Overview

Dataset statistics

Number of variables13
Number of observations2456
Missing cells14
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory259.2 KiB
Average record size in memory108.1 B

Variable types

Numeric4
Categorical8
Text1

Dataset

Description부산광역시 상수도사업본부에서 상하수도 요금 계산 및 징수를 위해 운영하는 수용가정보시스템에 사용되는 민원 신청 정보(급수공사_공사승인) 자료입니다.
Author부산광역시 상수도사업본부
URLhttps://www.data.go.kr/data/15083679/fileData.do

Alerts

사업소명 is highly overall correlated with 사업소코드 and 3 other fieldsHigh correlation
구명 is highly overall correlated with 사업소코드 and 3 other fieldsHigh correlation
구경(mm) is highly overall correlated with 계량기종류코드 and 1 other fieldsHigh correlation
급수관구경(mm) is highly overall correlated with 구경(mm) and 1 other fieldsHigh correlation
사업소코드 is highly overall correlated with 구코드 and 3 other fieldsHigh correlation
구코드 is highly overall correlated with 사업소코드 and 2 other fieldsHigh correlation
동코드 is highly overall correlated with 사업소코드 and 2 other fieldsHigh correlation
급수관종류 is highly overall correlated with 계량기종류코드High correlation
계량기종류코드 is highly overall correlated with 구경(mm) and 2 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-21 01:56:47.203909
Analysis finished2024-04-21 01:56:51.432251
Duration4.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct2456
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1228.5
Minimum1
Maximum2456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.7 KiB
2024-04-21T10:56:51.508356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile123.75
Q1614.75
median1228.5
Q31842.25
95-th percentile2333.25
Maximum2456
Range2455
Interquartile range (IQR)1227.5

Descriptive statistics

Standard deviation709.13045
Coefficient of variation (CV)0.57723277
Kurtosis-1.2
Mean1228.5
Median Absolute Deviation (MAD)614
Skewness0
Sum3017196
Variance502866
MonotonicityStrictly increasing
2024-04-21T10:56:51.638759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1642 1
 
< 0.1%
1635 1
 
< 0.1%
1636 1
 
< 0.1%
1637 1
 
< 0.1%
1638 1
 
< 0.1%
1639 1
 
< 0.1%
1640 1
 
< 0.1%
1641 1
 
< 0.1%
1643 1
 
< 0.1%
Other values (2446) 2446
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2456 1
< 0.1%
2455 1
< 0.1%
2454 1
< 0.1%
2453 1
< 0.1%
2452 1
< 0.1%
2451 1
< 0.1%
2450 1
< 0.1%
2449 1
< 0.1%
2448 1
< 0.1%
2447 1
< 0.1%

사업소코드
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296.46621
Minimum201
Maximum312
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.7 KiB
2024-04-21T10:56:51.746909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201
5-th percentile244
Q1303
median307
Q3311
95-th percentile312
Maximum312
Range111
Interquartile range (IQR)8

Descriptive statistics

Standard deviation25.546852
Coefficient of variation (CV)0.08617121
Kurtosis1.4962213
Mean296.46621
Median Absolute Deviation (MAD)4
Skewness-1.7522183
Sum728121
Variance652.64163
MonotonicityNot monotonic
2024-04-21T10:56:51.875185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
311 428
17.4%
244 415
16.9%
312 397
16.2%
306 245
10.0%
307 233
9.5%
304 202
8.2%
308 177
7.2%
309 129
 
5.3%
301 96
 
3.9%
302 59
 
2.4%
Other values (2) 75
 
3.1%
ValueCountFrequency (%)
201 18
 
0.7%
244 415
16.9%
301 96
 
3.9%
302 59
 
2.4%
303 57
 
2.3%
304 202
8.2%
306 245
10.0%
307 233
9.5%
308 177
7.2%
309 129
 
5.3%
ValueCountFrequency (%)
312 397
16.2%
311 428
17.4%
309 129
 
5.3%
308 177
7.2%
307 233
9.5%
306 245
10.0%
304 202
8.2%
303 57
 
2.3%
302 59
 
2.4%
301 96
 
3.9%

사업소명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
강서사업소
428 
동래통합사업소
415 
기장사업소
397 
남부사업소
245 
북부사업소
233 
Other values (7)
738 

Length

Max length9
Median length5
Mean length5.8065961
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서부 사업소
2nd row기장사업소
3rd row기장사업소
4th row기장사업소
5th row기장사업소

Common Values

ValueCountFrequency (%)
강서사업소 428
17.4%
동래통합사업소 415
16.9%
기장사업소 397
16.2%
남부사업소 245
10.0%
북부사업소 233
9.5%
부산진 사업소 202
8.2%
해운대사업소 177
7.2%
사하사업소 129
 
5.3%
중동부사업소 96
 
3.9%
서부 사업소 59
 
2.4%
Other values (2) 75
 
3.1%

Length

2024-04-21T10:56:52.020499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서사업소 428
15.8%
동래통합사업소 415
15.3%
기장사업소 397
14.6%
사업소 261
9.6%
남부사업소 245
9.0%
북부사업소 233
8.6%
부산진 202
7.4%
해운대사업소 177
6.5%
사하사업소 129
 
4.7%
중동부사업소 96
 
3.5%
Other values (3) 134
 
4.9%

구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean414.28502
Minimum101
Maximum710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.7 KiB
2024-04-21T10:56:52.143340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile170
Q1290
median410
Q3500
95-th percentile710
Maximum710
Range609
Interquartile range (IQR)210

Descriptive statistics

Standard deviation166.61007
Coefficient of variation (CV)0.40216292
Kurtosis-0.5751644
Mean414.28502
Median Absolute Deviation (MAD)120
Skewness0.36969545
Sum1017484
Variance27758.916
MonotonicityNot monotonic
2024-04-21T10:56:52.242798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
440 430
17.5%
710 398
16.2%
230 202
8.2%
350 177
7.2%
260 162
 
6.6%
530 136
 
5.5%
470 133
 
5.4%
380 129
 
5.3%
290 126
 
5.1%
410 121
 
4.9%
Other values (7) 442
18.0%
ValueCountFrequency (%)
101 14
 
0.6%
110 42
 
1.7%
140 59
 
2.4%
170 54
 
2.2%
200 57
 
2.3%
230 202
8.2%
260 162
6.6%
290 126
5.1%
320 97
3.9%
350 177
7.2%
ValueCountFrequency (%)
710 398
16.2%
530 136
 
5.5%
500 119
 
4.8%
470 133
 
5.4%
440 430
17.5%
410 121
 
4.9%
380 129
 
5.3%
350 177
7.2%
320 97
 
3.9%
290 126
 
5.1%

구명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
강서구
430 
기장군
398 
부산진구
202 
해운대구
177 
동래구
162 
Other values (12)
1087 

Length

Max length4
Median length3
Mean length2.9947068
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서구
2nd row기장군
3rd row기장군
4th row기장군
5th row기장군

Common Values

ValueCountFrequency (%)
강서구 430
17.5%
기장군 398
16.2%
부산진구 202
8.2%
해운대구 177
7.2%
동래구 162
 
6.6%
사상구 136
 
5.5%
연제구 133
 
5.4%
사하구 129
 
5.3%
남구 126
 
5.1%
금정구 121
 
4.9%
Other values (7) 442
18.0%

Length

2024-04-21T10:56:52.401705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 430
17.5%
기장군 398
16.2%
부산진구 202
8.2%
해운대구 177
7.2%
동래구 162
 
6.6%
사상구 136
 
5.5%
연제구 133
 
5.4%
사하구 129
 
5.3%
남구 126
 
5.1%
금정구 121
 
4.9%
Other values (7) 442
18.0%

동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean542.27158
Minimum101
Maximum800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size21.7 KiB
2024-04-21T10:56:52.539849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile253
Q1520
median560
Q3620
95-th percentile740
Maximum800
Range699
Interquartile range (IQR)100

Descriptive statistics

Standard deviation138.83193
Coefficient of variation (CV)0.25601918
Kurtosis0.44397591
Mean542.27158
Median Absolute Deviation (MAD)50
Skewness-0.86949469
Sum1331819
Variance19274.304
MonotonicityNot monotonic
2024-04-21T10:56:52.689573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
530 163
 
6.6%
510 160
 
6.5%
550 153
 
6.2%
560 150
 
6.1%
520 150
 
6.1%
580 112
 
4.6%
253 95
 
3.9%
620 93
 
3.8%
310 92
 
3.7%
250 89
 
3.6%
Other values (51) 1199
48.8%
ValueCountFrequency (%)
101 14
 
0.6%
250 89
3.6%
253 95
3.9%
256 42
 
1.7%
310 92
3.7%
330 80
3.3%
510 160
6.5%
520 150
6.1%
521 14
 
0.6%
525 1
 
< 0.1%
ValueCountFrequency (%)
800 34
1.4%
790 9
 
0.4%
780 21
0.9%
770 25
1.0%
762 1
 
< 0.1%
761 4
 
0.2%
760 17
0.7%
750 7
 
0.3%
740 35
1.4%
730 12
 
0.5%

동명
Text

Distinct203
Distinct (%)8.3%
Missing14
Missing (%)0.6%
Memory size19.3 KiB
2024-04-21T10:56:52.985373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5773956
Min length3

Characters and Unicode

Total characters8736
Distinct characters107
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.9%

Sample

1st row서대신3동
2nd row기장읍
3rd row기장읍
4th row기장읍
5th row일광읍
ValueCountFrequency (%)
장안읍 95
 
3.9%
일광읍 92
 
3.8%
기장읍 89
 
3.6%
녹산동 87
 
3.6%
대저2동 87
 
3.6%
철마면 80
 
3.3%
강동동 58
 
2.4%
대저1동 57
 
2.3%
가락동 51
 
2.1%
온천1동 48
 
2.0%
Other values (193) 1698
69.5%
2024-04-21T10:56:53.432147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 2144
24.5%
1 604
 
6.9%
2 476
 
5.4%
읍 328
 
3.8%
대 244
 
2.8%
장 238
 
2.7%
3 196
 
2.2%
산 172
 
2.0%
안 161
 
1.8%
천 154
 
1.8%
Other values (97) 4019
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7331
83.9%
Decimal Number 1405
 
16.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2144
29.2%
읍 328
 
4.5%
대 244
 
3.3%
장 238
 
3.2%
산 172
 
2.3%
안 161
 
2.2%
천 154
 
2.1%
저 144
 
2.0%
광 143
 
2.0%
연 133
 
1.8%
Other values (89) 3470
47.3%
Decimal Number
ValueCountFrequency (%)
1 604
43.0%
2 476
33.9%
3 196
 
14.0%
4 71
 
5.1%
5 35
 
2.5%
6 17
 
1.2%
9 3
 
0.2%
8 3
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7331
83.9%
Common 1405
 
16.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2144
29.2%
읍 328
 
4.5%
대 244
 
3.3%
장 238
 
3.2%
산 172
 
2.3%
안 161
 
2.2%
천 154
 
2.1%
저 144
 
2.0%
광 143
 
2.0%
연 133
 
1.8%
Other values (89) 3470
47.3%
Common
ValueCountFrequency (%)
1 604
43.0%
2 476
33.9%
3 196
 
14.0%
4 71
 
5.1%
5 35
 
2.5%
6 17
 
1.2%
9 3
 
0.2%
8 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7331
83.9%
ASCII 1405
 
16.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 2144
29.2%
읍 328
 
4.5%
대 244
 
3.3%
장 238
 
3.2%
산 172
 
2.3%
안 161
 
2.2%
천 154
 
2.1%
저 144
 
2.0%
광 143
 
2.0%
연 133
 
1.8%
Other values (89) 3470
47.3%
ASCII
ValueCountFrequency (%)
1 604
43.0%
2 476
33.9%
3 196
 
14.0%
4 71
 
5.1%
5 35
 
2.5%
6 17
 
1.2%
9 3
 
0.2%
8 3
 
0.2%

구경(mm)
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
15 mm
980 
<NA>
940 
25 mm
189 
20 mm
132 
40 mm
 
73
Other values (5)
142 

Length

Max length6
Median length5
Mean length4.6241857
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15 mm
2nd row15 mm
3rd row32 mm
4th row15 mm
5th row15 mm

Common Values

ValueCountFrequency (%)
15 mm 980
39.9%
<NA> 940
38.3%
25 mm 189
 
7.7%
20 mm 132
 
5.4%
40 mm 73
 
3.0%
50 mm 58
 
2.4%
32 mm 47
 
1.9%
80 mm 20
 
0.8%
100 mm 14
 
0.6%
150 mm 3
 
0.1%

Length

2024-04-21T10:56:53.580056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:56:53.699476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mm 1516
38.2%
15 980
24.7%
na 940
23.7%
25 189
 
4.8%
20 132
 
3.3%
40 73
 
1.8%
50 58
 
1.5%
32 47
 
1.2%
80 20
 
0.5%
100 14
 
0.4%

급수관종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
<NA>
943 
스테인레스관
836 
PFP
455 
기타
192 
닥타일주철관(에폭시)
 
25

Length

Max length11
Median length6
Mean length4.4246743
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd row기타
3rd rowPFP
4th row기타
5th rowPFP

Common Values

ValueCountFrequency (%)
<NA> 943
38.4%
스테인레스관 836
34.0%
PFP 455
18.5%
기타 192
 
7.8%
닥타일주철관(에폭시) 25
 
1.0%
닥타일주철관(시멘트) 5
 
0.2%

Length

2024-04-21T10:56:53.821585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:56:53.938127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 943
38.4%
스테인레스관 836
34.0%
pfp 455
18.5%
기타 192
 
7.8%
닥타일주철관(에폭시 25
 
1.0%
닥타일주철관(시멘트 5
 
0.2%

계량기종류코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
익차형
1479 
<NA>
941 
터어빈형
 
31
월트만형
 
5

Length

Max length4
Median length3
Mean length3.3978013
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
익차형 1479
60.2%
<NA> 941
38.3%
터어빈형 31
 
1.3%
월트만형 5
 
0.2%

Length

2024-04-21T10:56:54.296679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:56:54.402539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
익차형 1479
60.2%
na 941
38.3%
터어빈형 31
 
1.3%
월트만형 5
 
0.2%

연결본관종류
Categorical

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
<NA>
942 
PFP
546 
스테인레스관
396 
닥타일주철관(시멘트)
378 
닥타일주철관(에폭시)
181 
Other values (3)
 
13

Length

Max length11
Median length7
Mean length5.6868893
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기타
2nd rowPFP
3rd rowPFP
4th rowPFP
5th rowPFP

Common Values

ValueCountFrequency (%)
<NA> 942
38.4%
PFP 546
22.2%
스테인레스관 396
16.1%
닥타일주철관(시멘트) 378
15.4%
닥타일주철관(에폭시) 181
 
7.4%
기타 9
 
0.4%
에폭시라이닝관 2
 
0.1%
PE 2
 
0.1%

Length

2024-04-21T10:56:54.512588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:56:54.621802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 942
38.4%
pfp 546
22.2%
스테인레스관 396
16.1%
닥타일주철관(시멘트 378
15.4%
닥타일주철관(에폭시 181
 
7.4%
기타 9
 
0.4%
에폭시라이닝관 2
 
0.1%
pe 2
 
0.1%

연결본관구경(mm)
Categorical

Distinct9
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
<NA>
1232 
15 mm
295 
40 mm
245 
20 mm
211 
25 mm
211 
Other values (4)
262 

Length

Max length5
Median length4
Mean length4.4983713
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row40 mm
2nd row40 mm
3rd row65 mm
4th row20 mm
5th row15 mm

Common Values

ValueCountFrequency (%)
<NA> 1232
50.2%
15 mm 295
 
12.0%
40 mm 245
 
10.0%
20 mm 211
 
8.6%
25 mm 211
 
8.6%
50 mm 144
 
5.9%
65 mm 89
 
3.6%
80 mm 18
 
0.7%
32 mm 11
 
0.4%

Length

2024-04-21T10:56:54.749261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:56:54.860007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1232
33.5%
mm 1224
33.3%
15 295
 
8.0%
40 245
 
6.7%
20 211
 
5.7%
25 211
 
5.7%
50 144
 
3.9%
65 89
 
2.4%
80 18
 
0.5%
32 11
 
0.3%

급수관구경(mm)
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size19.3 KiB
15 mm
980 
<NA>
940 
25 mm
189 
20 mm
132 
40 mm
 
73
Other values (5)
142 

Length

Max length6
Median length5
Mean length4.6241857
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15 mm
2nd row15 mm
3rd row32 mm
4th row15 mm
5th row15 mm

Common Values

ValueCountFrequency (%)
15 mm 980
39.9%
<NA> 940
38.3%
25 mm 189
 
7.7%
20 mm 132
 
5.4%
40 mm 73
 
3.0%
50 mm 58
 
2.4%
32 mm 47
 
1.9%
80 mm 20
 
0.8%
100 mm 14
 
0.6%
150 mm 3
 
0.1%

Length

2024-04-21T10:56:55.000918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T10:56:55.140083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mm 1516
38.2%
15 980
24.7%
na 940
23.7%
25 189
 
4.8%
20 132
 
3.3%
40 73
 
1.8%
50 58
 
1.5%
32 47
 
1.2%
80 20
 
0.5%
100 14
 
0.4%

Interactions

2024-04-21T10:56:50.780482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:49.610390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.040033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.426106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.866817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:49.758106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.143785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.508255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.959002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:49.850990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.247706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.591672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:51.047452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:49.946267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.337135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:56:50.684676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:56:55.240277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업소코드사업소명구코드구명동코드구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
연번1.0000.0340.0000.0000.0000.0860.0460.0000.0440.0000.0650.046
사업소코드0.0341.0001.0000.5281.0000.2840.1030.2020.0580.0970.1110.103
사업소명0.0001.0001.0000.9600.9980.8540.2050.6290.2140.4840.2500.205
구코드0.0000.5280.9601.0001.0000.7440.2590.5150.2340.4020.2240.259
구명0.0001.0000.9981.0001.0000.8980.2700.6770.2660.5310.3430.270
동코드0.0860.2840.8540.7440.8981.0000.1820.3170.1060.3790.1850.182
구경(mm)0.0460.1030.2050.2590.2700.1821.0000.6860.9430.3830.2291.000
급수관종류0.0000.2020.6290.5150.6770.3170.6861.0000.6420.3960.2660.686
계량기종류코드0.0440.0580.2140.2340.2660.1060.9430.6421.0000.2250.1400.943
연결본관종류0.0000.0970.4840.4020.5310.3790.3830.3960.2251.0000.5730.383
연결본관구경(mm)0.0650.1110.2500.2240.3430.1850.2290.2660.1400.5731.0000.229
급수관구경(mm)0.0460.1030.2050.2590.2700.1821.0000.6860.9430.3830.2291.000
2024-04-21T10:56:55.382838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연결본관구경(mm)계량기종류코드사업소명급수관종류구명구경(mm)급수관구경(mm)연결본관종류
연결본관구경(mm)1.0000.0890.1200.1660.1260.1140.1140.353
계량기종류코드0.0891.0000.1270.6060.1480.7170.7170.154
사업소명0.1200.1271.0000.4090.9880.0940.0940.263
급수관종류0.1660.6060.4091.0000.4250.4840.4840.267
구명0.1260.1480.9880.4251.0000.1140.1140.276
구경(mm)0.1140.7170.0940.4840.1141.0001.0000.213
급수관구경(mm)0.1140.7170.0940.4840.1141.0001.0000.213
연결본관종류0.3530.1540.2630.2670.2760.2130.2131.000
2024-04-21T10:56:55.543345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업소코드구코드동코드사업소명구명구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
연번1.000-0.003-0.0050.0290.0000.0000.0210.0000.0260.0000.0310.021
사업소코드-0.0031.0000.644-0.6220.9980.9390.1030.2470.0960.1030.0830.103
구코드-0.0050.6441.000-0.3150.8330.9980.0850.3280.1050.2250.1110.085
동코드0.029-0.622-0.3151.0000.5720.6620.0960.2090.0710.1400.0990.096
사업소명0.0000.9980.8330.5721.0000.9880.0940.4090.1270.2630.1200.094
구명0.0000.9390.9980.6620.9881.0000.1140.4250.1480.2760.1260.114
구경(mm)0.0210.1030.0850.0960.0940.1141.0000.4840.7170.2130.1141.000
급수관종류0.0000.2470.3280.2090.4090.4250.4841.0000.6060.2670.1660.484
계량기종류코드0.0260.0960.1050.0710.1270.1480.7170.6061.0000.1540.0890.717
연결본관종류0.0000.1030.2250.1400.2630.2760.2130.2670.1541.0000.3530.213
연결본관구경(mm)0.0310.0830.1110.0990.1200.1260.1140.1660.0890.3531.0000.114
급수관구경(mm)0.0210.1030.0850.0960.0940.1141.0000.4840.7170.2130.1141.000

Missing values

2024-04-21T10:56:51.183277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:56:51.361014image/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.

Sample

연번사업소코드사업소명구코드구명동코드동명구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
01302서부 사업소140서구560서대신3동15 mm기타익차형기타40 mm15 mm
12312기장사업소710기장군250기장읍15 mm기타익차형PFP40 mm15 mm
23312기장사업소710기장군250기장읍32 mmPFP익차형PFP65 mm32 mm
34312기장사업소710기장군250기장읍15 mm기타익차형PFP20 mm15 mm
45312기장사업소710기장군310일광읍15 mmPFP익차형PFP15 mm15 mm
56244동래통합사업소260동래구570온천3동15 mm스테인레스관익차형닥타일주철관(시멘트)20 mm15 mm
67306남부사업소500수영구800민락동15 mm스테인레스관익차형스테인레스관25 mm15 mm
78303영도사업소200영도구640청학2동<NA><NA><NA><NA><NA><NA>
89244동래통합사업소260동래구550온천1동40 mmPFP익차형닥타일주철관(에폭시)15 mm40 mm
910244동래통합사업소260동래구550온천1동<NA><NA><NA><NA><NA><NA>
연번사업소코드사업소명구코드구명동코드동명구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
24462447244동래통합사업소260동래구580사직1동15 mm스테인레스관익차형PFP32 mm15 mm
24472448311강서사업소440강서구530강동동<NA><NA><NA><NA><NA><NA>
24482449311강서사업소440강서구530강동동<NA><NA><NA><NA><NA><NA>
24492450308해운대사업소350해운대구570반여1동15 mm스테인레스관익차형PFP50 mm15 mm
24502451304부산진 사업소230부산진구670당감1동15 mm기타익차형스테인레스관15 mm15 mm
24512452244동래통합사업소410금정구590부곡3동<NA><NA><NA><NA><NA><NA>
24522453308해운대사업소350해운대구510우1동15 mm스테인레스관익차형PFP40 mm15 mm
24532454312기장사업소710기장군253장안읍25 mm스테인레스관익차형닥타일주철관(에폭시)20 mm25 mm
24542455307북부사업소530사상구591모라1동15 mm스테인레스관익차형스테인레스관25 mm15 mm
24552456244동래통합사업소260동래구570온천3동20 mm스테인레스관익차형스테인레스관40 mm20 mm