Overview

Dataset statistics

Number of variables20
Number of observations10000
Missing cells6575
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. 2022년 7월 기준
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15109629/fileData.do

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
업종중분류 is highly overall correlated with 관리번호 and 1 other fieldsHigh correlation
업종대분류 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 4822 (48.2%) missing valuesMissing
주소_도로명 has 1753 (17.5%) missing valuesMissing
관리번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:56:57.312312
Analysis finished2023-12-12 16:57:03.348305
Duration6.04 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%
Mean22328.238
Minimum7
Maximum44489
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:57:03.441254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile2226.85
Q111285.75
median22312.5
Q333447.75
95-th percentile42282.1
Maximum44489
Range44482
Interquartile range (IQR)22162

Descriptive statistics

Standard deviation12836.495
Coefficient of variation (CV)0.57489958
Kurtosis-1.1925512
Mean22328.238
Median Absolute Deviation (MAD)11080.5
Skewness0.0032059925
Sum2.2328238 × 108
Variance1.647756 × 108
MonotonicityNot monotonic
2023-12-13T01:57:03.613192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15665 1
 
< 0.1%
35597 1
 
< 0.1%
22429 1
 
< 0.1%
19826 1
 
< 0.1%
33101 1
 
< 0.1%
31666 1
 
< 0.1%
22559 1
 
< 0.1%
1352 1
 
< 0.1%
28763 1
 
< 0.1%
14230 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
7 1
< 0.1%
10 1
< 0.1%
19 1
< 0.1%
23 1
< 0.1%
34 1
< 0.1%
35 1
< 0.1%
44 1
< 0.1%
46 1
< 0.1%
48 1
< 0.1%
50 1
< 0.1%
ValueCountFrequency (%)
44489 1
< 0.1%
44485 1
< 0.1%
44480 1
< 0.1%
44478 1
< 0.1%
44476 1
< 0.1%
44474 1
< 0.1%
44467 1
< 0.1%
44465 1
< 0.1%
44464 1
< 0.1%
44461 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

2023-12-13T01:57:03.738823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:04.072621image/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

2023-12-13T01:57:04.178036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:04.285180image/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

2023-12-13T01:57:04.382202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:04.486014image/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

2023-12-13T01:57:04.574090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:04.647977image/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
1726 
북부동
998 
활천동
985 
장유2동
937 
진영읍
848 
Other values (14)
4506 

Length

Max length5
Median length3
Mean length3.257
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대동면
2nd row주촌면
3rd row북부동
4th row북부동
5th row삼안동

Common Values

ValueCountFrequency (%)
내외동 1726
17.3%
북부동 998
10.0%
활천동 985
9.8%
장유2동 937
9.4%
진영읍 848
8.5%
삼안동 714
 
7.1%
장유3동 666
 
6.7%
장유1동 525
 
5.2%
부원동 472
 
4.7%
한림면 324
 
3.2%
Other values (9) 1805
18.1%

Length

2023-12-13T01:57:04.748528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
내외동 1726
17.3%
북부동 998
10.0%
활천동 985
9.8%
장유2동 937
9.4%
진영읍 848
8.5%
삼안동 714
 
7.1%
장유3동 666
 
6.7%
장유1동 525
 
5.2%
부원동 472
 
4.7%
한림면 324
 
3.2%
Other values (9) 1805
18.1%

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

2023-12-13T01:57:04.859073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:04.938303image/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

2023-12-13T01:57:05.033934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:05.110821image/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%
Mean4.8250516 × 109
Minimum4.825025 × 109
Maximum4.825063 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:57:05.186791image/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 deviation11598.866
Coefficient of variation (CV)2.4038843 × 10-6
Kurtosis0.23815511
Mean4.8250516 × 109
Median Absolute Deviation (MAD)4000
Skewness-1.2754582
Sum4.8250516 × 1013
Variance1.3453369 × 108
MonotonicityNot monotonic
2023-12-13T01:57:05.302261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
4825054000 1726
17.3%
4825055000 998
10.0%
4825058000 985
9.8%
4825062000 937
9.4%
4825025000 848
8.5%
4825059000 714
 
7.1%
4825063000 666
 
6.7%
4825061000 525
 
5.2%
4825053000 472
 
4.7%
4825034000 324
 
3.2%
Other values (9) 1805
18.1%
ValueCountFrequency (%)
4825025000 848
8.5%
4825032000 300
 
3.0%
4825033000 253
 
2.5%
4825034000 324
 
3.2%
4825035000 169
 
1.7%
4825036000 97
 
1.0%
4825037000 84
 
0.8%
4825051000 183
 
1.8%
4825052000 322
 
3.2%
4825053000 472
4.7%
ValueCountFrequency (%)
4825063000 666
 
6.7%
4825062000 937
9.4%
4825061000 525
 
5.2%
4825060000 176
 
1.8%
4825059000 714
7.1%
4825058000 985
9.8%
4825056500 221
 
2.2%
4825055000 998
10.0%
4825054000 1726
17.3%
4825053000 472
 
4.7%

업종대분류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
식품
6772 
생활
1047 
건강
818 
문화
 
642
동물
 
598

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row식품
2nd row식품
3rd row식품
4th row식품
5th row문화

Common Values

ValueCountFrequency (%)
식품 6772
67.7%
생활 1047
 
10.5%
건강 818
 
8.2%
문화 642
 
6.4%
동물 598
 
6.0%
기타 123
 
1.2%

Length

2023-12-13T01:57:05.431235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:05.525865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
식품 6772
67.7%
생활 1047
 
10.5%
건강 818
 
8.2%
문화 642
 
6.4%
동물 598
 
6.0%
기타 123
 
1.2%

업종중분류
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
식품제조/가공/판매
3472 
음식점
2807 
미용
808 
의료기관
485 
의료기기
 
333
Other values (17)
2095 

Length

Max length10
Median length9
Mean length5.4731
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
식품제조/가공/판매 3472
34.7%
음식점 2807
28.1%
미용 808
 
8.1%
의료기관 485
 
4.9%
의료기기 333
 
3.3%
축산 324
 
3.2%
게임 309
 
3.1%
동물 274
 
2.7%
유흥주점/단란주점 249
 
2.5%
급식 244
 
2.4%
Other values (12) 695
 
7.0%

Length

2023-12-13T01:57:05.637670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
식품제조/가공/판매 3472
34.7%
음식점 2807
28.1%
미용 808
 
8.1%
의료기관 485
 
4.9%
의료기기 333
 
3.3%
축산 324
 
3.2%
게임 309
 
3.1%
동물 274
 
2.7%
유흥주점/단란주점 249
 
2.5%
급식 244
 
2.4%
Other values (12) 695
 
7.0%

업종명
Text

Distinct89
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:57:05.862964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.3099
Min length2

Characters and Unicode

Total characters63099
Distinct characters135
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

Unique14 ?
Unique (%)0.1%

Sample

1st row집단급식소식품판매업
2nd row식품제조가공업
3rd row식품자동판매기업
4th row일반음식점
5th row문화예술법인
ValueCountFrequency (%)
일반음식점 2802
27.5%
즉석판매제조가공업 1182
11.6%
미용업 808
 
7.9%
건강기능식품일반판매업 632
 
6.2%
식품자동판매기업 447
 
4.4%
축산판매업 418
 
4.1%
가축사육업 298
 
2.9%
의료기기판매(임대)업 276
 
2.7%
유흥주점영업 190
 
1.9%
안전상비의약품 185
 
1.8%
Other values (81) 2951
29.0%
2023-12-13T01:57:06.195969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 6554
 
10.4%
식 4670
 
7.4%
반 3583
 
5.7%
일 3514
 
5.6%
판 3373
 
5.3%
매 3334
 
5.3%
점 3180
 
5.0%
음 2815
 
4.5%
제 1837
 
2.9%
기 1798
 
2.8%
Other values (125) 28441
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62217
98.6%
Open Punctuation 327
 
0.5%
Close Punctuation 327
 
0.5%
Space Separator 189
 
0.3%
Other Punctuation 39
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 6554
 
10.5%
식 4670
 
7.5%
반 3583
 
5.8%
일 3514
 
5.6%
판 3373
 
5.4%
매 3334
 
5.4%
점 3180
 
5.1%
음 2815
 
4.5%
제 1837
 
3.0%
기 1798
 
2.9%
Other values (119) 27559
44.3%
Other Punctuation
ValueCountFrequency (%)
· 34
87.2%
, 4
 
10.3%
. 1
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 327
100.0%
Close Punctuation
ValueCountFrequency (%)
) 327
100.0%
Space Separator
ValueCountFrequency (%)
189
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62217
98.6%
Common 882
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 6554
 
10.5%
식 4670
 
7.5%
반 3583
 
5.8%
일 3514
 
5.6%
판 3373
 
5.4%
매 3334
 
5.4%
점 3180
 
5.1%
음 2815
 
4.5%
제 1837
 
3.0%
기 1798
 
2.9%
Other values (119) 27559
44.3%
Common
ValueCountFrequency (%)
( 327
37.1%
) 327
37.1%
189
21.4%
· 34
 
3.9%
, 4
 
0.5%
. 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62217
98.6%
ASCII 848
 
1.3%
None 34
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 6554
 
10.5%
식 4670
 
7.5%
반 3583
 
5.8%
일 3514
 
5.6%
판 3373
 
5.4%
매 3334
 
5.4%
점 3180
 
5.1%
음 2815
 
4.5%
제 1837
 
3.0%
기 1798
 
2.9%
Other values (119) 27559
44.3%
ASCII
ValueCountFrequency (%)
( 327
38.6%
) 327
38.6%
189
22.3%
, 4
 
0.5%
. 1
 
0.1%
None
ValueCountFrequency (%)
· 34
100.0%

창업일자
Date

Distinct4907
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1963-10-10 00:00:00
Maximum2022-07-29 00:00:00
2023-12-13T01:57:06.315770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:06.445400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

폐업일자
Date

MISSING 

Distinct3125
Distinct (%)60.4%
Missing4822
Missing (%)48.2%
Memory size156.2 KiB
Minimum1993-06-26 00:00:00
Maximum2022-07-26 00:00:00
2023-12-13T01:57:06.577878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:06.683913image/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
4987 
영업/정상
4713 
취소/말소/만료/정지/중지
 
290
휴업
 
10

Length

Max length14
Median length5
Mean length3.7619
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 4987
49.9%
영업/정상 4713
47.1%
취소/말소/만료/정지/중지 290
 
2.9%
휴업 10
 
0.1%

Length

2023-12-13T01:57:06.792191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:57:06.873853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4987
49.9%
영업/정상 4713
47.1%
취소/말소/만료/정지/중지 290
 
2.9%
휴업 10
 
0.1%

주소_지번
Text

Distinct8423
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:57:07.081065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length47
Mean length23.4023
Min length13

Characters and Unicode

Total characters234023
Distinct characters448
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7570 ?
Unique (%)75.7%

Sample

1st row경상남도 김해시 대동면 초정리 952-528
2nd row경상남도 김해시 주촌면 원지리 680-1번지
3rd row경상남도 김해시 삼계동 1503-6 GS25김해삼계천로점 내
4th row경상남도 김해시 구산동 1062-5번지
5th row경상남도 김해시 삼방동 656번지 5호
ValueCountFrequency (%)
경상남도 10000
20.3%
김해시 10000
20.3%
외동 1020
 
2.1%
진영읍 848
 
1.7%
1층 736
 
1.5%
내동 703
 
1.4%
삼계동 662
 
1.3%
삼방동 611
 
1.2%
대청동 607
 
1.2%
어방동 598
 
1.2%
Other values (7899) 23528
47.7%
2023-12-13T01:57:07.447467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39313
 
16.8%
1 14307
 
6.1%
상 11043
 
4.7%
해 10375
 
4.4%
김 10365
 
4.4%
시 10149
 
4.3%
도 10078
 
4.3%
경 10047
 
4.3%
남 10037
 
4.3%
동 9568
 
4.1%
Other values (438) 98741
42.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134332
57.4%
Decimal Number 51401
 
22.0%
Space Separator 39313
 
16.8%
Dash Punctuation 8002
 
3.4%
Other Punctuation 415
 
0.2%
Uppercase Letter 384
 
0.2%
Open Punctuation 60
 
< 0.1%
Close Punctuation 60
 
< 0.1%
Lowercase Letter 42
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 11043
 
8.2%
해 10375
 
7.7%
김 10365
 
7.7%
시 10149
 
7.6%
도 10078
 
7.5%
경 10047
 
7.5%
남 10037
 
7.5%
동 9568
 
7.1%
지 5033
 
3.7%
번 4413
 
3.3%
Other values (379) 43224
32.2%
Uppercase Letter
ValueCountFrequency (%)
A 109
28.4%
B 103
26.8%
S 43
 
11.2%
G 30
 
7.8%
C 19
 
4.9%
D 16
 
4.2%
L 15
 
3.9%
I 8
 
2.1%
N 8
 
2.1%
T 5
 
1.3%
Other values (12) 28
 
7.3%
Lowercase Letter
ValueCountFrequency (%)
g 11
26.2%
s 9
21.4%
e 5
11.9%
o 4
 
9.5%
a 4
 
9.5%
i 2
 
4.8%
d 1
 
2.4%
c 1
 
2.4%
t 1
 
2.4%
y 1
 
2.4%
Other values (3) 3
 
7.1%
Decimal Number
ValueCountFrequency (%)
1 14307
27.8%
2 6369
12.4%
0 5077
 
9.9%
3 4743
 
9.2%
4 4356
 
8.5%
6 4086
 
7.9%
5 3910
 
7.6%
7 2947
 
5.7%
9 2820
 
5.5%
8 2786
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 371
89.4%
. 20
 
4.8%
/ 12
 
2.9%
' 8
 
1.9%
: 2
 
0.5%
@ 1
 
0.2%
· 1
 
0.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅲ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
39313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8002
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134332
57.4%
Common 99261
42.4%
Latin 430
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 11043
 
8.2%
해 10375
 
7.7%
김 10365
 
7.7%
시 10149
 
7.6%
도 10078
 
7.5%
경 10047
 
7.5%
남 10037
 
7.5%
동 9568
 
7.1%
지 5033
 
3.7%
번 4413
 
3.3%
Other values (379) 43224
32.2%
Latin
ValueCountFrequency (%)
A 109
25.3%
B 103
24.0%
S 43
 
10.0%
G 30
 
7.0%
C 19
 
4.4%
D 16
 
3.7%
L 15
 
3.5%
g 11
 
2.6%
s 9
 
2.1%
I 8
 
1.9%
Other values (27) 67
15.6%
Common
ValueCountFrequency (%)
39313
39.6%
1 14307
 
14.4%
- 8002
 
8.1%
2 6369
 
6.4%
0 5077
 
5.1%
3 4743
 
4.8%
4 4356
 
4.4%
6 4086
 
4.1%
5 3910
 
3.9%
7 2947
 
3.0%
Other values (12) 6151
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134324
57.4%
ASCII 99686
42.6%
Compat Jamo 8
 
< 0.1%
Number Forms 4
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39313
39.4%
1 14307
 
14.4%
- 8002
 
8.0%
2 6369
 
6.4%
0 5077
 
5.1%
3 4743
 
4.8%
4 4356
 
4.4%
6 4086
 
4.1%
5 3910
 
3.9%
7 2947
 
3.0%
Other values (46) 6576
 
6.6%
Hangul
ValueCountFrequency (%)
상 11043
 
8.2%
해 10375
 
7.7%
김 10365
 
7.7%
시 10149
 
7.6%
도 10078
 
7.5%
경 10047
 
7.5%
남 10037
 
7.5%
동 9568
 
7.1%
지 5033
 
3.7%
번 4413
 
3.3%
Other values (374) 43216
32.2%
Compat Jamo
ValueCountFrequency (%)
ㅇ 4
50.0%
ㅁ 1
 
12.5%
ㄷ 1
 
12.5%
ㄴ 1
 
12.5%
ㄱ 1
 
12.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
75.0%
Ⅲ 1
 
25.0%
None
ValueCountFrequency (%)
· 1
100.0%

주소_도로명
Text

MISSING 

Distinct7051
Distinct (%)85.5%
Missing1753
Missing (%)17.5%
Memory size156.2 KiB
2023-12-13T01:57:07.686866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length52
Mean length28.254396
Min length14

Characters and Unicode

Total characters233014
Distinct characters437
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6374 ?
Unique (%)77.3%

Sample

1st row경상남도 김해시 대동면 동남로41번길 22-2
2nd row경상남도 김해시 해반천로130번길 31, GS25김해삼계천로점 내 1층 (삼계동)
3rd row경상남도 김해시 해반천로16번길 15 (구산동)
4th row경상남도 김해시 삼안로 283 (삼방동)
5th row경상남도 김해시 장유로 319, 2층 (무계동)
ValueCountFrequency (%)
경상남도 8247
 
17.6%
김해시 8146
 
17.4%
1층 1324
 
2.8%
진영읍 733
 
1.6%
외동 628
 
1.3%
삼계동 441
 
0.9%
김해대로 394
 
0.8%
내동 384
 
0.8%
삼방동 362
 
0.8%
어방동 340
 
0.7%
Other values (4327) 25808
55.1%
2023-12-13T01:57:08.072861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
38560
 
16.5%
1 10943
 
4.7%
해 9698
 
4.2%
김 9489
 
4.1%
상 8999
 
3.9%
시 8389
 
3.6%
경 8365
 
3.6%
도 8327
 
3.6%
남 8323
 
3.6%
로 8220
 
3.5%
Other values (427) 113701
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133308
57.2%
Decimal Number 42634
 
18.3%
Space Separator 38560
 
16.5%
Close Punctuation 5619
 
2.4%
Open Punctuation 5619
 
2.4%
Other Punctuation 4800
 
2.1%
Dash Punctuation 2110
 
0.9%
Uppercase Letter 305
 
0.1%
Lowercase Letter 41
 
< 0.1%
Math Symbol 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
해 9698
 
7.3%
김 9489
 
7.1%
상 8999
 
6.8%
시 8389
 
6.3%
경 8365
 
6.3%
도 8327
 
6.2%
남 8323
 
6.2%
로 8220
 
6.2%
동 6898
 
5.2%
번 4590
 
3.4%
Other values (367) 52010
39.0%
Uppercase Letter
ValueCountFrequency (%)
B 76
24.9%
A 74
24.3%
S 44
14.4%
G 32
10.5%
C 21
 
6.9%
D 15
 
4.9%
N 8
 
2.6%
O 6
 
2.0%
I 5
 
1.6%
K 5
 
1.6%
Other values (12) 19
 
6.2%
Lowercase Letter
ValueCountFrequency (%)
g 11
26.8%
s 9
22.0%
e 4
 
9.8%
o 3
 
7.3%
a 3
 
7.3%
c 2
 
4.9%
i 2
 
4.9%
t 1
 
2.4%
j 1
 
2.4%
y 1
 
2.4%
Other values (4) 4
 
9.8%
Decimal Number
ValueCountFrequency (%)
1 10943
25.7%
2 7058
16.6%
3 4443
10.4%
0 3931
 
9.2%
4 3439
 
8.1%
5 3266
 
7.7%
6 2753
 
6.5%
7 2542
 
6.0%
9 2167
 
5.1%
8 2092
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 4776
99.5%
/ 10
 
0.2%
. 8
 
0.2%
· 3
 
0.1%
: 2
 
< 0.1%
' 1
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅲ 1
25.0%
Ⅰ 1
25.0%
Space Separator
ValueCountFrequency (%)
38560
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5619
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5619
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2110
100.0%
Math Symbol
ValueCountFrequency (%)
~ 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133308
57.2%
Common 99356
42.6%
Latin 350
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
해 9698
 
7.3%
김 9489
 
7.1%
상 8999
 
6.8%
시 8389
 
6.3%
경 8365
 
6.3%
도 8327
 
6.2%
남 8323
 
6.2%
로 8220
 
6.2%
동 6898
 
5.2%
번 4590
 
3.4%
Other values (367) 52010
39.0%
Latin
ValueCountFrequency (%)
B 76
21.7%
A 74
21.1%
S 44
12.6%
G 32
9.1%
C 21
 
6.0%
D 15
 
4.3%
g 11
 
3.1%
s 9
 
2.6%
N 8
 
2.3%
O 6
 
1.7%
Other values (29) 54
15.4%
Common
ValueCountFrequency (%)
38560
38.8%
1 10943
 
11.0%
2 7058
 
7.1%
) 5619
 
5.7%
( 5619
 
5.7%
, 4776
 
4.8%
3 4443
 
4.5%
0 3931
 
4.0%
4 3439
 
3.5%
5 3266
 
3.3%
Other values (11) 11702
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133304
57.2%
ASCII 99699
42.8%
Compat Jamo 4
 
< 0.1%
Number Forms 4
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
38560
38.7%
1 10943
 
11.0%
2 7058
 
7.1%
) 5619
 
5.6%
( 5619
 
5.6%
, 4776
 
4.8%
3 4443
 
4.5%
0 3931
 
3.9%
4 3439
 
3.4%
5 3266
 
3.3%
Other values (46) 12045
 
12.1%
Hangul
ValueCountFrequency (%)
해 9698
 
7.3%
김 9489
 
7.1%
상 8999
 
6.8%
시 8389
 
6.3%
경 8365
 
6.3%
도 8327
 
6.2%
남 8323
 
6.2%
로 8220
 
6.2%
동 6898
 
5.2%
번 4590
 
3.4%
Other values (366) 52006
39.0%
Compat Jamo
ValueCountFrequency (%)
ㅇ 4
100.0%
None
ValueCountFrequency (%)
· 3
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅲ 1
25.0%
Ⅰ 1
25.0%

사업장명
Text

Distinct9008
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-13T01:57:08.333132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length6.5599
Min length1

Characters and Unicode

Total characters65599
Distinct characters1038
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8446 ?
Unique (%)84.5%

Sample

1st row태양물산
2nd row고려원식품
3rd rowGS25김해삼계천로점
4th row리얼펍김해구산점
5th row사단법인 새삶의료선교회
ValueCountFrequency (%)
주식회사 91
 
0.8%
세븐일레븐 51
 
0.4%
씨유 43
 
0.4%
김해점 41
 
0.3%
pc방 32
 
0.3%
장유점 32
 
0.3%
주)정성 31
 
0.3%
현승유통 27
 
0.2%
진영점 25
 
0.2%
gs25 24
 
0.2%
Other values (9577) 11343
96.6%
2023-12-13T01:57:08.715743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1740
 
2.7%
점 1541
 
2.3%
이 1335
 
2.0%
) 1174
 
1.8%
( 1170
 
1.8%
주 1152
 
1.8%
장 1021
 
1.6%
스 972
 
1.5%
김 892
 
1.4%
해 890
 
1.4%
Other values (1028) 53712
81.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57826
88.2%
Uppercase Letter 1781
 
2.7%
Space Separator 1740
 
2.7%
Close Punctuation 1174
 
1.8%
Open Punctuation 1170
 
1.8%
Lowercase Letter 901
 
1.4%
Decimal Number 793
 
1.2%
Other Punctuation 185
 
0.3%
Dash Punctuation 16
 
< 0.1%
Modifier Symbol 6
 
< 0.1%
Other values (3) 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1541
 
2.7%
이 1335
 
2.3%
주 1152
 
2.0%
장 1021
 
1.8%
스 972
 
1.7%
김 892
 
1.5%
해 890
 
1.5%
식 856
 
1.5%
리 843
 
1.5%
원 826
 
1.4%
Other values (944) 47498
82.1%
Uppercase Letter
ValueCountFrequency (%)
C 238
13.4%
P 189
 
10.6%
S 172
 
9.7%
G 127
 
7.1%
O 99
 
5.6%
B 88
 
4.9%
A 83
 
4.7%
T 77
 
4.3%
N 75
 
4.2%
E 72
 
4.0%
Other values (16) 561
31.5%
Lowercase Letter
ValueCountFrequency (%)
a 102
 
11.3%
e 98
 
10.9%
o 92
 
10.2%
i 76
 
8.4%
n 58
 
6.4%
l 48
 
5.3%
r 44
 
4.9%
h 43
 
4.8%
s 42
 
4.7%
u 36
 
4.0%
Other values (16) 262
29.1%
Other Punctuation
ValueCountFrequency (%)
& 62
33.5%
. 54
29.2%
' 18
 
9.7%
, 18
 
9.7%
# 15
 
8.1%
: 7
 
3.8%
! 4
 
2.2%
/ 2
 
1.1%
· 2
 
1.1%
＆ 2
 
1.1%
Decimal Number
ValueCountFrequency (%)
2 257
32.4%
5 163
20.6%
1 112
14.1%
0 55
 
6.9%
4 52
 
6.6%
3 39
 
4.9%
9 37
 
4.7%
6 32
 
4.0%
7 28
 
3.5%
8 18
 
2.3%
Math Symbol
ValueCountFrequency (%)
> 1
33.3%
< 1
33.3%
+ 1
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 2
66.7%
℃ 1
33.3%
Space Separator
ValueCountFrequency (%)
1740
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1174
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57816
88.1%
Common 5088
 
7.8%
Latin 2683
 
4.1%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1541
 
2.7%
이 1335
 
2.3%
주 1152
 
2.0%
장 1021
 
1.8%
스 972
 
1.7%
김 892
 
1.5%
해 890
 
1.5%
식 856
 
1.5%
리 843
 
1.5%
원 826
 
1.4%
Other values (935) 47488
82.1%
Latin
ValueCountFrequency (%)
C 238
 
8.9%
P 189
 
7.0%
S 172
 
6.4%
G 127
 
4.7%
a 102
 
3.8%
O 99
 
3.7%
e 98
 
3.7%
o 92
 
3.4%
B 88
 
3.3%
A 83
 
3.1%
Other values (43) 1395
52.0%
Common
ValueCountFrequency (%)
1740
34.2%
) 1174
23.1%
( 1170
23.0%
2 257
 
5.1%
5 163
 
3.2%
1 112
 
2.2%
& 62
 
1.2%
0 55
 
1.1%
. 54
 
1.1%
4 52
 
1.0%
Other values (20) 249
 
4.9%
Han
ValueCountFrequency (%)
美 3
25.0%
古 1
 
8.3%
林 1
 
8.3%
園 1
 
8.3%
抵 1
 
8.3%
多 1
 
8.3%
夜 1
 
8.3%
粧 1
 
8.3%
院 1
 
8.3%
愛 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57811
88.1%
ASCII 7765
 
11.8%
CJK 12
 
< 0.1%
None 6
 
< 0.1%
Compat Jamo 3
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1740
22.4%
) 1174
15.1%
( 1170
15.1%
2 257
 
3.3%
C 238
 
3.1%
P 189
 
2.4%
S 172
 
2.2%
5 163
 
2.1%
G 127
 
1.6%
1 112
 
1.4%
Other values (69) 2423
31.2%
Hangul
ValueCountFrequency (%)
점 1541
 
2.7%
이 1335
 
2.3%
주 1152
 
2.0%
장 1021
 
1.8%
스 972
 
1.7%
김 892
 
1.5%
해 890
 
1.5%
식 856
 
1.5%
리 843
 
1.5%
원 826
 
1.4%
Other values (931) 47483
82.1%
CJK
ValueCountFrequency (%)
美 3
25.0%
古 1
 
8.3%
林 1
 
8.3%
園 1
 
8.3%
抵 1
 
8.3%
多 1
 
8.3%
夜 1
 
8.3%
粧 1
 
8.3%
院 1
 
8.3%
愛 1
 
8.3%
None
ValueCountFrequency (%)
㈜ 2
33.3%
· 2
33.3%
＆ 2
33.3%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
33.3%
ㅇ 1
33.3%
ㅂ 1
33.3%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

위치_경도
Real number (ℝ)

HIGH CORRELATION 

Distinct5462
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.84701
Minimum128.70685
Maximum129.00532
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:57:08.868487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.70685
5-th percentile128.73482
Q1128.8084
median128.86509
Q3128.88298
95-th percentile128.91199
Maximum129.00532
Range0.2984748
Interquartile range (IQR)0.074586275

Descriptive statistics

Standard deviation0.053330572
Coefficient of variation (CV)0.00041390618
Kurtosis-0.17860989
Mean128.84701
Median Absolute Deviation (MAD)0.03782695
Skewness-0.56124238
Sum1288470.1
Variance0.0028441499
MonotonicityNot monotonic
2023-12-13T01:57:09.002813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8721477 148
 
1.5%
128.8701773 94
 
0.9%
128.9074532 67
 
0.7%
128.8128999 65
 
0.7%
128.8012803 52
 
0.5%
128.8638896 41
 
0.4%
128.8546724 40
 
0.4%
128.8665195 39
 
0.4%
128.8353816 37
 
0.4%
128.8642087 35
 
0.4%
Other values (5452) 9382
93.8%
ValueCountFrequency (%)
128.7068469 2
< 0.1%
128.7069703 1
< 0.1%
128.7070928 1
< 0.1%
128.70772 1
< 0.1%
128.7084019 1
< 0.1%
128.7085762 1
< 0.1%
128.7086817 1
< 0.1%
128.709519 1
< 0.1%
128.709725 1
< 0.1%
128.7098486 1
< 0.1%
ValueCountFrequency (%)
129.0053217 1
 
< 0.1%
129.0028263 3
< 0.1%
129.0003661 1
 
< 0.1%
128.9978254 1
 
< 0.1%
128.9977495 1
 
< 0.1%
128.9959007 1
 
< 0.1%
128.9958761 1
 
< 0.1%
128.9954139 1
 
< 0.1%
128.994516 1
 
< 0.1%
128.9943092 1
 
< 0.1%

위치_위도
Real number (ℝ)

HIGH CORRELATION 

Distinct5472
Distinct (%)54.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.238495
Minimum35.15523
Maximum35.389769
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T01:57:09.129324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.15523
5-th percentile35.177423
Q135.225763
median35.234799
Q335.250153
95-th percentile35.308454
Maximum35.389769
Range0.23453921
Interquartile range (IQR)0.024389745

Descriptive statistics

Standard deviation0.037019726
Coefficient of variation (CV)0.0010505479
Kurtosis0.45205237
Mean35.238495
Median Absolute Deviation (MAD)0.01370234
Skewness0.55157635
Sum352384.95
Variance0.0013704601
MonotonicityNot monotonic
2023-12-13T01:57:09.262843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.22913159 148
 
1.5%
35.241828 94
 
0.9%
35.24413505 67
 
0.7%
35.22612787 65
 
0.7%
35.19303447 52
 
0.5%
35.23098643 41
 
0.4%
35.23398682 40
 
0.4%
35.25975828 39
 
0.4%
35.18508431 37
 
0.4%
35.23360735 35
 
0.4%
Other values (5462) 9382
93.8%
ValueCountFrequency (%)
35.1552298 1
 
< 0.1%
35.16270854 1
 
< 0.1%
35.1632937 2
 
< 0.1%
35.16419202 1
 
< 0.1%
35.16516256 1
 
< 0.1%
35.16599565 5
0.1%
35.16719459 1
 
< 0.1%
35.16760274 2
 
< 0.1%
35.16774724 1
 
< 0.1%
35.16783873 7
0.1%
ValueCountFrequency (%)
35.38976901 1
< 0.1%
35.38692101 1
< 0.1%
35.38595117 1
< 0.1%
35.3858712 1
< 0.1%
35.38579727 1
< 0.1%
35.3805313 1
< 0.1%
35.37935093 1
< 0.1%
35.37654581 1
< 0.1%
35.37262185 1
< 0.1%
35.37215499 1
< 0.1%

Interactions

2023-12-13T01:57:02.030225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:56:59.930350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:00.498087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:01.208832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:02.187399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:00.044970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:00.638774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:01.398010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:02.342137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:00.217718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:00.806291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:01.636611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:02.464137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:00.380529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:01.010729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:57:01.828404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:57:09.353415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동_명행정동_코드업종대분류업종중분류업종명영업상태위치_경도위치_위도
관리번호1.0000.3590.2900.8700.9270.9790.5870.2110.291
행정동_명0.3591.0001.0000.3910.4550.6270.1740.9390.923
행정동_코드0.2901.0001.0000.2700.4560.6050.1130.8590.747
업종대분류0.8700.3910.2701.0001.0001.0000.3930.1740.297
업종중분류0.9270.4550.4561.0001.0001.0000.6240.2580.413
업종명0.9790.6270.6051.0001.0001.0000.7700.4000.514
영업상태0.5870.1740.1130.3930.6240.7701.0000.0820.151
위치_경도0.2110.9390.8590.1740.2580.4000.0821.0000.842
위치_위도0.2910.9230.7470.2970.4130.5140.1510.8421.000
2023-12-13T01:57:09.460938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태행정동_명업종중분류업종대분류
영업상태1.0000.0960.3840.263
행정동_명0.0961.0000.1460.193
업종중분류0.3840.1461.0000.999
업종대분류0.2630.1930.9991.000
2023-12-13T01:57:09.549190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리번호행정동_코드위치_경도위치_위도행정동_명업종대분류업종중분류영업상태
관리번호1.0000.0550.020-0.0490.1420.7000.6900.392
행정동_코드0.0551.0000.132-0.6480.9990.1590.1930.074
위치_경도0.0200.1321.0000.0860.7270.0920.0980.049
위치_위도-0.049-0.6480.0861.0000.6820.1610.1660.091
행정동_명0.1420.9990.7270.6821.0000.1930.1460.096
업종대분류0.7000.1590.0920.1610.1931.0000.9990.263
업종중분류0.6900.1930.0980.1660.1460.9991.0000.384
영업상태0.3920.0740.0490.0910.0960.2630.3841.000

Missing values

2023-12-13T01:57:02.675078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:57:03.008559image/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.
2023-12-13T01:57:03.249376image/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
156641566520227경상남도김해시대동면48482504825037000식품식품제조/가공/판매집단급식소식품판매업2015-04-132019-09-16폐업경상남도 김해시 대동면 초정리 952-528경상남도 김해시 대동면 동남로41번길 22-2태양물산128.99277335.235432
241342413520227경상남도김해시주촌면48482504825032000식품식품제조/가공/판매식품제조가공업2000-05-092011-12-27폐업경상남도 김해시 주촌면 원지리 680-1번지<NA>고려원식품128.83317735.252447
232342323520227경상남도김해시북부동48482504825055000식품식품제조/가공/판매식품자동판매기업2018-07-312021-05-07폐업경상남도 김해시 삼계동 1503-6 GS25김해삼계천로점 내경상남도 김해시 해반천로130번길 31, GS25김해삼계천로점 내 1층 (삼계동)GS25김해삼계천로점128.87059635.260184
376193762020227경상남도김해시북부동48482504825055000식품음식점일반음식점2017-02-09<NA>영업/정상경상남도 김해시 구산동 1062-5번지경상남도 김해시 해반천로16번길 15 (구산동)리얼펍김해구산점128.87149235.250447
7976797720227경상남도김해시삼안동48482504825059000문화문화기획문화예술법인2011-07-07<NA>영업/정상경상남도 김해시 삼방동 656번지 5호경상남도 김해시 삼안로 283 (삼방동)사단법인 새삶의료선교회128.9077935.251901
370623706320227경상남도김해시장유1동48482504825061000식품음식점일반음식점2018-07-17<NA>영업/정상경상남도 김해시 무계동 242-1번지 2층경상남도 김해시 장유로 319, 2층 (무계동)6.25포차128.8161235.198152
276712767220227경상남도김해시장유2동48482504825062000식품식품제조/가공/판매즉석판매제조가공업2016-11-232018-01-31폐업경상남도 김해시 대청동 316-3경상남도 김해시 번화2로 33, 김해축산업협동조합하나로마트장유점 (대청동)황금찬 수영지점128.80468435.191888
7522752320227경상남도김해시북부동48482504825055000문화게임청소년게임제공업2016-06-242021-05-31폐업경상남도 김해시 삼계동 1463-2 1층 101호경상남도 김해시 해반천로168번길 26-7, 1층 101호 (삼계동)아이앤지게임존128.8700935.262991
198721987320227경상남도김해시활천동48482504825058000식품식품제조/가공/판매축산판매업1996-02-102001-02-19폐업경상남도 김해시 어방동 499<NA>대우한우전문점128.90133235.243276
351023510320227경상남도김해시장유2동48482504825062000식품음식점일반음식점2005-06-29<NA>영업/정상경상남도 김해시 대청동 301-5 트윈스빌딩104호경상남도 김해시 삼문로 9 (트윈스빌딩104호)막전128.80156735.192401
관리번호기준_년기준_월시도_명시군구_명행정동_명시도_코드시군구_코드행정동_코드업종대분류업종중분류업종명창업일자폐업일자영업상태주소_지번주소_도로명사업장명위치_경도위치_위도
117121171320227경상남도김해시활천동48482504825058000생활미용미용업2020-09-17<NA>영업/정상경상남도 김해시 삼정동 599-3경상남도 김해시 활천로24번길 6, 1층 (삼정동)D.W헤어#128.89450635.229593
255512555220227경상남도김해시동상동48482504825051000식품식품제조/가공/판매즉석판매제조가공업2019-02-27<NA>영업/정상경상남도 김해시 동상동 1100-1 동상동 베스티움 아파트 201호경상남도 김해시 가야로463번길 15, 2층 201호 (동상동, 동상동 베스티움 아파트)카페이레128.88668235.241314
270022700320227경상남도김해시내외동48482504825054000식품식품제조/가공/판매즉석판매제조가공업2003-02-132005-11-16폐업경상남도 김해시 외동 1253-1 그린파킹109호<NA>미래건강원128.86563435.233238
437384373920227경상남도김해시활천동48482504825058000식품음식점일반음식점1998-09-192012-01-03폐업경상남도 김해시 어방동 503-1번지<NA>불로만숯불바베큐128.90043635.240675
8828882920227경상남도김해시부원동48482504825053000문화숙박숙박업2000-03-16<NA>영업/정상경상남도 김해시 부원동 607-20경상남도 김해시 가락로16번길 4-1 (부원동)이문장여관128.8830935.227795
1644164520227경상남도김해시장유1동48482504825061000건강의료기관약국2002-07-162010-10-01폐업경상남도 김해시 장유면 삼문리 39번지 12호경상남도 김해시 장유면 능동로 159명약국128.80942735.205686
4380438120227경상남도김해시한림면48482504825034000동물동물동물생산업2017-11-092022-07-01취소/말소/만료/정지/중지경상남도 김해시 한림면 용덕리 1023-15경상남도 김해시 한림면 용덕로114번길 35킹덤농장128.83506335.289596
398913989220227경상남도김해시장유3동48482504825063000식품음식점일반음식점2005-12-022012-04-09폐업경상남도 김해시 관동동 461-2번지<NA>삼순이와곱창도령대패삼겹살128.80155435.177239
111761117720227경상남도김해시내외동48482504825054000생활미용미용업2000-01-21<NA>영업/정상경상남도 김해시 외동 706-1번지경상남도 김해시 평전로 27 (외동)영주헤어샵128.85184935.234404
160131601420227경상남도김해시부원동48482504825053000식품식품제조/가공/판매건강기능식품일반판매업2016-02-19<NA>영업/정상경상남도 김해시 부원동 607-6경상남도 김해시 가락로16번길 12GS25 김해하나점128.88381235.227901