Overview

Dataset statistics

Number of variables12
Number of observations28
Missing cells3
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory105.7 B

Variable types

Categorical5
Text3
Numeric4

Dataset

Description외국인전용관광기념품판매점 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=ROXUVCLT2SJ1ZG8561GA13654052&infSeq=1

Alerts

문화체육업종명 has constant value ""Constant
폐업일자 is highly overall correlated with 인허가일자 and 6 other fieldsHigh correlation
문화사업자구분명 is highly overall correlated with 인허가일자 and 6 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
영업상태명 is highly overall correlated with 인허가일자 and 3 other fieldsHigh correlation
인허가일자 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with 인허가일자 and 4 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 인허가일자 and 4 other fieldsHigh correlation
폐업일자 is highly imbalanced (66.9%)Imbalance
소재지도로명주소 has 3 (10.7%) missing valuesMissing
사업장명 has unique valuesUnique
소재지지번주소 has unique valuesUnique
WGS84위도 has unique valuesUnique
WGS84경도 has unique valuesUnique

Reproduction

Analysis started2023-12-10 22:32:05.440768
Analysis finished2023-12-10 22:32:07.323925
Duration1.88 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
이천시
14 
파주시
4 
고양시
3 
용인시
2 
가평군
 
1
Other values (4)
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique5 ?
Unique (%)17.9%

Sample

1st row가평군
2nd row고양시
3rd row고양시
4th row고양시
5th row김포시

Common Values

ValueCountFrequency (%)
이천시 14
50.0%
파주시 4
 
14.3%
고양시 3
 
10.7%
용인시 2
 
7.1%
가평군 1
 
3.6%
김포시 1
 
3.6%
수원시 1
 
3.6%
평택시 1
 
3.6%
화성시 1
 
3.6%

Length

2023-12-11T07:32:07.374682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:07.464972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
이천시 14
50.0%
파주시 4
 
14.3%
고양시 3
 
10.7%
용인시 2
 
7.1%
가평군 1
 
3.6%
김포시 1
 
3.6%
수원시 1
 
3.6%
평택시 1
 
3.6%
화성시 1
 
3.6%

사업장명
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T07:32:07.650600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11.5
Mean length5.6071429
Min length2

Characters and Unicode

Total characters157
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

Unique28 ?
Unique (%)100.0%

Sample

1st row가평요
2nd row(주)신생당
3rd row(주)김치스쿨
4th row해원
5th row우주산업
ValueCountFrequency (%)
가평요 1
 
3.0%
에띄드 1
 
3.0%
한미요 1
 
3.0%
평택항면세점 1
 
3.0%
한국관광공사 1
 
3.0%
오륜 1
 
3.0%
동화진흥주식회사 1
 
3.0%
스킨애니버셔리 1
 
3.0%
주식회사 1
 
3.0%
이채코리아 1
 
3.0%
Other values (23) 23
69.7%
2023-12-11T07:32:07.965121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
요 9
 
5.7%
도 9
 
5.7%
주 7
 
4.5%
예 5
 
3.2%
5
 
3.2%
점 4
 
2.5%
한 4
 
2.5%
청 3
 
1.9%
이 3
 
1.9%
스 3
 
1.9%
Other values (76) 105
66.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145
92.4%
Space Separator 5
 
3.2%
Close Punctuation 3
 
1.9%
Open Punctuation 3
 
1.9%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
요 9
 
6.2%
도 9
 
6.2%
주 7
 
4.8%
예 5
 
3.4%
점 4
 
2.8%
한 4
 
2.8%
청 3
 
2.1%
이 3
 
2.1%
스 3
 
2.1%
지 3
 
2.1%
Other values (72) 95
65.5%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
92.4%
Common 12
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
요 9
 
6.2%
도 9
 
6.2%
주 7
 
4.8%
예 5
 
3.4%
점 4
 
2.8%
한 4
 
2.8%
청 3
 
2.1%
이 3
 
2.1%
스 3
 
2.1%
지 3
 
2.1%
Other values (72) 95
65.5%
Common
ValueCountFrequency (%)
5
41.7%
) 3
25.0%
( 3
25.0%
- 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145
92.4%
ASCII 12
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
요 9
 
6.2%
도 9
 
6.2%
주 7
 
4.8%
예 5
 
3.4%
점 4
 
2.8%
한 4
 
2.8%
청 3
 
2.1%
이 3
 
2.1%
스 3
 
2.1%
지 3
 
2.1%
Other values (72) 95
65.5%
ASCII
ValueCountFrequency (%)
5
41.7%
) 3
25.0%
( 3
25.0%
- 1
 
8.3%

인허가일자
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20035556
Minimum19870911
Maximum20140818
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T07:32:08.134793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19870911
5-th percentile19874471
Q119997642
median20040718
Q320110306
95-th percentile20140610
Maximum20140818
Range269907
Interquartile range (IQR)112663.5

Descriptive statistics

Standard deviation88596.799
Coefficient of variation (CV)0.0044219786
Kurtosis-0.83819691
Mean20035556
Median Absolute Deviation (MAD)69693
Skewness-0.57025232
Sum5.6099556 × 108
Variance7.8493927 × 109
MonotonicityNot monotonic
2023-12-11T07:32:08.307575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
20110201 2
 
7.1%
19960216 1
 
3.6%
20130412 1
 
3.6%
20140613 1
 
3.6%
20011006 1
 
3.6%
20060501 1
 
3.6%
20110104 1
 
3.6%
20010118 1
 
3.6%
20010813 1
 
3.6%
20010226 1
 
3.6%
Other values (17) 17
60.7%
ValueCountFrequency (%)
19870911 1
3.6%
19871209 1
3.6%
19880528 1
3.6%
19900321 1
3.6%
19920416 1
3.6%
19950302 1
3.6%
19960216 1
3.6%
20010118 1
3.6%
20010226 1
3.6%
20010813 1
3.6%
ValueCountFrequency (%)
20140818 1
3.6%
20140613 1
3.6%
20140603 1
3.6%
20130916 1
3.6%
20130412 1
3.6%
20120203 1
3.6%
20110621 1
3.6%
20110201 2
7.1%
20110104 1
3.6%
20101209 1
3.6%

영업상태명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
운영중
22 
폐업 등
5 
휴업 등
 
1

Length

Max length4
Median length3
Mean length3.2142857
Min length3

Unique

Unique1 ?
Unique (%)3.6%

Sample

1st row폐업 등
2nd row운영중
3rd row운영중
4th row휴업 등
5th row운영중

Common Values

ValueCountFrequency (%)
운영중 22
78.6%
폐업 등 5
 
17.9%
휴업 등 1
 
3.6%

Length

2023-12-11T07:32:08.466450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:08.607031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 22
64.7%
등 6
 
17.6%
폐업 5
 
14.7%
휴업 1
 
2.9%

폐업일자
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
25 
20130620
 
1
20140228
 
1
20090331
 
1

Length

Max length8
Median length4
Mean length4.4285714
Min length4

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row20130620
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 25
89.3%
20130620 1
 
3.6%
20140228 1
 
3.6%
20090331 1
 
3.6%

Length

2023-12-11T07:32:08.738153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:08.877556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
89.3%
20130620 1
 
3.6%
20140228 1
 
3.6%
20090331 1
 
3.6%

문화체육업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
외국인전용관광기념품판매점
28 

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외국인전용관광기념품판매점 28
100.0%

Length

2023-12-11T07:32:08.988714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:09.106113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외국인전용관광기념품판매점 28
100.0%

문화사업자구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
관광사업
16 
<NA>
12 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관광사업 16
57.1%
<NA> 12
42.9%

Length

2023-12-11T07:32:09.216007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:32:09.325394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
관광사업 16
57.1%
na 12
42.9%

소재지도로명주소
Text

MISSING 

Distinct25
Distinct (%)100.0%
Missing3
Missing (%)10.7%
Memory size356.0 B
2023-12-11T07:32:09.549026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length24.44
Min length19

Characters and Unicode

Total characters611
Distinct characters93
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

Unique25 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 덕양구 중앙로46번길 4-1 (덕은동)
2nd row경기도 고양시 덕양구 중앙로62번길 6
3rd row경기도 고양시 일산서구 법곳길115번길 94 (법곳동)
4th row경기도 김포시 풍무로 189-3 (풍무동)
5th row경기도 수원시 팔달구 권광로 132 (인계동)
ValueCountFrequency (%)
경기도 25
 
18.7%
이천시 12
 
9.0%
신둔면 9
 
6.7%
파주시 4
 
3.0%
고양시 3
 
2.2%
경충대로 3
 
2.2%
처인구 2
 
1.5%
사음동 2
 
1.5%
문발로 2
 
1.5%
문발동 2
 
1.5%
Other values (67) 70
52.2%
2023-12-11T07:32:09.948718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
115
 
18.8%
경 32
 
5.2%
시 25
 
4.1%
기 25
 
4.1%
도 25
 
4.1%
로 22
 
3.6%
3 18
 
2.9%
1 16
 
2.6%
이 14
 
2.3%
면 13
 
2.1%
Other values (83) 306
50.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 364
59.6%
Space Separator 115
 
18.8%
Decimal Number 106
 
17.3%
Open Punctuation 10
 
1.6%
Close Punctuation 10
 
1.6%
Dash Punctuation 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 32
 
8.8%
시 25
 
6.9%
기 25
 
6.9%
도 25
 
6.9%
로 22
 
6.0%
이 14
 
3.8%
면 13
 
3.6%
길 13
 
3.6%
천 13
 
3.6%
신 10
 
2.7%
Other values (69) 172
47.3%
Decimal Number
ValueCountFrequency (%)
3 18
17.0%
1 16
15.1%
2 12
11.3%
4 12
11.3%
7 11
10.4%
6 10
9.4%
5 9
8.5%
8 8
7.5%
9 7
 
6.6%
0 3
 
2.8%
Space Separator
ValueCountFrequency (%)
115
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 364
59.6%
Common 247
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 32
 
8.8%
시 25
 
6.9%
기 25
 
6.9%
도 25
 
6.9%
로 22
 
6.0%
이 14
 
3.8%
면 13
 
3.6%
길 13
 
3.6%
천 13
 
3.6%
신 10
 
2.7%
Other values (69) 172
47.3%
Common
ValueCountFrequency (%)
115
46.6%
3 18
 
7.3%
1 16
 
6.5%
2 12
 
4.9%
4 12
 
4.9%
7 11
 
4.5%
( 10
 
4.0%
) 10
 
4.0%
6 10
 
4.0%
5 9
 
3.6%
Other values (4) 24
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 364
59.6%
ASCII 247
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
115
46.6%
3 18
 
7.3%
1 16
 
6.5%
2 12
 
4.9%
4 12
 
4.9%
7 11
 
4.5%
( 10
 
4.0%
) 10
 
4.0%
6 10
 
4.0%
5 9
 
3.6%
Other values (4) 24
 
9.7%
Hangul
ValueCountFrequency (%)
경 32
 
8.8%
시 25
 
6.9%
기 25
 
6.9%
도 25
 
6.9%
로 22
 
6.0%
이 14
 
3.8%
면 13
 
3.6%
길 13
 
3.6%
천 13
 
3.6%
신 10
 
2.7%
Other values (69) 172
47.3%

소재지지번주소
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-11T07:32:10.233488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length22.607143
Min length17

Characters and Unicode

Total characters633
Distinct characters95
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

Unique28 ?
Unique (%)100.0%

Sample

1st row경기도 가평군 하면 대보리 215번지
2nd row경기도 고양시 덕양구 덕은동 60-2번지
3rd row경기도 고양시 덕양구 덕은동 12-1번지 가동
4th row경기도 고양시 일산서구 법곳동 1761-3번지
5th row경기도 김포시 풍무동 6-1번지
ValueCountFrequency (%)
경기도 28
19.9%
이천시 14
 
9.9%
신둔면 10
 
7.1%
수광리 7
 
5.0%
파주시 4
 
2.8%
고양시 3
 
2.1%
처인구 2
 
1.4%
사음동 2
 
1.4%
문발동 2
 
1.4%
포곡읍 2
 
1.4%
Other values (64) 67
47.5%
2023-12-11T07:32:10.671093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
17.9%
경 28
 
4.4%
번 28
 
4.4%
기 28
 
4.4%
지 28
 
4.4%
도 28
 
4.4%
시 27
 
4.3%
1 25
 
3.9%
- 20
 
3.2%
리 18
 
2.8%
Other values (85) 290
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 396
62.6%
Space Separator 113
 
17.9%
Decimal Number 104
 
16.4%
Dash Punctuation 20
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 28
 
7.1%
번 28
 
7.1%
기 28
 
7.1%
지 28
 
7.1%
도 28
 
7.1%
시 27
 
6.8%
리 18
 
4.5%
면 15
 
3.8%
이 14
 
3.5%
천 14
 
3.5%
Other values (73) 168
42.4%
Decimal Number
ValueCountFrequency (%)
1 25
24.0%
2 18
17.3%
4 11
10.6%
3 9
 
8.7%
5 9
 
8.7%
0 8
 
7.7%
9 7
 
6.7%
6 7
 
6.7%
7 6
 
5.8%
8 4
 
3.8%
Space Separator
ValueCountFrequency (%)
113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 396
62.6%
Common 237
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 28
 
7.1%
번 28
 
7.1%
기 28
 
7.1%
지 28
 
7.1%
도 28
 
7.1%
시 27
 
6.8%
리 18
 
4.5%
면 15
 
3.8%
이 14
 
3.5%
천 14
 
3.5%
Other values (73) 168
42.4%
Common
ValueCountFrequency (%)
113
47.7%
1 25
 
10.5%
- 20
 
8.4%
2 18
 
7.6%
4 11
 
4.6%
3 9
 
3.8%
5 9
 
3.8%
0 8
 
3.4%
9 7
 
3.0%
6 7
 
3.0%
Other values (2) 10
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 396
62.6%
ASCII 237
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
47.7%
1 25
 
10.5%
- 20
 
8.4%
2 18
 
7.6%
4 11
 
4.6%
3 9
 
3.8%
5 9
 
3.8%
0 8
 
3.4%
9 7
 
3.0%
6 7
 
3.0%
Other values (2) 10
 
4.2%
Hangul
ValueCountFrequency (%)
경 28
 
7.1%
번 28
 
7.1%
기 28
 
7.1%
지 28
 
7.1%
도 28
 
7.1%
시 27
 
6.8%
리 18
 
4.5%
면 15
 
3.8%
이 14
 
3.5%
천 14
 
3.5%
Other values (73) 168
42.4%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449015.29
Minimum411420
Maximum477831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T07:32:10.837734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum411420
5-th percentile412170
Q1414777.75
median467080
Q3467842
95-th percentile467842.65
Maximum477831
Range66411
Interquartile range (IQR)53064.25

Descriptive statistics

Standard deviation24356.702
Coefficient of variation (CV)0.054244706
Kurtosis-1.3220705
Mean449015.29
Median Absolute Deviation (MAD)5757
Skewness-0.69211824
Sum12572428
Variance5.9324895 × 108
MonotonicityNot monotonic
2023-12-11T07:32:10.994788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
467842 6
21.4%
467841 3
 
10.7%
467080 2
 
7.1%
413832 2
 
7.1%
412170 2
 
7.1%
467804 1
 
3.6%
445883 1
 
3.6%
451821 1
 
3.6%
413901 1
 
3.6%
413841 1
 
3.6%
Other values (8) 8
28.6%
ValueCountFrequency (%)
411420 1
3.6%
412170 2
7.1%
413832 2
7.1%
413841 1
3.6%
413901 1
3.6%
415070 1
3.6%
442835 1
3.6%
445883 1
3.6%
449812 1
3.6%
449815 1
3.6%
ValueCountFrequency (%)
477831 1
 
3.6%
467843 1
 
3.6%
467842 6
21.4%
467841 3
10.7%
467813 1
 
3.6%
467804 1
 
3.6%
467080 2
 
7.1%
451821 1
 
3.6%
449815 1
 
3.6%
449812 1
 
3.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.410416
Minimum36.95927
Maximum37.889267
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T07:32:11.160362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.95927
5-th percentile37.20099
Q137.288078
median37.307712
Q337.599906
95-th percentile37.791532
Maximum37.889267
Range0.92999631
Interquartile range (IQR)0.31182784

Descriptive statistics

Standard deviation0.22481966
Coefficient of variation (CV)0.0060095472
Kurtosis-0.35044132
Mean37.410416
Median Absolute Deviation (MAD)0.031386185
Skewness0.61840964
Sum1047.4916
Variance0.050543879
MonotonicityNot monotonic
2023-12-11T07:32:11.319053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
37.8013759114 1
 
3.6%
37.3114882058 1
 
3.6%
37.1738535627 1
 
3.6%
36.9592702775 1
 
3.6%
37.8892665891 1
 
3.6%
37.7732493546 1
 
3.6%
37.7139028313 1
 
3.6%
37.7150662667 1
 
3.6%
37.3066276503 1
 
3.6%
37.2513860494 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
36.9592702775 1
3.6%
37.1738535627 1
3.6%
37.2513860494 1
3.6%
37.2591307292 1
3.6%
37.2731281747 1
3.6%
37.2795244391 1
3.6%
37.2880239189 1
3.6%
37.2880959552 1
3.6%
37.2923546943 1
3.6%
37.2965988209 1
3.6%
ValueCountFrequency (%)
37.8892665891 1
3.6%
37.8013759114 1
3.6%
37.7732493546 1
3.6%
37.7150662667 1
3.6%
37.7139028313 1
3.6%
37.6602938897 1
3.6%
37.6123829159 1
3.6%
37.5957467468 1
3.6%
37.5943874969 1
3.6%
37.3151003485 1
3.6%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.14309
Minimum126.67379
Maximum127.4459
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-11T07:32:11.453761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.67379
5-th percentile126.68075
Q1126.82072
median127.37295
Q3127.40101
95-th percentile127.40998
Maximum127.4459
Range0.77211824
Interquartile range (IQR)0.58029145

Descriptive statistics

Standard deviation0.31180752
Coefficient of variation (CV)0.0024524142
Kurtosis-1.6175941
Mean127.14309
Median Absolute Deviation (MAD)0.055444522
Skewness-0.53883223
Sum3560.0065
Variance0.097223928
MonotonicityNot monotonic
2023-12-11T07:32:11.601125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
127.3715421093 1
 
3.6%
127.3988268443 1
 
3.6%
126.6737861006 1
 
3.6%
126.8476165744 1
 
3.6%
126.7400181725 1
 
3.6%
126.677378808 1
 
3.6%
126.6870177537 1
 
3.6%
126.6874664693 1
 
3.6%
127.4053774273 1
 
3.6%
127.4027164004 1
 
3.6%
Other values (18) 18
64.3%
ValueCountFrequency (%)
126.6737861006 1
3.6%
126.677378808 1
3.6%
126.6870177537 1
3.6%
126.6874664693 1
3.6%
126.7219354244 1
3.6%
126.7230218175 1
3.6%
126.7400181725 1
3.6%
126.8476165744 1
3.6%
126.8783712457 1
3.6%
126.8795397857 1
3.6%
ValueCountFrequency (%)
127.4459043436 1
3.6%
127.4108837815 1
3.6%
127.4082964783 1
3.6%
127.4053774273 1
3.6%
127.4048576501 1
3.6%
127.402910447 1
3.6%
127.4027164004 1
3.6%
127.400439101 1
3.6%
127.4001924054 1
3.6%
127.3991052501 1
3.6%

Interactions

2023-12-11T07:32:06.791075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:05.943183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.231218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.521777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.856895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.017147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.300917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.586076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.939679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.099834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.370164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.652646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:07.007652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.161857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.442767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:32:06.721009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:32:11.972919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자영업상태명폐업일자소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0001.0000.6600.8631.0001.0001.0001.0000.9290.943
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자0.6601.0001.0000.9541.0001.0001.0000.6540.5980.000
영업상태명0.8631.0000.9541.000NaN1.0001.0000.8030.6370.652
폐업일자1.0001.0001.000NaN1.0000.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0000.0001.0001.0001.0001.0001.000
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0000.6540.8031.0001.0001.0001.0000.8060.955
WGS84위도0.9291.0000.5980.6371.0001.0001.0000.8061.0000.652
WGS84경도0.9431.0000.0000.6521.0001.0001.0000.9550.6521.000
2023-12-11T07:32:12.115174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐업일자문화사업자구분명시군명영업상태명
폐업일자1.0001.0001.0001.000
문화사업자구분명1.0001.0001.0001.000
시군명1.0001.0001.0000.501
영업상태명1.0001.0000.5011.000
2023-12-11T07:32:12.233715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가일자소재지우편번호WGS84위도WGS84경도시군명영업상태명폐업일자문화사업자구분명
인허가일자1.000-0.646-0.052-0.5440.2690.6511.0001.000
소재지우편번호-0.6461.000-0.1990.6900.9290.3331.0001.000
WGS84위도-0.052-0.1991.000-0.3720.7920.4851.0001.000
WGS84경도-0.5440.690-0.3721.0000.7350.3121.0001.000
시군명0.2690.9290.7920.7351.0000.5011.0001.000
영업상태명0.6510.3330.4850.3120.5011.0001.0001.000
폐업일자1.0001.0001.0001.0001.0001.0001.0001.000
문화사업자구분명1.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-11T07:32:07.129618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:32:07.271796image/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

시군명사업장명인허가일자영업상태명폐업일자문화체육업종명문화사업자구분명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군가평요19960216폐업 등20130620외국인전용관광기념품판매점관광사업<NA>경기도 가평군 하면 대보리 215번지47783137.801376127.371542
1고양시(주)신생당20130412운영중<NA>외국인전용관광기념품판매점<NA>경기도 고양시 덕양구 중앙로46번길 4-1 (덕은동)경기도 고양시 덕양구 덕은동 60-2번지41217037.594387126.87954
2고양시(주)김치스쿨20060306운영중<NA>외국인전용관광기념품판매점관광사업경기도 고양시 덕양구 중앙로62번길 6경기도 고양시 덕양구 덕은동 12-1번지 가동41217037.595747126.878371
3고양시해원20050705휴업 등<NA>외국인전용관광기념품판매점관광사업경기도 고양시 일산서구 법곳길115번길 94 (법곳동)경기도 고양시 일산서구 법곳동 1761-3번지41142037.660294126.721935
4김포시우주산업20140603운영중<NA>외국인전용관광기념품판매점<NA>경기도 김포시 풍무로 189-3 (풍무동)경기도 김포시 풍무동 6-1번지41507037.612383126.723022
5수원시앙코르면세점20130916운영중<NA>외국인전용관광기념품판매점<NA>경기도 수원시 팔달구 권광로 132 (인계동)경기도 수원시 팔달구 인계동 1132-12번지44283537.259131127.031312
6용인시김치나라20110621폐업 등<NA>외국인전용관광기념품판매점<NA>경기도 용인시 처인구 포곡읍 성산로 677경기도 용인시 처인구 포곡읍 전대리 342-1번지44981537.288096127.212984
7용인시(주)태성토산-용인지점20140818폐업 등<NA>외국인전용관광기념품판매점<NA>경기도 용인시 처인구 포곡읍 포곡로 180경기도 용인시 처인구 포곡읍 둔전리 52-21번지44981237.273128127.223845
8이천시한청도요20120203운영중<NA>외국인전용관광기념품판매점<NA>경기도 이천시 신둔면 경충대로3159번길 12-27경기도 이천시 신둔면 수광리 257-2번지46784337.309185127.400439
9이천시세창도예19871209운영중<NA>외국인전용관광기념품판매점관광사업<NA>경기도 이천시 신둔면 수광리 210-1번지46784237.306849127.398408
시군명사업장명인허가일자영업상태명폐업일자문화체육업종명문화사업자구분명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
18이천시도예농20030718운영중<NA>외국인전용관광기념품판매점관광사업경기도 이천시 신둔면 서이천로 882경기도 이천시 신둔면 수남리 211-1번지46784137.296599127.400192
19이천시청파요20010226운영중<NA>외국인전용관광기념품판매점관광사업경기도 이천시 경충대로2993번길 87 (사음동)경기도 이천시 사음동 490번지46708037.292355127.410884
20이천시지선도예20010813운영중<NA>외국인전용관광기념품판매점관광사업경기도 이천시 마장면 중부대로644번길 87-1경기도 이천시 마장면 표교리 285번지46781337.251386127.402716
21이천시항산도예20010118운영중<NA>외국인전용관광기념품판매점관광사업경기도 이천시 신둔면 황무로517번길 57경기도 이천시 신둔면 수광리 318-3번지46784237.306628127.405377
22파주시이채코리아20110201운영중<NA>외국인전용관광기념품판매점<NA>경기도 파주시 문발로 233 (문발동)경기도 파주시 문발동 502-1번지41383237.715066126.687466
23파주시주식회사 스킨애니버셔리20110104운영중<NA>외국인전용관광기념품판매점<NA>경기도 파주시 문발로 219 (문발동)경기도 파주시 문발동 508-1번지41383237.713903126.687018
24파주시동화진흥주식회사20110201폐업 등20140228외국인전용관광기념품판매점<NA>경기도 파주시 탄현면 필승로 369경기도 파주시 탄현면 성동리 659번지41384137.773249126.677379
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