Overview

Dataset statistics

Number of variables18
Number of observations10000
Missing cells73125
Missing cells (%)40.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 MiB
Average record size in memory160.0 B

Variable types

Categorical3
Text6
DateTime2
Unsupported3
Numeric4

Dataset

Description안전 상비의약품 판매업소 현황
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=82P31T89XJ65241384Q7118669&infSeq=1

Alerts

영업상태명 is highly overall correlated with 영업상태구분코드High correlation
영업상태구분코드 is highly overall correlated with 영업상태명High correlation
WGS84위도 is highly overall correlated with Y좌표값 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with X좌표값 and 1 other fieldsHigh correlation
X좌표값 is highly overall correlated with WGS84경도 and 1 other fieldsHigh correlation
Y좌표값 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
시군명 is highly overall correlated with WGS84위도 and 3 other fieldsHigh correlation
영업상태구분코드 is highly imbalanced (68.8%)Imbalance
인허가취소일자 has 10000 (100.0%) missing valuesMissing
폐업일자 has 6770 (67.7%) missing valuesMissing
소재지시설전화번호 has 9756 (97.6%) missing valuesMissing
소재지면적정보 has 10000 (100.0%) missing valuesMissing
도로명우편번호 has 8578 (85.8%) missing valuesMissing
WGS84위도 has 272 (2.7%) missing valuesMissing
WGS84경도 has 272 (2.7%) missing valuesMissing
업태구분명정보 has 10000 (100.0%) missing valuesMissing
X좌표값 has 8638 (86.4%) missing valuesMissing
Y좌표값 has 8638 (86.4%) missing valuesMissing
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:30:51.920285
Analysis finished2023-12-10 21:30:56.208512
Duration4.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
수원시
919 
성남시
721 
용인시
669 
고양시
665 
부천시
663 
Other values (27)
6363 

Length

Max length4
Median length3
Mean length3.0908
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row성남시
2nd row김포시
3rd row이천시
4th row양평군
5th row수원시

Common Values

ValueCountFrequency (%)
수원시 919
 
9.2%
성남시 721
 
7.2%
용인시 669
 
6.7%
고양시 665
 
6.7%
부천시 663
 
6.6%
안산시 606
 
6.1%
화성시 599
 
6.0%
평택시 569
 
5.7%
남양주시 429
 
4.3%
시흥시 397
 
4.0%
Other values (22) 3763
37.6%

Length

2023-12-11T06:30:56.270682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 919
 
9.2%
성남시 721
 
7.2%
용인시 669
 
6.7%
고양시 665
 
6.7%
부천시 663
 
6.6%
안산시 606
 
6.1%
화성시 599
 
6.0%
평택시 569
 
5.7%
남양주시 429
 
4.3%
시흥시 397
 
4.0%
Other values (22) 3763
37.6%

사업장명
Text

Distinct9208
Distinct (%)92.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:30:56.584179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length19
Mean length10.2464
Min length3

Characters and Unicode

Total characters102464
Distinct characters642
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8494 ?
Unique (%)84.9%

Sample

1st rowGS25 성남테크
2nd row365PLUS김포나비
3rd row씨유 이천대우점
4th rowCU양평한전점
5th row세븐일레븐수원조원증앙점
ValueCountFrequency (%)
gs25 1329
 
8.3%
씨유 1315
 
8.2%
세븐일레븐 1057
 
6.6%
미니스톱 421
 
2.6%
주)코리아세븐 322
 
2.0%
지에스25 311
 
1.9%
cu 276
 
1.7%
지에스(gs)25 95
 
0.6%
이마트24 76
 
0.5%
위드미 57
 
0.4%
Other values (8789) 10739
67.1%
2023-12-11T06:30:57.069891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 9187
 
9.0%
6017
 
5.9%
븐 3648
 
3.6%
2 3563
 
3.5%
5 3446
 
3.4%
S 2782
 
2.7%
G 2716
 
2.7%
유 2451
 
2.4%
씨 2324
 
2.3%
세 2193
 
2.1%
Other values (632) 64137
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79240
77.3%
Decimal Number 7620
 
7.4%
Uppercase Letter 7430
 
7.3%
Space Separator 6017
 
5.9%
Open Punctuation 974
 
1.0%
Close Punctuation 970
 
0.9%
Lowercase Letter 154
 
0.2%
Other Symbol 39
 
< 0.1%
Dash Punctuation 12
 
< 0.1%
Other Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 9187
 
11.6%
븐 3648
 
4.6%
유 2451
 
3.1%
씨 2324
 
2.9%
세 2193
 
2.8%
일 2152
 
2.7%
스 2114
 
2.7%
레 1673
 
2.1%
주 1477
 
1.9%
지 1426
 
1.8%
Other values (573) 50595
63.9%
Uppercase Letter
ValueCountFrequency (%)
S 2782
37.4%
G 2716
36.6%
C 817
 
11.0%
U 792
 
10.7%
K 63
 
0.8%
I 56
 
0.8%
L 37
 
0.5%
P 36
 
0.5%
A 18
 
0.2%
R 16
 
0.2%
Other values (12) 97
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
u 30
19.5%
s 22
14.3%
c 17
11.0%
l 16
10.4%
p 14
9.1%
g 8
 
5.2%
e 8
 
5.2%
i 5
 
3.2%
o 5
 
3.2%
r 5
 
3.2%
Other values (10) 24
15.6%
Decimal Number
ValueCountFrequency (%)
2 3563
46.8%
5 3446
45.2%
3 181
 
2.4%
6 154
 
2.0%
4 150
 
2.0%
1 84
 
1.1%
7 22
 
0.3%
8 11
 
0.1%
9 6
 
0.1%
0 3
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
& 6
75.0%
. 2
 
25.0%
Space Separator
ValueCountFrequency (%)
6017
100.0%
Open Punctuation
ValueCountFrequency (%)
( 974
100.0%
Close Punctuation
ValueCountFrequency (%)
) 970
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79279
77.4%
Common 15601
 
15.2%
Latin 7584
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 9187
 
11.6%
븐 3648
 
4.6%
유 2451
 
3.1%
씨 2324
 
2.9%
세 2193
 
2.8%
일 2152
 
2.7%
스 2114
 
2.7%
레 1673
 
2.1%
주 1477
 
1.9%
지 1426
 
1.8%
Other values (574) 50634
63.9%
Latin
ValueCountFrequency (%)
S 2782
36.7%
G 2716
35.8%
C 817
 
10.8%
U 792
 
10.4%
K 63
 
0.8%
I 56
 
0.7%
L 37
 
0.5%
P 36
 
0.5%
u 30
 
0.4%
s 22
 
0.3%
Other values (32) 233
 
3.1%
Common
ValueCountFrequency (%)
6017
38.6%
2 3563
22.8%
5 3446
22.1%
( 974
 
6.2%
) 970
 
6.2%
3 181
 
1.2%
6 154
 
1.0%
4 150
 
1.0%
1 84
 
0.5%
7 22
 
0.1%
Other values (6) 40
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79240
77.3%
ASCII 23185
 
22.6%
None 39
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 9187
 
11.6%
븐 3648
 
4.6%
유 2451
 
3.1%
씨 2324
 
2.9%
세 2193
 
2.8%
일 2152
 
2.7%
스 2114
 
2.7%
레 1673
 
2.1%
주 1477
 
1.9%
지 1426
 
1.8%
Other values (573) 50595
63.9%
ASCII
ValueCountFrequency (%)
6017
26.0%
2 3563
15.4%
5 3446
14.9%
S 2782
12.0%
G 2716
11.7%
( 974
 
4.2%
) 970
 
4.2%
C 817
 
3.5%
U 792
 
3.4%
3 181
 
0.8%
Other values (48) 927
 
4.0%
None
ValueCountFrequency (%)
㈜ 39
100.0%

인허가일자
Date

Distinct1972
Distinct (%)19.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2011-11-08 00:00:00
Maximum2023-12-04 00:00:00
2023-12-11T06:30:57.200140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:57.319630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

영업상태구분코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
8578 
13
996 
3
 
414
24
 
6
2
 
6

Length

Max length4
Median length4
Mean length3.6736
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 8578
85.8%
13 996
 
10.0%
3 414
 
4.1%
24 6
 
0.1%
2 6
 
0.1%

Length

2023-12-11T06:30:57.441495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:30:57.535183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 8578
85.8%
13 996
 
10.0%
3 414
 
4.1%
24 6
 
0.1%
2 6
 
0.1%

영업상태명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
운영중
5752 
폐업 등
2816 
영업중
996 
폐업
 
414
휴업 등
 
10
Other values (2)
 
12

Length

Max length4
Median length3
Mean length3.2412
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영중 5752
57.5%
폐업 등 2816
28.2%
영업중 996
 
10.0%
폐업 414
 
4.1%
휴업 등 10
 
0.1%
직권폐업 6
 
0.1%
휴업 6
 
0.1%

Length

2023-12-11T06:30:57.652797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:30:57.770323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영중 5752
44.8%
폐업 3230
25.2%
등 2826
22.0%
영업중 996
 
7.8%
휴업 16
 
0.1%
직권폐업 6
 
< 0.1%

폐업일자
Date

MISSING 

Distinct1382
Distinct (%)42.8%
Missing6770
Missing (%)67.7%
Memory size156.2 KiB
Minimum2012-04-30 00:00:00
Maximum2023-12-05 00:00:00
2023-12-11T06:30:57.888732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:58.025609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

소재지시설전화번호
Text

MISSING 

Distinct233
Distinct (%)95.5%
Missing9756
Missing (%)97.6%
Memory size156.2 KiB
2023-12-11T06:30:58.282344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length12
Mean length11.45082
Min length8

Characters and Unicode

Total characters2794
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique226 ?
Unique (%)92.6%

Sample

1st row031-667-0416
2nd row031-668-1528
3rd row031-438-1640
4th row031-8003-0654
5th row02-3442-8713
ValueCountFrequency (%)
1577-0711 4
 
1.6%
1577-8007 3
 
1.2%
02-1577-8007 3
 
1.2%
02-3284-8112 2
 
0.8%
031-422-7230 2
 
0.8%
1577-9621 2
 
0.8%
031-712-0122 2
 
0.8%
031-708-6725 1
 
0.4%
031-662-1498 1
 
0.4%
031-212--1031 1
 
0.4%
Other values (226) 226
91.5%
2023-12-11T06:30:58.642429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 428
15.3%
1 379
13.6%
0 358
12.8%
3 352
12.6%
2 248
8.9%
7 219
7.8%
5 187
6.7%
6 170
 
6.1%
4 166
 
5.9%
8 155
 
5.5%
Other values (3) 132
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2360
84.5%
Dash Punctuation 428
 
15.3%
Space Separator 5
 
0.2%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 379
16.1%
0 358
15.2%
3 352
14.9%
2 248
10.5%
7 219
9.3%
5 187
7.9%
6 170
7.2%
4 166
7.0%
8 155
6.6%
9 126
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 428
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2794
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 428
15.3%
1 379
13.6%
0 358
12.8%
3 352
12.6%
2 248
8.9%
7 219
7.8%
5 187
6.7%
6 170
 
6.1%
4 166
 
5.9%
8 155
 
5.5%
Other values (3) 132
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2794
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 428
15.3%
1 379
13.6%
0 358
12.8%
3 352
12.6%
2 248
8.9%
7 219
7.8%
5 187
6.7%
6 170
 
6.1%
4 166
 
5.9%
8 155
 
5.5%
Other values (3) 132
 
4.7%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

도로명우편번호
Text

MISSING 

Distinct1066
Distinct (%)75.0%
Missing8578
Missing (%)85.8%
Memory size156.2 KiB
2023-12-11T06:30:58.948529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0028129
Min length5

Characters and Unicode

Total characters7114
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique799 ?
Unique (%)56.2%

Sample

1st row12748
2nd row17767
3rd row18141
4th row12632
5th row12999
ValueCountFrequency (%)
17095 5
 
0.4%
11800 5
 
0.4%
10099 5
 
0.4%
12248 5
 
0.4%
17941 4
 
0.3%
10113 4
 
0.3%
12777 4
 
0.3%
17035 4
 
0.3%
18017 4
 
0.3%
10871 4
 
0.3%
Other values (1056) 1378
96.9%
2023-12-11T06:30:59.385865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1996
28.1%
4 635
 
8.9%
0 633
 
8.9%
7 623
 
8.8%
5 601
 
8.4%
6 573
 
8.1%
8 562
 
7.9%
2 548
 
7.7%
3 512
 
7.2%
9 429
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7112
> 99.9%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1996
28.1%
4 635
 
8.9%
0 633
 
8.9%
7 623
 
8.8%
5 601
 
8.5%
6 573
 
8.1%
8 562
 
7.9%
2 548
 
7.7%
3 512
 
7.2%
9 429
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7114
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1996
28.1%
4 635
 
8.9%
0 633
 
8.9%
7 623
 
8.8%
5 601
 
8.4%
6 573
 
8.1%
8 562
 
7.9%
2 548
 
7.7%
3 512
 
7.2%
9 429
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1996
28.1%
4 635
 
8.9%
0 633
 
8.9%
7 623
 
8.8%
5 601
 
8.4%
6 573
 
8.1%
8 562
 
7.9%
2 548
 
7.7%
3 512
 
7.2%
9 429
 
6.0%

소재지도로명주소
Text

Distinct9125
Distinct (%)91.4%
Missing16
Missing (%)0.2%
Memory size156.2 KiB
2023-12-11T06:30:59.713105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length58
Mean length30.326823
Min length17

Characters and Unicode

Total characters302783
Distinct characters663
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8348 ?
Unique (%)83.6%

Sample

1st row경기도 성남시 중원구 사기막골로 124 (상대원동, SKn테크노파크 메가센터동B2층201호)
2nd row경기도 김포시 김포한강8로 377 (구래동)
3rd row경기도 이천시 이섭대천로1407번길 18-2 (증포동)
4th row경기도 양평군 강상면 강남로 931
5th row경기도 수원시 장안구 금당로9번길 76, 1층 (조원동)
ValueCountFrequency (%)
경기도 9983
 
15.6%
1층 2270
 
3.5%
수원시 915
 
1.4%
성남시 720
 
1.1%
용인시 666
 
1.0%
고양시 665
 
1.0%
부천시 663
 
1.0%
101호 655
 
1.0%
안산시 606
 
0.9%
화성시 594
 
0.9%
Other values (9818) 46253
72.3%
2023-12-11T06:31:00.174371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54013
 
17.8%
1 15613
 
5.2%
시 10604
 
3.5%
동 10543
 
3.5%
기 10449
 
3.5%
도 10418
 
3.4%
경 10381
 
3.4%
로 9398
 
3.1%
) 8285
 
2.7%
( 8284
 
2.7%
Other values (653) 154795
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171441
56.6%
Space Separator 54013
 
17.8%
Decimal Number 50430
 
16.7%
Close Punctuation 8285
 
2.7%
Open Punctuation 8284
 
2.7%
Other Punctuation 7906
 
2.6%
Dash Punctuation 1628
 
0.5%
Uppercase Letter 630
 
0.2%
Math Symbol 80
 
< 0.1%
Lowercase Letter 75
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10604
 
6.2%
동 10543
 
6.1%
기 10449
 
6.1%
도 10418
 
6.1%
경 10381
 
6.1%
로 9398
 
5.5%
구 4384
 
2.6%
길 4076
 
2.4%
호 3917
 
2.3%
번 3103
 
1.8%
Other values (584) 94168
54.9%
Uppercase Letter
ValueCountFrequency (%)
B 119
18.9%
A 87
13.8%
S 48
 
7.6%
I 44
 
7.0%
K 39
 
6.2%
E 32
 
5.1%
C 32
 
5.1%
H 27
 
4.3%
L 27
 
4.3%
T 26
 
4.1%
Other values (15) 149
23.7%
Lowercase Letter
ValueCountFrequency (%)
e 39
52.0%
t 6
 
8.0%
h 5
 
6.7%
n 4
 
5.3%
s 4
 
5.3%
i 3
 
4.0%
l 3
 
4.0%
o 2
 
2.7%
r 2
 
2.7%
k 2
 
2.7%
Other values (5) 5
 
6.7%
Decimal Number
ValueCountFrequency (%)
1 15613
31.0%
2 6127
 
12.1%
0 6044
 
12.0%
3 4529
 
9.0%
4 3779
 
7.5%
5 3411
 
6.8%
6 3079
 
6.1%
7 2810
 
5.6%
8 2596
 
5.1%
9 2442
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 7835
99.1%
. 46
 
0.6%
@ 10
 
0.1%
& 4
 
0.1%
· 3
 
< 0.1%
/ 3
 
< 0.1%
# 2
 
< 0.1%
% 1
 
< 0.1%
; 1
 
< 0.1%
＃ 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
54.5%
Ⅲ 3
27.3%
Ⅰ 2
 
18.2%
Math Symbol
ValueCountFrequency (%)
~ 78
97.5%
∥ 2
 
2.5%
Space Separator
ValueCountFrequency (%)
54013
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8285
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8284
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1628
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171437
56.6%
Common 130626
43.1%
Latin 716
 
0.2%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10604
 
6.2%
동 10543
 
6.1%
기 10449
 
6.1%
도 10418
 
6.1%
경 10381
 
6.1%
로 9398
 
5.5%
구 4384
 
2.6%
길 4076
 
2.4%
호 3917
 
2.3%
번 3103
 
1.8%
Other values (581) 94164
54.9%
Latin
ValueCountFrequency (%)
B 119
16.6%
A 87
 
12.2%
S 48
 
6.7%
I 44
 
6.1%
e 39
 
5.4%
K 39
 
5.4%
E 32
 
4.5%
C 32
 
4.5%
H 27
 
3.8%
L 27
 
3.8%
Other values (33) 222
31.0%
Common
ValueCountFrequency (%)
54013
41.3%
1 15613
 
12.0%
) 8285
 
6.3%
( 8284
 
6.3%
, 7835
 
6.0%
2 6127
 
4.7%
0 6044
 
4.6%
3 4529
 
3.5%
4 3779
 
2.9%
5 3411
 
2.6%
Other values (16) 12706
 
9.7%
Han
ValueCountFrequency (%)
家 2
50.0%
美 1
25.0%
苑 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171436
56.6%
ASCII 131325
43.4%
Number Forms 11
 
< 0.1%
None 4
 
< 0.1%
CJK 4
 
< 0.1%
Math Operators 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54013
41.1%
1 15613
 
11.9%
) 8285
 
6.3%
( 8284
 
6.3%
, 7835
 
6.0%
2 6127
 
4.7%
0 6044
 
4.6%
3 4529
 
3.4%
4 3779
 
2.9%
5 3411
 
2.6%
Other values (53) 13405
 
10.2%
Hangul
ValueCountFrequency (%)
시 10604
 
6.2%
동 10543
 
6.1%
기 10449
 
6.1%
도 10418
 
6.1%
경 10381
 
6.1%
로 9398
 
5.5%
구 4384
 
2.6%
길 4076
 
2.4%
호 3917
 
2.3%
번 3103
 
1.8%
Other values (580) 94163
54.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
54.5%
Ⅲ 3
27.3%
Ⅰ 2
 
18.2%
None
ValueCountFrequency (%)
· 3
75.0%
＃ 1
 
25.0%
Math Operators
ValueCountFrequency (%)
∥ 2
100.0%
CJK
ValueCountFrequency (%)
家 2
50.0%
美 1
25.0%
苑 1
25.0%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
100.0%

소재지지번주소
Text

Distinct9015
Distinct (%)91.0%
Missing96
Missing (%)1.0%
Memory size156.2 KiB
2023-12-11T06:31:00.491521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length51
Mean length24.982431
Min length9

Characters and Unicode

Total characters247426
Distinct characters608
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8225 ?
Unique (%)83.0%

Sample

1st row경기도 성남시 중원구 190번지 1호 SKn테크노파크 메가센터동B2층201호
2nd row경기도 김포시 구래동 6888번지 2호
3rd row경기도 이천시 증포동 211번지 2호 외2필지
4th row경기도 양평군 강상면 병산리 29-3번지
5th row경기도 수원시 장안구 조원동 851번지 1호 1층
ValueCountFrequency (%)
경기도 9899
 
17.7%
수원시 899
 
1.6%
1호 872
 
1.6%
1층 801
 
1.4%
성남시 722
 
1.3%
용인시 665
 
1.2%
고양시 661
 
1.2%
부천시 660
 
1.2%
안산시 604
 
1.1%
화성시 587
 
1.0%
Other values (7842) 39684
70.8%
2023-12-11T06:31:01.005281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46251
18.7%
1 11913
 
4.8%
시 10354
 
4.2%
도 10228
 
4.1%
기 10228
 
4.1%
경 9949
 
4.0%
지 9768
 
3.9%
동 9336
 
3.8%
번 8915
 
3.6%
호 6833
 
2.8%
Other values (598) 113651
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150001
60.6%
Decimal Number 47643
 
19.3%
Space Separator 46251
 
18.7%
Dash Punctuation 2423
 
1.0%
Uppercase Letter 428
 
0.2%
Other Punctuation 420
 
0.2%
Open Punctuation 69
 
< 0.1%
Close Punctuation 68
 
< 0.1%
Lowercase Letter 63
 
< 0.1%
Math Symbol 49
 
< 0.1%
Other values (2) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10354
 
6.9%
도 10228
 
6.8%
기 10228
 
6.8%
경 9949
 
6.6%
지 9768
 
6.5%
동 9336
 
6.2%
번 8915
 
5.9%
호 6833
 
4.6%
구 4250
 
2.8%
양 2639
 
1.8%
Other values (534) 67501
45.0%
Uppercase Letter
ValueCountFrequency (%)
B 71
16.6%
A 59
13.8%
S 37
 
8.6%
K 28
 
6.5%
I 28
 
6.5%
C 24
 
5.6%
E 23
 
5.4%
L 21
 
4.9%
H 17
 
4.0%
T 16
 
3.7%
Other values (14) 104
24.3%
Lowercase Letter
ValueCountFrequency (%)
e 30
47.6%
t 5
 
7.9%
s 5
 
7.9%
h 4
 
6.3%
r 3
 
4.8%
n 3
 
4.8%
i 3
 
4.8%
l 3
 
4.8%
k 3
 
4.8%
o 2
 
3.2%
Other values (2) 2
 
3.2%
Decimal Number
ValueCountFrequency (%)
1 11913
25.0%
2 5127
10.8%
0 4819
10.1%
3 4417
 
9.3%
4 4079
 
8.6%
5 3990
 
8.4%
6 3762
 
7.9%
7 3594
 
7.5%
8 3058
 
6.4%
9 2884
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 379
90.2%
. 23
 
5.5%
@ 9
 
2.1%
/ 3
 
0.7%
· 3
 
0.7%
& 2
 
0.5%
# 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 47
95.9%
= 1
 
2.0%
∥ 1
 
2.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
60.0%
Ⅲ 2
 
20.0%
Ⅰ 2
 
20.0%
Space Separator
ValueCountFrequency (%)
46251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2423
100.0%
Open Punctuation
ValueCountFrequency (%)
( 69
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 149998
60.6%
Common 96923
39.2%
Latin 501
 
0.2%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10354
 
6.9%
도 10228
 
6.8%
기 10228
 
6.8%
경 9949
 
6.6%
지 9768
 
6.5%
동 9336
 
6.2%
번 8915
 
5.9%
호 6833
 
4.6%
구 4250
 
2.8%
양 2639
 
1.8%
Other values (532) 67498
45.0%
Latin
ValueCountFrequency (%)
B 71
14.2%
A 59
 
11.8%
S 37
 
7.4%
e 30
 
6.0%
K 28
 
5.6%
I 28
 
5.6%
C 24
 
4.8%
E 23
 
4.6%
L 21
 
4.2%
H 17
 
3.4%
Other values (29) 163
32.5%
Common
ValueCountFrequency (%)
46251
47.7%
1 11913
 
12.3%
2 5127
 
5.3%
0 4819
 
5.0%
3 4417
 
4.6%
4 4079
 
4.2%
5 3990
 
4.1%
6 3762
 
3.9%
7 3594
 
3.7%
8 3058
 
3.2%
Other values (14) 5913
 
6.1%
Han
ValueCountFrequency (%)
家 2
50.0%
苑 1
25.0%
美 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 149996
60.6%
ASCII 97410
39.4%
Number Forms 10
 
< 0.1%
None 4
 
< 0.1%
CJK 4
 
< 0.1%
Math Operators 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46251
47.5%
1 11913
 
12.2%
2 5127
 
5.3%
0 4819
 
4.9%
3 4417
 
4.5%
4 4079
 
4.2%
5 3990
 
4.1%
6 3762
 
3.9%
7 3594
 
3.7%
8 3058
 
3.1%
Other values (48) 6400
 
6.6%
Hangul
ValueCountFrequency (%)
시 10354
 
6.9%
도 10228
 
6.8%
기 10228
 
6.8%
경 9949
 
6.6%
지 9768
 
6.5%
동 9336
 
6.2%
번 8915
 
5.9%
호 6833
 
4.6%
구 4250
 
2.8%
양 2639
 
1.8%
Other values (530) 67496
45.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
60.0%
Ⅲ 2
 
20.0%
Ⅰ 2
 
20.0%
None
ValueCountFrequency (%)
· 3
75.0%
㈜ 1
 
25.0%
CJK
ValueCountFrequency (%)
家 2
50.0%
苑 1
25.0%
美 1
25.0%
Math Operators
ValueCountFrequency (%)
∥ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

소재지우편번호
Text

Distinct4424
Distinct (%)44.6%
Missing89
Missing (%)0.9%
Memory size156.2 KiB
2023-12-11T06:31:01.324100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4161033
Min length5

Characters and Unicode

Total characters53679
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2164 ?
Unique (%)21.8%

Sample

1st row462721
2nd row415080
3rd row467802
4th row12571
5th row440200
ValueCountFrequency (%)
420852 31
 
0.3%
447140 27
 
0.3%
410837 25
 
0.3%
472501 20
 
0.2%
16489 19
 
0.2%
480090 18
 
0.2%
459813 18
 
0.2%
480848 18
 
0.2%
11184 17
 
0.2%
472120 17
 
0.2%
Other values (4414) 9701
97.9%
2023-12-11T06:31:01.773902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10799
20.1%
4 8508
15.8%
8 5629
10.5%
0 5506
10.3%
2 4871
9.1%
6 4099
 
7.6%
5 4049
 
7.5%
3 3989
 
7.4%
7 3615
 
6.7%
9 2524
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53589
99.8%
Dash Punctuation 90
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10799
20.2%
4 8508
15.9%
8 5629
10.5%
0 5506
10.3%
2 4871
9.1%
6 4099
 
7.6%
5 4049
 
7.6%
3 3989
 
7.4%
7 3615
 
6.7%
9 2524
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53679
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 10799
20.1%
4 8508
15.8%
8 5629
10.5%
0 5506
10.3%
2 4871
9.1%
6 4099
 
7.6%
5 4049
 
7.5%
3 3989
 
7.4%
7 3615
 
6.7%
9 2524
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53679
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10799
20.1%
4 8508
15.8%
8 5629
10.5%
0 5506
10.3%
2 4871
9.1%
6 4099
 
7.6%
5 4049
 
7.5%
3 3989
 
7.4%
7 3615
 
6.7%
9 2524
 
4.7%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7816
Distinct (%)80.3%
Missing272
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean37.420982
Minimum36.920176
Maximum38.185232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:01.905751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.920176
5-th percentile37.016575
Q137.273148
median37.387758
Q337.619546
95-th percentile37.807866
Maximum38.185232
Range1.2650553
Interquartile range (IQR)0.34639837

Descriptive statistics

Standard deviation0.22716017
Coefficient of variation (CV)0.0060703957
Kurtosis-0.45679435
Mean37.420982
Median Absolute Deviation (MAD)0.13668088
Skewness0.23465824
Sum364031.31
Variance0.051601742
MonotonicityNot monotonic
2023-12-11T06:31:02.027987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.3196879674 5
 
0.1%
37.3172504315 5
 
0.1%
37.2424110308 5
 
0.1%
37.6757114107 5
 
0.1%
37.1305618256 5
 
0.1%
37.4872306675 4
 
< 0.1%
37.3690855069 4
 
< 0.1%
37.5008686102 4
 
< 0.1%
37.6555702667 4
 
< 0.1%
37.3058518358 4
 
< 0.1%
Other values (7806) 9683
96.8%
(Missing) 272
 
2.7%
ValueCountFrequency (%)
36.9201763461 1
< 0.1%
36.9237078934 2
< 0.1%
36.9374359077 1
< 0.1%
36.9386381812 1
< 0.1%
36.9390963076 1
< 0.1%
36.9433037262 2
< 0.1%
36.9449600423 2
< 0.1%
36.945845635 1
< 0.1%
36.9494769474 1
< 0.1%
36.9522591921 1
< 0.1%
ValueCountFrequency (%)
38.1852316508 1
 
< 0.1%
38.1581607278 1
 
< 0.1%
38.1334276678 1
 
< 0.1%
38.122598679 1
 
< 0.1%
38.1056939412 1
 
< 0.1%
38.1051802472 1
 
< 0.1%
38.0914319891 1
 
< 0.1%
38.0910958227 3
< 0.1%
38.091004052 1
 
< 0.1%
38.0909642099 2
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7816
Distinct (%)80.3%
Missing272
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean127.01147
Minimum126.53739
Maximum127.75406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:02.154441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53739
5-th percentile126.73883
Q1126.83831
median127.0374
Q3127.13062
95-th percentile127.35198
Maximum127.75406
Range1.2166684
Interquartile range (IQR)0.2923037

Descriptive statistics

Standard deviation0.19658048
Coefficient of variation (CV)0.001547738
Kurtosis0.15865247
Mean127.01147
Median Absolute Deviation (MAD)0.1343435
Skewness0.42214745
Sum1235567.6
Variance0.038643883
MonotonicityNot monotonic
2023-12-11T06:31:02.281989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0877650656 5
 
0.1%
126.9513991646 5
 
0.1%
126.9841427398 5
 
0.1%
126.8075996704 5
 
0.1%
126.9228932429 5
 
0.1%
126.7426175783 4
 
< 0.1%
127.1122507875 4
 
< 0.1%
126.7757637783 4
 
< 0.1%
127.1455817556 4
 
< 0.1%
126.9864178872 4
 
< 0.1%
Other values (7806) 9683
96.8%
(Missing) 272
 
2.7%
ValueCountFrequency (%)
126.5373874904 1
< 0.1%
126.5536043075 1
< 0.1%
126.5541581093 2
< 0.1%
126.5544009287 1
< 0.1%
126.557720191 1
< 0.1%
126.5601124039 1
< 0.1%
126.568761468 1
< 0.1%
126.5691305132 1
< 0.1%
126.569517857 1
< 0.1%
126.5700428049 2
< 0.1%
ValueCountFrequency (%)
127.7540559028 1
< 0.1%
127.7319366806 1
< 0.1%
127.7278774409 1
< 0.1%
127.6806468826 1
< 0.1%
127.679776056 1
< 0.1%
127.6642792342 1
< 0.1%
127.6628124288 1
< 0.1%
127.6621119016 1
< 0.1%
127.6594616227 2
< 0.1%
127.6582099328 1
< 0.1%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

X좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1233
Distinct (%)90.5%
Missing8638
Missing (%)86.4%
Infinite0
Infinite (%)0.0%
Mean201200.31
Minimum160617.87
Maximum258763.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:02.626550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160617.87
5-th percentile176099.72
Q1186602.54
median203944.09
Q3211505.85
95-th percentile228158.43
Maximum258763.47
Range98145.605
Interquartile range (IQR)24903.309

Descriptive statistics

Standard deviation17239.325
Coefficient of variation (CV)0.085682396
Kurtosis0.24506991
Mean201200.31
Median Absolute Deviation (MAD)11872.521
Skewness0.33690048
Sum2.7403482 × 108
Variance2.9719432 × 108
MonotonicityNot monotonic
2023-12-11T06:31:02.782771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198525.615075746 3
 
< 0.1%
200491.516963794 3
 
< 0.1%
195625.160754442 3
 
< 0.1%
186651.484470924 3
 
< 0.1%
217264.407301322 2
 
< 0.1%
180719.225076389 2
 
< 0.1%
184057.157742335 2
 
< 0.1%
205655.716453605 2
 
< 0.1%
211529.164231468 2
 
< 0.1%
221039.88049516 2
 
< 0.1%
Other values (1223) 1338
 
13.4%
(Missing) 8638
86.4%
ValueCountFrequency (%)
160617.867680121 1
< 0.1%
160652.154614071 1
< 0.1%
160945.833123713 1
< 0.1%
161893.250712491 1
< 0.1%
163026.598601128 1
< 0.1%
164105.580712711 1
< 0.1%
164214.507122961 1
< 0.1%
164552.768314325 1
< 0.1%
164622.522236964 1
< 0.1%
164734.006037554 1
< 0.1%
ValueCountFrequency (%)
258763.472727938 1
< 0.1%
258397.571772807 1
< 0.1%
257406.362654 1
< 0.1%
257357.51245075 1
< 0.1%
256682.377133234 1
< 0.1%
256658.646601645 1
< 0.1%
256537.001493366 1
< 0.1%
256272.913340987 1
< 0.1%
255904.434162324 1
< 0.1%
255850.784610469 1
< 0.1%

Y좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1233
Distinct (%)90.5%
Missing8638
Missing (%)86.4%
Infinite0
Infinite (%)0.0%
Mean433414.01
Minimum379861.12
Maximum511429.55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:31:02.947263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum379861.12
5-th percentile389913.04
Q1416030.91
median428898.25
Q3456283.42
95-th percentile477773.88
Maximum511429.55
Range131568.44
Interquartile range (IQR)40252.519

Descriptive statistics

Standard deviation26198.193
Coefficient of variation (CV)0.060446114
Kurtosis-0.69114194
Mean433414.01
Median Absolute Deviation (MAD)17171.785
Skewness0.22002512
Sum5.9030988 × 108
Variance6.863453 × 108
MonotonicityNot monotonic
2023-12-11T06:31:03.085907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
415612.855445573 3
 
< 0.1%
421858.819491837 3
 
< 0.1%
423917.199120807 3
 
< 0.1%
425455.065152743 3
 
< 0.1%
450891.418634933 2
 
< 0.1%
443247.736013507 2
 
< 0.1%
440729.418255952 2
 
< 0.1%
420360.087162086 2
 
< 0.1%
436814.911504063 2
 
< 0.1%
421416.265991666 2
 
< 0.1%
Other values (1223) 1338
 
13.4%
(Missing) 8638
86.4%
ValueCountFrequency (%)
379861.115630476 1
< 0.1%
382445.272004504 1
< 0.1%
384312.056730553 1
< 0.1%
384566.054942627 1
< 0.1%
384850.302517862 1
< 0.1%
384894.826850076 1
< 0.1%
385626.028389184 1
< 0.1%
386133.704987091 2
< 0.1%
386344.430461067 1
< 0.1%
386549.665248928 1
< 0.1%
ValueCountFrequency (%)
511429.554714288 1
< 0.1%
511374.940354442 1
< 0.1%
502397.316680318 1
< 0.1%
498094.541410037 1
< 0.1%
496371.422415109 1
< 0.1%
495967.09749588 1
< 0.1%
495936.329172121 1
< 0.1%
495109.959987727 1
< 0.1%
494679.669455772 1
< 0.1%
492689.484042078 1
< 0.1%

Interactions

2023-12-11T06:30:55.071160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:53.932994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.295866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.711844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:55.154533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.023514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.405232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.811476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:55.238392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.107430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.515896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.890751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:55.335154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.202958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.612280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:30:54.979086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:31:03.177635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태구분코드영업상태명WGS84위도WGS84경도X좌표값Y좌표값
시군명1.0000.1200.1010.9510.9330.9430.958
영업상태구분코드0.1201.0001.0000.0040.0000.1000.000
영업상태명0.1011.0001.0000.0430.0000.1000.000
WGS84위도0.9510.0040.0431.0000.6000.6250.984
WGS84경도0.9330.0000.0000.6001.0000.9880.583
X좌표값0.9430.1000.1000.6250.9881.0000.600
Y좌표값0.9580.0000.0000.9840.5830.6001.000
2023-12-11T06:31:03.278708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명영업상태구분코드시군명
영업상태명1.0001.0000.042
영업상태구분코드1.0001.0000.062
시군명0.0420.0621.000
2023-12-11T06:31:03.371608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
WGS84위도WGS84경도X좌표값Y좌표값시군명영업상태구분코드영업상태명
WGS84위도1.000-0.188-0.1481.0000.7360.0020.022
WGS84경도-0.1881.0001.000-0.1470.6790.0000.000
X좌표값-0.1481.0001.000-0.1450.7060.0590.059
Y좌표값1.000-0.147-0.1451.0000.7590.0000.000
시군명0.7360.6790.7060.7591.0000.0620.042
영업상태구분코드0.0020.0000.0590.0000.0621.0001.000
영업상태명0.0220.0000.0590.0000.0421.0001.000

Missing values

2023-12-11T06:30:55.483531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:30:55.709263image/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.
2023-12-11T06:30:56.084897image/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

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값
5325성남시GS25 성남테크20130927<NA><NA>폐업 등20150115<NA><NA><NA>경기도 성남시 중원구 사기막골로 124 (상대원동, SKn테크노파크 메가센터동B2층201호)경기도 성남시 중원구 190번지 1호 SKn테크노파크 메가센터동B2층201호46272137.439948127.176987<NA><NA><NA>
2663김포시365PLUS김포나비20150310<NA><NA>폐업 등20171220<NA><NA><NA>경기도 김포시 김포한강8로 377 (구래동)경기도 김포시 구래동 6888번지 2호415080<NA><NA><NA><NA><NA>
12399이천시씨유 이천대우점20130603<NA><NA>운영중<NA><NA><NA><NA>경기도 이천시 이섭대천로1407번길 18-2 (증포동)경기도 이천시 증포동 211번지 2호 외2필지46780237.293869127.454994<NA><NA><NA>
9823양평군CU양평한전점20140217<NA><NA>운영중<NA><NA><NA><NA>경기도 양평군 강상면 강남로 931경기도 양평군 강상면 병산리 29-3번지1257137.487205127.48051<NA><NA><NA>
6133수원시세븐일레븐수원조원증앙점20150106<NA><NA>운영중<NA><NA><NA><NA>경기도 수원시 장안구 금당로9번길 76, 1층 (조원동)경기도 수원시 장안구 조원동 851번지 1호 1층44020037.304099127.013218<NA><NA><NA>
13047파주시GS25산내현대점20161208<NA><NA>폐업 등20170608<NA><NA><NA>경기도 파주시 청암로17번길 33, 110호 (목동동)경기도 파주시 목동동 933번지1089237.728711126.736386<NA><NA><NA>
5189성남시GS25 성남푸르지오점20160627<NA><NA>운영중<NA><NA><NA><NA>경기도 성남시 수정구 산성대로437번길 7, A1동 104호 (단대동, 성남단대동 푸르지오)경기도 성남시 수정구 단대동 100번지 A1동 104호1314437.451006127.15703<NA><NA><NA>
1395광주시지에스25 광주벽산점2023-09-18<NA>13영업중<NA><NA><NA>12748경기도 광주시 회안대로 621-21, 102-2호 (탄벌동, 벽산블루밍1단지)경기도 광주시 탄벌동 769 벽산블루밍1단지1274837.40787127.235872<NA>220785.371091433991.522417
14431하남시(주)코리아세븐 하남교산점20160610<NA><NA>폐업 등20180807<NA><NA><NA>경기도 하남시 샘재로 33, 1층 (교산동)경기도 하남시 교산동 24번지 1호1301837.525073127.207992<NA><NA><NA>
6346수원시세븐일레븐 수원곡반중앙점20150302<NA><NA>운영중<NA><NA><NA><NA>경기도 수원시 권선구 동수원로146번길 101, 101호 (곡반정동)경기도 수원시 권선구 곡반정동 506번지 1호44140037.245809127.034103<NA><NA><NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명폐업일자소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값
1725광주시미니스톱 광주초월점20151023<NA><NA>폐업 등20180628<NA><NA><NA>경기도 광주시 초월읍 산수로 500경기도 광주시 초월읍 신월리 472번지1272937.405118127.309179<NA><NA><NA>
3084남양주시세븐일레븐 남양주장내점20140411<NA><NA>운영중<NA><NA><NA><NA>경기도 남양주시 평내로29번안길 21 (평내동)경기도 남양주시 평내동 574번지 3호47293837.645896127.23375<NA><NA><NA>
9670양주시GS25양주봉양점20150907<NA><NA>운영중<NA><NA><NA><NA>경기도 양주시 칠봉산로 116 (봉양동)경기도 양주시 회암동 469-6번지1146437.846384127.083396<NA><NA><NA>
12546이천시미니스톱 이천원용농원점20121109<NA><NA>폐업 등20130503<NA><NA><NA>경기도 이천시 장호원읍 중원대로 1372경기도 이천시 장호원읍 진암리 167번지 14호46790437.102469127.616052<NA><NA><NA>
14319하남시씨유미사20단지점20180605<NA><NA>운영중<NA><NA><NA><NA>경기도 하남시 미사강변서로 85-1, 105호 (풍산동)경기도 하남시 풍산동 470번지1291637.558128127.184505<NA><NA><NA>
4932성남시GS25 분당이매역점20121112<NA><NA>운영중<NA><NA><NA><NA>경기도 성남시 분당구 방아로 8 (이매동)경기도 성남시 분당구 이매동 92번지 1호46382937.397859127.129637<NA><NA><NA>
6612수원시㈜비지에프리테일 수원현대점20130610<NA><NA>폐업 등20171114<NA><NA><NA>경기도 수원시 장안구 경수대로1020번길 6, 1층 (송죽동)경기도 수원시 장안구 송죽동 481번지44021037.30713127.000639<NA><NA><NA>
6119수원시GS25광교힐스점20180702<NA><NA>운영중<NA><NA><NA><NA>경기도 수원시 영통구 센트럴파크로 6, 301동 127호 (하동, 힐스테이트 광교)경기도 수원시 영통구 하동 1021번지 힐스테이트 광교 301동 127호1651437.284238127.0656<NA><NA><NA>
15141화성시씨유 화성효성점20121119<NA><NA>운영중<NA><NA><NA><NA>경기도 화성시 봉담읍 와우안길 59경기도 화성시 봉담읍 와우리 82-1번지1832137.216629126.975358<NA><NA><NA>
12952파주시GS25 금촌로데오점20121129<NA><NA>폐업 등20161208<NA><NA><NA>경기도 파주시 문화로 87 (금촌동)경기도 파주시 금촌동 67번지 5호41381437.762014126.774928<NA><NA><NA>