%
경 21
 
6.8%
남 21
 
6.8%
도 21
 
6.8%
시 21
 
6.8%
로 21
 
6.8%
번 16
 
5.2%
길 16
 
5.2%
Other values (34) 103
33.3%

위도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.254439
Minimum35.193432
Maximum35.323308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T08:02:44.640773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.193432
5-th percentile35.19387
Q135.229161
median35.253257
Q335.291141
95-th percentile35.312829
Maximum35.323308
Range0.12987637
Interquartile range (IQR)0.06198004

Descriptive statistics

Standard deviation0.040461417
Coefficient of variation (CV)0.0011476971
Kurtosis-1.1941563
Mean35.254439
Median Absolute Deviation (MAD)0.03788458
Skewness0.087292806
Sum740.34322
Variance0.0016371262
MonotonicityNot monotonic
2023-12-11T08:02:44.770928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
35.27700563 1
 
4.8%
35.23636255 1
 
4.8%
35.211067 1
 
4.8%
35.22916106 1
 
4.8%
35.312829 1
 
4.8%
35.2911411 1
 
4.8%
35.29809934 1
 
4.8%
35.25325652 1
 
4.8%
35.21072647 1
 
4.8%
35.19343212 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
35.19343212 1
4.8%
35.1938696 1
4.8%
35.20492878 1
4.8%
35.21072647 1
4.8%
35.211067 1
4.8%
35.22916106 1
4.8%
35.23197385 1
4.8%
35.23472751 1
4.8%
35.23514896 1
4.8%
35.23636255 1
4.8%
ValueCountFrequency (%)
35.32330849 1
4.8%
35.312829 1
4.8%
35.3078348 1
4.8%
35.29809934 1
4.8%
35.29269474 1
4.8%
35.2911411 1
4.8%
35.27700563 1
4.8%
35.27341346 1
4.8%
35.26876172 1
4.8%
35.26347721 1
4.8%

경도
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.82539
Minimum128.71824
Maximum128.95745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T08:02:44.885638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.71824
5-th percentile128.75225
Q1128.76252
median128.81423
Q3128.85004
95-th percentile128.92208
Maximum128.95745
Range0.2392145
Interquartile range (IQR)0.0875181

Descriptive statistics

Standard deviation0.065698189
Coefficient of variation (CV)0.00050997859
Kurtosis-0.6452691
Mean128.82539
Median Absolute Deviation (MAD)0.0517079
Skewness0.40886375
Sum2705.3331
Variance0.004316252
MonotonicityNot monotonic
2023-12-11T08:02:45.003638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
128.8433693 1
 
4.8%
128.8142278 1
 
4.8%
128.8047784 1
 
4.8%
128.8366379 1
 
4.8%
128.7572404 1
 
4.8%
128.9138265 1
 
4.8%
128.8146233 1
 
4.8%
128.907737 1
 
4.8%
128.8040576 1
 
4.8%
128.8411927 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
128.7182367 1
4.8%
128.7522537 1
4.8%
128.7542924 1
4.8%
128.7556082 1
4.8%
128.7572404 1
4.8%
128.7625199 1
4.8%
128.8040576 1
4.8%
128.8047784 1
4.8%
128.806022 1
4.8%
128.8105515 1
4.8%
ValueCountFrequency (%)
128.9574512 1
4.8%
128.9220767 1
4.8%
128.9138265 1
4.8%
128.907737 1
4.8%
128.9063816 1
4.8%
128.850038 1
4.8%
128.8433693 1
4.8%
128.8411927 1
4.8%
128.8366379 1
4.8%
128.8146233 1
4.8%

상태
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
정좌표
21 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정좌표 21
100.0%

Length

2023-12-11T08:02:45.117450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:45.461056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정좌표 21
100.0%

영업장면적
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)92.3%
Missing8
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean196.95846
Minimum0
Maximum497.98
Zeros2
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T08:02:45.555194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q158.72
median142.08
Q3334.4
95-th percentile468.328
Maximum497.98
Range497.98
Interquartile range (IQR)275.68

Descriptive statistics

Standard deviation180.12181
Coefficient of variation (CV)0.91451673
Kurtosis-1.4218153
Mean196.95846
Median Absolute Deviation (MAD)142.08
Skewness0.48260776
Sum2560.46
Variance32443.866
MonotonicityNot monotonic
2023-12-11T08:02:45.671292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 2
 
9.5%
448.56 1
 
4.8%
70.0 1
 
4.8%
497.98 1
 
4.8%
142.08 1
 
4.8%
58.72 1
 
4.8%
334.4 1
 
4.8%
323.4 1
 
4.8%
28.59 1
 
4.8%
396.0 1
 
4.8%
Other values (2) 2
 
9.5%
(Missing) 8
38.1%
ValueCountFrequency (%)
0.0 2
9.5%
28.59 1
4.8%
58.72 1
4.8%
67.63 1
4.8%
70.0 1
4.8%
142.08 1
4.8%
193.1 1
4.8%
323.4 1
4.8%
334.4 1
4.8%
396.0 1
4.8%
ValueCountFrequency (%)
497.98 1
4.8%
448.56 1
4.8%
396.0 1
4.8%
334.4 1
4.8%
323.4 1
4.8%
193.1 1
4.8%
142.08 1
4.8%
70.0 1
4.8%
67.63 1
4.8%
58.72 1
4.8%

영업상태
Categorical

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
정상
11 
폐업(자진)
5 
폐업
3 
휴업
 
1
폐업(기타)
 
1

Length

Max length6
Median length2
Mean length3.1428571
Min length2

Unique

Unique2 ?
Unique (%)9.5%

Sample

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

Common Values

ValueCountFrequency (%)
정상 11
52.4%
폐업(자진) 5
23.8%
폐업 3
 
14.3%
휴업 1
 
4.8%
폐업(기타) 1
 
4.8%

Length

2023-12-11T08:02:45.824517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:02:45.948692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 11
52.4%
폐업(자진 5
23.8%
폐업 3
 
14.3%
휴업 1
 
4.8%
폐업(기타 1
 
4.8%

Interactions

2023-12-11T08:02:40.413421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.223917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.645048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.061484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.506618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.322418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.777372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.140020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.601768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.430617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.879355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.244673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.686435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.546570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:39.978689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:02:40.326115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T08:02:46.056714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호사업장명소재지전화영업자소재지전체주소도로명전체주소위도경도영업장면적영업상태
인허가번호1.0001.0001.0001.0001.0001.0000.7560.7630.0000.000
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
영업자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지전체주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명전체주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도0.7561.0001.0001.0001.0001.0001.0000.5260.5940.782
경도0.7631.0001.0001.0001.0001.0000.5261.0000.6040.000
영업장면적0.0001.0001.0001.0001.0001.0000.5940.6041.0000.000
영업상태0.0001.0001.0001.0001.0001.0000.7820.0000.0001.000
2023-12-11T08:02:46.184695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가번호위도경도영업장면적영업상태
인허가번호1.0000.1910.1160.2040.000
위도0.1911.000-0.1690.2860.332
경도0.116-0.1691.000-0.2310.000
영업장면적0.2040.286-0.2311.0000.000
영업상태0.0000.3320.0000.0001.000

Missing values

2023-12-11T08:02:40.822405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T08:02:41.015702image/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.
2023-12-11T08:02:41.151660image/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

업종명인허가번호사업장명소재지전화영업자소재지전체주소도로명전체주소위도경도상태영업장면적영업상태
0위생용품제조업19829607001동림산업055-343-0407손봉길경상남도 김해시 한림면 신천리 195-7경상남도 김해시 한림면 김해대로1559번길 2235.277006128.843369정좌표0.0정상
1위생용품제조업20019607002S. G(에스.지)055-323-8480김준기경상남도 김해시 주촌면 내삼리 985-21, A동경상남도 김해시 주촌면 서부로1541번길 87-1, A동35.236363128.814228정좌표448.56정상
2위생용품제조업20099607001유광<NA>고영란경상남도 김해시 진영읍 의전리 344-9경상남도 김해시 진영읍 서부로396번길 20-1935.268762128.752254정좌표70.0정상
3위생용품제조업20129607001팔도산업055-343-2211유청연경상남도 김해시 진영읍 내룡리 328경상남도 김해시 진영읍 진영로454번길 8535.292695128.754292정좌표497.98정상
4위생용품제조업20159607001주식회사 홍여사세정제055-331-0008조윤기경상남도 김해시 삼문동 572-6 1층경상남도 김해시 삼문로43번길 4-18, 1층 (삼문동)35.19387128.806022정좌표142.08정상
5위생용품제조업20169607001태왕애드컴055-322-8730신대철경상남도 김해시 화목동 971-2 1층경상남도 김해시 칠산로179번길 233, 1층 (화목동)35.204929128.850038정좌표58.72정상
6위생용품제조업20189607003화이트페이퍼055-325-2223이경숙경상남도 김해시 주촌면 덕암리 694경상남도 김해시 주촌면 서부로1637번길 44235.263477128.810552정좌표334.4정상
7위생용품제조업20199607001주식회사 승우비엔에스055-346-5308정승원경상남도 김해시 진영읍 진영리 730 2동 1,2층경상남도 김해시 진영읍 진산대로 235, 2동 1,2층35.323308128.718237정좌표323.4정상
8위생용품제조업20199607002(주)아이온070-4352-6582권소연경상남도 김해시 진영읍 죽곡리 693-5 1층경상남도 김해시 진영읍 서부로 283-8, 1층35.273413128.76252정좌표28.59정상
9위생용품제조업20209607002삼성테크하나055-337-0201김문호경상남도 김해시 상동면 매리 511-6 1층경상남도 김해시 상동면 동북로473번길 132, 1층35.307835128.957451정좌표396.0정상
업종명인허가번호사업장명소재지전화영업자소재지전체주소도로명전체주소위도경도상태영업장면적영업상태
11위생용품제조업20019607004청아산업055-328-1428이신자경상남도 김해시 어방동 1065-16경상남도 김해시 김해대로2553번길 38-14 (어방동)35.231974128.906382정좌표0.0폐업
12위생용품제조업20199607003세아(사회복지법인해윤)<NA>박해경경상남도 김해시 진례면 초전리 908-20 1층경상남도 김해시 진례면 진례로 58-2, 1층35.234728128.755608정좌표67.63휴업
13위생용품제조업20209607001동심<NA>장선훈경상남도 김해시 이동 114-12 1층경상남도 김해시 칠산로197번길 12-15, 1층 (이동)35.193432128.841193정좌표193.1폐업
14위생용품제조업19939607003세광지기산업<NA><NA>경상남도 김해시 부곡동 705-1경상남도 김해시 장유로149번길 14-735.210726128.804058정좌표<NA>폐업(자진)
15위생용품제조업20039607001에버그린<NA><NA>경상남도 김해시 삼방동 644-1경상남도 김해시 삼안로292번길 2235.253257128.907737정좌표<NA>폐업(자진)
16위생용품제조업20189607002(주)백양산업<NA>장*영경상남도 김해시 한림면 명동리 467-1경상남도 김해시 한림면 명동로4번길 3735.298099128.814623정좌표<NA>폐업(기타)
17위생용품제조업20189607001(주)창전산업<NA>김*창경상남도 김해시 상동면 묵방리 302 A동경상남도 김해시 상동면 묵방로 10-21 A동35.291141128.913826정좌표<NA>폐업(자진)
18위생용품제조업20109607003유림코리아<NA>정*현경상남도 김해시 진영읍 본산리 314-6경상남도 김해시 진영읍 본산2로 11535.312829128.75724정좌표<NA>폐업(자진)
19위생용품제조업20009607001그린풀<NA>엄*숙경상남도 김해시 주촌면 천곡리 1086-2경상남도 김해시 주촌면 서부로1638번길 133-3435.229161128.836638정좌표<NA>폐업
20위생용품제조업19939607002성진지기산업<NA>서*수경상남도 김해시 부곡동 706-1경상남도 김해시 장유로149번길 16-3435.211067128.804778정좌표<NA>폐업(자진)