Overview

Dataset statistics

Number of variables19
Number of observations528
Missing cells2763
Missing cells (%)27.5%
Duplicate rows2
Duplicate rows (%)0.4%
Total size in memory83.7 KiB
Average record size in memory162.2 B

Variable types

Categorical3
Text7
Unsupported4
Numeric5

Alerts

Dataset has 2 (0.4%) duplicate rowsDuplicates
영업상태구분코드 is highly overall correlated with 영업상태명High correlation
영업상태명 is highly overall correlated with 영업상태구분코드High 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 X좌표값 and 1 other fieldsHigh correlation
X좌표값 is highly overall correlated with WGS84경도 and 1 other fieldsHigh correlation
Y좌표값 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
시군명 is highly overall correlated with 소재지우편번호 and 4 other fieldsHigh correlation
영업상태구분코드 is highly imbalanced (52.7%)Imbalance
영업상태명 is highly imbalanced (52.7%)Imbalance
인허가취소일자 has 528 (100.0%) missing valuesMissing
소재지시설전화번호 has 58 (11.0%) missing valuesMissing
소재지면적정보 has 528 (100.0%) missing valuesMissing
도로명우편번호 has 197 (37.3%) missing valuesMissing
소재지도로명주소 has 68 (12.9%) missing valuesMissing
소재지우편번호 has 55 (10.4%) missing valuesMissing
WGS84위도 has 38 (7.2%) missing valuesMissing
WGS84경도 has 38 (7.2%) missing valuesMissing
업태구분명정보 has 528 (100.0%) missing valuesMissing
X좌표값 has 87 (16.5%) missing valuesMissing
Y좌표값 has 87 (16.5%) missing valuesMissing
사무소전화번호 has 19 (3.6%) missing valuesMissing
사업장전화번호 has 528 (100.0%) 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
사업장전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:33:43.292320
Analysis finished2023-12-10 22:33:47.536876
Duration4.24 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
화성시
76 
김포시
64 
평택시
36 
양주시
36 
파주시
32 
Other values (26)
284 

Length

Max length4
Median length3
Mean length3.0606061
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
화성시 76
14.4%
김포시 64
 
12.1%
평택시 36
 
6.8%
양주시 36
 
6.8%
파주시 32
 
6.1%
안성시 30
 
5.7%
포천시 27
 
5.1%
시흥시 22
 
4.2%
용인시 20
 
3.8%
이천시 19
 
3.6%
Other values (21) 166
31.4%

Length

2023-12-11T07:33:47.639710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 76
14.4%
김포시 64
 
12.1%
평택시 36
 
6.8%
양주시 36
 
6.8%
파주시 32
 
6.1%
안성시 30
 
5.7%
포천시 27
 
5.1%
시흥시 22
 
4.2%
용인시 20
 
3.8%
이천시 19
 
3.6%
Other values (21) 166
31.4%

사업장명
Text

Distinct493
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-11T07:33:47.941244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length7.3181818
Min length2

Characters and Unicode

Total characters3864
Distinct characters302
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique465 ?
Unique (%)88.1%

Sample

1st row가평 보.명축산계
2nd row가평 보.명축산계
3rd row대한양계협회 가평육계분회
4th row성광계기
5th row가평보·명 축산계
ValueCountFrequency (%)
주식회사 21
 
3.6%
계량소 7
 
1.2%
공단계량증명업소 4
 
0.7%
현신계량공사 3
 
0.5%
국제계량증명업소 3
 
0.5%
남양계량증명업소 3
 
0.5%
삼구저울 3
 
0.5%
시화계량증명업소 3
 
0.5%
시화기름나라계량증명업소 2
 
0.3%
삼환환경(주 2
 
0.3%
Other values (500) 525
91.1%
2023-12-11T07:33:48.466875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 319
 
8.3%
소 311
 
8.0%
량 298
 
7.7%
업 204
 
5.3%
명 194
 
5.0%
증 182
 
4.7%
주 142
 
3.7%
) 92
 
2.4%
( 91
 
2.4%
사 60
 
1.6%
Other values (292) 1971
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3587
92.8%
Close Punctuation 92
 
2.4%
Open Punctuation 91
 
2.4%
Space Separator 48
 
1.2%
Uppercase Letter 22
 
0.6%
Decimal Number 15
 
0.4%
Other Punctuation 5
 
0.1%
Other Symbol 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 319
 
8.9%
소 311
 
8.7%
량 298
 
8.3%
업 204
 
5.7%
명 194
 
5.4%
증 182
 
5.1%
주 142
 
4.0%
사 60
 
1.7%
원 56
 
1.6%
산 52
 
1.4%
Other values (263) 1769
49.3%
Uppercase Letter
ValueCountFrequency (%)
S 3
13.6%
I 3
13.6%
G 3
13.6%
C 3
13.6%
K 2
9.1%
H 1
 
4.5%
L 1
 
4.5%
J 1
 
4.5%
Y 1
 
4.5%
E 1
 
4.5%
Other values (3) 3
13.6%
Decimal Number
ValueCountFrequency (%)
2 4
26.7%
4 3
20.0%
0 2
13.3%
5 2
13.3%
6 1
 
6.7%
7 1
 
6.7%
3 1
 
6.7%
1 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 2
40.0%
· 2
40.0%
, 1
20.0%
Close Punctuation
ValueCountFrequency (%)
) 92
100.0%
Open Punctuation
ValueCountFrequency (%)
( 91
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3590
92.9%
Common 251
 
6.5%
Latin 23
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 319
 
8.9%
소 311
 
8.7%
량 298
 
8.3%
업 204
 
5.7%
명 194
 
5.4%
증 182
 
5.1%
주 142
 
4.0%
사 60
 
1.7%
원 56
 
1.6%
산 52
 
1.4%
Other values (264) 1772
49.4%
Common
ValueCountFrequency (%)
) 92
36.7%
( 91
36.3%
48
19.1%
2 4
 
1.6%
4 3
 
1.2%
. 2
 
0.8%
0 2
 
0.8%
5 2
 
0.8%
· 2
 
0.8%
6 1
 
0.4%
Other values (4) 4
 
1.6%
Latin
ValueCountFrequency (%)
S 3
13.0%
I 3
13.0%
G 3
13.0%
C 3
13.0%
K 2
8.7%
n 1
 
4.3%
H 1
 
4.3%
L 1
 
4.3%
J 1
 
4.3%
Y 1
 
4.3%
Other values (4) 4
17.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3587
92.8%
ASCII 272
 
7.0%
None 5
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 319
 
8.9%
소 311
 
8.7%
량 298
 
8.3%
업 204
 
5.7%
명 194
 
5.4%
증 182
 
5.1%
주 142
 
4.0%
사 60
 
1.7%
원 56
 
1.6%
산 52
 
1.4%
Other values (263) 1769
49.3%
ASCII
ValueCountFrequency (%)
) 92
33.8%
( 91
33.5%
48
17.6%
2 4
 
1.5%
S 3
 
1.1%
I 3
 
1.1%
G 3
 
1.1%
C 3
 
1.1%
4 3
 
1.1%
. 2
 
0.7%
Other values (17) 20
 
7.4%
None
ValueCountFrequency (%)
㈜ 3
60.0%
· 2
40.0%

인허가일자
Text

Distinct502
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-11T07:33:48.820645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1401515
Min length8

Characters and Unicode

Total characters4298
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique478 ?
Unique (%)90.5%

Sample

1st row20010207
2nd row20010207
3rd row19991209
4th row19991203
5th row19970227
ValueCountFrequency (%)
19971110 3
 
0.6%
19941104 3
 
0.6%
20060112 2
 
0.4%
20010207 2
 
0.4%
19860415 2
 
0.4%
20191128 2
 
0.4%
20101230 2
 
0.4%
20070928 2
 
0.4%
20020708 2
 
0.4%
20000222 2
 
0.4%
Other values (496) 510
95.9%
2023-12-11T07:33:49.357888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1201
27.9%
1 868
20.2%
2 846
19.7%
9 405
 
9.4%
8 174
 
4.0%
3 173
 
4.0%
7 159
 
3.7%
5 132
 
3.1%
6 132
 
3.1%
4 128
 
3.0%
Other values (2) 80
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4218
98.1%
Dash Punctuation 74
 
1.7%
Space Separator 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1201
28.5%
1 868
20.6%
2 846
20.1%
9 405
 
9.6%
8 174
 
4.1%
3 173
 
4.1%
7 159
 
3.8%
5 132
 
3.1%
6 132
 
3.1%
4 128
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4298
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1201
27.9%
1 868
20.2%
2 846
19.7%
9 405
 
9.4%
8 174
 
4.0%
3 173
 
4.0%
7 159
 
3.7%
5 132
 
3.1%
6 132
 
3.1%
4 128
 
3.0%
Other values (2) 80
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4298
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1201
27.9%
1 868
20.2%
2 846
19.7%
9 405
 
9.4%
8 174
 
4.0%
3 173
 
4.0%
7 159
 
3.7%
5 132
 
3.1%
6 132
 
3.1%
4 128
 
3.0%
Other values (2) 80
 
1.9%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing528
Missing (%)100.0%
Memory size4.8 KiB

영업상태구분코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
1
366 
3
158 
4
 
3
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 366
69.3%
3 158
29.9%
4 3
 
0.6%
2 1
 
0.2%

Length

2023-12-11T07:33:49.514209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:49.644835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 366
69.3%
3 158
29.9%
4 3
 
0.6%
2 1
 
0.2%

영업상태명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
영업중
366 
폐업
158 
타시군구이관
 
3
휴업
 
1

Length

Max length6
Median length3
Mean length2.7159091
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 366
69.3%
폐업 158
29.9%
타시군구이관 3
 
0.6%
휴업 1
 
0.2%

Length

2023-12-11T07:33:49.767646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:33:49.894846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 366
69.3%
폐업 158
29.9%
타시군구이관 3
 
0.6%
휴업 1
 
0.2%

소재지시설전화번호
Text

MISSING 

Distinct450
Distinct (%)95.7%
Missing58
Missing (%)11.0%
Memory size4.3 KiB
2023-12-11T07:33:50.128078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.193617
Min length1

Characters and Unicode

Total characters5261
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique435 ?
Unique (%)92.6%

Sample

1st row0356584 3218
2nd row0356582 7958
3rd row02 302 4546
4th row000231597368
5th row0031979 2109
ValueCountFrequency (%)
031 272
27.3%
997 6
 
0.6%
498 6
 
0.6%
351 5
 
0.5%
02 5
 
0.5%
236 5
 
0.5%
7436 5
 
0.5%
676 5
 
0.5%
983 4
 
0.4%
684 4
 
0.4%
Other values (589) 678
68.1%
2023-12-11T07:33:50.514935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 807
15.3%
3 798
15.2%
1 703
13.4%
568
10.8%
5 380
7.2%
6 368
7.0%
9 365
6.9%
4 353
6.7%
8 325
6.2%
7 288
 
5.5%
Other values (2) 306
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4667
88.7%
Space Separator 568
 
10.8%
Dash Punctuation 26
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 807
17.3%
3 798
17.1%
1 703
15.1%
5 380
8.1%
6 368
7.9%
9 365
7.8%
4 353
7.6%
8 325
7.0%
7 288
 
6.2%
2 280
 
6.0%
Space Separator
ValueCountFrequency (%)
568
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5261
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 807
15.3%
3 798
15.2%
1 703
13.4%
568
10.8%
5 380
7.2%
6 368
7.0%
9 365
6.9%
4 353
6.7%
8 325
6.2%
7 288
 
5.5%
Other values (2) 306
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5261
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 807
15.3%
3 798
15.2%
1 703
13.4%
568
10.8%
5 380
7.2%
6 368
7.0%
9 365
6.9%
4 353
6.7%
8 325
6.2%
7 288
 
5.5%
Other values (2) 306
 
5.8%

소재지면적정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing528
Missing (%)100.0%
Memory size4.8 KiB

도로명우편번호
Text

MISSING 

Distinct280
Distinct (%)84.6%
Missing197
Missing (%)37.3%
Memory size4.3 KiB
2023-12-11T07:33:50.848608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.5377644
Min length5

Characters and Unicode

Total characters1833
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

Unique241 ?
Unique (%)72.8%

Sample

1st row477800
2nd row10540
3rd row10432
4th row10547
5th row410-530
ValueCountFrequency (%)
17962 4
 
1.2%
456894 4
 
1.2%
10010 4
 
1.2%
18581 3
 
0.9%
17406 3
 
0.9%
464070 3
 
0.9%
483-080 3
 
0.9%
10048 3
 
0.9%
10809 3
 
0.9%
483100 2
 
0.6%
Other values (270) 299
90.3%
2023-12-11T07:33:51.320704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 327
17.8%
4 306
16.7%
8 232
12.7%
0 195
10.6%
5 170
9.3%
6 135
7.4%
2 134
7.3%
7 132
7.2%
9 98
 
5.3%
3 92
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1821
99.3%
Dash Punctuation 12
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 327
18.0%
4 306
16.8%
8 232
12.7%
0 195
10.7%
5 170
9.3%
6 135
7.4%
2 134
7.4%
7 132
7.2%
9 98
 
5.4%
3 92
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1833
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 327
17.8%
4 306
16.7%
8 232
12.7%
0 195
10.6%
5 170
9.3%
6 135
7.4%
2 134
7.3%
7 132
7.2%
9 98
 
5.3%
3 92
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1833
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 327
17.8%
4 306
16.7%
8 232
12.7%
0 195
10.6%
5 170
9.3%
6 135
7.4%
2 134
7.3%
7 132
7.2%
9 98
 
5.3%
3 92
 
5.0%

소재지도로명주소
Text

MISSING 

Distinct440
Distinct (%)95.7%
Missing68
Missing (%)12.9%
Memory size4.3 KiB
2023-12-11T07:33:51.600623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length40
Mean length23.126087
Min length15

Characters and Unicode

Total characters10638
Distinct characters292
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

Unique425 ?
Unique (%)92.4%

Sample

1st row경기도 가평군 가평읍 경반안로 106-130 (경반리)
2nd row경기도 가평군 가평읍 경반안로 106-130 (경반리)
3rd row경기도 가평군 설악면 신천중앙로 11 (신천리)
4th row경기도 가평군 가평읍 가화로 90
5th row경기도 가평군 청평면 경춘로 1457 (상천리)
ValueCountFrequency (%)
경기도 453
 
18.6%
화성시 72
 
2.9%
김포시 55
 
2.3%
평택시 30
 
1.2%
안성시 29
 
1.2%
28
 
1.1%
양주시 27
 
1.1%
파주시 26
 
1.1%
포천시 26
 
1.1%
용인시 18
 
0.7%
Other values (959) 1677
68.7%
2023-12-11T07:33:52.047062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1981
 
18.6%
경 480
 
4.5%
도 473
 
4.4%
시 468
 
4.4%
기 464
 
4.4%
로 427
 
4.0%
1 310
 
2.9%
2 213
 
2.0%
동 211
 
2.0%
) 199
 
1.9%
Other values (282) 5412
50.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6393
60.1%
Space Separator 1981
 
18.6%
Decimal Number 1604
 
15.1%
Close Punctuation 199
 
1.9%
Open Punctuation 199
 
1.9%
Other Punctuation 158
 
1.5%
Dash Punctuation 95
 
0.9%
Uppercase Letter 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 480
 
7.5%
도 473
 
7.4%
시 468
 
7.3%
기 464
 
7.3%
로 427
 
6.7%
동 211
 
3.3%
면 178
 
2.8%
성 156
 
2.4%
양 139
 
2.2%
읍 117
 
1.8%
Other values (256) 3280
51.3%
Decimal Number
ValueCountFrequency (%)
1 310
19.3%
2 213
13.3%
3 187
11.7%
5 169
10.5%
4 133
8.3%
7 130
8.1%
6 126
7.9%
8 125
7.8%
0 108
 
6.7%
9 103
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
G 1
11.1%
M 1
11.1%
P 1
11.1%
T 1
11.1%
I 1
11.1%
N 1
11.1%
D 1
11.1%
K 1
11.1%
A 1
11.1%
Other Punctuation
ValueCountFrequency (%)
* 109
69.0%
, 42
 
26.6%
. 7
 
4.4%
Space Separator
ValueCountFrequency (%)
1981
100.0%
Close Punctuation
ValueCountFrequency (%)
) 199
100.0%
Open Punctuation
ValueCountFrequency (%)
( 199
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6393
60.1%
Common 4236
39.8%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 480
 
7.5%
도 473
 
7.4%
시 468
 
7.3%
기 464
 
7.3%
로 427
 
6.7%
동 211
 
3.3%
면 178
 
2.8%
성 156
 
2.4%
양 139
 
2.2%
읍 117
 
1.8%
Other values (256) 3280
51.3%
Common
ValueCountFrequency (%)
1981
46.8%
1 310
 
7.3%
2 213
 
5.0%
) 199
 
4.7%
( 199
 
4.7%
3 187
 
4.4%
5 169
 
4.0%
4 133
 
3.1%
7 130
 
3.1%
6 126
 
3.0%
Other values (7) 589
 
13.9%
Latin
ValueCountFrequency (%)
G 1
11.1%
M 1
11.1%
P 1
11.1%
T 1
11.1%
I 1
11.1%
N 1
11.1%
D 1
11.1%
K 1
11.1%
A 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6393
60.1%
ASCII 4245
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1981
46.7%
1 310
 
7.3%
2 213
 
5.0%
) 199
 
4.7%
( 199
 
4.7%
3 187
 
4.4%
5 169
 
4.0%
4 133
 
3.1%
7 130
 
3.1%
6 126
 
3.0%
Other values (16) 598
 
14.1%
Hangul
ValueCountFrequency (%)
경 480
 
7.5%
도 473
 
7.4%
시 468
 
7.3%
기 464
 
7.3%
로 427
 
6.7%
동 211
 
3.3%
면 178
 
2.8%
성 156
 
2.4%
양 139
 
2.2%
읍 117
 
1.8%
Other values (256) 3280
51.3%

소재지지번주소
Text

Distinct510
Distinct (%)97.3%
Missing4
Missing (%)0.8%
Memory size4.3 KiB
2023-12-11T07:33:52.412193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length23.078244
Min length10

Characters and Unicode

Total characters12093
Distinct characters269
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

Unique496 ?
Unique (%)94.7%

Sample

1st row경기도 가평군 가평읍 경반리 216-2번지
2nd row경기도 가평군 가평읍 경반리 216-2번지
3rd row경기도 가평군 설악면 신천리 345번지
4th row경기도 가평군 가평읍 읍내리 475번지 34호
5th row경기도 가평군 외서면 상천리 205번지
ValueCountFrequency (%)
경기도 516
 
18.2%
화성시 68
 
2.4%
1호 63
 
2.2%
김포시 63
 
2.2%
호 41
 
1.4%
평택시 36
 
1.3%
양주시 34
 
1.2%
파주시 32
 
1.1%
안성시 29
 
1.0%
포천시 27
 
1.0%
Other values (1042) 1929
68.0%
2023-12-11T07:33:52.943034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2397
19.8%
도 536
 
4.4%
시 527
 
4.4%
기 524
 
4.3%
경 522
 
4.3%
지 475
 
3.9%
번 454
 
3.8%
1 381
 
3.2%
리 330
 
2.7%
호 291
 
2.4%
Other values (259) 5656
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7360
60.9%
Space Separator 2397
 
19.8%
Decimal Number 2026
 
16.8%
Dash Punctuation 158
 
1.3%
Other Punctuation 123
 
1.0%
Close Punctuation 10
 
0.1%
Open Punctuation 10
 
0.1%
Uppercase Letter 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 536
 
7.3%
시 527
 
7.2%
기 524
 
7.1%
경 522
 
7.1%
지 475
 
6.5%
번 454
 
6.2%
리 330
 
4.5%
호 291
 
4.0%
동 249
 
3.4%
면 206
 
2.8%
Other values (232) 3246
44.1%
Decimal Number
ValueCountFrequency (%)
1 381
18.8%
2 255
12.6%
3 233
11.5%
4 209
10.3%
6 194
9.6%
5 187
9.2%
7 172
8.5%
8 134
 
6.6%
0 131
 
6.5%
9 130
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
M 1
11.1%
G 1
11.1%
P 1
11.1%
A 1
11.1%
T 1
11.1%
I 1
11.1%
N 1
11.1%
D 1
11.1%
K 1
11.1%
Other Punctuation
ValueCountFrequency (%)
* 112
91.1%
. 5
 
4.1%
, 5
 
4.1%
/ 1
 
0.8%
Space Separator
ValueCountFrequency (%)
2397
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7360
60.9%
Common 4724
39.1%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 536
 
7.3%
시 527
 
7.2%
기 524
 
7.1%
경 522
 
7.1%
지 475
 
6.5%
번 454
 
6.2%
리 330
 
4.5%
호 291
 
4.0%
동 249
 
3.4%
면 206
 
2.8%
Other values (232) 3246
44.1%
Common
ValueCountFrequency (%)
2397
50.7%
1 381
 
8.1%
2 255
 
5.4%
3 233
 
4.9%
4 209
 
4.4%
6 194
 
4.1%
5 187
 
4.0%
7 172
 
3.6%
- 158
 
3.3%
8 134
 
2.8%
Other values (8) 404
 
8.6%
Latin
ValueCountFrequency (%)
M 1
11.1%
G 1
11.1%
P 1
11.1%
A 1
11.1%
T 1
11.1%
I 1
11.1%
N 1
11.1%
D 1
11.1%
K 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7360
60.9%
ASCII 4733
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2397
50.6%
1 381
 
8.0%
2 255
 
5.4%
3 233
 
4.9%
4 209
 
4.4%
6 194
 
4.1%
5 187
 
4.0%
7 172
 
3.6%
- 158
 
3.3%
8 134
 
2.8%
Other values (17) 413
 
8.7%
Hangul
ValueCountFrequency (%)
도 536
 
7.3%
시 527
 
7.2%
기 524
 
7.1%
경 522
 
7.1%
지 475
 
6.5%
번 454
 
6.2%
리 330
 
4.5%
호 291
 
4.0%
동 249
 
3.4%
면 206
 
2.8%
Other values (232) 3246
44.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct362
Distinct (%)76.5%
Missing55
Missing (%)10.4%
Infinite0
Infinite (%)0.0%
Mean14520.025
Minimum5576
Maximum59722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-11T07:33:53.114108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5576
5-th percentile10029.6
Q111139
median14446
Q317595
95-th percentile18576.8
Maximum59722
Range54146
Interquartile range (IQR)6456

Descriptive statistics

Standard deviation4497.656
Coefficient of variation (CV)0.30975538
Kurtosis41.679135
Mean14520.025
Median Absolute Deviation (MAD)3289
Skewness4.3507567
Sum6867972
Variance20228909
MonotonicityNot monotonic
2023-12-11T07:33:53.278746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17962 5
 
0.9%
18581 4
 
0.8%
13386 4
 
0.8%
11426 4
 
0.8%
10806 4
 
0.8%
10010 4
 
0.8%
10949 4
 
0.8%
10809 4
 
0.8%
13951 3
 
0.6%
18537 3
 
0.6%
Other values (352) 434
82.2%
(Missing) 55
 
10.4%
ValueCountFrequency (%)
5576 1
 
0.2%
6050 1
 
0.2%
7720 1
 
0.2%
10008 1
 
0.2%
10010 4
0.8%
10011 3
0.6%
10013 2
0.4%
10014 1
 
0.2%
10016 1
 
0.2%
10022 2
0.4%
ValueCountFrequency (%)
59722 2
0.4%
31750 1
0.2%
22532 1
0.2%
18633 1
0.2%
18631 2
0.4%
18627 1
0.2%
18626 2
0.4%
18625 2
0.4%
18623 1
0.2%
18614 1
0.2%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct467
Distinct (%)95.3%
Missing38
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean37.435698
Minimum34.754606
Maximum38.157766
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-11T07:33:53.409316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.754606
5-th percentile37.004522
Q137.173442
median37.370506
Q337.70892
95-th percentile37.927783
Maximum38.157766
Range3.4031602
Interquartile range (IQR)0.53547773

Descriptive statistics

Standard deviation0.35379775
Coefficient of variation (CV)0.009450812
Kurtosis11.687699
Mean37.435698
Median Absolute Deviation (MAD)0.27151651
Skewness-1.5924905
Sum18343.492
Variance0.12517285
MonotonicityNot monotonic
2023-12-11T07:33:53.563665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4283847 4
 
0.8%
37.6204111 3
 
0.6%
37.1052791042 3
 
0.6%
37.7123635908 3
 
0.6%
37.3125061 2
 
0.4%
37.2383887365 2
 
0.4%
37.3472818 2
 
0.4%
37.3363073 2
 
0.4%
37.1900662683 2
 
0.4%
37.0449078 2
 
0.4%
Other values (457) 465
88.1%
(Missing) 38
 
7.2%
ValueCountFrequency (%)
34.7546059369 2
0.4%
36.9434127 1
0.2%
36.9448383842 1
0.2%
36.9469985 1
0.2%
36.9515344024 1
0.2%
36.9536926 1
0.2%
36.9544505 1
0.2%
36.9546017307 1
0.2%
36.9548582999 1
0.2%
36.9572059826 1
0.2%
ValueCountFrequency (%)
38.1577661 1
0.2%
38.1113048 1
0.2%
38.087663 1
0.2%
38.0512151605 1
0.2%
38.0508112 1
0.2%
38.0239231 1
0.2%
38.0151201 1
0.2%
38.0133697 1
0.2%
38.0084436375 1
0.2%
38.0016516 1
0.2%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct467
Distinct (%)95.3%
Missing38
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean126.982
Minimum126.5499
Maximum127.73277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-11T07:33:53.705784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5499
5-th percentile126.59801
Q1126.79208
median126.95851
Q3127.14319
95-th percentile127.48971
Maximum127.73277
Range1.182874
Interquartile range (IQR)0.35110757

Descriptive statistics

Standard deviation0.26049578
Coefficient of variation (CV)0.0020514386
Kurtosis-0.20134454
Mean126.982
Median Absolute Deviation (MAD)0.1729122
Skewness0.55314264
Sum62221.18
Variance0.06785805
MonotonicityNot monotonic
2023-12-11T07:33:53.851748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.138266 4
 
0.8%
126.8197355 3
 
0.6%
126.8411878977 3
 
0.6%
126.6143411891 3
 
0.6%
126.7088971 2
 
0.4%
126.9614076567 2
 
0.4%
126.7545256 2
 
0.4%
126.745997 2
 
0.4%
127.4408591099 2
 
0.4%
127.4146141 2
 
0.4%
Other values (457) 465
88.1%
(Missing) 38
 
7.2%
ValueCountFrequency (%)
126.5498972352 1
0.2%
126.5540329 1
0.2%
126.5555431 1
0.2%
126.5588119 1
0.2%
126.560614 1
0.2%
126.5609809 1
0.2%
126.5706172 1
0.2%
126.5707812 1
0.2%
126.5718409169 1
0.2%
126.5727831 1
0.2%
ValueCountFrequency (%)
127.7327712747 2
0.4%
127.696268 1
0.2%
127.6605972308 1
0.2%
127.6483039 1
0.2%
127.6454104 1
0.2%
127.6366885 1
0.2%
127.6323021 1
0.2%
127.622551 1
0.2%
127.601679 1
0.2%
127.5531356841 1
0.2%

업태구분명정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing528
Missing (%)100.0%
Memory size4.8 KiB

X좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct423
Distinct (%)95.9%
Missing87
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean198472.89
Minimum160229.86
Maximum267019.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-11T07:33:53.989238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum160229.86
5-th percentile164214.84
Q1181556.57
median196246
Q3213589.48
95-th percentile239772.99
Maximum267019.91
Range106790.05
Interquartile range (IQR)32032.908

Descriptive statistics

Standard deviation22868.372
Coefficient of variation (CV)0.11522164
Kurtosis-0.18989627
Mean198472.89
Median Absolute Deviation (MAD)15444.372
Skewness0.51730925
Sum87526543
Variance5.2296244 × 108
MonotonicityNot monotonic
2023-12-11T07:33:54.128679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
212172.952406177 3
 
0.6%
192850.481930147 2
 
0.4%
197685.579308327 2
 
0.4%
212514.133832289 2
 
0.4%
162185.013959121 2
 
0.4%
177424.38206524 2
 
0.4%
178184.894681268 2
 
0.4%
185817.350487837 2
 
0.4%
189489.894747707 2
 
0.4%
183814.962461862 2
 
0.4%
Other values (413) 420
79.5%
(Missing) 87
 
16.5%
ValueCountFrequency (%)
160229.862634056 1
0.2%
160595.079777878 1
0.2%
160720.345802687 1
0.2%
161031.174768922 1
0.2%
161169.086647101 1
0.2%
161190.425283683 1
0.2%
162030.054717286 1
0.2%
162091.411266625 1
0.2%
162185.013959121 2
0.4%
162245.505167242 1
0.2%
ValueCountFrequency (%)
267019.914665 2
0.4%
261468.164658831 1
0.2%
258397.814218655 1
0.2%
257448.745185653 1
0.2%
257163.825304072 1
0.2%
256386.824433802 1
0.2%
255022.958894762 1
0.2%
249127.08584407 1
0.2%
248795.715909157 1
0.2%
248635.056842528 1
0.2%

Y좌표값
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct423
Distinct (%)95.9%
Missing87
Missing (%)16.5%
Infinite0
Infinite (%)0.0%
Mean435446.63
Minimum139808.05
Maximum517219.74
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-11T07:33:54.269761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum139808.05
5-th percentile387457.51
Q1406859.54
median428410.91
Q3465802.81
95-th percentile492808.17
Maximum517219.74
Range377411.68
Interquartile range (IQR)58943.262

Descriptive statistics

Standard deviation40106.289
Coefficient of variation (CV)0.092103799
Kurtosis11.639309
Mean435446.63
Median Absolute Deviation (MAD)30219.101
Skewness-1.5878637
Sum1.9203196 × 108
Variance1.6085144 × 109
MonotonicityNot monotonic
2023-12-11T07:33:54.409134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
436267.331920785 3
 
0.6%
497386.692339368 2
 
0.4%
432956.359797123 2
 
0.4%
399140.802559973 2
 
0.4%
464143.141112762 2
 
0.4%
426069.6087203 2
 
0.4%
427285.811308053 2
 
0.4%
400410.579263588 2
 
0.4%
486393.785992382 2
 
0.4%
408704.473915771 2
 
0.4%
Other values (413) 420
79.5%
(Missing) 87
 
16.5%
ValueCountFrequency (%)
139808.054703 2
0.4%
382436.706692255 1
0.2%
382557.0 1
0.2%
382576.761319389 1
0.2%
382834.427779004 1
0.2%
383362.254616049 1
0.2%
383505.377987887 1
0.2%
383667.0 1
0.2%
383688.207098156 1
0.2%
383710.299146961 1
0.2%
ValueCountFrequency (%)
517219.736187111 1
0.2%
512097.921311495 1
0.2%
509439.979404634 1
0.2%
505722.751625 1
0.2%
505377.625125447 1
0.2%
502376.264964638 1
0.2%
501420.779153703 1
0.2%
501205.593448469 1
0.2%
500623.194053818 1
0.2%
499916.083663411 1
0.2%

사무소전화번호
Text

MISSING 

Distinct491
Distinct (%)96.5%
Missing19
Missing (%)3.6%
Memory size4.3 KiB
2023-12-11T07:33:54.926271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.251473
Min length1

Characters and Unicode

Total characters5727
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

Unique477 ?
Unique (%)93.7%

Sample

1st row0356584 3218
2nd row01197405889
3rd row0356582 7958
4th row02 302 4546
5th row000231597368
ValueCountFrequency (%)
031 272
 
25.6%
010 16
 
1.5%
011 7
 
0.7%
997 6
 
0.6%
498 6
 
0.6%
676 5
 
0.5%
7436 5
 
0.5%
02 5
 
0.5%
351 5
 
0.5%
236 5
 
0.5%
Other values (633) 730
68.7%
2023-12-11T07:33:55.333557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 903
15.8%
3 819
14.3%
1 782
13.7%
612
10.7%
5 406
7.1%
6 392
6.8%
4 392
6.8%
9 392
6.8%
8 355
 
6.2%
7 325
 
5.7%
Other values (3) 349
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5079
88.7%
Space Separator 612
 
10.7%
Dash Punctuation 28
 
0.5%
Other Punctuation 8
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 903
17.8%
3 819
16.1%
1 782
15.4%
5 406
8.0%
6 392
7.7%
4 392
7.7%
9 392
7.7%
8 355
 
7.0%
7 325
 
6.4%
2 313
 
6.2%
Space Separator
ValueCountFrequency (%)
612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Other Punctuation
ValueCountFrequency (%)
* 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5727
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 903
15.8%
3 819
14.3%
1 782
13.7%
612
10.7%
5 406
7.1%
6 392
6.8%
4 392
6.8%
9 392
6.8%
8 355
 
6.2%
7 325
 
5.7%
Other values (3) 349
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5727
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 903
15.8%
3 819
14.3%
1 782
13.7%
612
10.7%
5 406
7.1%
6 392
6.8%
4 392
6.8%
9 392
6.8%
8 355
 
6.2%
7 325
 
5.7%
Other values (3) 349
 
6.1%

사업장전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing528
Missing (%)100.0%
Memory size4.8 KiB

Interactions

2023-12-11T07:33:45.971984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.176080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.616794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.059815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.511196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:46.283897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.258965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.698072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.145185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.602932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:46.378264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.345249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.786676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.239841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.689662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:46.489444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.434368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.875999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.330298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.770804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:46.610051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.519502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:44.963416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.425913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:33:45.872472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:33:55.433170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태구분코드영업상태명소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값
시군명1.0000.2050.2051.0000.9630.9560.9530.967
영업상태구분코드0.2051.0001.0000.6440.5450.3200.3790.000
영업상태명0.2051.0001.0000.6440.5450.3200.3790.000
소재지우편번호1.0000.6440.6441.0000.8030.6530.6660.624
WGS84위도0.9630.5450.5450.8031.0000.7560.7831.000
WGS84경도0.9560.3200.3200.6530.7561.0000.9960.613
X좌표값0.9530.3790.3790.6660.7830.9961.0000.604
Y좌표값0.9670.0000.0000.6241.0000.6130.6041.000
2023-12-11T07:33:55.542124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태구분코드영업상태명시군명
영업상태구분코드1.0001.0000.104
영업상태명1.0001.0000.104
시군명0.1040.1041.000
2023-12-11T07:33:55.653542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값시군명영업상태구분코드영업상태명
소재지우편번호1.000-0.8410.2560.246-0.8430.9620.4720.472
WGS84위도-0.8411.000-0.158-0.1790.9970.8320.4710.471
WGS84경도0.256-0.1581.0001.000-0.1810.6700.1950.195
X좌표값0.246-0.1791.0001.000-0.1750.6610.2330.233
Y좌표값-0.8430.997-0.181-0.1751.0000.8400.4680.468
시군명0.9620.8320.6700.6610.8401.0000.1040.104
영업상태구분코드0.4720.4710.1950.2330.4680.1041.0001.000
영업상태명0.4720.4710.1950.2330.4680.1041.0001.000

Missing values

2023-12-11T07:33:46.831994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:33:47.184957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-11T07:33:47.396495image/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

시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값사무소전화번호사업장전화번호
0가평군가평 보.명축산계20010207<NA>1영업중<NA><NA><NA>경기도 가평군 가평읍 경반안로 106-130 (경반리)경기도 가평군 가평읍 경반리 216-2번지1241537.834679127.493914<NA><NA><NA><NA><NA>
1가평군가평 보.명축산계20010207<NA>1영업중<NA><NA><NA>경기도 가평군 가평읍 경반안로 106-130 (경반리)경기도 가평군 가평읍 경반리 216-2번지1241537.834679127.493914<NA><NA><NA><NA><NA>
2가평군대한양계협회 가평육계분회19991209<NA>1영업중0356584 3218<NA><NA>경기도 가평군 설악면 신천중앙로 11 (신천리)경기도 가평군 설악면 신천리 345번지1246737.671501127.489221<NA>243097.969595463354.9234450356584 3218<NA>
3가평군성광계기19991203<NA>1영업중<NA><NA>477800경기도 가평군 가평읍 가화로 90경기도 가평군 가평읍 읍내리 475번지 34호1241937.827707127.514632<NA>245244.716969480703.06230201197405889<NA>
4가평군가평보·명 축산계19970227<NA>1영업중0356582 7958<NA><NA>경기도 가평군 청평면 경춘로 1457 (상천리)경기도 가평군 외서면 상천리 205번지1244937.779653127.464026<NA><NA><NA>0356582 7958<NA>
5고양시고양공인계량증명업소20200214<NA>1영업중02 302 4546<NA>10540경기도 고양시 덕양구 대덕로86번길 111 (현천동)경기도 고양시 덕양구 현천동 157번지1054037.594941126.866698<NA>188162.753693454754.70654902 302 4546<NA>
6고양시경기고양 공인계량소20190219<NA>1영업중000231597368<NA><NA><NA>경기도 고양시 덕양구 화전동 772번지 3호10537<NA><NA><NA>187965.225268456687.471123000231597368<NA>
7고양시주신자원(주)20190115<NA>1영업중0031979 2109<NA><NA><NA>경기도 고양시 덕양구 도내동 694번지 9호<NA><NA><NA><NA>187546.308044456579.5128150031979 2109<NA>
8고양시장항공인계량증명업소20160510<NA>1영업중031 905 8595<NA>10432경기도 고양시 일산동구 장항로 203-22 (장항동, 한남리사이팅)경기도 고양시 일산동구 장항동 601번지 3호1043237.638993126.77513<NA>180086.903087459660.405924031 905 8595<NA>
9고양시동산계량증명업소20150921<NA>1영업중02 359 0980<NA>10547경기도 고양시 덕양구 고양대로 1856-2 (동산동)경기도 고양시 덕양구 동산동 261번지 3호1054737.64183126.885704<NA>189848.572644459955.7216302 359 0980<NA>
시군명사업장명인허가일자인허가취소일자영업상태구분코드영업상태명소재지시설전화번호소재지면적정보도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도업태구분명정보X좌표값Y좌표값사무소전화번호사업장전화번호
518화성시발안계량증명업소19880219<NA>1영업중031 352 0095<NA><NA>경기도 화성시 향남읍 삼천병마로 265-10경기도 화성군 향남면 장짐리 273번지 1 호1858737.136201126.911141<NA><NA><NA>031 352 0095<NA>
519<NA>평택당진중앙부두(주)20221219<NA>1영업중0316849211<NA>31750충청남도 당진시 신평면 당진항만로 151충청남도 당진시 신평면 매산리 976-43175036.954602126.825022<NA>184537.289389383815.091260316849211<NA>
520<NA>(주)평일20200428<NA>1영업중031 420 6600<NA>05576서울특별시 송파구 백제고분로 154, 평일빌딩 (잠실동)서울특별시 송파구 잠실동 314-7 평일빌딩557637.505294127.083748<NA>207334.760008444791.170296031 420 6600<NA>
521<NA>인그리디언코리아 유한회사2018-12-19<NA>1영업중000234851400<NA>06050서울특별시 강남구 언주로 725, 보전빌딩 (논현동)서울특별시 강남구 논현동 70-13번지 보전빌딩605037.519297127.034456<NA>202973.705446342.07000234851400<NA>
522<NA>내트럭 주식회사 평택사업소20160719<NA>1영업중07077474949<NA>17962경기도 포승읍 하만호길 229경기도 평택시 포승읍 만호리 668번지1796236.953693126.847673<NA>186614.0383667.007077474949<NA>
523<NA>대창철재20091111<NA>1영업중0325836214<NA><NA>인천광역시 동구 방축로191번길 35 (송림동)인천광역시 동구 송림1동 297번지 18호2253237.481154126.666074<NA>170425.501638442137.544860325836214<NA>
524<NA>(주)대명아이티20040330<NA>1영업중<NA><NA><NA>서울특별시 강서구 가로공원로 227서울특별시 강서구 화곡동 400-45번지772037.538269126.840962<NA><NA><NA><NA><NA>
525<NA>교하계량증명업소20021119<NA>3폐업031 943 4333<NA><NA><NA>서울특별시 영등포구 당산동4가 1-505번지<NA>37.526924126.900399<NA><NA><NA>031 943 4333<NA>
526<NA>화성계량증명소19910702<NA>4타시군구이관0000<NA><NA>전라남도 여수시 충민사길 11-18 (덕충동)전라남도 여수시 덕충동 1972번지5972234.754606127.732771<NA>267019.914665139808.0547030000<NA>
527<NA>화성계량증명소19910702<NA>4타시군구이관031 962 8059<NA><NA>전라남도 여수시 충민사길 11-18 (덕충동)전라남도 여수시 덕충동 1972번지5972234.754606127.732771<NA>267019.914665139808.054703031 962 8059<NA>

Duplicate rows

Most frequently occurring

시군명사업장명인허가일자영업상태구분코드영업상태명소재지시설전화번호도로명우편번호소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도X좌표값Y좌표값사무소전화번호# duplicates
0가평군가평 보.명축산계200102071영업중<NA><NA>경기도 가평군 가평읍 경반안로 106-130 (경반리)경기도 가평군 가평읍 경반리 216-2번지1241537.834679127.493914<NA><NA><NA>2
1이천시현신계량공사200101133폐업031 637 5992<NA><NA>경기도 이천시 대월면 사동리 347-173번지1733837.243476127.49579<NA><NA>031 637 59922