Overview

Dataset statistics

Number of variables10
Number of observations5564
Missing cells4714
Missing cells (%)8.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory440.2 KiB
Average record size in memory81.0 B

Variable types

Text4
Categorical5
Numeric1

Dataset

Description울산소방본부에서 제공하는 서센터별 다중이용업소 정보로서 관할서명, 서센터명, 업종명, 영업장전체층, 건물구조층, 건축구조연면적 정보를 제공하는 데이터임
Author소방청
URLhttps://www.data.go.kr/data/15080959/fileData.do

Alerts

업소 시도명 has constant value ""Constant
업소 구군명 is highly overall correlated with 관할서명 and 1 other fieldsHigh correlation
서센터명 is highly overall correlated with 관할서명 and 1 other fieldsHigh correlation
관할서명 is highly overall correlated with 서센터명 and 1 other fieldsHigh correlation
업소 리명 has 4694 (84.4%) missing valuesMissing
일련번호 has unique valuesUnique
업소 우편번호 has 60 (1.1%) zerosZeros

Reproduction

Analysis started2023-12-12 22:51:35.511853
Analysis finished2023-12-12 22:51:37.092502
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Text

UNIQUE 

Distinct5564
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
2023-12-13T07:51:37.468224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.6214953
Min length1

Characters and Unicode

Total characters25714
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

Unique5564 ?
Unique (%)100.0%

Sample

1st row1
2nd row2
3rd row3
4th row4
5th row5
ValueCountFrequency (%)
1 1
 
< 0.1%
3,705 1
 
< 0.1%
3,713 1
 
< 0.1%
3,712 1
 
< 0.1%
3,711 1
 
< 0.1%
3,710 1
 
< 0.1%
3,709 1
 
< 0.1%
3,708 1
 
< 0.1%
3,720 1
 
< 0.1%
3,706 1
 
< 0.1%
Other values (5554) 5554
99.8%
2023-12-13T07:51:38.287190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 4565
17.8%
1 2717
10.6%
3 2717
10.6%
4 2717
10.6%
2 2717
10.6%
5 2246
8.7%
6 1611
 
6.3%
7 1606
 
6.2%
8 1606
 
6.2%
9 1606
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21149
82.2%
Other Punctuation 4565
 
17.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2717
12.8%
3 2717
12.8%
4 2717
12.8%
2 2717
12.8%
5 2246
10.6%
6 1611
7.6%
7 1606
7.6%
8 1606
7.6%
9 1606
7.6%
0 1606
7.6%
Other Punctuation
ValueCountFrequency (%)
, 4565
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25714
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 4565
17.8%
1 2717
10.6%
3 2717
10.6%
4 2717
10.6%
2 2717
10.6%
5 2246
8.7%
6 1611
 
6.3%
7 1606
 
6.2%
8 1606
 
6.2%
9 1606
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25714
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 4565
17.8%
1 2717
10.6%
3 2717
10.6%
4 2717
10.6%
2 2717
10.6%
5 2246
8.7%
6 1611
 
6.3%
7 1606
 
6.2%
8 1606
 
6.2%
9 1606
 
6.2%

관할서명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
남부소방서
2121 
중부소방서
1227 
동부소방서
1031 
북부소방서
718 
온산소방서
461 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남부소방서
2nd row남부소방서
3rd row동부소방서
4th row온산소방서
5th row남부소방서

Common Values

ValueCountFrequency (%)
남부소방서 2121
38.1%
중부소방서 1227
22.1%
동부소방서 1031
18.5%
북부소방서 718
 
12.9%
온산소방서 461
 
8.3%
울주소방서 6
 
0.1%

Length

2023-12-13T07:51:38.427809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:51:38.536970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남부소방서 2121
38.1%
중부소방서 1227
22.1%
동부소방서 1031
18.5%
북부소방서 718
 
12.9%
온산소방서 461
 
8.3%
울주소방서 6
 
0.1%

서센터명
Categorical

HIGH CORRELATION 

Distinct29
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
삼산119안전센터
968 
화정119안전센터
425 
전하119안전센터
416 
신정119안전센터
372 
무거119안전센터
329 
Other values (24)
3054 

Length

Max length10
Median length9
Mean length9.0003595
Min length8

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row옥동119안전센터
2nd row옥동119안전센터
3rd row화정119안전센터
4th row온산119안전센터
5th row삼산119안전센터

Common Values

ValueCountFrequency (%)
삼산119안전센터 968
17.4%
화정119안전센터 425
 
7.6%
전하119안전센터 416
 
7.5%
신정119안전센터 372
 
6.7%
무거119안전센터 329
 
5.9%
성남119안전센터 316
 
5.7%
언양119안전센터 251
 
4.5%
옥동119안전센터 247
 
4.4%
온산119안전센터 232
 
4.2%
병영119안전센터 222
 
4.0%
Other values (19) 1786
32.1%

Length

2023-12-13T07:51:38.694816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
삼산119안전센터 968
17.4%
화정119안전센터 425
 
7.6%
전하119안전센터 416
 
7.5%
신정119안전센터 372
 
6.7%
무거119안전센터 329
 
5.9%
성남119안전센터 316
 
5.7%
언양119안전센터 251
 
4.5%
옥동119안전센터 247
 
4.4%
온산119안전센터 232
 
4.2%
병영119안전센터 222
 
4.0%
Other values (19) 1786
32.1%

업소 우편번호
Real number (ℝ)

ZEROS 

Distinct560
Distinct (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean436879.62
Minimum0
Maximum689934
Zeros60
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size49.0 KiB
2023-12-13T07:51:38.824849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile44067
Q144705
median680809.5
Q3682803
95-th percentile689855
Maximum689934
Range689934
Interquartile range (IQR)638098

Descriptive statistics

Standard deviation311232.39
Coefficient of variation (CV)0.71239851
Kurtosis-1.7737456
Mean436879.62
Median Absolute Deviation (MAD)2590.5
Skewness-0.4749728
Sum2.4307982 × 109
Variance9.6865602 × 1010
MonotonicityNot monotonic
2023-12-13T07:51:38.949092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
680805 154
 
2.8%
44254 132
 
2.4%
680813 125
 
2.2%
680804 103
 
1.9%
680030 103
 
1.9%
681812 89
 
1.6%
682810 88
 
1.6%
682808 77
 
1.4%
680812 74
 
1.3%
689894 67
 
1.2%
Other values (550) 4552
81.8%
ValueCountFrequency (%)
0 60
1.1%
44006 4
 
0.1%
44007 11
 
0.2%
44010 1
 
< 0.1%
44012 6
 
0.1%
44013 14
 
0.3%
44016 3
 
0.1%
44017 1
 
< 0.1%
44019 1
 
< 0.1%
44025 1
 
< 0.1%
ValueCountFrequency (%)
689934 1
 
< 0.1%
689933 1
 
< 0.1%
689905 9
 
0.2%
689904 1
 
< 0.1%
689903 44
0.8%
689902 2
 
< 0.1%
689901 2
 
< 0.1%
689895 8
 
0.1%
689894 67
1.2%
689893 67
1.2%

업소 시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
울산
5564 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
울산 5564
100.0%

Length

2023-12-13T07:51:39.062316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:51:39.146947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산 5564
100.0%

업소 구군명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
남구
2121 
동구
1031 
울주군
901 
중구
793 
북구
718 

Length

Max length3
Median length2
Mean length2.1619339
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남구
2nd row남구
3rd row동구
4th row울주군
5th row남구

Common Values

ValueCountFrequency (%)
남구 2121
38.1%
동구 1031
18.5%
울주군 901
16.2%
중구 793
 
14.3%
북구 718
 
12.9%

Length

2023-12-13T07:51:39.230105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:51:39.332419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남구 2121
38.1%
동구 1031
18.5%
울주군 901
16.2%
중구 793
 
14.3%
북구 718
 
12.9%

업소 동명
Text

Distinct72
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
2023-12-13T07:51:39.546196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.8772466
Min length2

Characters and Unicode

Total characters16009
Distinct characters75
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row신정동
2nd row신정동
3rd row일산동
4th row온산읍
5th row달동
ValueCountFrequency (%)
달동 609
 
10.9%
삼산동 494
 
8.9%
신정동 459
 
8.2%
무거동 328
 
5.9%
일산동 270
 
4.9%
전하동 211
 
3.8%
온산읍 205
 
3.7%
방어동 173
 
3.1%
서부동 162
 
2.9%
범서읍 157
 
2.8%
Other values (62) 2496
44.9%
2023-12-13T07:51:39.973001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 4745
29.6%
산 1102
 
6.9%
정 748
 
4.7%
읍 628
 
3.9%
달 610
 
3.8%
삼 577
 
3.6%
신 494
 
3.1%
서 429
 
2.7%
무 328
 
2.0%
거 328
 
2.0%
Other values (65) 6020
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16009
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4745
29.6%
산 1102
 
6.9%
정 748
 
4.7%
읍 628
 
3.9%
달 610
 
3.8%
삼 577
 
3.6%
신 494
 
3.1%
서 429
 
2.7%
무 328
 
2.0%
거 328
 
2.0%
Other values (65) 6020
37.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16009
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4745
29.6%
산 1102
 
6.9%
정 748
 
4.7%
읍 628
 
3.9%
달 610
 
3.8%
삼 577
 
3.6%
신 494
 
3.1%
서 429
 
2.7%
무 328
 
2.0%
거 328
 
2.0%
Other values (65) 6020
37.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16009
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 4745
29.6%
산 1102
 
6.9%
정 748
 
4.7%
읍 628
 
3.9%
달 610
 
3.8%
삼 577
 
3.6%
신 494
 
3.1%
서 429
 
2.7%
무 328
 
2.0%
거 328
 
2.0%
Other values (65) 6020
37.6%

업소 리명
Text

MISSING 

Distinct69
Distinct (%)7.9%
Missing4694
Missing (%)84.4%
Memory size43.6 KiB
2023-12-13T07:51:40.197877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.0011494
Min length2

Characters and Unicode

Total characters2611
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.7%

Sample

1st row덕신리
2nd row남창리
3rd row운화리
4th row운화리
5th row진하리
ValueCountFrequency (%)
덕신리 191
22.0%
구영리 86
 
9.9%
대안리 72
 
8.3%
교동리 61
 
7.0%
동부리 54
 
6.2%
남부리 39
 
4.5%
서부리 33
 
3.8%
진하리 31
 
3.6%
굴화리 29
 
3.3%
천상리 24
 
2.8%
Other values (59) 250
28.7%
2023-12-13T07:51:40.647034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 870
33.3%
신 202
 
7.7%
덕 193
 
7.4%
부 126
 
4.8%
동 123
 
4.7%
대 98
 
3.8%
구 90
 
3.4%
영 86
 
3.3%
안 72
 
2.8%
남 63
 
2.4%
Other values (73) 688
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2611
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 870
33.3%
신 202
 
7.7%
덕 193
 
7.4%
부 126
 
4.8%
동 123
 
4.7%
대 98
 
3.8%
구 90
 
3.4%
영 86
 
3.3%
안 72
 
2.8%
남 63
 
2.4%
Other values (73) 688
26.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2611
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 870
33.3%
신 202
 
7.7%
덕 193
 
7.4%
부 126
 
4.8%
동 123
 
4.7%
대 98
 
3.8%
구 90
 
3.4%
영 86
 
3.3%
안 72
 
2.8%
남 63
 
2.4%
Other values (73) 688
26.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2611
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 870
33.3%
신 202
 
7.7%
덕 193
 
7.4%
부 126
 
4.8%
동 123
 
4.7%
대 98
 
3.8%
구 90
 
3.4%
영 86
 
3.3%
안 72
 
2.8%
남 63
 
2.4%
Other values (73) 688
26.4%

업소 도로명
Text

Distinct973
Distinct (%)17.6%
Missing20
Missing (%)0.4%
Memory size43.6 KiB
2023-12-13T07:51:40.999078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.7357504
Min length3

Characters and Unicode

Total characters26255
Distinct characters235
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique385 ?
Unique (%)6.9%

Sample

1st row삼산로55번길
2nd row삼산로35번길
3rd row방어진순환도로
4th row신온8길
5th row삼산로199번길
ValueCountFrequency (%)
방어진순환도로 216
 
3.9%
수암로 132
 
2.4%
화합로 92
 
1.7%
삼산로 72
 
1.3%
대학로147번길 72
 
1.3%
중앙로 71
 
1.3%
염포로 60
 
1.1%
번영로 60
 
1.1%
젊음의거리 57
 
1.0%
동해안로 56
 
1.0%
Other values (964) 4658
84.0%
2023-12-13T07:51:41.471216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 3580
 
13.6%
길 3114
 
11.9%
번 1454
 
5.5%
1 1033
 
3.9%
4 674
 
2.6%
2 660
 
2.5%
산 583
 
2.2%
삼 514
 
2.0%
진 480
 
1.8%
대 468
 
1.8%
Other values (225) 13695
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21523
82.0%
Decimal Number 4730
 
18.0%
Space Separator 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3580
 
16.6%
길 3114
 
14.5%
번 1454
 
6.8%
산 583
 
2.7%
삼 514
 
2.4%
진 480
 
2.2%
대 468
 
2.2%
중 385
 
1.8%
동 337
 
1.6%
수 332
 
1.5%
Other values (214) 10276
47.7%
Decimal Number
ValueCountFrequency (%)
1 1033
21.8%
4 674
14.2%
2 660
14.0%
3 450
9.5%
7 397
 
8.4%
6 392
 
8.3%
5 363
 
7.7%
8 311
 
6.6%
0 292
 
6.2%
9 158
 
3.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21523
82.0%
Common 4732
 
18.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3580
 
16.6%
길 3114
 
14.5%
번 1454
 
6.8%
산 583
 
2.7%
삼 514
 
2.4%
진 480
 
2.2%
대 468
 
2.2%
중 385
 
1.8%
동 337
 
1.6%
수 332
 
1.5%
Other values (214) 10276
47.7%
Common
ValueCountFrequency (%)
1 1033
21.8%
4 674
14.2%
2 660
13.9%
3 450
9.5%
7 397
 
8.4%
6 392
 
8.3%
5 363
 
7.7%
8 311
 
6.6%
0 292
 
6.2%
9 158
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21523
82.0%
ASCII 4732
 
18.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 3580
 
16.6%
길 3114
 
14.5%
번 1454
 
6.8%
산 583
 
2.7%
삼 514
 
2.4%
진 480
 
2.2%
대 468
 
2.2%
중 385
 
1.8%
동 337
 
1.6%
수 332
 
1.5%
Other values (214) 10276
47.7%
ASCII
ValueCountFrequency (%)
1 1033
21.8%
4 674
14.2%
2 660
13.9%
3 450
9.5%
7 397
 
8.4%
6 392
 
8.3%
5 363
 
7.7%
8 311
 
6.6%
0 292
 
6.2%
9 158
 
3.3%

업종명
Categorical

Distinct21
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size43.6 KiB
일반음식점
1412 
유흥주점
1143 
노래연습장업
824 
단란주점
477 
휴게음식점
409 
Other values (16)
1299 

Length

Max length18
Median length12
Mean length5.9521927
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row유흥주점
2nd row유흥주점
3rd row비디오물감상실업
4th row노래연습장업
5th row단란주점

Common Values

ValueCountFrequency (%)
일반음식점 1412
25.4%
유흥주점 1143
20.5%
노래연습장업 824
14.8%
단란주점 477
 
8.6%
휴게음식점 409
 
7.4%
인터넷컴퓨터게임시설제공업(PC방) 363
 
6.5%
스크린 골프연습장 300
 
5.4%
고시원업 230
 
4.1%
게임제공업 206
 
3.7%
목욕장(찜질방) 45
 
0.8%
Other values (11) 155
 
2.8%

Length

2023-12-13T07:51:41.627519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
일반음식점 1412
24.1%
유흥주점 1143
19.5%
노래연습장업 824
14.1%
단란주점 477
 
8.1%
휴게음식점 409
 
7.0%
인터넷컴퓨터게임시설제공업(pc방 363
 
6.2%
스크린 300
 
5.1%
골프연습장 300
 
5.1%
고시원업 230
 
3.9%
게임제공업 206
 
3.5%
Other values (12) 200
 
3.4%

Interactions

2023-12-13T07:51:36.620662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:51:41.730297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관할서명서센터명업소 우편번호업소 구군명업소 동명업소 리명업종명
관할서명1.0000.9910.2870.9380.9950.9670.248
서센터명0.9911.0000.2630.9990.9960.9900.369
업소 우편번호0.2870.2631.0000.1680.3740.4220.468
업소 구군명0.9380.9990.1681.0001.000NaN0.262
업소 동명0.9950.9960.3741.0001.0000.9970.505
업소 리명0.9670.9900.422NaN0.9971.0000.799
업종명0.2480.3690.4680.2620.5050.7991.000
2023-12-13T07:51:41.872148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소 구군명서센터명관할서명업종명
업소 구군명1.0000.9970.9130.131
서센터명0.9971.0000.9470.104
관할서명0.9130.9471.0000.114
업종명0.1310.1040.1141.000
2023-12-13T07:51:41.996115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소 우편번호관할서명서센터명업소 구군명업종명
업소 우편번호1.0000.2070.2240.2060.412
관할서명0.2071.0000.9470.9130.114
서센터명0.2240.9471.0000.9970.104
업소 구군명0.2060.9130.9971.0000.131
업종명0.4120.1140.1040.1311.000

Missing values

2023-12-13T07:51:36.776154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:51:36.916368image/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.
2023-12-13T07:51:37.028927image/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

일련번호관할서명서센터명업소 우편번호업소 시도명업소 구군명업소 동명업소 리명업소 도로명업종명
01남부소방서옥동119안전센터680828울산남구신정동<NA>삼산로55번길유흥주점
12남부소방서옥동119안전센터680828울산남구신정동<NA>삼산로35번길유흥주점
23동부소방서화정119안전센터682811울산동구일산동<NA>방어진순환도로비디오물감상실업
34온산소방서온산119안전센터689893울산울주군온산읍덕신리신온8길노래연습장업
45남부소방서삼산119안전센터680805울산남구달동<NA>삼산로199번길단란주점
56남부소방서삼산119안전센터680805울산남구달동<NA>번영로150번길유흥주점
67남부소방서삼산119안전센터680805울산남구달동<NA>왕생로일반음식점
78동부소방서화정119안전센터682050울산동구일산동<NA>꽃밭등길일반음식점
89남부소방서삼산119안전센터680805울산남구달동<NA>왕생로노래연습장업
910남부소방서삼산119안전센터680805울산남구달동<NA>왕생로100번길노래연습장업
일련번호관할서명서센터명업소 우편번호업소 시도명업소 구군명업소 동명업소 리명업소 도로명업종명
55545,555북부소방서송정119안전센터44236울산북구송정동<NA>박상진6로일반음식점
55555,556북부소방서송정119안전센터44249울산북구진장동<NA>진장유통1로휴게음식점
55565,557북부소방서송정119안전센터44236울산북구송정동<NA>송정33길가상체험체육시설(스크린골프연습장)
55575,558남부소방서신정119안전센터44694울산남구달동<NA>신정로88번길일반음식점
55585,559남부소방서신정119안전센터44722울산남구달동<NA>도산로휴게음식점
55595,560북부소방서염포119안전센터44257울산북구양정동<NA>염포로가상체험체육시설(스크린골프연습장)
55605,561남부소방서여천119안전센터44772울산남구선암동<NA>선암호수길휴게음식점
55615,562중부소방서유곡119안전센터44452울산중구태화동<NA>유곡로일반음식점
55625,563북부소방서염포119안전센터44254울산북구명촌동<NA>명촌로인터넷컴퓨터게임시설제공업(PC방)
55635,564북부소방서염포119안전센터44254울산북구명촌동<NA>명촌로복합유통게임제공업