Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells23642
Missing cells (%)16.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory124.0 B

Variable types

Categorical4
Text3
DateTime2
Boolean1
Unsupported1
Numeric3

Dataset

Description휴게음식점(편의점) 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=CPMB3F3D1SDTN6V7LTWE13467194&infSeq=1

Alerts

위생업태명 has constant value ""Constant
영업상태명 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
위생업종명 is highly overall correlated with 소재지우편번호 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with WGS84위도 and 2 other fieldsHigh correlation
다중이용업소여부 is highly overall correlated with 위생업종명High correlation
소재지우편번호 is highly overall correlated with 영업상태명 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
다중이용업소여부 is highly imbalanced (99.4%)Imbalance
폐업일자 has 7518 (75.2%) missing valuesMissing
다중이용업소여부 has 5744 (57.4%) missing valuesMissing
총시설규모(㎡) has 10000 (100.0%) missing valuesMissing
WGS84위도 has 113 (1.1%) missing valuesMissing
WGS84경도 has 113 (1.1%) missing valuesMissing
총시설규모(㎡) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-10 21:21:05.714341
Analysis finished2024-05-10 21:21:18.444816
Duration12.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
화성시
821 
부천시
709 
용인시
683 
평택시
651 
수원시
 
640
Other values (26)
6496 

Length

Max length4
Median length3
Mean length3.0857
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의왕시
2nd row부천시
3rd row성남시
4th row의정부시
5th row용인시

Common Values

ValueCountFrequency (%)
화성시 821
 
8.2%
부천시 709
 
7.1%
용인시 683
 
6.8%
평택시 651
 
6.5%
수원시 640
 
6.4%
안산시 544
 
5.4%
성남시 505
 
5.1%
김포시 462
 
4.6%
파주시 448
 
4.5%
고양시 403
 
4.0%
Other values (21) 4134
41.3%

Length

2024-05-10T21:21:18.657156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 821
 
8.2%
부천시 709
 
7.1%
용인시 683
 
6.8%
평택시 651
 
6.5%
수원시 640
 
6.4%
안산시 544
 
5.4%
성남시 505
 
5.1%
김포시 462
 
4.6%
파주시 448
 
4.5%
고양시 403
 
4.0%
Other values (21) 4134
41.3%

사업장명
Text

Distinct8883
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-10T21:21:19.433468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length10.5793
Min length2

Characters and Unicode

Total characters105793
Distinct characters707
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7882 ?
Unique (%)78.8%

Sample

1st row지에스GS25포일대림점
2nd row이마트24R부천심곡점
3rd row세븐일레븐성남모란본점
4th rowCU (녹양원룸점)
5th row미니스톱 용인교동점
ValueCountFrequency (%)
세븐일레븐 1603
 
10.5%
씨유 1047
 
6.8%
gs25 742
 
4.8%
지에스25 408
 
2.7%
이마트24 394
 
2.6%
미니스톱 300
 
2.0%
지에스(gs)25 209
 
1.4%
cu 81
 
0.5%
씨유(cu 47
 
0.3%
지에스25(gs25 46
 
0.3%
Other values (8752) 10455
68.2%
2024-05-10T21:21:20.494673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 9184
 
8.7%
5344
 
5.1%
븐 5120
 
4.8%
2 3809
 
3.6%
5 3050
 
2.9%
일 2979
 
2.8%
세 2690
 
2.5%
스 2662
 
2.5%
레 2654
 
2.5%
유 2242
 
2.1%
Other values (697) 66059
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 84178
79.6%
Decimal Number 7842
 
7.4%
Uppercase Letter 5858
 
5.5%
Space Separator 5344
 
5.1%
Close Punctuation 1205
 
1.1%
Open Punctuation 1204
 
1.1%
Lowercase Letter 141
 
0.1%
Other Punctuation 13
 
< 0.1%
Dash Punctuation 4
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 9184
 
10.9%
븐 5120
 
6.1%
일 2979
 
3.5%
세 2690
 
3.2%
스 2662
 
3.2%
레 2654
 
3.2%
유 2242
 
2.7%
씨 2176
 
2.6%
지 1911
 
2.3%
이 1568
 
1.9%
Other values (633) 50992
60.6%
Uppercase Letter
ValueCountFrequency (%)
S 2209
37.7%
G 2204
37.6%
C 516
 
8.8%
U 446
 
7.6%
R 145
 
2.5%
I 74
 
1.3%
L 43
 
0.7%
K 33
 
0.6%
T 29
 
0.5%
A 21
 
0.4%
Other values (15) 138
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
s 23
16.3%
e 15
10.6%
g 15
10.6%
u 14
9.9%
t 13
9.2%
c 12
8.5%
r 8
 
5.7%
a 8
 
5.7%
f 5
 
3.5%
i 5
 
3.5%
Other values (9) 23
16.3%
Decimal Number
ValueCountFrequency (%)
2 3809
48.6%
5 3050
38.9%
4 697
 
8.9%
1 106
 
1.4%
3 80
 
1.0%
6 43
 
0.5%
7 27
 
0.3%
9 13
 
0.2%
8 12
 
0.2%
0 5
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 6
46.2%
& 5
38.5%
, 1
 
7.7%
/ 1
 
7.7%
Math Symbol
ValueCountFrequency (%)
< 2
50.0%
> 2
50.0%
Space Separator
ValueCountFrequency (%)
5344
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1205
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 84178
79.6%
Common 15616
 
14.8%
Latin 5999
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 9184
 
10.9%
븐 5120
 
6.1%
일 2979
 
3.5%
세 2690
 
3.2%
스 2662
 
3.2%
레 2654
 
3.2%
유 2242
 
2.7%
씨 2176
 
2.6%
지 1911
 
2.3%
이 1568
 
1.9%
Other values (633) 50992
60.6%
Latin
ValueCountFrequency (%)
S 2209
36.8%
G 2204
36.7%
C 516
 
8.6%
U 446
 
7.4%
R 145
 
2.4%
I 74
 
1.2%
L 43
 
0.7%
K 33
 
0.6%
T 29
 
0.5%
s 23
 
0.4%
Other values (34) 277
 
4.6%
Common
ValueCountFrequency (%)
5344
34.2%
2 3809
24.4%
5 3050
19.5%
) 1205
 
7.7%
( 1204
 
7.7%
4 697
 
4.5%
1 106
 
0.7%
3 80
 
0.5%
6 43
 
0.3%
7 27
 
0.2%
Other values (10) 51
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 84178
79.6%
ASCII 21615
 
20.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 9184
 
10.9%
븐 5120
 
6.1%
일 2979
 
3.5%
세 2690
 
3.2%
스 2662
 
3.2%
레 2654
 
3.2%
유 2242
 
2.7%
씨 2176
 
2.6%
지 1911
 
2.3%
이 1568
 
1.9%
Other values (633) 50992
60.6%
ASCII
ValueCountFrequency (%)
5344
24.7%
2 3809
17.6%
5 3050
14.1%
S 2209
10.2%
G 2204
10.2%
) 1205
 
5.6%
( 1204
 
5.6%
4 697
 
3.2%
C 516
 
2.4%
U 446
 
2.1%
Other values (54) 931
 
4.3%

인허가일자
Date

Distinct3216
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1988-05-09 00:00:00
Maximum2024-04-30 00:00:00
2024-05-10T21:21:20.880221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:21.266825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
영업
4276 
운영중
3242 
폐업
1468 
폐업 등
1014 

Length

Max length4
Median length2
Mean length2.527
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 4276
42.8%
운영중 3242
32.4%
폐업 1468
 
14.7%
폐업 등 1014
 
10.1%

Length

2024-05-10T21:21:21.730533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:21:22.010304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 4276
38.8%
운영중 3242
29.4%
폐업 2482
22.5%
등 1014
 
9.2%

폐업일자
Date

MISSING 

Distinct1396
Distinct (%)56.2%
Missing7518
Missing (%)75.2%
Memory size156.2 KiB
Minimum1996-12-24 00:00:00
Maximum2024-04-30 00:00:00
2024-05-10T21:21:22.307689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:22.619463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

다중이용업소여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing5744
Missing (%)57.4%
Memory size97.7 KiB
False
4254 
True
 
2
(Missing)
5744 
ValueCountFrequency (%)
False 4254
42.5%
True 2
 
< 0.1%
(Missing) 5744
57.4%
2024-05-10T21:21:22.941152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

총시설규모(㎡)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

위생업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
5744 
휴게음식점
4256 

Length

Max length5
Median length4
Mean length4.4256
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 5744
57.4%
휴게음식점 4256
42.6%

Length

2024-05-10T21:21:23.278228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:21:23.518291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 5744
57.4%
휴게음식점 4256
42.6%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
편의점
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
편의점 10000
100.0%

Length

2024-05-10T21:21:23.755762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:21:24.016651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
편의점 10000
100.0%

소재지도로명주소
Text

Distinct8949
Distinct (%)90.2%
Missing75
Missing (%)0.8%
Memory size156.2 KiB
2024-05-10T21:21:24.629088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length65
Mean length34.270529
Min length13

Characters and Unicode

Total characters340135
Distinct characters695
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8004 ?
Unique (%)80.6%

Sample

1st row경기도 의왕시 내손로 59, 의왕내손이편한세상 상가동 1층 103호 (내손동)
2nd row경기도 부천시 성주로 158, 상가동 지하3층 102호 일부호 (심곡본동, e편한세상 부천심곡)
3rd row경기도 성남시 중원구 둔촌대로101번길 6, 1층 (성남동)
4th row경기도 의정부시 녹양로103번길 36, 지상1층 (녹양동)
5th row경기도 용인시 기흥구 마북로 126 (마북동,1층)
ValueCountFrequency (%)
경기도 9925
 
13.7%
1층 5402
 
7.4%
일부호 1268
 
1.7%
일부 1011
 
1.4%
화성시 819
 
1.1%
부천시 707
 
1.0%
용인시 677
 
0.9%
평택시 649
 
0.9%
수원시 631
 
0.9%
상가동 616
 
0.8%
Other values (11010) 50829
70.1%
2024-05-10T21:21:25.849344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
62653
 
18.4%
1 20376
 
6.0%
시 10726
 
3.2%
동 10619
 
3.1%
, 10537
 
3.1%
기 10469
 
3.1%
도 10368
 
3.0%
경 10365
 
3.0%
로 9190
 
2.7%
) 8015
 
2.4%
Other values (685) 176817
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191236
56.2%
Space Separator 62653
 
18.4%
Decimal Number 56341
 
16.6%
Other Punctuation 10612
 
3.1%
Close Punctuation 8015
 
2.4%
Open Punctuation 8015
 
2.4%
Dash Punctuation 1770
 
0.5%
Uppercase Letter 1256
 
0.4%
Lowercase Letter 156
 
< 0.1%
Math Symbol 66
 
< 0.1%
Other values (2) 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10726
 
5.6%
동 10619
 
5.6%
기 10469
 
5.5%
도 10368
 
5.4%
경 10365
 
5.4%
로 9190
 
4.8%
층 6661
 
3.5%
호 5742
 
3.0%
부 5043
 
2.6%
일 4089
 
2.1%
Other values (610) 107964
56.5%
Uppercase Letter
ValueCountFrequency (%)
B 257
20.5%
A 180
14.3%
S 100
 
8.0%
I 82
 
6.5%
G 75
 
6.0%
C 74
 
5.9%
E 64
 
5.1%
T 51
 
4.1%
R 48
 
3.8%
L 47
 
3.7%
Other values (16) 278
22.1%
Lowercase Letter
ValueCountFrequency (%)
e 59
37.8%
c 11
 
7.1%
r 10
 
6.4%
t 9
 
5.8%
a 9
 
5.8%
l 7
 
4.5%
n 7
 
4.5%
s 7
 
4.5%
i 6
 
3.8%
o 6
 
3.8%
Other values (11) 25
16.0%
Decimal Number
ValueCountFrequency (%)
1 20376
36.2%
2 6532
 
11.6%
0 6252
 
11.1%
3 4608
 
8.2%
4 3926
 
7.0%
5 3589
 
6.4%
6 3064
 
5.4%
7 2913
 
5.2%
8 2616
 
4.6%
9 2465
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 10537
99.3%
. 55
 
0.5%
@ 10
 
0.1%
& 6
 
0.1%
: 1
 
< 0.1%
· 1
 
< 0.1%
' 1
 
< 0.1%
/ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
57.1%
Ⅰ 5
35.7%
Ⅲ 1
 
7.1%
Math Symbol
ValueCountFrequency (%)
~ 63
95.5%
+ 3
 
4.5%
Space Separator
ValueCountFrequency (%)
62653
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8015
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8015
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1770
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191233
56.2%
Common 147473
43.4%
Latin 1426
 
0.4%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10726
 
5.6%
동 10619
 
5.6%
기 10469
 
5.5%
도 10368
 
5.4%
경 10365
 
5.4%
로 9190
 
4.8%
층 6661
 
3.5%
호 5742
 
3.0%
부 5043
 
2.6%
일 4089
 
2.1%
Other values (607) 107961
56.5%
Latin
ValueCountFrequency (%)
B 257
18.0%
A 180
12.6%
S 100
 
7.0%
I 82
 
5.8%
G 75
 
5.3%
C 74
 
5.2%
E 64
 
4.5%
e 59
 
4.1%
T 51
 
3.6%
R 48
 
3.4%
Other values (40) 436
30.6%
Common
ValueCountFrequency (%)
62653
42.5%
1 20376
 
13.8%
, 10537
 
7.1%
) 8015
 
5.4%
( 8015
 
5.4%
2 6532
 
4.4%
0 6252
 
4.2%
3 4608
 
3.1%
4 3926
 
2.7%
5 3589
 
2.4%
Other values (15) 12970
 
8.8%
Han
ValueCountFrequency (%)
家 1
33.3%
苑 1
33.3%
美 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191233
56.2%
ASCII 148884
43.8%
Number Forms 14
 
< 0.1%
CJK 3
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
62653
42.1%
1 20376
 
13.7%
, 10537
 
7.1%
) 8015
 
5.4%
( 8015
 
5.4%
2 6532
 
4.4%
0 6252
 
4.2%
3 4608
 
3.1%
4 3926
 
2.6%
5 3589
 
2.4%
Other values (61) 14381
 
9.7%
Hangul
ValueCountFrequency (%)
시 10726
 
5.6%
동 10619
 
5.6%
기 10469
 
5.5%
도 10368
 
5.4%
경 10365
 
5.4%
로 9190
 
4.8%
층 6661
 
3.5%
호 5742
 
3.0%
부 5043
 
2.6%
일 4089
 
2.1%
Other values (607) 107961
56.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
57.1%
Ⅰ 5
35.7%
Ⅲ 1
 
7.1%
CJK
ValueCountFrequency (%)
家 1
33.3%
苑 1
33.3%
美 1
33.3%
None
ValueCountFrequency (%)
· 1
100.0%

소재지지번주소
Text

Distinct9798
Distinct (%)98.0%
Missing2
Missing (%)< 0.1%
Memory size156.2 KiB
2024-05-10T21:21:26.501985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length57
Mean length27.803661
Min length14

Characters and Unicode

Total characters277981
Distinct characters661
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9605 ?
Unique (%)96.1%

Sample

1st row경기도 의왕시 내손동 846 의왕내손이편한세상
2nd row경기도 부천시 심곡본동 820-2 e편한세상 부천심곡, 상가동 지하3층 102호 일부
3rd row경기도 성남시 중원구 성남동 4121번지 1층
4th row경기도 의정부시 녹양동 375-8번지 지상1층
5th row경기도 용인시 기흥구 마북동 168-6번지 1층
ValueCountFrequency (%)
경기도 9998
 
16.6%
1층 2710
 
4.5%
일부 1147
 
1.9%
화성시 821
 
1.4%
부천시 709
 
1.2%
용인시 683
 
1.1%
평택시 651
 
1.1%
수원시 640
 
1.1%
안산시 544
 
0.9%
성남시 505
 
0.8%
Other values (12985) 41731
69.4%
2024-05-10T21:21:27.664161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55109
19.8%
1 15873
 
5.7%
시 10570
 
3.8%
기 10392
 
3.7%
도 10349
 
3.7%
경 10091
 
3.6%
동 9677
 
3.5%
- 7427
 
2.7%
지 5906
 
2.1%
2 5831
 
2.1%
Other values (651) 136756
49.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158104
56.9%
Space Separator 55109
 
19.8%
Decimal Number 54327
 
19.5%
Dash Punctuation 7427
 
2.7%
Uppercase Letter 995
 
0.4%
Other Punctuation 776
 
0.3%
Open Punctuation 533
 
0.2%
Close Punctuation 533
 
0.2%
Lowercase Letter 123
 
< 0.1%
Math Symbol 40
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10570
 
6.7%
기 10392
 
6.6%
도 10349
 
6.5%
경 10091
 
6.4%
동 9677
 
6.1%
지 5906
 
3.7%
번 4280
 
2.7%
구 3851
 
2.4%
부 3763
 
2.4%
층 3674
 
2.3%
Other values (580) 85551
54.1%
Uppercase Letter
ValueCountFrequency (%)
B 174
17.5%
A 128
12.9%
S 91
 
9.1%
I 70
 
7.0%
G 64
 
6.4%
E 54
 
5.4%
C 50
 
5.0%
L 41
 
4.1%
T 39
 
3.9%
R 38
 
3.8%
Other values (16) 246
24.7%
Lowercase Letter
ValueCountFrequency (%)
e 52
42.3%
c 9
 
7.3%
r 9
 
7.3%
n 7
 
5.7%
i 6
 
4.9%
a 6
 
4.9%
t 6
 
4.9%
l 4
 
3.3%
d 4
 
3.3%
h 3
 
2.4%
Other values (9) 17
 
13.8%
Decimal Number
ValueCountFrequency (%)
1 15873
29.2%
2 5831
 
10.7%
0 5342
 
9.8%
3 4743
 
8.7%
4 4375
 
8.1%
5 4356
 
8.0%
6 3978
 
7.3%
7 3550
 
6.5%
8 3237
 
6.0%
9 3042
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 714
92.0%
. 42
 
5.4%
@ 11
 
1.4%
& 6
 
0.8%
# 1
 
0.1%
/ 1
 
0.1%
' 1
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
57.1%
Ⅰ 5
35.7%
Ⅲ 1
 
7.1%
Math Symbol
ValueCountFrequency (%)
~ 37
92.5%
+ 3
 
7.5%
Space Separator
ValueCountFrequency (%)
55109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7427
100.0%
Open Punctuation
ValueCountFrequency (%)
( 533
100.0%
Close Punctuation
ValueCountFrequency (%)
) 533
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158100
56.9%
Common 118745
42.7%
Latin 1132
 
0.4%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10570
 
6.7%
기 10392
 
6.6%
도 10349
 
6.5%
경 10091
 
6.4%
동 9677
 
6.1%
지 5906
 
3.7%
번 4280
 
2.7%
구 3851
 
2.4%
부 3763
 
2.4%
층 3674
 
2.3%
Other values (576) 85547
54.1%
Latin
ValueCountFrequency (%)
B 174
15.4%
A 128
 
11.3%
S 91
 
8.0%
I 70
 
6.2%
G 64
 
5.7%
E 54
 
4.8%
e 52
 
4.6%
C 50
 
4.4%
L 41
 
3.6%
T 39
 
3.4%
Other values (38) 369
32.6%
Common
ValueCountFrequency (%)
55109
46.4%
1 15873
 
13.4%
- 7427
 
6.3%
2 5831
 
4.9%
0 5342
 
4.5%
3 4743
 
4.0%
4 4375
 
3.7%
5 4356
 
3.7%
6 3978
 
3.4%
7 3550
 
3.0%
Other values (13) 8161
 
6.9%
Han
ValueCountFrequency (%)
家 1
25.0%
內 1
25.0%
苑 1
25.0%
美 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158098
56.9%
ASCII 119863
43.1%
Number Forms 14
 
< 0.1%
CJK 4
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55109
46.0%
1 15873
 
13.2%
- 7427
 
6.2%
2 5831
 
4.9%
0 5342
 
4.5%
3 4743
 
4.0%
4 4375
 
3.7%
5 4356
 
3.6%
6 3978
 
3.3%
7 3550
 
3.0%
Other values (58) 9279
 
7.7%
Hangul
ValueCountFrequency (%)
시 10570
 
6.7%
기 10392
 
6.6%
도 10349
 
6.5%
경 10091
 
6.4%
동 9677
 
6.1%
지 5906
 
3.7%
번 4280
 
2.7%
구 3851
 
2.4%
부 3763
 
2.4%
층 3674
 
2.3%
Other values (574) 85545
54.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
57.1%
Ⅰ 5
35.7%
Ⅲ 1
 
7.1%
CJK
ValueCountFrequency (%)
家 1
25.0%
內 1
25.0%
苑 1
25.0%
美 1
25.0%
Compat Jamo
ValueCountFrequency (%)
ㄷ 1
50.0%
ㅁ 1
50.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct4293
Distinct (%)43.3%
Missing77
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean192277.55
Minimum10003
Maximum487915
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T21:21:28.100946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10003
5-th percentile10826
Q114087
median17767
Q3445235
95-th percentile477811.2
Maximum487915
Range477912
Interquartile range (IQR)431148

Descriptive statistics

Standard deviation214103.55
Coefficient of variation (CV)1.113513
Kurtosis-1.8368333
Mean192277.55
Median Absolute Deviation (MAD)6419
Skewness0.38213649
Sum1.9079702 × 109
Variance4.584033 × 1010
MonotonicityNot monotonic
2024-05-10T21:21:28.537690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
415060 41
 
0.4%
10071 24
 
0.2%
447140 23
 
0.2%
445160 19
 
0.2%
483030 19
 
0.2%
472501 19
 
0.2%
415080 19
 
0.2%
429856 18
 
0.2%
14786 18
 
0.2%
459813 17
 
0.2%
Other values (4283) 9706
97.1%
(Missing) 77
 
0.8%
ValueCountFrequency (%)
10003 1
 
< 0.1%
10008 1
 
< 0.1%
10009 1
 
< 0.1%
10010 3
< 0.1%
10011 5
0.1%
10012 2
 
< 0.1%
10014 1
 
< 0.1%
10016 1
 
< 0.1%
10017 3
< 0.1%
10018 1
 
< 0.1%
ValueCountFrequency (%)
487915 2
 
< 0.1%
487914 4
< 0.1%
487913 5
0.1%
487911 1
 
< 0.1%
487899 1
 
< 0.1%
487896 2
 
< 0.1%
487892 6
0.1%
487883 2
 
< 0.1%
487882 1
 
< 0.1%
487878 2
 
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7964
Distinct (%)80.6%
Missing113
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean37.422109
Minimum36.928476
Maximum38.185874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T21:21:29.390027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.928476
5-th percentile37.017492
Q137.259372
median37.38883
Q337.634203
95-th percentile37.824844
Maximum38.185874
Range1.2573975
Interquartile range (IQR)0.37483188

Descriptive statistics

Standard deviation0.23945902
Coefficient of variation (CV)0.006398865
Kurtosis-0.63611399
Mean37.422109
Median Absolute Deviation (MAD)0.16206488
Skewness0.23536967
Sum369992.39
Variance0.057340624
MonotonicityNot monotonic
2024-05-10T21:21:29.957685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4017965187 6
 
0.1%
37.3970275535 6
 
0.1%
37.3039712756 6
 
0.1%
37.393257409 5
 
0.1%
37.4811539491 5
 
0.1%
37.7319945034 5
 
0.1%
37.5000449964 5
 
0.1%
37.3509798931 4
 
< 0.1%
37.487843769 4
 
< 0.1%
37.7468858429 4
 
< 0.1%
Other values (7954) 9837
98.4%
(Missing) 113
 
1.1%
ValueCountFrequency (%)
36.9284762331 1
< 0.1%
36.9390963076 1
< 0.1%
36.9445891982 1
< 0.1%
36.9448447964 1
< 0.1%
36.9449600423 1
< 0.1%
36.945223949 1
< 0.1%
36.945845635 1
< 0.1%
36.9494769474 1
< 0.1%
36.9522591921 2
< 0.1%
36.9527499579 1
< 0.1%
ValueCountFrequency (%)
38.1858737821 1
 
< 0.1%
38.1416766138 1
 
< 0.1%
38.1334276678 1
 
< 0.1%
38.122598679 2
< 0.1%
38.1084726669 1
 
< 0.1%
38.1056939412 2
< 0.1%
38.1005066857 1
 
< 0.1%
38.1002521779 1
 
< 0.1%
38.0914319891 1
 
< 0.1%
38.0910958227 3
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7964
Distinct (%)80.6%
Missing113
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean127.00764
Minimum126.5324
Maximum127.75406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-10T21:21:30.479735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5324
5-th percentile126.70858
Q1126.82498
median127.03344
Q3127.13582
95-th percentile127.36713
Maximum127.75406
Range1.221653
Interquartile range (IQR)0.31084165

Descriptive statistics

Standard deviation0.20811597
Coefficient of variation (CV)0.0016386099
Kurtosis0.043115943
Mean127.00764
Median Absolute Deviation (MAD)0.15432975
Skewness0.37700691
Sum1255724.5
Variance0.043312258
MonotonicityNot monotonic
2024-05-10T21:21:30.976320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9910176434 6
 
0.1%
126.9743742407 6
 
0.1%
127.1046527186 6
 
0.1%
126.9347696759 5
 
0.1%
126.7813152457 5
 
0.1%
126.7466453308 5
 
0.1%
126.7811115921 5
 
0.1%
127.1104696178 4
 
< 0.1%
126.7830949203 4
 
< 0.1%
127.0461782874 4
 
< 0.1%
Other values (7954) 9837
98.4%
(Missing) 113
 
1.1%
ValueCountFrequency (%)
126.53240288 1
 
< 0.1%
126.5367878817 1
 
< 0.1%
126.5434441568 1
 
< 0.1%
126.5485079113 1
 
< 0.1%
126.5507752527 1
 
< 0.1%
126.5513354228 1
 
< 0.1%
126.5516304184 1
 
< 0.1%
126.5541379101 1
 
< 0.1%
126.5541581093 3
< 0.1%
126.5542252238 1
 
< 0.1%
ValueCountFrequency (%)
127.7540559028 1
< 0.1%
127.7105943188 1
< 0.1%
127.6642792342 2
< 0.1%
127.6628124288 1
< 0.1%
127.6621119016 2
< 0.1%
127.6594616227 1
< 0.1%
127.6552913078 1
< 0.1%
127.6531572174 2
< 0.1%
127.6507481685 1
< 0.1%
127.6482480426 1
< 0.1%

Interactions

2024-05-10T21:21:16.122648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:14.316784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:15.290252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:16.400811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:14.585603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:15.560915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:16.675576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:15.018014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:21:15.833228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:21:31.275381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명다중이용업소여부소재지우편번호WGS84위도WGS84경도
시군명1.0000.2390.0000.7200.9510.932
영업상태명0.2391.0000.0000.6540.1410.103
다중이용업소여부0.0000.0001.0000.0000.0000.000
소재지우편번호0.7200.6540.0001.0000.4170.531
WGS84위도0.9510.1410.0000.4171.0000.623
WGS84경도0.9320.1030.0000.5310.6231.000
2024-05-10T21:21:31.580516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명위생업종명시군명다중이용업소여부
영업상태명1.0001.0000.1260.000
위생업종명1.0001.0001.0001.000
시군명0.1261.0001.0000.000
다중이용업소여부0.0001.0000.0001.000
2024-05-10T21:21:31.861199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명영업상태명다중이용업소여부위생업종명
소재지우편번호1.000-0.3170.2650.4960.6800.0001.000
WGS84위도-0.3171.000-0.1950.7360.0840.0001.000
WGS84경도0.265-0.1951.0000.6770.0620.0001.000
시군명0.4960.7360.6771.0000.1260.0001.000
영업상태명0.6800.0840.0620.1261.0000.0001.000
다중이용업소여부0.0000.0000.0000.0000.0001.0001.000
위생업종명1.0001.0001.0001.0001.0001.0001.000

Missing values

2024-05-10T21:21:17.015172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:21:17.624047image/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.
2024-05-10T21:21:18.149250image/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
8613의왕시지에스GS25포일대림점20190627폐업20211221<NA><NA><NA>편의점경기도 의왕시 내손로 59, 의왕내손이편한세상 상가동 1층 103호 (내손동)경기도 의왕시 내손동 846 의왕내손이편한세상1602537.386335126.977985
2826부천시이마트24R부천심곡점20210804영업<NA><NA><NA><NA>편의점경기도 부천시 성주로 158, 상가동 지하3층 102호 일부호 (심곡본동, e편한세상 부천심곡)경기도 부천시 심곡본동 820-2 e편한세상 부천심곡, 상가동 지하3층 102호 일부1474737.478428126.773345
3861성남시세븐일레븐성남모란본점20170405운영중<NA>N<NA>휴게음식점편의점경기도 성남시 중원구 둔촌대로101번길 6, 1층 (성남동)경기도 성남시 중원구 성남동 4121번지 1층46282937.430329127.130427
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8133용인시미니스톱 용인교동점20090601운영중<NA>N<NA>휴게음식점편의점경기도 용인시 기흥구 마북로 126 (마북동,1층)경기도 용인시 기흥구 마북동 168-6번지 1층44650637.301584127.121715
9144이천시CU 이천신하점20190109영업<NA><NA><NA><NA>편의점경기도 이천시 부발읍 경충대로2265번길 27경기도 이천시 부발읍 신하리 397-41732837.260352127.473836
11839화성시씨유(CU) 화성무하로점20160317운영중<NA>N<NA>휴게음식점편의점경기도 화성시 팔탄면 무하로 168, 1층경기도 화성시 팔탄면 하저리 933-5번지 1층44595837.184175126.860905
6095안산시로얄식품스타프라자점19900504폐업 등20000920N<NA>휴게음식점편의점<NA>경기도 안산시 상록구 성포동 583번지 지층 38호42683737.322432126.844737
9998평택시세븐일레븐 평택청북부영점20220125영업<NA><NA><NA><NA>편의점경기도 평택시 청북읍 청북남로 277, 101호 (부영사랑으로)경기도 평택시 청북읍 옥길리 1104 부영사랑으로 101호1780937.017795126.913877
6748안양시씨유안양관양중앙점20190213폐업20210511<NA><NA><NA>편의점경기도 안양시 동안구 관악대로389번길 8, 일부 1층 (관양동)경기도 안양시 동안구 관양동 1433-14 일층 일부1393937.405274126.96608
시군명사업장명인허가일자영업상태명폐업일자다중이용업소여부총시설규모(㎡)위생업종명위생업태명소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
8933의정부시세븐일레븐 의정부본점20160415운영중<NA>N<NA>휴게음식점편의점경기도 의정부시 시민로 83, 109호 (의정부동)경기도 의정부시 의정부동 442-12번지 광장타워48081037.738822127.044502
3490부천시(주)웅진플레이도시 세븐일레븐2014-05-16폐업2018-10-08<NA><NA><NA>편의점경기도 부천시 원미구 조마루로 2 (상동, 부천체육문화센타 스포츠센타동 FF109호일부,FF110일부)경기도 부천시 원미구 상동 572-1 부천체육문화센타 스포츠센타동 FF109호일부,FF110일부1459237.498867126.745385
4121성남시씨유 성남SK테크노점20110126폐업 등20141015N<NA>휴게음식점편의점경기도 성남시 중원구 사기막골로 124, 비즈센터동 113호 (상대원동)경기도 성남시 중원구 상대원동 190-1번지 비즈센터동 113호46280737.439518127.177916
8407용인시미니스톱 수지풍덕천점20070831폐업 등20100616N<NA>휴게음식점편의점경기도 용인시 수지구 수지로296번길 51-7경기도 용인시 수지구 풍덕천동 1080-15번지 가람빌딩 103호44850937.321875127.094751
6569안양시세븐일레븐 안양미도점20170410영업<NA><NA><NA><NA>편의점경기도 안양시 만안구 안양로 29, 지상1층 (안양동)경기도 안양시 만안구 안양동 371-6 지상1층1409637.378646126.938562
9085이천시씨유이천백사점20151204영업<NA><NA><NA><NA>편의점경기도 이천시 백사면 청백리로 77, 1층경기도 이천시 백사면 모전리 533-1 (1층)1731637.304033127.470142
223고양시세븐일레븐행신역점2019-03-04영업<NA><NA><NA><NA>편의점경기도 고양시 덕양구 용현로5번길 24, 백산오피스텔 108(일부)호 (행신동)경기도 고양시 덕양구 행신동 763-2 외1필지 백산오피스텔 108호일부1052637.613533126.834996
5231시흥시씨유 시화라성점20130304운영중<NA>N<NA>휴게음식점편의점경기도 시흥시 산기대학로 29경기도 시흥시 정왕동 2164-8번지 101호42945037.351036126.714993
2046김포시씨유김포고촌점20110405폐업 등20121231N<NA>휴게음식점편의점경기도 김포시 고촌읍 장차로 4, 1층경기도 김포시 고촌읍 신곡리 532-84번지 1층41581137.602405126.769977
8085용인시세븐일레븐용인풍덕천사거리점20180207운영중<NA>N<NA>휴게음식점편의점경기도 용인시 수지구 풍덕천로190번길 25, 신건프라자 103호 일부호 (풍덕천동)경기도 용인시 수지구 풍덕천동 945번지 신건프라자 103호44885437.324309127.102548