Overview

Dataset statistics

Number of variables13
Number of observations3277
Missing cells15
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory345.8 KiB
Average record size in memory108.0 B

Variable types

Numeric4
Categorical8
Text1

Dataset

Description부산광역시상수도사업본부_수용가정보시스템_민원신청정보_급수공사(공사승인)_20230403
Author부산광역시 상수도사업본부
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15083679

Alerts

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

Reproduction

Analysis started2023-12-10 16:14:36.312028
Analysis finished2023-12-10 16:14:40.628429
Duration4.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct3277
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1639
Minimum1
Maximum3277
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2023-12-11T01:14:40.733079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile164.8
Q1820
median1639
Q32458
95-th percentile3113.2
Maximum3277
Range3276
Interquartile range (IQR)1638

Descriptive statistics

Standard deviation946.13274
Coefficient of variation (CV)0.5772622
Kurtosis-1.2
Mean1639
Median Absolute Deviation (MAD)819
Skewness0
Sum5371003
Variance895167.17
MonotonicityStrictly increasing
2023-12-11T01:14:40.939524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2190 1
 
< 0.1%
2180 1
 
< 0.1%
2181 1
 
< 0.1%
2182 1
 
< 0.1%
2183 1
 
< 0.1%
2184 1
 
< 0.1%
2185 1
 
< 0.1%
2186 1
 
< 0.1%
2187 1
 
< 0.1%
Other values (3267) 3267
99.7%
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 (%)
3277 1
< 0.1%
3276 1
< 0.1%
3275 1
< 0.1%
3274 1
< 0.1%
3273 1
< 0.1%
3272 1
< 0.1%
3271 1
< 0.1%
3270 1
< 0.1%
3269 1
< 0.1%
3268 1
< 0.1%

사업소코드
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean297.52518
Minimum101
Maximum312
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2023-12-11T01:14:41.095454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile244
Q1304
median307
Q3311
95-th percentile312
Maximum312
Range211
Interquartile range (IQR)7

Descriptive statistics

Standard deviation25.131651
Coefficient of variation (CV)0.084468989
Kurtosis4.0036794
Mean297.52518
Median Absolute Deviation (MAD)4
Skewness-2.0826854
Sum974990
Variance631.59987
MonotonicityNot monotonic
2023-12-11T01:14:41.264462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
311 635
19.4%
312 562
17.1%
244 500
15.3%
306 323
9.9%
307 296
9.0%
304 279
8.5%
309 196
 
6.0%
308 172
 
5.2%
301 104
 
3.2%
303 96
 
2.9%
Other values (3) 114
 
3.5%
ValueCountFrequency (%)
101 2
 
0.1%
201 23
 
0.7%
244 500
15.3%
301 104
 
3.2%
302 89
 
2.7%
303 96
 
2.9%
304 279
8.5%
306 323
9.9%
307 296
9.0%
308 172
 
5.2%
ValueCountFrequency (%)
312 562
17.1%
311 635
19.4%
309 196
 
6.0%
308 172
 
5.2%
307 296
9.0%
306 323
9.9%
304 279
8.5%
303 96
 
2.9%
302 89
 
2.7%
301 104
 
3.2%

사업소명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
강서 사업소
635 
기장 사업소
562 
동래통합사업소
500 
남부 사업소
323 
북부 사업소
296 
Other values (8)
961 

Length

Max length9
Median length9
Mean length8.5090021
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기장 사업소
2nd row북부 사업소
3rd row동래통합사업소
4th row남부 사업소
5th row기장 사업소

Common Values

ValueCountFrequency (%)
강서 사업소 635
19.4%
기장 사업소 562
17.1%
동래통합사업소 500
15.3%
남부 사업소 323
9.9%
북부 사업소 296
9.0%
부산진 사업소 279
8.5%
사하 사업소 196
 
6.0%
해운대 사업소 172
 
5.2%
중동부 사업소 104
 
3.2%
영도 사업소 96
 
2.9%
Other values (3) 114
 
3.5%

Length

2023-12-11T01:14:41.445818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
사업소 2752
45.6%
강서 635
 
10.5%
기장 562
 
9.3%
동래통합사업소 500
 
8.3%
남부 323
 
5.4%
북부 296
 
4.9%
부산진 279
 
4.6%
사하 196
 
3.3%
해운대 172
 
2.9%
중동부 104
 
1.7%
Other values (4) 210
 
3.5%

구코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean421.36863
Minimum101
Maximum710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2023-12-11T01:14:41.589734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile170
Q1290
median440
Q3500
95-th percentile710
Maximum710
Range609
Interquartile range (IQR)210

Descriptive statistics

Standard deviation167.11476
Coefficient of variation (CV)0.39659991
Kurtosis-0.64424508
Mean421.36863
Median Absolute Deviation (MAD)90
Skewness0.33351686
Sum1380825
Variance27927.343
MonotonicityNot monotonic
2023-12-11T01:14:41.705327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
440 637
19.4%
710 564
17.2%
230 280
8.5%
380 196
 
6.0%
530 193
 
5.9%
410 181
 
5.5%
350 172
 
5.2%
290 171
 
5.2%
260 166
 
5.1%
470 155
 
4.7%
Other values (8) 562
17.1%
ValueCountFrequency (%)
101 11
 
0.3%
110 32
 
1.0%
140 90
 
2.7%
170 73
 
2.2%
200 96
 
2.9%
201 4
 
0.1%
230 280
8.5%
260 166
5.1%
290 171
5.2%
320 104
 
3.2%
ValueCountFrequency (%)
710 564
17.2%
530 193
 
5.9%
500 152
 
4.6%
470 155
 
4.7%
440 637
19.4%
410 181
 
5.5%
380 196
 
6.0%
350 172
 
5.2%
320 104
 
3.2%
290 171
 
5.2%

구명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
강서구
637 
기장군
564 
부산진구
280 
사하구
196 
사상구
193 
Other values (13)
1407 

Length

Max length4
Median length3
Mean length2.9899298
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기장군
2nd row사상구
3rd row연제구
4th row수영구
5th row기장군

Common Values

ValueCountFrequency (%)
강서구 637
19.4%
기장군 564
17.2%
부산진구 280
8.5%
사하구 196
 
6.0%
사상구 193
 
5.9%
금정구 181
 
5.5%
해운대구 172
 
5.2%
남구 171
 
5.2%
동래구 166
 
5.1%
연제구 155
 
4.7%
Other values (8) 562
17.1%

Length

2023-12-11T01:14:41.833952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강서구 637
19.4%
기장군 564
17.2%
부산진구 280
8.5%
사하구 196
 
6.0%
사상구 193
 
5.9%
금정구 181
 
5.5%
해운대구 172
 
5.2%
남구 171
 
5.2%
동래구 166
 
5.1%
연제구 155
 
4.7%
Other values (8) 562
17.1%

동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct63
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean540.69484
Minimum101
Maximum800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size28.9 KiB
2023-12-11T01:14:41.961977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum101
5-th percentile253
Q1510
median560
Q3635
95-th percentile740
Maximum800
Range699
Interquartile range (IQR)125

Descriptive statistics

Standard deviation139.39412
Coefficient of variation (CV)0.25780552
Kurtosis0.18870694
Mean540.69484
Median Absolute Deviation (MAD)50
Skewness-0.84925211
Sum1771857
Variance19430.72
MonotonicityNot monotonic
2023-12-11T01:14:42.159132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
510 253
 
7.7%
560 199
 
6.1%
520 188
 
5.7%
550 179
 
5.5%
530 156
 
4.8%
310 155
 
4.7%
580 143
 
4.4%
540 139
 
4.2%
253 139
 
4.2%
330 100
 
3.1%
Other values (53) 1626
49.6%
ValueCountFrequency (%)
101 11
 
0.3%
201 4
 
0.1%
250 89
 
2.7%
253 139
4.2%
256 81
 
2.5%
310 155
4.7%
330 100
 
3.1%
510 253
7.7%
520 188
5.7%
521 12
 
0.4%
ValueCountFrequency (%)
800 43
1.3%
790 6
 
0.2%
780 10
 
0.3%
770 18
 
0.5%
762 4
 
0.1%
761 8
 
0.2%
760 24
0.7%
750 16
 
0.5%
740 53
1.6%
730 28
0.9%

동명
Text

Distinct204
Distinct (%)6.3%
Missing15
Missing (%)0.5%
Memory size25.7 KiB
2023-12-11T01:14:42.589700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.5567137
Min length3

Characters and Unicode

Total characters11602
Distinct characters108
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

Unique15 ?
Unique (%)0.5%

Sample

1st row철마면
2nd row학장동
3rd row연산1동
4th row망미1동
5th row기장읍
ValueCountFrequency (%)
일광읍 155
 
4.8%
장안읍 139
 
4.3%
대저2동 129
 
4.0%
대저1동 114
 
3.5%
녹산동 113
 
3.5%
철마면 100
 
3.1%
명지동 90
 
2.8%
기장읍 89
 
2.7%
정관읍 81
 
2.5%
가덕도동 77
 
2.4%
Other values (194) 2175
66.7%
2023-12-11T01:14:43.284845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 2799
24.1%
1 823
 
7.1%
2 583
 
5.0%
읍 488
 
4.2%
대 344
 
3.0%
장 327
 
2.8%
산 251
 
2.2%
저 243
 
2.1%
안 213
 
1.8%
광 201
 
1.7%
Other values (98) 5330
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9864
85.0%
Decimal Number 1738
 
15.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2799
28.4%
읍 488
 
4.9%
대 344
 
3.5%
장 327
 
3.3%
산 251
 
2.5%
저 243
 
2.5%
안 213
 
2.2%
광 201
 
2.0%
정 183
 
1.9%
연 182
 
1.8%
Other values (89) 4633
47.0%
Decimal Number
ValueCountFrequency (%)
1 823
47.4%
2 583
33.5%
3 187
 
10.8%
4 60
 
3.5%
5 45
 
2.6%
6 24
 
1.4%
9 7
 
0.4%
8 7
 
0.4%
7 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9864
85.0%
Common 1738
 
15.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2799
28.4%
읍 488
 
4.9%
대 344
 
3.5%
장 327
 
3.3%
산 251
 
2.5%
저 243
 
2.5%
안 213
 
2.2%
광 201
 
2.0%
정 183
 
1.9%
연 182
 
1.8%
Other values (89) 4633
47.0%
Common
ValueCountFrequency (%)
1 823
47.4%
2 583
33.5%
3 187
 
10.8%
4 60
 
3.5%
5 45
 
2.6%
6 24
 
1.4%
9 7
 
0.4%
8 7
 
0.4%
7 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9864
85.0%
ASCII 1738
 
15.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 2799
28.4%
읍 488
 
4.9%
대 344
 
3.5%
장 327
 
3.3%
산 251
 
2.5%
저 243
 
2.5%
안 213
 
2.2%
광 201
 
2.0%
정 183
 
1.9%
연 182
 
1.8%
Other values (89) 4633
47.0%
ASCII
ValueCountFrequency (%)
1 823
47.4%
2 583
33.5%
3 187
 
10.8%
4 60
 
3.5%
5 45
 
2.6%
6 24
 
1.4%
9 7
 
0.4%
8 7
 
0.4%
7 2
 
0.1%

구경(mm)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
15 mm
1413 
<NA>
1239 
20 mm
206 
25 mm
201 
50 mm
 
69
Other values (6)
149 

Length

Max length6
Median length5
Mean length4.6249619
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row15 mm
2nd row25 mm
3rd row<NA>
4th row<NA>
5th row15 mm

Common Values

ValueCountFrequency (%)
15 mm 1413
43.1%
<NA> 1239
37.8%
20 mm 206
 
6.3%
25 mm 201
 
6.1%
50 mm 69
 
2.1%
40 mm 61
 
1.9%
32 mm 50
 
1.5%
80 mm 28
 
0.9%
100 mm 5
 
0.2%
150 mm 4
 
0.1%

Length

2023-12-11T01:14:43.489506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
mm 2038
38.3%
15 1413
26.6%
na 1239
23.3%
20 206
 
3.9%
25 201
 
3.8%
50 69
 
1.3%
40 61
 
1.1%
32 50
 
0.9%
80 28
 
0.5%
100 5
 
0.1%
Other values (2) 5
 
0.1%

급수관종류
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
1239 
스테인레스관
1115 
PFP
628 
기타
259 
닥타일주철관(에폭시)
 
28

Length

Max length11
Median length6
Mean length4.40769
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row스테인레스관
2nd row스테인레스관
3rd row<NA>
4th row<NA>
5th row스테인레스관

Common Values

ValueCountFrequency (%)
<NA> 1239
37.8%
스테인레스관 1115
34.0%
PFP 628
19.2%
기타 259
 
7.9%
닥타일주철관(에폭시) 28
 
0.9%
닥타일주철관(시멘트) 8
 
0.2%

Length

2023-12-11T01:14:43.621475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:43.743825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1239
37.8%
스테인레스관 1115
34.0%
pfp 628
19.2%
기타 259
 
7.9%
닥타일주철관(에폭시 28
 
0.9%
닥타일주철관(시멘트 8
 
0.2%

계량기종류코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
익차형
2003 
<NA>
1239 
터어빈형
 
31
월트만형
 
4

Length

Max length4
Median length3
Mean length3.3887702
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row익차형
2nd row익차형
3rd row<NA>
4th row<NA>
5th row익차형

Common Values

ValueCountFrequency (%)
익차형 2003
61.1%
<NA> 1239
37.8%
터어빈형 31
 
0.9%
월트만형 4
 
0.1%

Length

2023-12-11T01:14:43.923799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:44.045903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
익차형 2003
61.1%
na 1239
37.8%
터어빈형 31
 
0.9%
월트만형 4
 
0.1%

연결본관종류
Categorical

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
1239 
PFP
895 
스테인레스관
509 
닥타일주철관(시멘트)
406 
닥타일주철관(에폭시)
208 
Other values (4)
 
20

Length

Max length11
Median length6
Mean length5.3405554
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPFP
2nd row닥타일주철관(시멘트)
3rd row<NA>
4th row<NA>
5th rowPFP

Common Values

ValueCountFrequency (%)
<NA> 1239
37.8%
PFP 895
27.3%
스테인레스관 509
15.5%
닥타일주철관(시멘트) 406
 
12.4%
닥타일주철관(에폭시) 208
 
6.3%
기타 13
 
0.4%
PE 3
 
0.1%
도복장강관 2
 
0.1%
HI-3P 2
 
0.1%

Length

2023-12-11T01:14:44.550648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:44.727791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1239
37.8%
pfp 895
27.3%
스테인레스관 509
15.5%
닥타일주철관(시멘트 406
 
12.4%
닥타일주철관(에폭시 208
 
6.3%
기타 13
 
0.4%
pe 3
 
0.1%
도복장강관 2
 
0.1%
hi-3p 2
 
0.1%

연결본관구경(mm)
Categorical

Distinct9
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
<NA>
1562 
40 mm
392 
25 mm
313 
15 mm
289 
20 mm
286 
Other values (4)
435 

Length

Max length5
Median length5
Mean length4.5233445
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row65 mm
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row40 mm

Common Values

ValueCountFrequency (%)
<NA> 1562
47.7%
40 mm 392
 
12.0%
25 mm 313
 
9.6%
15 mm 289
 
8.8%
20 mm 286
 
8.7%
50 mm 223
 
6.8%
65 mm 144
 
4.4%
80 mm 38
 
1.2%
32 mm 30
 
0.9%

Length

2023-12-11T01:14:44.973513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:14:45.164534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
mm 1715
34.4%
na 1562
31.3%
40 392
 
7.9%
25 313
 
6.3%
15 289
 
5.8%
20 286
 
5.7%
50 223
 
4.5%
65 144
 
2.9%
80 38
 
0.8%
32 30
 
0.6%

급수관구경(mm)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size25.7 KiB
15 mm
1413 
<NA>
1239 
20 mm
206 
25 mm
201 
50 mm
 
69
Other values (6)
149 

Length

Max length6
Median length5
Mean length4.6249619
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row15 mm
2nd row25 mm
3rd row<NA>
4th row<NA>
5th row15 mm

Common Values

ValueCountFrequency (%)
15 mm 1413
43.1%
<NA> 1239
37.8%
20 mm 206
 
6.3%
25 mm 201
 
6.1%
50 mm 69
 
2.1%
40 mm 61
 
1.9%
32 mm 50
 
1.5%
80 mm 28
 
0.9%
100 mm 5
 
0.2%
150 mm 4
 
0.1%

Length

2023-12-11T01:14:45.375882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
mm 2038
38.3%
15 1413
26.6%
na 1239
23.3%
20 206
 
3.9%
25 201
 
3.8%
50 69
 
1.3%
40 61
 
1.1%
32 50
 
0.9%
80 28
 
0.5%
100 5
 
0.1%
Other values (2) 5
 
0.1%

Interactions

2023-12-11T01:14:39.672587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:37.762753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:38.527019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:39.104243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:39.807402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:37.893654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:38.673832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:39.252344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:39.915892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:38.059081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:38.802731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:39.369329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:40.065989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:38.259286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:38.937645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:14:39.521992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:14:45.638343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업소코드사업소명구코드구명동코드구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
연번1.0000.0560.0000.0000.0000.0830.0770.0270.0920.0890.0660.077
사업소코드0.0561.0001.0000.4530.9030.6790.0000.2160.0000.2720.1920.000
사업소명0.0001.0001.0000.9580.9910.8110.2800.6510.0920.5370.2770.280
구코드0.0000.4530.9581.0001.0000.8650.2360.5180.0920.4560.2430.236
구명0.0000.9030.9911.0001.0000.9660.3260.6820.0690.6540.3730.326
동코드0.0830.6790.8110.8650.9661.0000.1520.4090.0190.2590.2010.152
구경(mm)0.0770.0000.2800.2360.3260.1521.0000.8770.8590.4560.1651.000
급수관종류0.0270.2160.6510.5180.6820.4090.8771.0000.6890.4300.3340.877
계량기종류코드0.0920.0000.0920.0920.0690.0190.8590.6891.0000.4310.0950.859
연결본관종류0.0890.2720.5370.4560.6540.2590.4560.4300.4311.0000.5830.456
연결본관구경(mm)0.0660.1920.2770.2430.3730.2010.1650.3340.0950.5831.0000.165
급수관구경(mm)0.0770.0000.2800.2360.3260.1521.0000.8770.8590.4560.1651.000
2023-12-11T01:14:45.876377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급수관구경(mm)급수관종류연결본관구경(mm)연결본관종류계량기종류코드구명사업소명구경(mm)
급수관구경(mm)1.0000.5520.0790.2380.7800.1340.1231.000
급수관종류0.5521.0000.2120.2810.6680.4310.4300.552
연결본관구경(mm)0.0790.2121.0000.3610.0600.1390.1340.079
연결본관종류0.2380.2810.3611.0000.3040.2880.2880.238
계량기종류코드0.7800.6680.0600.3041.0000.0370.0530.780
구명0.1340.4310.1390.2880.0371.0000.9410.134
사업소명0.1230.4300.1340.2880.0530.9411.0000.123
구경(mm)1.0000.5520.0790.2380.7800.1340.1231.000
2023-12-11T01:14:46.077618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업소코드구코드동코드사업소명구명구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
연번1.000-0.002-0.0150.0010.0000.0000.0240.0110.0550.0420.0310.024
사업소코드-0.0021.0000.666-0.6650.9990.7430.0000.2640.0000.2040.1440.000
구코드-0.0150.6661.000-0.3450.8460.9990.1090.3320.0400.2430.1210.109
동코드0.001-0.665-0.3451.0000.5240.7100.0770.2770.0130.1420.1090.077
사업소명0.0000.9990.8460.5241.0000.9410.1230.4300.0530.2880.1340.123
구명0.0000.7430.9990.7100.9411.0000.1340.4310.0370.2880.1390.134
구경(mm)0.0240.0000.1090.0770.1230.1341.0000.5520.7800.2380.0791.000
급수관종류0.0110.2640.3320.2770.4300.4310.5521.0000.6680.2810.2120.552
계량기종류코드0.0550.0000.0400.0130.0530.0370.7800.6681.0000.3040.0600.780
연결본관종류0.0420.2040.2430.1420.2880.2880.2380.2810.3041.0000.3610.238
연결본관구경(mm)0.0310.1440.1210.1090.1340.1390.0790.2120.0600.3611.0000.079
급수관구경(mm)0.0240.0000.1090.0770.1230.1341.0000.5520.7800.2380.0791.000

Missing values

2023-12-11T01:14:40.278236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:14:40.525728image/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)
01312기장 사업소710기장군330철마면15 mm스테인레스관익차형PFP65 mm15 mm
12307북부 사업소530사상구670학장동25 mm스테인레스관익차형닥타일주철관(시멘트)<NA>25 mm
23244동래통합사업소470연제구650연산1동<NA><NA><NA><NA><NA><NA>
34306남부 사업소500수영구740망미1동<NA><NA><NA><NA><NA><NA>
45312기장 사업소710기장군250기장읍15 mm스테인레스관익차형PFP40 mm15 mm
56311강서 사업소440강서구510대저1동15 mmPFP익차형PFP40 mm15 mm
67306남부 사업소500수영구660남천1동15 mm기타익차형스테인레스관15 mm15 mm
78306남부 사업소500수영구800민락동<NA><NA><NA><NA><NA><NA>
89304부산진 사업소230부산진구600전포1동15 mm기타익차형스테인레스관20 mm15 mm
910307북부 사업소530사상구645감전동15 mm스테인레스관익차형PFP40 mm15 mm
연번사업소코드사업소명구코드구명동코드동명구경(mm)급수관종류계량기종류코드연결본관종류연결본관구경(mm)급수관구경(mm)
32673268311강서 사업소440강서구530강동동15 mmPFP익차형PFP40 mm15 mm
32683269307북부 사업소530사상구620괘법동15 mm스테인레스관익차형PFP40 mm15 mm
32693270244동래통합사업소410금정구530서3동25 mm스테인레스관익차형PFP40 mm25 mm
32703271311강서 사업소440강서구510대저1동15 mmPFP익차형PFP40 mm15 mm
32713272309사하 사업소380사하구561하단1동<NA><NA><NA><NA><NA><NA>
32723273311강서 사업소440강서구560녹산동15 mmPFP익차형PFP65 mm15 mm
32733274312기장 사업소710기장군253장안읍15 mm스테인레스관익차형닥타일주철관(시멘트)20 mm15 mm
32743275309사하 사업소380사하구590장림2동<NA><NA><NA><NA><NA><NA>
32753276311강서 사업소440강서구520대저2동<NA><NA><NA><NA><NA><NA>
32763277307북부 사업소530사상구620괘법동<NA><NA><NA><NA><NA><NA>