Overview

Dataset statistics

Number of variables14
Number of observations136
Missing cells397
Missing cells (%)20.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.7 KiB
Average record size in memory118.0 B

Variable types

Categorical4
Text3
DateTime2
Unsupported2
Numeric3

Dataset

Description휴게음식점(철도역구내) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4567464HOC5WBS33QXPG13491026&infSeq=1

Alerts

위생업태명 has constant value ""Constant
시군명 is highly overall correlated with 소재지우편번호 and 3 other fieldsHigh correlation
영업상태명 is highly overall correlated with 위생업종명High correlation
위생업종명 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
소재지우편번호 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
폐업일자 has 84 (61.8%) missing valuesMissing
다중이용업소여부 has 136 (100.0%) missing valuesMissing
총시설규모(㎡) has 136 (100.0%) missing valuesMissing
소재지도로명주소 has 17 (12.5%) missing valuesMissing
소재지우편번호 has 6 (4.4%) missing valuesMissing
WGS84위도 has 9 (6.6%) missing valuesMissing
WGS84경도 has 9 (6.6%) missing valuesMissing
다중이용업소여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총시설규모(㎡) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-10 21:06:11.332042
Analysis finished2024-05-10 21:06:17.972993
Duration6.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
성남시
29 
부천시
17 
안산시
12 
남양주시
12 
의정부시
11 
Other values (15)
55 

Length

Max length4
Median length3
Mean length3.1985294
Min length3

Unique

Unique4 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 29
21.3%
부천시 17
12.5%
안산시 12
8.8%
남양주시 12
8.8%
의정부시 11
 
8.1%
안양시 10
 
7.4%
고양시 9
 
6.6%
과천시 5
 
3.7%
수원시 5
 
3.7%
군포시 5
 
3.7%
Other values (10) 21
15.4%

Length

2024-05-10T21:06:18.129800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 29
21.3%
부천시 17
12.5%
안산시 12
8.8%
남양주시 12
8.8%
의정부시 11
 
8.1%
안양시 10
 
7.4%
고양시 9
 
6.6%
과천시 5
 
3.7%
수원시 5
 
3.7%
군포시 5
 
3.7%
Other values (10) 21
15.4%

사업장명
Text

Distinct125
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-10T21:06:18.540073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length16
Mean length8.3235294
Min length2

Characters and Unicode

Total characters1132
Distinct characters239
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)85.3%

Sample

1st row행신역 카페센트
2nd row대화역 마리야
3rd row코레일유통(주)히코코
4th row커피앤스위트 화정역점
5th row원당역사던킨도너츠
ValueCountFrequency (%)
어묵나라 7
 
3.8%
모란역점 4
 
2.2%
야탑역 4
 
2.2%
부산오뎅 4
 
2.2%
호밀호두 3
 
1.6%
토리만쥬 3
 
1.6%
야탑역점 3
 
1.6%
베이크0515 2
 
1.1%
코레일유통(주 2
 
1.1%
데일리베이커리 2
 
1.1%
Other values (145) 152
81.7%
2024-05-10T21:06:19.421528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 56
 
4.9%
50
 
4.4%
점 50
 
4.4%
스 35
 
3.1%
( 29
 
2.6%
) 29
 
2.6%
리 25
 
2.2%
이 25
 
2.2%
주 19
 
1.7%
일 19
 
1.7%
Other values (229) 795
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 969
85.6%
Space Separator 50
 
4.4%
Open Punctuation 29
 
2.6%
Close Punctuation 29
 
2.6%
Lowercase Letter 25
 
2.2%
Uppercase Letter 18
 
1.6%
Decimal Number 11
 
1.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 56
 
5.8%
점 50
 
5.2%
스 35
 
3.6%
리 25
 
2.6%
이 25
 
2.6%
주 19
 
2.0%
일 19
 
2.0%
도 18
 
1.9%
코 17
 
1.8%
레 17
 
1.8%
Other values (198) 688
71.0%
Lowercase Letter
ValueCountFrequency (%)
s 4
16.0%
o 4
16.0%
l 3
12.0%
r 3
12.0%
e 2
8.0%
i 2
8.0%
t 2
8.0%
b 1
 
4.0%
h 1
 
4.0%
f 1
 
4.0%
Other values (2) 2
8.0%
Uppercase Letter
ValueCountFrequency (%)
E 3
16.7%
G 2
11.1%
U 2
11.1%
B 2
11.1%
A 2
11.1%
O 2
11.1%
K 1
 
5.6%
J 1
 
5.6%
L 1
 
5.6%
C 1
 
5.6%
Decimal Number
ValueCountFrequency (%)
5 4
36.4%
1 4
36.4%
0 2
18.2%
3 1
 
9.1%
Space Separator
ValueCountFrequency (%)
50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 969
85.6%
Common 120
 
10.6%
Latin 43
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 56
 
5.8%
점 50
 
5.2%
스 35
 
3.6%
리 25
 
2.6%
이 25
 
2.6%
주 19
 
2.0%
일 19
 
2.0%
도 18
 
1.9%
코 17
 
1.8%
레 17
 
1.8%
Other values (198) 688
71.0%
Latin
ValueCountFrequency (%)
s 4
 
9.3%
o 4
 
9.3%
l 3
 
7.0%
E 3
 
7.0%
r 3
 
7.0%
G 2
 
4.7%
e 2
 
4.7%
i 2
 
4.7%
t 2
 
4.7%
U 2
 
4.7%
Other values (13) 16
37.2%
Common
ValueCountFrequency (%)
50
41.7%
( 29
24.2%
) 29
24.2%
5 4
 
3.3%
1 4
 
3.3%
0 2
 
1.7%
3 1
 
0.8%
& 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 968
85.5%
ASCII 163
 
14.4%
Compat Jamo 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 56
 
5.8%
점 50
 
5.2%
스 35
 
3.6%
리 25
 
2.6%
이 25
 
2.6%
주 19
 
2.0%
일 19
 
2.0%
도 18
 
1.9%
코 17
 
1.8%
레 17
 
1.8%
Other values (197) 687
71.0%
ASCII
ValueCountFrequency (%)
50
30.7%
( 29
17.8%
) 29
17.8%
5 4
 
2.5%
s 4
 
2.5%
o 4
 
2.5%
1 4
 
2.5%
l 3
 
1.8%
E 3
 
1.8%
r 3
 
1.8%
Other values (21) 30
18.4%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

인허가일자
Date

Distinct95
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum1999-10-12 00:00:00
Maximum2024-02-29 00:00:00
2024-05-10T21:06:19.811493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:20.260292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
영업
44 
운영중
40 
폐업 등
32 
폐업
20 

Length

Max length4
Median length3
Mean length2.7647059
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 44
32.4%
운영중 40
29.4%
폐업 등 32
23.5%
폐업 20
14.7%

Length

2024-05-10T21:06:20.693328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:06:20.976686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 52
31.0%
영업 44
26.2%
운영중 40
23.8%
등 32
19.0%

폐업일자
Date

MISSING 

Distinct49
Distinct (%)94.2%
Missing84
Missing (%)61.8%
Memory size1.2 KiB
Minimum2002-03-19 00:00:00
Maximum2024-01-23 00:00:00
2024-05-10T21:06:21.310910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:21.693502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)

다중이용업소여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing136
Missing (%)100.0%
Memory size1.3 KiB

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing136
Missing (%)100.0%
Memory size1.3 KiB

위생업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
휴게음식점
72 
<NA>
64 

Length

Max length5
Median length5
Mean length4.5294118
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
휴게음식점 72
52.9%
<NA> 64
47.1%

Length

2024-05-10T21:06:22.026262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:06:22.268842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
휴게음식점 72
52.9%
na 64
47.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
철도역구내
136 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
철도역구내 136
100.0%

Length

2024-05-10T21:06:22.643348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:06:22.954012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
철도역구내 136
100.0%

소재지도로명주소
Text

MISSING 

Distinct85
Distinct (%)71.4%
Missing17
Missing (%)12.5%
Memory size1.2 KiB
2024-05-10T21:06:23.476272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length43
Mean length34.915966
Min length18

Characters and Unicode

Total characters4155
Distinct characters169
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

Unique57 ?
Unique (%)47.9%

Sample

1st row경기도 고양시 덕양구 소원로 102 (행신동,외 3필지 행신역사 2층일부)
2nd row경기도 고양시 일산서구 중앙로 지하 1569, 지하1층 일부호 (대화동, 대화역구내)
3rd row경기도 고양시 덕양구 소원로 102 (행신동,외 3필지 행신역사 2층일부)
4th row경기도 고양시 덕양구 고양대로 1429 (성사동)
5th row경기도 고양시 일산서구 중앙로 지하 1569
ValueCountFrequency (%)
경기도 119
 
13.0%
지하 40
 
4.4%
성남시 23
 
2.5%
성남대로 18
 
2.0%
2층 16
 
1.7%
부천시 16
 
1.7%
분당구 16
 
1.7%
남양주시 12
 
1.3%
송내동 12
 
1.3%
1층 12
 
1.3%
Other values (268) 632
69.0%
2024-05-10T21:06:24.546160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
799
 
19.2%
동 135
 
3.2%
경 131
 
3.2%
도 128
 
3.1%
, 121
 
2.9%
시 120
 
2.9%
기 120
 
2.9%
로 119
 
2.9%
( 115
 
2.8%
) 115
 
2.8%
Other values (159) 2252
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2504
60.3%
Space Separator 799
 
19.2%
Decimal Number 491
 
11.8%
Other Punctuation 121
 
2.9%
Open Punctuation 115
 
2.8%
Close Punctuation 115
 
2.8%
Dash Punctuation 9
 
0.2%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 135
 
5.4%
경 131
 
5.2%
도 128
 
5.1%
시 120
 
4.8%
기 120
 
4.8%
로 119
 
4.8%
역 97
 
3.9%
구 86
 
3.4%
지 73
 
2.9%
대 71
 
2.8%
Other values (143) 1424
56.9%
Decimal Number
ValueCountFrequency (%)
1 88
17.9%
2 87
17.7%
3 76
15.5%
0 51
10.4%
4 51
10.4%
5 44
9.0%
9 32
 
6.5%
6 27
 
5.5%
7 22
 
4.5%
8 13
 
2.6%
Space Separator
ValueCountFrequency (%)
799
100.0%
Other Punctuation
ValueCountFrequency (%)
, 121
100.0%
Open Punctuation
ValueCountFrequency (%)
( 115
100.0%
Close Punctuation
ValueCountFrequency (%)
) 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2504
60.3%
Common 1650
39.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 135
 
5.4%
경 131
 
5.2%
도 128
 
5.1%
시 120
 
4.8%
기 120
 
4.8%
로 119
 
4.8%
역 97
 
3.9%
구 86
 
3.4%
지 73
 
2.9%
대 71
 
2.8%
Other values (143) 1424
56.9%
Common
ValueCountFrequency (%)
799
48.4%
, 121
 
7.3%
( 115
 
7.0%
) 115
 
7.0%
1 88
 
5.3%
2 87
 
5.3%
3 76
 
4.6%
0 51
 
3.1%
4 51
 
3.1%
5 44
 
2.7%
Other values (5) 103
 
6.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2504
60.3%
ASCII 1651
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
799
48.4%
, 121
 
7.3%
( 115
 
7.0%
) 115
 
7.0%
1 88
 
5.3%
2 87
 
5.3%
3 76
 
4.6%
0 51
 
3.1%
4 51
 
3.1%
5 44
 
2.7%
Other values (6) 104
 
6.3%
Hangul
ValueCountFrequency (%)
동 135
 
5.4%
경 131
 
5.2%
도 128
 
5.1%
시 120
 
4.8%
기 120
 
4.8%
로 119
 
4.8%
역 97
 
3.9%
구 86
 
3.4%
지 73
 
2.9%
대 71
 
2.8%
Other values (143) 1424
56.9%

소재지지번주소
Text

Distinct125
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-05-10T21:06:25.031537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length36
Mean length29.382353
Min length16

Characters and Unicode

Total characters3996
Distinct characters152
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

Unique114 ?
Unique (%)83.8%

Sample

1st row경기도 고양시 덕양구 행신동 812 외 3필지 행신역사 2층일부
2nd row경기도 고양시 일산서구 대화동 2221번지 대화역구내
3rd row경기도 고양시 덕양구 행신동 812번지 외 3필지 행신역사 2층일부
4th row경기도 고양시 덕양구 화정동 1098-3번지 화정지하철역사 내
5th row경기도 고양시 덕양구 성사동 410-7번지
ValueCountFrequency (%)
경기도 136
 
15.9%
성남시 29
 
3.4%
분당구 22
 
2.6%
부천시 17
 
2.0%
지하1층 14
 
1.6%
송내동 13
 
1.5%
남양주시 12
 
1.4%
안산시 12
 
1.4%
의정부시 11
 
1.3%
2층 11
 
1.3%
Other values (276) 581
67.7%
2024-05-10T21:06:25.893324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
784
 
19.6%
동 157
 
3.9%
1 153
 
3.8%
도 144
 
3.6%
경 140
 
3.5%
기 137
 
3.4%
시 137
 
3.4%
지 112
 
2.8%
역 103
 
2.6%
2 103
 
2.6%
Other values (142) 2026
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2409
60.3%
Space Separator 784
 
19.6%
Decimal Number 667
 
16.7%
Dash Punctuation 103
 
2.6%
Other Punctuation 17
 
0.4%
Open Punctuation 7
 
0.2%
Close Punctuation 7
 
0.2%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 157
 
6.5%
도 144
 
6.0%
경 140
 
5.8%
기 137
 
5.7%
시 137
 
5.7%
지 112
 
4.6%
역 103
 
4.3%
구 103
 
4.3%
번 79
 
3.3%
부 68
 
2.8%
Other values (124) 1229
51.0%
Decimal Number
ValueCountFrequency (%)
1 153
22.9%
2 103
15.4%
3 71
10.6%
4 62
9.3%
6 62
9.3%
5 51
 
7.6%
0 51
 
7.6%
8 42
 
6.3%
7 39
 
5.8%
9 33
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 16
94.1%
. 1
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
L 1
50.0%
Space Separator
ValueCountFrequency (%)
784
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2409
60.3%
Common 1585
39.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 157
 
6.5%
도 144
 
6.0%
경 140
 
5.8%
기 137
 
5.7%
시 137
 
5.7%
지 112
 
4.6%
역 103
 
4.3%
구 103
 
4.3%
번 79
 
3.3%
부 68
 
2.8%
Other values (124) 1229
51.0%
Common
ValueCountFrequency (%)
784
49.5%
1 153
 
9.7%
2 103
 
6.5%
- 103
 
6.5%
3 71
 
4.5%
4 62
 
3.9%
6 62
 
3.9%
5 51
 
3.2%
0 51
 
3.2%
8 42
 
2.6%
Other values (6) 103
 
6.5%
Latin
ValueCountFrequency (%)
A 1
50.0%
L 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2409
60.3%
ASCII 1587
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
784
49.4%
1 153
 
9.6%
2 103
 
6.5%
- 103
 
6.5%
3 71
 
4.5%
4 62
 
3.9%
6 62
 
3.9%
5 51
 
3.2%
0 51
 
3.2%
8 42
 
2.6%
Other values (8) 105
 
6.6%
Hangul
ValueCountFrequency (%)
동 157
 
6.5%
도 144
 
6.0%
경 140
 
5.8%
기 137
 
5.7%
시 137
 
5.7%
지 112
 
4.6%
역 103
 
4.3%
구 103
 
4.3%
번 79
 
3.3%
부 68
 
2.8%
Other values (124) 1229
51.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct57
Distinct (%)43.8%
Missing6
Missing (%)4.4%
Infinite0
Infinite (%)0.0%
Mean13599.792
Minimum10097
Maximum18412
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T21:06:26.306813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10097
5-th percentile10500
Q112210
median13609
Q314742
95-th percentile16476.05
Maximum18412
Range8315
Interquartile range (IQR)2532

Descriptive statistics

Standard deviation1776.6585
Coefficient of variation (CV)0.13063865
Kurtosis-0.31802895
Mean13599.792
Median Absolute Deviation (MAD)1350
Skewness0.10757507
Sum1767973
Variance3156515.5
MonotonicityNot monotonic
2024-05-10T21:06:26.780221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14742 11
 
8.1%
13497 8
 
5.9%
13951 5
 
3.7%
11696 5
 
3.7%
15431 5
 
3.7%
12259 5
 
3.7%
13376 4
 
2.9%
12210 4
 
2.9%
11922 3
 
2.2%
15809 3
 
2.2%
Other values (47) 77
56.6%
(Missing) 6
 
4.4%
ValueCountFrequency (%)
10097 1
 
0.7%
10293 1
 
0.7%
10381 2
1.5%
10387 1
 
0.7%
10500 3
2.2%
10523 2
1.5%
11307 2
1.5%
11350 2
1.5%
11496 1
 
0.7%
11643 1
 
0.7%
ValueCountFrequency (%)
18412 2
1.5%
16896 2
1.5%
16622 2
1.5%
16571 1
 
0.7%
16360 2
1.5%
16081 1
 
0.7%
15869 1
 
0.7%
15851 1
 
0.7%
15809 3
2.2%
15517 2
1.5%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct60
Distinct (%)47.2%
Missing9
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean37.489082
Minimum37.206811
Maximum37.947952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T21:06:27.272563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.206811
5-th percentile37.300976
Q137.378655
median37.441642
Q337.608845
95-th percentile37.743663
Maximum37.947952
Range0.74114111
Interquartile range (IQR)0.23019081

Descriptive statistics

Standard deviation0.15778765
Coefficient of variation (CV)0.0042088961
Kurtosis0.036143155
Mean37.489082
Median Absolute Deviation (MAD)0.10168251
Skewness0.74533928
Sum4761.1134
Variance0.024896942
MonotonicityNot monotonic
2024-05-10T21:06:27.767322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4876739598 11
 
8.1%
37.411061479 8
 
5.9%
37.6088454388 5
 
3.7%
37.4015357346 5
 
3.7%
37.3279765041 5
 
3.7%
37.7379343921 5
 
3.7%
37.4321816494 4
 
2.9%
37.5868984794 4
 
2.9%
37.4357317261 3
 
2.2%
37.4930021636 3
 
2.2%
Other values (50) 74
54.4%
(Missing) 9
 
6.6%
ValueCountFrequency (%)
37.2068110952 2
1.5%
37.261742817 1
0.7%
37.2656360259 2
1.5%
37.3001829323 2
1.5%
37.302827882 2
1.5%
37.3101404775 1
0.7%
37.3160151192 1
0.7%
37.3169134593 2
1.5%
37.321121147 1
0.7%
37.3248835992 1
0.7%
ValueCountFrequency (%)
37.9479522078 1
 
0.7%
37.9278110071 1
 
0.7%
37.8918798163 2
 
1.5%
37.7736496761 1
 
0.7%
37.7483744241 1
 
0.7%
37.7436629733 2
 
1.5%
37.7379343921 5
3.7%
37.7241850058 2
 
1.5%
37.7134036548 1
 
0.7%
37.6759548984 2
 
1.5%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct60
Distinct (%)47.2%
Missing9
Missing (%)6.6%
Infinite0
Infinite (%)0.0%
Mean126.99448
Minimum126.71983
Maximum127.49176
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-05-10T21:06:28.492869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.71983
5-th percentile126.75278
Q1126.8342
median127.00556
Q3127.12872
95-th percentile127.20878
Maximum127.49176
Range0.77193297
Interquartile range (IQR)0.294521

Descriptive statistics

Standard deviation0.16912404
Coefficient of variation (CV)0.0013317432
Kurtosis0.079683902
Mean126.99448
Median Absolute Deviation (MAD)0.12316283
Skewness0.30577715
Sum16128.3
Variance0.028602942
MonotonicityNot monotonic
2024-05-10T21:06:29.004120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.752782027 11
 
8.1%
127.1287246805 8
 
5.9%
127.1611782671 5
 
3.7%
126.9767041488 5
 
3.7%
126.7872918171 5
 
3.7%
127.045835705 5
 
3.7%
127.1290386086 4
 
2.9%
127.2087814585 4
 
2.9%
127.0055618471 3
 
2.2%
127.4917645803 3
 
2.2%
Other values (50) 74
54.4%
(Missing) 9
 
6.6%
ValueCountFrequency (%)
126.71983161 1
 
0.7%
126.7450951268 1
 
0.7%
126.7473030513 2
 
1.5%
126.752782027 11
8.1%
126.7610450549 1
 
0.7%
126.7644882326 2
 
1.5%
126.7764902399 2
 
1.5%
126.7826449277 1
 
0.7%
126.7872918171 5
3.7%
126.8220323077 2
 
1.5%
ValueCountFrequency (%)
127.4917645803 3
 
2.2%
127.3118359189 1
 
0.7%
127.2444371219 2
 
1.5%
127.2087814585 4
2.9%
127.1611782671 5
3.7%
127.1608483796 1
 
0.7%
127.1597973452 2
 
1.5%
127.1436205695 3
 
2.2%
127.1290386086 4
2.9%
127.1287246805 8
5.9%

Interactions

2024-05-10T21:06:15.872609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:14.111117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:14.983492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:16.132327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:14.348185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:15.283358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:16.460165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:14.652301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:15.571063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:06:29.424749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명인허가일자영업상태명폐업일자소재지도로명주소소재지우편번호WGS84위도WGS84경도
시군명1.0000.9990.6421.0001.0000.9900.9610.953
인허가일자0.9991.0000.6210.9880.9900.9990.9960.994
영업상태명0.6420.6211.0001.0000.5140.3740.3540.321
폐업일자1.0000.9881.0001.0000.9841.0001.0001.000
소재지도로명주소1.0000.9900.5140.9841.0001.0001.0001.000
소재지우편번호0.9900.9990.3741.0001.0001.0000.8730.832
WGS84위도0.9610.9960.3541.0001.0000.8731.0000.709
WGS84경도0.9530.9940.3211.0001.0000.8320.7091.000
2024-05-10T21:06:29.723967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명위생업종명
시군명1.0000.3311.000
영업상태명0.3311.0001.000
위생업종명1.0001.0001.000
2024-05-10T21:06:29.945617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태명위생업종명
소재지우편번호1.000-0.847-0.3970.8980.2191.000
WGS84위도-0.8471.0000.1660.7620.1611.000
WGS84경도-0.3970.1661.0000.7570.2051.000
시군명0.8980.7620.7571.0000.3311.000
영업상태명0.2190.1610.2050.3311.0001.000
위생업종명1.0001.0001.0001.0001.0001.000

Missing values

2024-05-10T21:06:16.855329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:06:17.458691image/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.
2024-05-10T21:06:17.782238image/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

시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0고양시행신역 카페센트2011-08-12영업<NA><NA><NA><NA>철도역구내경기도 고양시 덕양구 소원로 102 (행신동,외 3필지 행신역사 2층일부)경기도 고양시 덕양구 행신동 812 외 3필지 행신역사 2층일부1052337.61215126.834204
1고양시대화역 마리야20170329운영중<NA><NA><NA>휴게음식점철도역구내경기도 고양시 일산서구 중앙로 지하 1569, 지하1층 일부호 (대화동, 대화역구내)경기도 고양시 일산서구 대화동 2221번지 대화역구내1038137.675955126.747303
2고양시코레일유통(주)히코코20110812운영중<NA><NA><NA>휴게음식점철도역구내경기도 고양시 덕양구 소원로 102 (행신동,외 3필지 행신역사 2층일부)경기도 고양시 덕양구 행신동 812번지 외 3필지 행신역사 2층일부1052337.61215126.834204
3고양시커피앤스위트 화정역점20101126운영중<NA><NA><NA>휴게음식점철도역구내<NA>경기도 고양시 덕양구 화정동 1098-3번지 화정지하철역사 내1050037.634786126.832327
4고양시원당역사던킨도너츠20091123운영중<NA><NA><NA>휴게음식점철도역구내경기도 고양시 덕양구 고양대로 1429 (성사동)경기도 고양시 덕양구 성사동 410-7번지1029337.653435126.843109
5고양시후식화정역점20101126폐업20220708<NA><NA><NA>철도역구내<NA>경기도 고양시 덕양구 화정동 1098-3 화정지하철역사 내1050037.634786126.832327
6고양시피자스토리20100212폐업 등20111212<NA><NA>휴게음식점철도역구내경기도 고양시 일산서구 중앙로 지하 1569경기도 고양시 일산서구 대화동 2221번지 대화역구내지하1층일부1038137.675955126.747303
7고양시미스터도넛주엽역점20091214폐업 등20110422<NA><NA>휴게음식점철도역구내경기도 고양시 일산서구 중앙로 지하 1432경기도 고양시 일산서구 주엽동 166-7번지 주엽역 구내 지하1층일부1038737.670436126.761045
8고양시코레일유통 휴게음식점120100826폐업 등20100909<NA><NA>휴게음식점철도역구내<NA>경기도 고양시 덕양구 화정동 1098-3번지 화정지하철역 내1050037.634786126.832327
9과천시대공원역 구이점20060202폐업 등20171103<NA><NA>휴게음식점철도역구내경기도 과천시 대공원대로 지하 50경기도 과천시 과천동 727-1 일부번지 대공원역 구내1382937.435732127.005562
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
126의정부시와플대학20161209운영중<NA><NA><NA>휴게음식점철도역구내경기도 의정부시 평화로 363, 지상2층 (호원동, 회룡역사)경기도 의정부시 호원동 50-5번지 회룡역사, 지상2층1170537.724185127.047088
127의정부시부산오뎅20131126운영중<NA><NA><NA>휴게음식점철도역구내경기도 의정부시 평화로 525, 지상2층 (의정부동, 의정부역 대합실)경기도 의정부시 의정부동 168-54번지 의정부역 2층 대합실1169637.737934127.045836
128의정부시맵땡20161214폐업20221229<NA><NA><NA>철도역구내경기도 의정부시 호국로 1305, 지상2층 (의정부동, 의정부경전철중앙역사)경기도 의정부시 의정부동 15-10 의정부경전철중앙역사, 지상2층1168937.743663127.049535
129의정부시부산오뎅2013-11-26폐업2023-06-20<NA><NA><NA>철도역구내경기도 의정부시 평화로 525, 지상2층 (의정부동, 의정부역 대합실)경기도 의정부시 의정부동 168-54 의정부역 2층 대합실1169637.737934127.045836
130의정부시(주)한국철도유통의정부국수20000623폐업 등20070724<NA><NA>휴게음식점철도역구내<NA>경기도 의정부시 의정부동 168-54번지1169637.737934127.045836
131의정부시코레일유통(주)3층푸드20020222폐업 등20090916<NA><NA>휴게음식점철도역구내<NA>경기도 의정부시 의정부동 168-54번지 외 3필지 지상3층1169637.737934127.045836
132의정부시스토리카페20130702폐업 등20160428<NA><NA>휴게음식점철도역구내경기도 의정부시 호암로 142, 지상3층 (호원동, 회룡역사내)경기도 의정부시 호원동 50-5번지 회룡역사 지상3층1164337.713404127.0467
133의정부시코레일유통(주)홈스넥20020222폐업 등20120322<NA><NA>휴게음식점철도역구내<NA>경기도 의정부시 의정부동 168-54번지 외 3필지 지상1층1169637.737934127.045836
134화성시데일리베이커리2015-06-16영업<NA><NA><NA><NA>철도역구내경기도 화성시 떡전골로 97, 2층 (진안동)경기도 화성시 진안동 824-11841237.206811127.033238
135화성시데일리베이커리20150616운영중<NA><NA><NA>휴게음식점철도역구내경기도 화성시 떡전골로 97, 2층 (진안동)경기도 화성시 진안동 824-1번지1841237.206811127.033238