Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells6554
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 MiB
Average record size in memory176.0 B

Variable types

Numeric4
Categorical10
Text4
DateTime2

Dataset

Description경상남도 김해시 소상공인 현황 경위도 좌표 기준 정보데이터로 관리번호, 기준(년, 월), 업종대분류, 업종중분류, 업종명, 창업일자, 폐업일자 등에 대한 항목으로 구성되어 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15109629

Alerts

기준_년 has constant value ""Constant
기준_월 has constant value ""Constant
시도_명 has constant value ""Constant
시군구_명 has constant value ""Constant
시도_코드 has constant value ""Constant
시군구_코드 has constant value ""Constant
업종대분류 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
업종중분류 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
관리번호 is highly overall correlated with 업종대분류 and 1 other fieldsHigh correlation
행정동_코드 is highly overall correlated with 위치_위도 and 1 other fieldsHigh correlation
위치_경도 is highly overall correlated with 행정동_명High correlation
위치_위도 is highly overall correlated with 행정동_코드 and 1 other fieldsHigh correlation
행정동_명 is highly overall correlated with 행정동_코드 and 2 other fieldsHigh correlation
폐업일자 has 4830 (48.3%) missing valuesMissing
주소_도로명 has 1724 (17.2%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:26:07.495895
Analysis finished2023-12-11 00:26:12.493076
Duration5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22366.822
Minimum1
Maximum44491
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:26:12.552770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2318.95
Q111299
median22467
Q333474.5
95-th percentile42328.7
Maximum44491
Range44490
Interquartile range (IQR)22175.5

Descriptive statistics

Standard deviation12838.293
Coefficient of variation (CV)0.57398827
Kurtosis-1.1915977
Mean22366.822
Median Absolute Deviation (MAD)11087.5
Skewness-0.0090477899
Sum2.2366822 × 108
Variance1.6482177 × 108
MonotonicityNot monotonic
2023-12-11T09:26:12.666205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12336 1
 
< 0.1%
9747 1
 
< 0.1%
22722 1
 
< 0.1%
27397 1
 
< 0.1%
7461 1
 
< 0.1%
35946 1
 
< 0.1%
21126 1
 
< 0.1%
10380 1
 
< 0.1%
37518 1
 
< 0.1%
13256 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
25 1
< 0.1%
26 1
< 0.1%
27 1
< 0.1%
31 1
< 0.1%
37 1
< 0.1%
40 1
< 0.1%
43 1
< 0.1%
51 1
< 0.1%
ValueCountFrequency (%)
44491 1
< 0.1%
44490 1
< 0.1%
44489 1
< 0.1%
44486 1
< 0.1%
44483 1
< 0.1%
44482 1
< 0.1%
44474 1
< 0.1%
44472 1
< 0.1%
44469 1
< 0.1%
44465 1
< 0.1%

기준_년
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2022
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 10000
100.0%

Length

2023-12-11T09:26:12.766956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:12.836199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 10000
100.0%

기준_월
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
7
10000 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7
2nd row7
3rd row7
4th row7
5th row7

Common Values

ValueCountFrequency (%)
7 10000
100.0%

Length

2023-12-11T09:26:12.921389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:13.006444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
7 10000
100.0%

시도_명
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 10000
100.0%

Length

2023-12-11T09:26:13.077322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:13.146963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 10000
100.0%

시군구_명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
김해시 10000
100.0%

Length

2023-12-11T09:26:13.222270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:13.292754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해시 10000
100.0%

행정동_명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
내외동
1774 
북부동
976 
활천동
975 
장유2동
931 
진영읍
892 
Other values (14)
4452 

Length

Max length5
Median length3
Mean length3.2521
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row칠산서부동
2nd row장유1동
3rd row북부동
4th row삼안동
5th row진례면

Common Values

ValueCountFrequency (%)
내외동 1774
17.7%
북부동 976
9.8%
활천동 975
9.8%
장유2동 931
9.3%
진영읍 892
8.9%
삼안동 722
7.2%
장유3동 664
 
6.6%
장유1동 498
 
5.0%
부원동 446
 
4.5%
회현동 347
 
3.5%
Other values (9) 1775
17.8%

Length

2023-12-11T09:26:13.379293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내외동 1774
17.7%
북부동 976
9.8%
활천동 975
9.8%
장유2동 931
9.3%
진영읍 892
8.9%
삼안동 722
7.2%
장유3동 664
 
6.6%
장유1동 498
 
5.0%
부원동 446
 
4.5%
회현동 347
 
3.5%
Other values (9) 1775
17.8%

시도_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
48
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48
2nd row48
3rd row48
4th row48
5th row48

Common Values

ValueCountFrequency (%)
48 10000
100.0%

Length

2023-12-11T09:26:13.497996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:13.594576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48 10000
100.0%

시군구_코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
48250
10000 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row48250
2nd row48250
3rd row48250
4th row48250
5th row48250

Common Values

ValueCountFrequency (%)
48250 10000
100.0%

Length

2023-12-11T09:26:13.696225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:13.774679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
48250 10000
100.0%

행정동_코드
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8250515 × 109
Minimum4.825025 × 109
Maximum4.825063 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:26:13.844626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.825025 × 109
5-th percentile4.825025 × 109
Q14.825052 × 109
median4.825055 × 109
Q34.825059 × 109
95-th percentile4.825063 × 109
Maximum4.825063 × 109
Range38000
Interquartile range (IQR)7000

Descriptive statistics

Standard deviation11669.385
Coefficient of variation (CV)2.4184997 × 10-6
Kurtosis0.21249267
Mean4.8250515 × 109
Median Absolute Deviation (MAD)4000
Skewness-1.2677357
Sum4.8250515 × 1013
Variance1.3617456 × 108
MonotonicityNot monotonic
2023-12-11T09:26:13.942436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4825054000 1774
17.7%
4825055000 976
9.8%
4825058000 975
9.8%
4825062000 931
9.3%
4825025000 892
8.9%
4825059000 722
7.2%
4825063000 664
 
6.6%
4825061000 498
 
5.0%
4825053000 446
 
4.5%
4825052000 347
 
3.5%
Other values (9) 1775
17.8%
ValueCountFrequency (%)
4825025000 892
8.9%
4825032000 311
 
3.1%
4825033000 218
 
2.2%
4825034000 314
 
3.1%
4825035000 147
 
1.5%
4825036000 104
 
1.0%
4825037000 105
 
1.1%
4825051000 191
 
1.9%
4825052000 347
 
3.5%
4825053000 446
4.5%
ValueCountFrequency (%)
4825063000 664
 
6.6%
4825062000 931
9.3%
4825061000 498
 
5.0%
4825060000 171
 
1.7%
4825059000 722
7.2%
4825058000 975
9.8%
4825056500 214
 
2.1%
4825055000 976
9.8%
4825054000 1774
17.7%
4825053000 446
 
4.5%

업종대분류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
식품
6815 
생활
988 
건강
823 
문화
 
627
동물
 
616

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활
2nd row생활
3rd row건강
4th row식품
5th row식품

Common Values

ValueCountFrequency (%)
식품 6815
68.2%
생활 988
 
9.9%
건강 823
 
8.2%
문화 627
 
6.3%
동물 616
 
6.2%
기타 131
 
1.3%

Length

2023-12-11T09:26:14.049424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:14.140049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품 6815
68.2%
생활 988
 
9.9%
건강 823
 
8.2%
문화 627
 
6.3%
동물 616
 
6.2%
기타 131
 
1.3%

업종중분류
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
식품제조/가공/판매
3505 
음식점
2812 
미용
779 
의료기관
468 
의료기기
355 
Other values (17)
2081 

Length

Max length10
Median length9
Mean length5.5135
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미용
2nd row미용
3rd row의료기관
4th row음식점
5th row식품제조/가공/판매

Common Values

ValueCountFrequency (%)
식품제조/가공/판매 3505
35.0%
음식점 2812
28.1%
미용 779
 
7.8%
의료기관 468
 
4.7%
의료기기 355
 
3.5%
축산 315
 
3.1%
게임 306
 
3.1%
동물 301
 
3.0%
유흥주점/단란주점 260
 
2.6%
급식 238
 
2.4%
Other values (12) 661
 
6.6%

Length

2023-12-11T09:26:14.337091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
식품제조/가공/판매 3505
35.0%
음식점 2812
28.1%
미용 779
 
7.8%
의료기관 468
 
4.7%
의료기기 355
 
3.5%
축산 315
 
3.1%
게임 306
 
3.1%
동물 301
 
3.0%
유흥주점/단란주점 260
 
2.6%
급식 238
 
2.4%
Other values (12) 661
 
6.6%

업종명
Text

Distinct90
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:26:14.536941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.3671
Min length2

Characters and Unicode

Total characters63671
Distinct characters132
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.1%

Sample

1st row미용업
2nd row미용업
3rd row약국
4th row일반음식점
5th row건강기능식품일반판매업
ValueCountFrequency (%)
일반음식점 2802
27.5%
즉석판매제조가공업 1210
11.9%
미용업 779
 
7.6%
건강기능식품일반판매업 643
 
6.3%
식품자동판매기업 453
 
4.4%
축산판매업 411
 
4.0%
의료기기판매(임대)업 312
 
3.1%
가축사육업 277
 
2.7%
유흥주점영업 209
 
2.1%
안전상비의약품 182
 
1.8%
Other values (82) 2910
28.6%
2023-12-11T09:26:14.861588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 6572
 
10.3%
식 4688
 
7.4%
반 3567
 
5.6%
일 3524
 
5.5%
판 3432
 
5.4%
매 3398
 
5.3%
점 3207
 
5.0%
음 2815
 
4.4%
제 1875
 
2.9%
기 1866
 
2.9%
Other values (122) 28727
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62724
98.5%
Open Punctuation 361
 
0.6%
Close Punctuation 361
 
0.6%
Space Separator 188
 
0.3%
Other Punctuation 37
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6572
 
10.5%
식 4688
 
7.5%
반 3567
 
5.7%
일 3524
 
5.6%
판 3432
 
5.5%
매 3398
 
5.4%
점 3207
 
5.1%
음 2815
 
4.5%
제 1875
 
3.0%
기 1866
 
3.0%
Other values (117) 27780
44.3%
Other Punctuation
ValueCountFrequency (%)
· 31
83.8%
, 6
 
16.2%
Open Punctuation
ValueCountFrequency (%)
( 361
100.0%
Close Punctuation
ValueCountFrequency (%)
) 361
100.0%
Space Separator
ValueCountFrequency (%)
188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62724
98.5%
Common 947
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6572
 
10.5%
식 4688
 
7.5%
반 3567
 
5.7%
일 3524
 
5.6%
판 3432
 
5.5%
매 3398
 
5.4%
점 3207
 
5.1%
음 2815
 
4.5%
제 1875
 
3.0%
기 1866
 
3.0%
Other values (117) 27780
44.3%
Common
ValueCountFrequency (%)
( 361
38.1%
) 361
38.1%
188
19.9%
· 31
 
3.3%
, 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62724
98.5%
ASCII 916
 
1.4%
None 31
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 6572
 
10.5%
식 4688
 
7.5%
반 3567
 
5.7%
일 3524
 
5.6%
판 3432
 
5.5%
매 3398
 
5.4%
점 3207
 
5.1%
음 2815
 
4.5%
제 1875
 
3.0%
기 1866
 
3.0%
Other values (117) 27780
44.3%
ASCII
ValueCountFrequency (%)
( 361
39.4%
) 361
39.4%
188
20.5%
, 6
 
0.7%
None
ValueCountFrequency (%)
· 31
100.0%

창업일자
Date

Distinct4927
Distinct (%)49.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1964-02-11 00:00:00
Maximum2022-07-29 00:00:00
2023-12-11T09:26:14.990908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:15.122747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

MISSING 

Distinct3055
Distinct (%)59.1%
Missing4830
Missing (%)48.3%
Memory size156.2 KiB
Minimum1993-12-28 00:00:00
Maximum2022-07-28 00:00:00
2023-12-11T09:26:15.248739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:15.375058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
4963 
영업/정상
4698 
취소/말소/만료/정지/중지
 
326
휴업
 
13

Length

Max length14
Median length5
Mean length3.8006
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐업
2nd row영업/정상
3rd row폐업
4th row폐업
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 4963
49.6%
영업/정상 4698
47.0%
취소/말소/만료/정지/중지 326
 
3.3%
휴업 13
 
0.1%

Length

2023-12-11T09:26:15.490928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:26:15.582677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4963
49.6%
영업/정상 4698
47.0%
취소/말소/만료/정지/중지 326
 
3.3%
휴업 13
 
0.1%

주소_지번
Text

Distinct8305
Distinct (%)83.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:26:15.838348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length48
Mean length23.3299
Min length14

Characters and Unicode

Total characters233299
Distinct characters457
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7402 ?
Unique (%)74.0%

Sample

1st row경상남도 김해시 흥동 48-4번지 1층
2nd row경상남도 김해시 내덕동 221-11
3rd row경상남도 김해시 삼계동 1511번지 3호
4th row경상남도 김해시 삼방동 160-1번지
5th row경상남도 김해시 진례면 산본리 47-13
ValueCountFrequency (%)
경상남도 10000
20.3%
김해시 10000
20.3%
외동 1057
 
2.1%
진영읍 892
 
1.8%
1층 736
 
1.5%
내동 714
 
1.4%
삼방동 623
 
1.3%
삼계동 618
 
1.3%
대청동 606
 
1.2%
어방동 591
 
1.2%
Other values (7806) 23425
47.6%
2023-12-11T09:26:16.259458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39262
 
16.8%
1 14235
 
6.1%
상 11055
 
4.7%
해 10397
 
4.5%
김 10387
 
4.5%
시 10138
 
4.3%
도 10070
 
4.3%
경 10049
 
4.3%
남 10035
 
4.3%
동 9504
 
4.1%
Other values (447) 98167
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134002
57.4%
Decimal Number 51021
 
21.9%
Space Separator 39262
 
16.8%
Dash Punctuation 8027
 
3.4%
Uppercase Letter 384
 
0.2%
Other Punctuation 376
 
0.2%
Open Punctuation 79
 
< 0.1%
Close Punctuation 79
 
< 0.1%
Lowercase Letter 55
 
< 0.1%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 11055
 
8.2%
해 10397
 
7.8%
김 10387
 
7.8%
시 10138
 
7.6%
도 10070
 
7.5%
경 10049
 
7.5%
남 10035
 
7.5%
동 9504
 
7.1%
지 4919
 
3.7%
번 4318
 
3.2%
Other values (387) 43130
32.2%
Uppercase Letter
ValueCountFrequency (%)
B 110
28.6%
A 100
26.0%
S 41
 
10.7%
G 27
 
7.0%
L 20
 
5.2%
C 16
 
4.2%
D 11
 
2.9%
T 11
 
2.9%
P 7
 
1.8%
O 7
 
1.8%
Other values (13) 34
 
8.9%
Lowercase Letter
ValueCountFrequency (%)
g 11
20.0%
s 10
18.2%
e 9
16.4%
o 6
10.9%
a 4
 
7.3%
i 3
 
5.5%
y 2
 
3.6%
d 2
 
3.6%
t 2
 
3.6%
b 1
 
1.8%
Other values (5) 5
9.1%
Decimal Number
ValueCountFrequency (%)
1 14235
27.9%
2 6280
12.3%
0 4774
 
9.4%
3 4742
 
9.3%
4 4312
 
8.5%
6 4217
 
8.3%
5 3972
 
7.8%
7 2940
 
5.8%
9 2819
 
5.5%
8 2730
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 334
88.8%
. 19
 
5.1%
' 9
 
2.4%
/ 9
 
2.4%
@ 3
 
0.8%
: 2
 
0.5%
Space Separator
ValueCountFrequency (%)
39262
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8027
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134002
57.4%
Common 98857
42.4%
Latin 440
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 11055
 
8.2%
해 10397
 
7.8%
김 10387
 
7.8%
시 10138
 
7.6%
도 10070
 
7.5%
경 10049
 
7.5%
남 10035
 
7.5%
동 9504
 
7.1%
지 4919
 
3.7%
번 4318
 
3.2%
Other values (387) 43130
32.2%
Latin
ValueCountFrequency (%)
B 110
25.0%
A 100
22.7%
S 41
 
9.3%
G 27
 
6.1%
L 20
 
4.5%
C 16
 
3.6%
D 11
 
2.5%
T 11
 
2.5%
g 11
 
2.5%
s 10
 
2.3%
Other values (29) 83
18.9%
Common
ValueCountFrequency (%)
39262
39.7%
1 14235
 
14.4%
- 8027
 
8.1%
2 6280
 
6.4%
0 4774
 
4.8%
3 4742
 
4.8%
4 4312
 
4.4%
6 4217
 
4.3%
5 3972
 
4.0%
7 2940
 
3.0%
Other values (11) 6096
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133998
57.4%
ASCII 99296
42.6%
Compat Jamo 4
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39262
39.5%
1 14235
 
14.3%
- 8027
 
8.1%
2 6280
 
6.3%
0 4774
 
4.8%
3 4742
 
4.8%
4 4312
 
4.3%
6 4217
 
4.2%
5 3972
 
4.0%
7 2940
 
3.0%
Other values (49) 6535
 
6.6%
Hangul
ValueCountFrequency (%)
상 11055
 
8.3%
해 10397
 
7.8%
김 10387
 
7.8%
시 10138
 
7.6%
도 10070
 
7.5%
경 10049
 
7.5%
남 10035
 
7.5%
동 9504
 
7.1%
지 4919
 
3.7%
번 4318
 
3.2%
Other values (383) 43126
32.2%
Compat Jamo
ValueCountFrequency (%)
ㅁ 1
25.0%
ㄷ 1
25.0%
ㄴ 1
25.0%
ㄱ 1
25.0%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%

주소_도로명
Text

MISSING 

Distinct7017
Distinct (%)84.8%
Missing1724
Missing (%)17.2%
Memory size156.2 KiB
2023-12-11T09:26:16.561779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length55
Mean length28.076365
Min length14

Characters and Unicode

Total characters232360
Distinct characters449
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6314 ?
Unique (%)76.3%

Sample

1st row경상남도 김해시 흥동로 78, 1층 (흥동)
2nd row경상남도 김해시 금관대로599번길 4-26, 1층 (내덕동)
3rd row경상남도 김해시 가야로 201 (삼계동)
4th row경상남도 김해시 진례면 고모로 67
5th row경상남도 김해시 칠산로399번길 31 (화목동)
ValueCountFrequency (%)
경상남도 8276
 
17.7%
김해시 8188
 
17.5%
1층 1314
 
2.8%
진영읍 778
 
1.7%
외동 655
 
1.4%
김해대로 408
 
0.9%
내동 394
 
0.8%
삼계동 393
 
0.8%
삼방동 357
 
0.8%
어방동 341
 
0.7%
Other values (4274) 25611
54.8%
2023-12-11T09:26:17.339411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38439
 
16.5%
1 10749
 
4.6%
해 9800
 
4.2%
김 9611
 
4.1%
상 9015
 
3.9%
시 8408
 
3.6%
경 8395
 
3.6%
도 8351
 
3.6%
남 8348
 
3.6%
로 8259
 
3.6%
Other values (439) 112985
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133110
57.3%
Decimal Number 42520
 
18.3%
Space Separator 38439
 
16.5%
Close Punctuation 5555
 
2.4%
Open Punctuation 5555
 
2.4%
Other Punctuation 4628
 
2.0%
Dash Punctuation 2147
 
0.9%
Uppercase Letter 316
 
0.1%
Lowercase Letter 67
 
< 0.1%
Math Symbol 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 9800
 
7.4%
김 9611
 
7.2%
상 9015
 
6.8%
시 8408
 
6.3%
경 8395
 
6.3%
도 8351
 
6.3%
남 8348
 
6.3%
로 8259
 
6.2%
동 6788
 
5.1%
번 4630
 
3.5%
Other values (378) 51505
38.7%
Uppercase Letter
ValueCountFrequency (%)
B 84
26.6%
A 65
20.6%
S 41
13.0%
G 29
 
9.2%
C 23
 
7.3%
D 13
 
4.1%
O 9
 
2.8%
I 7
 
2.2%
N 5
 
1.6%
T 5
 
1.6%
Other values (15) 35
11.1%
Lowercase Letter
ValueCountFrequency (%)
g 12
17.9%
s 12
17.9%
e 11
16.4%
o 6
9.0%
i 5
7.5%
n 4
 
6.0%
a 4
 
6.0%
d 3
 
4.5%
t 2
 
3.0%
y 2
 
3.0%
Other values (6) 6
9.0%
Decimal Number
ValueCountFrequency (%)
1 10749
25.3%
2 6913
16.3%
3 4607
10.8%
0 3999
 
9.4%
4 3483
 
8.2%
5 3227
 
7.6%
6 2643
 
6.2%
7 2535
 
6.0%
9 2234
 
5.3%
8 2130
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 4610
99.6%
/ 8
 
0.2%
. 6
 
0.1%
: 4
 
0.1%
Space Separator
ValueCountFrequency (%)
38439
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5555
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2147
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133110
57.3%
Common 98865
42.5%
Latin 385
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 9800
 
7.4%
김 9611
 
7.2%
상 9015
 
6.8%
시 8408
 
6.3%
경 8395
 
6.3%
도 8351
 
6.3%
남 8348
 
6.3%
로 8259
 
6.2%
동 6788
 
5.1%
번 4630
 
3.5%
Other values (378) 51505
38.7%
Latin
ValueCountFrequency (%)
B 84
21.8%
A 65
16.9%
S 41
10.6%
G 29
 
7.5%
C 23
 
6.0%
D 13
 
3.4%
g 12
 
3.1%
s 12
 
3.1%
e 11
 
2.9%
O 9
 
2.3%
Other values (32) 86
22.3%
Common
ValueCountFrequency (%)
38439
38.9%
1 10749
 
10.9%
2 6913
 
7.0%
) 5555
 
5.6%
( 5555
 
5.6%
, 4610
 
4.7%
3 4607
 
4.7%
0 3999
 
4.0%
4 3483
 
3.5%
5 3227
 
3.3%
Other values (9) 11728
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133110
57.3%
ASCII 99248
42.7%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38439
38.7%
1 10749
 
10.8%
2 6913
 
7.0%
) 5555
 
5.6%
( 5555
 
5.6%
, 4610
 
4.6%
3 4607
 
4.6%
0 3999
 
4.0%
4 3483
 
3.5%
5 3227
 
3.3%
Other values (50) 12111
 
12.2%
Hangul
ValueCountFrequency (%)
해 9800
 
7.4%
김 9611
 
7.2%
상 9015
 
6.8%
시 8408
 
6.3%
경 8395
 
6.3%
도 8351
 
6.3%
남 8348
 
6.3%
로 8259
 
6.2%
동 6788
 
5.1%
번 4630
 
3.5%
Other values (378) 51505
38.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 2
100.0%

사업장명
Text

Distinct8955
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T09:26:17.583337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length27
Mean length6.5447
Min length1

Characters and Unicode

Total characters65447
Distinct characters1033
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

Unique8352 ?
Unique (%)83.5%

Sample

1st row심상희헤어아트
2nd row빅마마미용실
3rd row고운손약국
4th row상류사회(한식점)
5th row웰빙녹즙
ValueCountFrequency (%)
주식회사 85
 
0.7%
김해점 55
 
0.5%
씨유 46
 
0.4%
세븐일레븐 45
 
0.4%
pc방 39
 
0.3%
주)정성 34
 
0.3%
진영점 30
 
0.3%
장유점 28
 
0.2%
주)미트벨리 25
 
0.2%
다정 23
 
0.2%
Other values (9537) 11320
96.5%
2023-12-11T09:26:18.001167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1730
 
2.6%
점 1547
 
2.4%
이 1289
 
2.0%
주 1167
 
1.8%
) 1151
 
1.8%
( 1146
 
1.8%
장 964
 
1.5%
스 951
 
1.5%
해 907
 
1.4%
식 886
 
1.4%
Other values (1023) 53709
82.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57847
88.4%
Space Separator 1730
 
2.6%
Uppercase Letter 1667
 
2.5%
Close Punctuation 1151
 
1.8%
Open Punctuation 1146
 
1.8%
Lowercase Letter 915
 
1.4%
Decimal Number 763
 
1.2%
Other Punctuation 188
 
0.3%
Dash Punctuation 32
 
< 0.1%
Other Symbol 3
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1547
 
2.7%
이 1289
 
2.2%
주 1167
 
2.0%
장 964
 
1.7%
스 951
 
1.6%
해 907
 
1.6%
식 886
 
1.5%
김 872
 
1.5%
리 862
 
1.5%
원 821
 
1.4%
Other values (941) 47581
82.3%
Uppercase Letter
ValueCountFrequency (%)
C 259
15.5%
P 183
 
11.0%
S 152
 
9.1%
G 139
 
8.3%
O 82
 
4.9%
B 82
 
4.9%
A 77
 
4.6%
N 74
 
4.4%
U 62
 
3.7%
T 61
 
3.7%
Other values (16) 496
29.8%
Lowercase Letter
ValueCountFrequency (%)
e 105
11.5%
o 88
 
9.6%
a 85
 
9.3%
i 67
 
7.3%
n 65
 
7.1%
l 59
 
6.4%
s 53
 
5.8%
r 49
 
5.4%
u 45
 
4.9%
t 39
 
4.3%
Other values (16) 260
28.4%
Other Punctuation
ValueCountFrequency (%)
& 62
33.0%
. 55
29.3%
, 25
13.3%
# 13
 
6.9%
' 11
 
5.9%
· 7
 
3.7%
! 6
 
3.2%
＆ 4
 
2.1%
/ 3
 
1.6%
． 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 254
33.3%
5 167
21.9%
1 101
 
13.2%
0 56
 
7.3%
4 54
 
7.1%
3 42
 
5.5%
6 27
 
3.5%
7 24
 
3.1%
9 24
 
3.1%
8 14
 
1.8%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Math Symbol
ValueCountFrequency (%)
+ 1
50.0%
~ 1
50.0%
Space Separator
ValueCountFrequency (%)
1730
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1151
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57840
88.4%
Common 5012
 
7.7%
Latin 2585
 
3.9%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1547
 
2.7%
이 1289
 
2.2%
주 1167
 
2.0%
장 964
 
1.7%
스 951
 
1.6%
해 907
 
1.6%
식 886
 
1.5%
김 872
 
1.5%
리 862
 
1.5%
원 821
 
1.4%
Other values (934) 47574
82.3%
Latin
ValueCountFrequency (%)
C 259
 
10.0%
P 183
 
7.1%
S 152
 
5.9%
G 139
 
5.4%
e 105
 
4.1%
o 88
 
3.4%
a 85
 
3.3%
O 82
 
3.2%
B 82
 
3.2%
A 77
 
3.0%
Other values (44) 1333
51.6%
Common
ValueCountFrequency (%)
1730
34.5%
) 1151
23.0%
( 1146
22.9%
2 254
 
5.1%
5 167
 
3.3%
1 101
 
2.0%
& 62
 
1.2%
0 56
 
1.1%
. 55
 
1.1%
4 54
 
1.1%
Other values (17) 236
 
4.7%
Han
ValueCountFrequency (%)
美 2
20.0%
一 2
20.0%
品 1
10.0%
粧 1
10.0%
院 1
10.0%
光 1
10.0%
春 1
10.0%
毛 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57837
88.4%
ASCII 7582
 
11.6%
None 15
 
< 0.1%
CJK 10
 
< 0.1%
Number Forms 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1730
22.8%
) 1151
15.2%
( 1146
15.1%
C 259
 
3.4%
2 254
 
3.4%
P 183
 
2.4%
5 167
 
2.2%
S 152
 
2.0%
G 139
 
1.8%
e 105
 
1.4%
Other values (66) 2296
30.3%
Hangul
ValueCountFrequency (%)
점 1547
 
2.7%
이 1289
 
2.2%
주 1167
 
2.0%
장 964
 
1.7%
스 951
 
1.6%
해 907
 
1.6%
식 886
 
1.5%
김 872
 
1.5%
리 862
 
1.5%
원 821
 
1.4%
Other values (933) 47571
82.3%
None
ValueCountFrequency (%)
· 7
46.7%
＆ 4
26.7%
㈜ 3
20.0%
． 1
 
6.7%
CJK
ValueCountFrequency (%)
美 2
20.0%
一 2
20.0%
品 1
10.0%
粧 1
10.0%
院 1
10.0%
光 1
10.0%
春 1
10.0%
毛 1
10.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%

위치_경도
Real number (ℝ)

HIGH CORRELATION 

Distinct5412
Distinct (%)54.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.84729
Minimum128.70647
Maximum129.00301
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:26:18.151894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70647
5-th percentile128.73451
Q1128.80856
median128.86552
Q3128.88295
95-th percentile128.91241
Maximum129.00301
Range0.2965427
Interquartile range (IQR)0.0743872

Descriptive statistics

Standard deviation0.053946577
Coefficient of variation (CV)0.00041868617
Kurtosis-0.13949581
Mean128.84729
Median Absolute Deviation (MAD)0.03782655
Skewness-0.55118057
Sum1288472.9
Variance0.0029102331
MonotonicityNot monotonic
2023-12-11T09:26:18.288920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8721477 162
 
1.6%
128.8701773 101
 
1.0%
128.9074532 66
 
0.7%
128.8128999 58
 
0.6%
128.8012803 50
 
0.5%
128.9003747 42
 
0.4%
128.8665195 40
 
0.4%
128.8642087 37
 
0.4%
128.8638896 35
 
0.4%
128.8546724 34
 
0.3%
Other values (5402) 9375
93.8%
ValueCountFrequency (%)
128.7064701 1
 
< 0.1%
128.7068469 1
 
< 0.1%
128.7069703 1
 
< 0.1%
128.7070445 1
 
< 0.1%
128.70772 1
 
< 0.1%
128.7077487 3
< 0.1%
128.7079225 1
 
< 0.1%
128.7079353 1
 
< 0.1%
128.7079642 1
 
< 0.1%
128.7080469 1
 
< 0.1%
ValueCountFrequency (%)
129.0030128 1
 
< 0.1%
129.0028263 3
< 0.1%
129.0003661 2
< 0.1%
129.0001766 1
 
< 0.1%
129.0000431 1
 
< 0.1%
128.9992819 1
 
< 0.1%
128.9971042 1
 
< 0.1%
128.9959007 1
 
< 0.1%
128.9949714 1
 
< 0.1%
128.9943471 1
 
< 0.1%

위치_위도
Real number (ℝ)

HIGH CORRELATION 

Distinct5420
Distinct (%)54.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.238645
Minimum35.162709
Maximum35.389769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T09:26:18.440036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.162709
5-th percentile35.17742
Q135.226069
median35.234805
Q335.250147
95-th percentile35.308559
Maximum35.389769
Range0.22706047
Interquartile range (IQR)0.02407789

Descriptive statistics

Standard deviation0.036923914
Coefficient of variation (CV)0.0010478245
Kurtosis0.45662921
Mean35.238645
Median Absolute Deviation (MAD)0.01332633
Skewness0.55149486
Sum352386.45
Variance0.0013633754
MonotonicityNot monotonic
2023-12-11T09:26:18.587446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.22913159 162
 
1.6%
35.241828 101
 
1.0%
35.24413505 66
 
0.7%
35.22612787 58
 
0.6%
35.19303447 50
 
0.5%
35.22606878 42
 
0.4%
35.25975828 40
 
0.4%
35.23360735 37
 
0.4%
35.23098643 35
 
0.4%
35.19188777 34
 
0.3%
Other values (5410) 9375
93.8%
ValueCountFrequency (%)
35.16270854 1
 
< 0.1%
35.1632937 3
< 0.1%
35.16599565 3
< 0.1%
35.16617377 1
 
< 0.1%
35.16750032 1
 
< 0.1%
35.16760274 2
 
< 0.1%
35.16774724 1
 
< 0.1%
35.16783873 5
0.1%
35.16800268 1
 
< 0.1%
35.16821295 1
 
< 0.1%
ValueCountFrequency (%)
35.38976901 1
< 0.1%
35.38595117 1
< 0.1%
35.38584594 1
< 0.1%
35.38579727 1
< 0.1%
35.3805313 1
< 0.1%
35.37935093 1
< 0.1%
35.37478453 1
< 0.1%
35.374252 1
< 0.1%
35.3740484 1
< 0.1%
35.37306661 2
< 0.1%

Interactions

2023-12-11T09:26:11.572616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.015110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.391381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.905378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:11.670201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.097453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.511233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:11.216486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:11.785171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.212929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.642166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:11.347537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:11.917763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.300899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:10.778336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:26:11.469311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:26:18.696812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동_명행정동_코드업종대분류업종중분류업종명영업상태위치_경도위치_위도
관리번호1.0000.3410.2770.8700.9270.9840.5910.2160.275
행정동_명0.3411.0001.0000.3540.4340.6040.1640.9350.921
행정동_코드0.2771.0001.0000.2500.4460.5920.1110.8560.762
업종대분류0.8700.3540.2501.0001.0001.0000.4060.1710.252
업종중분류0.9270.4340.4461.0001.0001.0000.6310.2560.380
업종명0.9840.6040.5921.0001.0001.0000.7750.3940.566
영업상태0.5910.1640.1110.4060.6310.7751.0000.0890.145
위치_경도0.2160.9350.8560.1710.2560.3940.0891.0000.846
위치_위도0.2750.9210.7620.2520.3800.5660.1450.8461.000
2023-12-11T09:26:18.838202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종대분류업종중분류행정동_명영업상태
업종대분류1.0000.9990.1720.272
업종중분류0.9991.0000.1380.390
행정동_명0.1720.1381.0000.090
영업상태0.2720.3900.0901.000
2023-12-11T09:26:18.955593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동_코드위치_경도위치_위도행정동_명업종대분류업종중분류영업상태
관리번호1.0000.048-0.000-0.0480.1340.7000.6880.396
행정동_코드0.0481.0000.131-0.6440.9990.1460.1860.076
위치_경도-0.0000.1311.0000.0890.7160.0900.0970.053
위치_위도-0.048-0.6440.0891.0000.6750.1350.1500.087
행정동_명0.1340.9990.7160.6751.0000.1720.1380.090
업종대분류0.7000.1460.0900.1350.1721.0000.9990.272
업종중분류0.6880.1860.0970.1500.1380.9991.0000.390
영업상태0.3960.0760.0530.0870.0900.2720.3901.000

Missing values

2023-12-11T09:26:12.079791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:26:12.301162image/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.
2023-12-11T09:26:12.430249image/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

관리번호기준_년기준_월시도_명시군구_명행정동_명시도_코드시군구_코드행정동_코드업종대분류업종중분류업종명창업일자폐업일자영업상태주소_지번주소_도로명사업장명위치_경도위치_위도
123351233620227경상남도김해시칠산서부동48482504825056500생활미용미용업2013-04-192019-02-28폐업경상남도 김해시 흥동 48-4번지 1층경상남도 김해시 흥동로 78, 1층 (흥동)심상희헤어아트128.85714735.221737
104191042020227경상남도김해시장유1동48482504825061000생활미용미용업2012-03-08<NA>영업/정상경상남도 김해시 내덕동 221-11경상남도 김해시 금관대로599번길 4-26, 1층 (내덕동)빅마마미용실128.81507935.203225
1776177720227경상남도김해시북부동48482504825055000건강의료기관약국2010-11-292011-08-02폐업경상남도 김해시 삼계동 1511번지 3호경상남도 김해시 가야로 201 (삼계동)고운손약국128.8724135.25967
423864238720227경상남도김해시삼안동48482504825059000식품음식점일반음식점1997-03-141999-11-19폐업경상남도 김해시 삼방동 160-1번지<NA>상류사회(한식점)128.90420835.24729
166981669920227경상남도김해시진례면48482504825033000식품식품제조/가공/판매건강기능식품일반판매업2021-01-15<NA>영업/정상경상남도 김해시 진례면 산본리 47-13경상남도 김해시 진례면 고모로 67웰빙녹즙128.76847135.234216
205952059620227경상남도김해시칠산서부동48482504825056500식품식품제조/가공/판매축산가공업2013-08-232022-06-29폐업경상남도 김해시 화목동 1052-1경상남도 김해시 칠산로399번길 31 (화목동)금계식품128.8498335.207954
321053210620227경상남도김해시부원동48482504825053000식품음식점일반음식점2018-12-27<NA>영업/정상경상남도 김해시 부원동 1043번지 부원역 푸르지오 아이스퀘어몰 A동 201호경상남도 김해시 김해대로 2342, 부원역 푸르지오 아이스퀘어몰 A동 2층 201호 (부원동)샤브쌈주머니(아이스퀘어몰)128.88325735.225073
9787978820227경상남도김해시북부동48482504825055000기타미디어출판사2022-03-29<NA>영업/정상경상남도 김해시 삼계동 1490-10경상남도 김해시 삼계중앙로 25(주)휴마인128.86773635.260692
7824782520227경상남도김해시북부동48482504825055000문화관광관광사업자2008-10-10<NA>영업/정상경상남도 김해시 삼계동 1487경상남도 김해시 삼계중앙로 30 (삼계동)(주)가야드림128.86845835.260196
411014110220227경상남도김해시칠산서부동48482504825056500식품음식점일반음식점2011-07-132022-07-21폐업경상남도 김해시 흥동 4-4 외1필지경상남도 김해시 전하로 233 (흥동,외1필지)하면옥 김해점128.87194835.224839
관리번호기준_년기준_월시도_명시군구_명행정동_명시도_코드시군구_코드행정동_코드업종대분류업종중분류업종명창업일자폐업일자영업상태주소_지번주소_도로명사업장명위치_경도위치_위도
111921119320227경상남도김해시삼안동48482504825059000생활미용미용업2017-11-15<NA>영업/정상경상남도 김해시 삼방동 666-9번지경상남도 김해시 삼안로 249, 2층 (삼방동)듀네일128.90999135.250182
210302103120227경상남도김해시장유3동48482504825063000식품식품제조/가공/판매식품소분업2015-11-05<NA>영업/정상경상남도 김해시 관동동 448-5 , 롯데슈퍼 내경상남도 김해시 계동로23번길 12 (관동동, 롯데슈퍼 내)아이생선128.79480335.178551
435134351420227경상남도김해시내외동48482504825054000식품음식점일반음식점1996-08-032011-12-12폐업경상남도 김해시 외동 696-5번지<NA>진경양식128.8528935.235426
148041480520227경상남도김해시장유1동48482504825061000식품급식집단급식소2007-07-30<NA>영업/정상경상남도 김해시 부곡동 100번지경상남도 김해시 장유로55번길 29-17 (부곡동)우리텍주식회사128.79846535.216874
278592786020227경상남도김해시활천동48482504825058000식품식품제조/가공/판매즉석판매제조가공업2012-02-132018-01-29폐업경상남도 김해시 삼정동 659-9경상남도 김해시 김해대로2491번길 16 (삼정동)하동명품재첩국128.89921435.229436
7959796020227경상남도김해시삼안동48482504825059000문화관광종합유원시설업1991-10-05<NA>영업/정상경상남도 김해시 삼방동 산 123경상남도 김해시 인제로 368 (삼방동)가야랜드128.90226835.262086
186181861920227경상남도김해시내외동48482504825054000식품식품제조/가공/판매건강기능식품일반판매업2020-06-292021-07-23폐업경상남도 김해시 외동 677-6경상남도 김해시 평전로71번길 7드림 인 파크128.8544135.237755
335513355220227경상남도김해시생림면48482504825035000식품음식점일반음식점2009-06-03<NA>영업/정상경상남도 김해시 생림면 나전리 82-4번지경상남도 김해시 생림면 인제로 605해다미128.88847235.279302
256892569020227경상남도김해시내외동48482504825054000식품식품제조/가공/판매즉석판매제조가공업1999-04-03<NA>영업/정상경상남도 김해시 내동 131-1경상남도 김해시 금관대로1365번길 10-22 (내동)한진건강원128.86609435.24574
9599960020227경상남도김해시활천동48482504825058000기타미디어옥외광고업2006-04-21<NA>폐업경상남도 김해시 어방동 725-5경상남도 김해시 분성로499번길 6-3예담디자인애드128.90004335.236015