Overview

Dataset statistics

Number of variables12
Number of observations24
Missing cells5
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory105.5 B

Variable types

Text4
Numeric4
Categorical3
Boolean1

Dataset

Description공중이용시설(공연장) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=GCJHPFN1ABDLV192J7KJ13727403&infSeq=1

Alerts

다중이용업소여부 has constant value ""Constant
위생업종명 is highly overall correlated with 인허가일자 and 5 other fieldsHigh correlation
영업상태명 is highly overall correlated with 인허가일자 and 2 other fieldsHigh correlation
위생업태명 is highly overall correlated with 인허가일자 and 5 other fieldsHigh correlation
인허가일자 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 인허가일자 and 3 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
영업상태명 is highly imbalanced (75.0%)Imbalance
위생업종명 is highly imbalanced (75.0%)Imbalance
위생업태명 is highly imbalanced (75.0%)Imbalance
다중이용업소여부 has 1 (4.2%) missing valuesMissing
소재지도로명주소 has 2 (8.3%) missing valuesMissing
WGS84위도 has 1 (4.2%) missing valuesMissing
WGS84경도 has 1 (4.2%) missing valuesMissing
사업장명 has unique valuesUnique
소재지지번주소 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:21:50.809031
Analysis finished2023-12-10 22:21:52.908370
Duration2.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

Distinct13
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T07:21:52.981853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.3333333
Min length3

Characters and Unicode

Total characters80
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)37.5%

Sample

1st row과천시
2nd row광주시
3rd row구리시
4th row군포시
5th row부천시
ValueCountFrequency (%)
의정부시 8
33.3%
안산시 3
 
12.5%
성남시 2
 
8.3%
수원시 2
 
8.3%
과천시 1
 
4.2%
광주시 1
 
4.2%
구리시 1
 
4.2%
군포시 1
 
4.2%
부천시 1
 
4.2%
안양시 1
 
4.2%
Other values (3) 3
 
12.5%
2023-12-11T07:21:53.205376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 24
30.0%
의 9
 
11.2%
부 9
 
11.2%
정 8
 
10.0%
안 4
 
5.0%
산 3
 
3.8%
원 2
 
2.5%
천 2
 
2.5%
수 2
 
2.5%
남 2
 
2.5%
Other values (14) 15
18.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 24
30.0%
의 9
 
11.2%
부 9
 
11.2%
정 8
 
10.0%
안 4
 
5.0%
산 3
 
3.8%
원 2
 
2.5%
천 2
 
2.5%
수 2
 
2.5%
남 2
 
2.5%
Other values (14) 15
18.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 24
30.0%
의 9
 
11.2%
부 9
 
11.2%
정 8
 
10.0%
안 4
 
5.0%
산 3
 
3.8%
원 2
 
2.5%
천 2
 
2.5%
수 2
 
2.5%
남 2
 
2.5%
Other values (14) 15
18.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 24
30.0%
의 9
 
11.2%
부 9
 
11.2%
정 8
 
10.0%
안 4
 
5.0%
산 3
 
3.8%
원 2
 
2.5%
천 2
 
2.5%
수 2
 
2.5%
남 2
 
2.5%
Other values (14) 15
18.8%

사업장명
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T07:21:53.408106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length7.25
Min length4

Characters and Unicode

Total characters174
Distinct characters86
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row과천시민회관
2nd row광주시 문화스포츠센터
3rd row롯데씨네(구리시네마)
4th row군포문화예술회관
5th row부천시민회관
ValueCountFrequency (%)
과천시민회관 1
 
3.8%
광주시 1
 
3.8%
숭문상가 1
 
3.8%
성혼예식장 1
 
3.8%
삼천리탄업(주 1
 
3.8%
의장부기독교청년회 1
 
3.8%
행복예식장 1
 
3.8%
허니문예식장 1
 
3.8%
동원웨딩홀 1
 
3.8%
경기도북부여성회관3 1
 
3.8%
Other values (16) 16
61.5%
2023-12-11T07:21:53.700875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 8
 
4.6%
관 8
 
4.6%
문 8
 
4.6%
예 8
 
4.6%
시 7
 
4.0%
장 5
 
2.9%
성 4
 
2.3%
민 4
 
2.3%
부 4
 
2.3%
화 4
 
2.3%
Other values (76) 114
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 164
94.3%
Open Punctuation 3
 
1.7%
Close Punctuation 3
 
1.7%
Space Separator 2
 
1.1%
Decimal Number 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 8
 
4.9%
관 8
 
4.9%
문 8
 
4.9%
예 8
 
4.9%
시 7
 
4.3%
장 5
 
3.0%
성 4
 
2.4%
민 4
 
2.4%
부 4
 
2.4%
화 4
 
2.4%
Other values (71) 104
63.4%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
5 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 164
94.3%
Common 10
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 8
 
4.9%
관 8
 
4.9%
문 8
 
4.9%
예 8
 
4.9%
시 7
 
4.3%
장 5
 
3.0%
성 4
 
2.4%
민 4
 
2.4%
부 4
 
2.4%
화 4
 
2.4%
Other values (71) 104
63.4%
Common
ValueCountFrequency (%)
( 3
30.0%
) 3
30.0%
2
20.0%
3 1
 
10.0%
5 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 164
94.3%
ASCII 10
 
5.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 8
 
4.9%
관 8
 
4.9%
문 8
 
4.9%
예 8
 
4.9%
시 7
 
4.3%
장 5
 
3.0%
성 4
 
2.4%
민 4
 
2.4%
부 4
 
2.4%
화 4
 
2.4%
Other values (71) 104
63.4%
ASCII
ValueCountFrequency (%)
( 3
30.0%
) 3
30.0%
2
20.0%
3 1
 
10.0%
5 1
 
10.0%

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20011758
Minimum19910408
Maximum20130911
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:21:53.839042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19910408
5-th percentile19950331
Q119957707
median19975460
Q320070336
95-th percentile20109489
Maximum20130911
Range220503
Interquartile range (IQR)112628.5

Descriptive statistics

Standard deviation66295.947
Coefficient of variation (CV)0.0033128498
Kurtosis-1.5074902
Mean20011758
Median Absolute Deviation (MAD)45090.5
Skewness0.29484174
Sum4.8028218 × 108
Variance4.3951526 × 109
MonotonicityNot monotonic
2023-12-11T07:21:53.963171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
19950331 3
 
12.5%
19960703 2
 
8.3%
19960108 1
 
4.2%
20111110 1
 
4.2%
19910408 1
 
4.2%
19950504 1
 
4.2%
19960704 1
 
4.2%
19950408 1
 
4.2%
20080102 1
 
4.2%
20130911 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
19910408 1
 
4.2%
19950331 3
12.5%
19950408 1
 
4.2%
19950504 1
 
4.2%
19960108 1
 
4.2%
19960415 1
 
4.2%
19960703 2
8.3%
19960704 1
 
4.2%
19970701 1
 
4.2%
19980219 1
 
4.2%
ValueCountFrequency (%)
20130911 1
4.2%
20111110 1
4.2%
20100302 1
4.2%
20080102 1
4.2%
20071029 1
4.2%
20070406 1
4.2%
20070312 1
4.2%
20070306 1
4.2%
20070216 1
4.2%
20050920 1
4.2%

영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
운영중
23 
폐업 등
 
1

Length

Max length4
Median length3
Mean length3.0416667
Min length3

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 23
95.8%
폐업 등 1
 
4.2%

Length

2023-12-11T07:21:54.078250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:21:54.155448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 23
92.0%
폐업 1
 
4.0%
등 1
 
4.0%

다중이용업소여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)4.3%
Missing1
Missing (%)4.2%
Memory size180.0 B
False
23 
(Missing)
 
1
ValueCountFrequency (%)
False 23
95.8%
(Missing) 1
 
4.2%
2023-12-11T07:21:54.217994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위생업종명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
공중이용시설
23 
<NA>
 
1

Length

Max length6
Median length6
Mean length5.9166667
Min length4

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row공중이용시설
2nd row공중이용시설
3rd row공중이용시설
4th row공중이용시설
5th row<NA>

Common Values

ValueCountFrequency (%)
공중이용시설 23
95.8%
<NA> 1
 
4.2%

Length

2023-12-11T07:21:54.302204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:21:54.390666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공중이용시설 23
95.8%
na 1
 
4.2%

위생업태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size324.0 B
공연장
23 
<NA>
 
1

Length

Max length4
Median length3
Mean length3.0416667
Min length3

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row공연장
2nd row공연장
3rd row공연장
4th row공연장
5th row<NA>

Common Values

ValueCountFrequency (%)
공연장 23
95.8%
<NA> 1
 
4.2%

Length

2023-12-11T07:21:54.477660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:21:54.580254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공연장 23
95.8%
na 1
 
4.2%

소재지도로명주소
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing2
Missing (%)8.3%
Memory size324.0 B
2023-12-11T07:21:54.776264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28.5
Mean length24.454545
Min length19

Characters and Unicode

Total characters538
Distinct characters90
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 통영로 5 (중앙동)
2nd row경기도 광주시 회안대로 891 (송정동)
3rd row경기도 구리시 경춘로 243 (인창동)
4th row경기도 군포시 고산로 599 (산본동, 군포문화예술회관)
5th row경기도 부천시 부일로 365 (중동)
ValueCountFrequency (%)
경기도 22
 
18.5%
의정부시 8
 
6.7%
의정부동 4
 
3.4%
안산시 3
 
2.5%
16 2
 
1.7%
가능동 2
 
1.7%
성남시 2
 
1.7%
태평로 2
 
1.7%
상록구 2
 
1.7%
죽전동 1
 
0.8%
Other values (71) 71
59.7%
2023-12-11T07:21:55.101616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
97
 
18.0%
경 25
 
4.6%
기 23
 
4.3%
로 22
 
4.1%
도 22
 
4.1%
시 22
 
4.1%
) 21
 
3.9%
동 21
 
3.9%
( 21
 
3.9%
정 18
 
3.3%
Other values (80) 246
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 317
58.9%
Space Separator 97
 
18.0%
Decimal Number 74
 
13.8%
Close Punctuation 21
 
3.9%
Open Punctuation 21
 
3.9%
Other Punctuation 8
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 25
 
7.9%
기 23
 
7.3%
로 22
 
6.9%
도 22
 
6.9%
시 22
 
6.9%
동 21
 
6.6%
정 18
 
5.7%
부 16
 
5.0%
의 15
 
4.7%
구 9
 
2.8%
Other values (66) 124
39.1%
Decimal Number
ValueCountFrequency (%)
1 15
20.3%
3 12
16.2%
2 11
14.9%
6 9
12.2%
5 8
10.8%
8 6
 
8.1%
9 5
 
6.8%
7 4
 
5.4%
4 2
 
2.7%
0 2
 
2.7%
Space Separator
ValueCountFrequency (%)
97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 317
58.9%
Common 221
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 25
 
7.9%
기 23
 
7.3%
로 22
 
6.9%
도 22
 
6.9%
시 22
 
6.9%
동 21
 
6.6%
정 18
 
5.7%
부 16
 
5.0%
의 15
 
4.7%
구 9
 
2.8%
Other values (66) 124
39.1%
Common
ValueCountFrequency (%)
97
43.9%
) 21
 
9.5%
( 21
 
9.5%
1 15
 
6.8%
3 12
 
5.4%
2 11
 
5.0%
6 9
 
4.1%
5 8
 
3.6%
, 8
 
3.6%
8 6
 
2.7%
Other values (4) 13
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 317
58.9%
ASCII 221
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
97
43.9%
) 21
 
9.5%
( 21
 
9.5%
1 15
 
6.8%
3 12
 
5.4%
2 11
 
5.0%
6 9
 
4.1%
5 8
 
3.6%
, 8
 
3.6%
8 6
 
2.7%
Other values (4) 13
 
5.9%
Hangul
ValueCountFrequency (%)
경 25
 
7.9%
기 23
 
7.3%
로 22
 
6.9%
도 22
 
6.9%
시 22
 
6.9%
동 21
 
6.6%
정 18
 
5.7%
부 16
 
5.0%
의 15
 
4.7%
구 9
 
2.8%
Other values (66) 124
39.1%

소재지지번주소
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-11T07:21:55.299712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length21.333333
Min length16

Characters and Unicode

Total characters512
Distinct characters82
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row경기도 과천시 중앙동 6-2번지
2nd row경기도 광주시 송정동 340-1번지 52필지
3rd row경기도 구리시 인창동 676-2번지
4th row경기도 군포시 산본동 1101번지 군포문화예술회관
5th row경기도 부천시 중동 788번지
ValueCountFrequency (%)
경기도 24
22.0%
의정부시 8
 
7.3%
의정부동 6
 
5.5%
안산시 3
 
2.8%
수원시 2
 
1.8%
성남시 2
 
1.8%
상록구 2
 
1.8%
가능동 2
 
1.8%
안양동 1
 
0.9%
550번지 1
 
0.9%
Other values (58) 58
53.2%
2023-12-11T07:21:55.607904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
85
 
16.6%
지 26
 
5.1%
경 24
 
4.7%
번 24
 
4.7%
도 24
 
4.7%
시 24
 
4.7%
기 24
 
4.7%
동 24
 
4.7%
1 24
 
4.7%
정 17
 
3.3%
Other values (72) 216
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 312
60.9%
Decimal Number 99
 
19.3%
Space Separator 85
 
16.6%
Dash Punctuation 12
 
2.3%
Other Punctuation 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 26
 
8.3%
경 24
 
7.7%
번 24
 
7.7%
도 24
 
7.7%
시 24
 
7.7%
기 24
 
7.7%
동 24
 
7.7%
정 17
 
5.4%
의 15
 
4.8%
부 15
 
4.8%
Other values (59) 95
30.4%
Decimal Number
ValueCountFrequency (%)
1 24
24.2%
0 14
14.1%
6 9
 
9.1%
7 9
 
9.1%
5 9
 
9.1%
3 9
 
9.1%
2 8
 
8.1%
4 7
 
7.1%
8 6
 
6.1%
9 4
 
4.0%
Space Separator
ValueCountFrequency (%)
85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 312
60.9%
Common 200
39.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 26
 
8.3%
경 24
 
7.7%
번 24
 
7.7%
도 24
 
7.7%
시 24
 
7.7%
기 24
 
7.7%
동 24
 
7.7%
정 17
 
5.4%
의 15
 
4.8%
부 15
 
4.8%
Other values (59) 95
30.4%
Common
ValueCountFrequency (%)
85
42.5%
1 24
 
12.0%
0 14
 
7.0%
- 12
 
6.0%
6 9
 
4.5%
7 9
 
4.5%
5 9
 
4.5%
3 9
 
4.5%
2 8
 
4.0%
4 7
 
3.5%
Other values (3) 14
 
7.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 312
60.9%
ASCII 200
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
85
42.5%
1 24
 
12.0%
0 14
 
7.0%
- 12
 
6.0%
6 9
 
4.5%
7 9
 
4.5%
5 9
 
4.5%
3 9
 
4.5%
2 8
 
4.0%
4 7
 
3.5%
Other values (3) 14
 
7.0%
Hangul
ValueCountFrequency (%)
지 26
 
8.3%
경 24
 
7.7%
번 24
 
7.7%
도 24
 
7.7%
시 24
 
7.7%
기 24
 
7.7%
동 24
 
7.7%
정 17
 
5.4%
의 15
 
4.8%
부 15
 
4.8%
Other values (59) 95
30.4%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean438652.08
Minimum14613
Maximum480849
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:21:55.716010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14613
5-th percentile426043.7
Q1434556.75
median460817.5
Q3480209.5
95-th percentile480848.85
Maximum480849
Range466236
Interquartile range (IQR)45652.75

Descriptive statistics

Standard deviation92788.954
Coefficient of variation (CV)0.211532
Kurtosis21.213282
Mean438652.08
Median Absolute Deviation (MAD)20010
Skewness-4.4866692
Sum10527650
Variance8.60979 × 109
MonotonicityNot monotonic
2023-12-11T07:21:55.830496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
480010 2
 
8.3%
480849 2
 
8.3%
427805 1
 
4.2%
430821 1
 
4.2%
459813 1
 
4.2%
480842 1
 
4.2%
480813 1
 
4.2%
480808 1
 
4.2%
480848 1
 
4.2%
437802 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
14613 1
4.2%
425906 1
4.2%
426824 1
4.2%
426863 1
4.2%
427805 1
4.2%
430821 1
4.2%
435802 1
4.2%
437802 1
4.2%
442835 1
4.2%
443803 1
4.2%
ValueCountFrequency (%)
480849 2
8.3%
480848 1
4.2%
480842 1
4.2%
480813 1
4.2%
480808 1
4.2%
480010 2
8.3%
471010 1
4.2%
464903 1
4.2%
463839 1
4.2%
461822 1
4.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)100.0%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean37.491465
Minimum37.0666
Maximum37.752881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:21:55.928635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.0666
5-th percentile37.25704
Q137.323203
median37.428207
Q337.736478
95-th percentile37.749342
Maximum37.752881
Range0.68628106
Interquartile range (IQR)0.41327495

Descriptive statistics

Standard deviation0.21012001
Coefficient of variation (CV)0.0056044759
Kurtosis-1.1845071
Mean37.491465
Median Absolute Deviation (MAD)0.16353829
Skewness-0.020592886
Sum862.30368
Variance0.044150419
MonotonicityNot monotonic
2023-12-11T07:21:56.022264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37.4282074501 1
 
4.2%
37.4269117267 1
 
4.2%
37.0665995289 1
 
4.2%
37.739217295 1
 
4.2%
37.7504667396 1
 
4.2%
37.736264577 1
 
4.2%
37.7344392904 1
 
4.2%
37.7528805936 1
 
4.2%
37.7384448943 1
 
4.2%
37.7370265468 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
37.0665995289 1
4.2%
37.2561922841 1
4.2%
37.2646691609 1
4.2%
37.2936578348 1
4.2%
37.3090490579 1
4.2%
37.320535452 1
4.2%
37.325870193 1
4.2%
37.365784472 1
4.2%
37.3846057882 1
4.2%
37.4029548133 1
4.2%
ValueCountFrequency (%)
37.7528805936 1
4.2%
37.7504667396 1
4.2%
37.739217295 1
4.2%
37.7384448943 1
4.2%
37.7370265468 1
4.2%
37.7366909733 1
4.2%
37.736264577 1
4.2%
37.7344392904 1
4.2%
37.6017945695 1
4.2%
37.4886329267 1
4.2%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct23
Distinct (%)100.0%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean127.01842
Minimum126.77066
Maximum127.25473
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-11T07:21:56.124158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.77066
5-th percentile126.82477
Q1126.96022
median127.0417
Q3127.06237
95-th percentile127.14154
Maximum127.25473
Range0.4840691
Interquartile range (IQR)0.10214771

Descriptive statistics

Standard deviation0.11395264
Coefficient of variation (CV)0.00089713479
Kurtosis0.31093619
Mean127.01842
Median Absolute Deviation (MAD)0.052593732
Skewness-0.47178771
Sum2921.4236
Variance0.012985205
MonotonicityNot monotonic
2023-12-11T07:21:56.239937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
126.9891095986 1
 
4.2%
127.2547251024 1
 
4.2%
127.0649540068 1
 
4.2%
127.0513324742 1
 
4.2%
127.0352931095 1
 
4.2%
127.0452216968 1
 
4.2%
127.041703331 1
 
4.2%
127.0325876394 1
 
4.2%
127.05205216 1
 
4.2%
127.0395083036 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
126.770655999 1
4.2%
126.82176276 1
4.2%
126.8518153123 1
4.2%
126.8559187691 1
4.2%
126.9274658783 1
4.2%
126.9313328724 1
4.2%
126.9891095986 1
4.2%
127.0325876394 1
4.2%
127.0352931095 1
4.2%
127.0394452641 1
4.2%
ValueCountFrequency (%)
127.2547251024 1
4.2%
127.1420645232 1
4.2%
127.1368317888 1
4.2%
127.1305498953 1
4.2%
127.1059037739 1
4.2%
127.0649540068 1
4.2%
127.0597838938 1
4.2%
127.05205216 1
4.2%
127.0513324742 1
4.2%
127.0452216968 1
4.2%

Interactions

2023-12-11T07:21:52.041946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.204524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.507850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.760421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:52.105107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.309808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.569691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.829250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:52.172776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.375618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.630112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.900895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:52.262701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.443916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.698335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:21:51.974697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:21:56.316669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자영업상태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.9020.0001.0001.0001.0000.9981.000
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자0.9021.0001.0001.0001.0001.0000.2110.8380.884
영업상태명0.0001.0001.0001.0001.0001.0000.0000.0000.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0000.2110.0001.0001.0001.0000.4740.836
WGS84위도0.9981.0000.8380.0001.0001.0000.4741.0000.955
WGS84경도1.0001.0000.8840.0001.0001.0000.8360.9551.000
2023-12-11T07:21:56.413461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위생업종명영업상태명위생업태명
위생업종명1.0001.0001.000
영업상태명1.0001.0001.000
위생업태명1.0001.0001.000
2023-12-11T07:21:56.486999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지우편번호WGS84위도WGS84경도영업상태명위생업종명위생업태명
인허가일자1.000-0.433-0.5220.0720.8261.0001.000
소재지우편번호-0.4331.0000.7240.5030.2861.0001.000
WGS84위도-0.5220.7241.0000.0830.0001.0001.000
WGS84경도0.0720.5030.0831.0000.0001.0001.000
영업상태명0.8260.2860.0000.0001.0001.0001.000
위생업종명1.0001.0001.0001.0001.0001.0001.000
위생업태명1.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T07:21:52.584615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:21:52.731888image/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.
2023-12-11T07:21:52.839708image/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

시군명사업장명인허가일자영업상태명다중이용업소여부위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0과천시과천시민회관19960108운영중N공중이용시설공연장경기도 과천시 통영로 5 (중앙동)경기도 과천시 중앙동 6-2번지42780537.428207126.98911
1광주시광주시 문화스포츠센터20111110운영중N공중이용시설공연장경기도 광주시 회안대로 891 (송정동)경기도 광주시 송정동 340-1번지 52필지46490337.426912127.254725
2구리시롯데씨네(구리시네마)20100302운영중N공중이용시설공연장경기도 구리시 경춘로 243 (인창동)경기도 구리시 인창동 676-2번지47101037.601795127.142065
3군포시군포문화예술회관20070216운영중N공중이용시설공연장경기도 군포시 고산로 599 (산본동, 군포문화예술회관)경기도 군포시 산본동 1101번지 군포문화예술회관43580237.365784126.927466
4부천시부천시민회관19980219운영중<NA><NA><NA>경기도 부천시 부일로 365 (중동)경기도 부천시 중동 788번지1461337.488633126.770656
5성남시성남시민회관19960415운영중N공중이용시설공연장경기도 성남시 수정구 수정로153번길 3 (태평동)경기도 성남시 수정구 태평동 3493-1번지46182237.442788127.136832
6성남시성남아트센터 대극장20050920운영중N공중이용시설공연장경기도 성남시 분당구 성남대로 808 (야탑동)경기도 성남시 분당구 야탑동 757번지46383937.402955127.13055
7수원시영통키넥스520071029운영중N공중이용시설공연장경기도 수원시 영통구 신원로 231 (매탄동)경기도 수원시 영통구 매탄동 491-10번지44380337.256192127.059784
8수원시경기도문화의전당20070306운영중N공중이용시설공연장<NA>경기도 수원시 팔달구 인계동 1117번지44283537.264669127.039445
9안산시안산문화예술의전당20070406운영중N공중이용시설공연장경기도 안산시 단원구 화랑로 312 (고잔동, 817)경기도 안산시 단원구 고잔동 817번지42590637.320535126.821763
시군명사업장명인허가일자영업상태명다중이용업소여부위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
14의왕시우경예술관20080102운영중N공중이용시설공연장<NA>경기도 의왕시 내손동 66번지437802<NA><NA>
15의정부시경기도북부여성회관319950331운영중N공중이용시설공연장경기도 의정부시 신흥로 232 (의정부동)경기도 의정부시 의정부동 500번지48084837.736691127.043607
16의정부시동원웨딩홀19960703운영중N공중이용시설공연장경기도 의정부시 둔야로 11 (의정부동)경기도 의정부시 의정부동 512-1번지48084937.737027127.039508
17의정부시허니문예식장19950408운영중N공중이용시설공연장경기도 의정부시 태평로 66 (의정부동,,11,12)경기도 의정부시 의정부동 126-10번지 ,11,1248001037.738445127.052052
18의정부시행복예식장19950331운영중N공중이용시설공연장경기도 의정부시 녹양로 16 (가능동)경기도 의정부시 가능동 353-1번지48080837.752881127.032588
19의정부시의장부기독교청년회19960704운영중N공중이용시설공연장경기도 의정부시 경의로55번길 30 (의정부동)경기도 의정부시 의정부동 560번지48084937.734439127.041703
20의정부시삼천리탄업(주)19950331운영중N공중이용시설공연장경기도 의정부시 신흥로222번길 31 (의정부동,,7,8)경기도 의정부시 의정부동 499-6번지 ,7,848001037.736265127.045222
21의정부시성혼예식장19950504운영중N공중이용시설공연장경기도 의정부시 신촌로 7 (가능동)경기도 의정부시 가능동 604-3번지48081337.750467127.035293
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