Overview

Dataset statistics

Number of variables6
Number of observations153
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.9 KiB
Average record size in memory52.9 B

Variable types

Numeric4
Categorical2

Dataset

Description부산광역시사하구_U-옥외광고물통합관리시스템_법정동행정동매칭_20221021
Author부산광역시 사하구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15092250

Alerts

행정동명 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동명 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
시작번지 is highly overall correlated with 종료번지High correlation
종료번지 is highly overall correlated with 시작번지High correlation
시작번지 has 2 (1.3%) zerosZeros

Reproduction

Analysis started2023-12-10 17:16:51.603418
Analysis finished2023-12-10 17:16:56.102561
Duration4.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6380104 × 109
Minimum2.6380101 × 109
Maximum2.6380108 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T02:16:56.211645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6380101 × 109
5-th percentile2.6380101 × 109
Q12.6380101 × 109
median2.6380104 × 109
Q32.6380106 × 109
95-th percentile2.6380108 × 109
Maximum2.6380108 × 109
Range700
Interquartile range (IQR)500

Descriptive statistics

Standard deviation239.06063
Coefficient of variation (CV)9.0621563 × 10-8
Kurtosis-1.1516279
Mean2.6380104 × 109
Median Absolute Deviation (MAD)200
Skewness0.11210147
Sum4.0361559 × 1011
Variance57149.983
MonotonicityNot monotonic
2023-12-11T02:16:56.437551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2638010100 43
28.1%
2638010600 26
17.0%
2638010500 24
15.7%
2638010300 21
13.7%
2638010800 20
13.1%
2638010400 17
 
11.1%
2638010200 1
 
0.7%
2638010700 1
 
0.7%
ValueCountFrequency (%)
2638010100 43
28.1%
2638010200 1
 
0.7%
2638010300 21
13.7%
2638010400 17
 
11.1%
2638010500 24
15.7%
2638010600 26
17.0%
2638010700 1
 
0.7%
2638010800 20
13.1%
ValueCountFrequency (%)
2638010800 20
13.1%
2638010700 1
 
0.7%
2638010600 26
17.0%
2638010500 24
15.7%
2638010400 17
 
11.1%
2638010300 21
13.7%
2638010200 1
 
0.7%
2638010100 43
28.1%

법정동명
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
괴정동
43 
다대동
26 
장림동
24 
하단동
21 
감천동
20 
Other values (3)
19 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row장림동
2nd row하단동
3rd row장림동
4th row장림동
5th row장림동

Common Values

ValueCountFrequency (%)
괴정동 43
28.1%
다대동 26
17.0%
장림동 24
15.7%
하단동 21
13.7%
감천동 20
13.1%
신평동 17
 
11.1%
당리동 1
 
0.7%
구평동 1
 
0.7%

Length

2023-12-11T02:16:56.707885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:16:56.950141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
괴정동 43
28.1%
다대동 26
17.0%
장림동 24
15.7%
하단동 21
13.7%
감천동 20
13.1%
신평동 17
 
11.1%
당리동 1
 
0.7%
구평동 1
 
0.7%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3340034.4
Minimum3340027
Maximum3340042
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T02:16:57.198271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3340027
5-th percentile3340027
Q13340030
median3340035
Q33340038
95-th percentile3340041.4
Maximum3340042
Range15
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.6170795
Coefficient of variation (CV)1.3823449 × 10-6
Kurtosis-1.1579305
Mean3340034.4
Median Absolute Deviation (MAD)3
Skewness-0.091588433
Sum5.1102526 × 108
Variance21.317423
MonotonicityNot monotonic
2023-12-11T02:16:57.454569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3340038 17
11.1%
3340036 13
 
8.5%
3340028 12
 
7.8%
3340033 12
 
7.8%
3340041 12
 
7.8%
3340027 12
 
7.8%
3340037 11
 
7.2%
3340029 10
 
6.5%
3340034 9
 
5.9%
3340039 9
 
5.9%
Other values (6) 36
23.5%
ValueCountFrequency (%)
3340027 12
7.8%
3340028 12
7.8%
3340029 10
6.5%
3340030 9
5.9%
3340031 1
 
0.7%
3340032 9
5.9%
3340033 12
7.8%
3340034 9
5.9%
3340035 8
5.2%
3340036 13
8.5%
ValueCountFrequency (%)
3340042 8
5.2%
3340041 12
7.8%
3340040 1
 
0.7%
3340039 9
5.9%
3340038 17
11.1%
3340037 11
7.2%
3340036 13
8.5%
3340035 8
5.2%
3340034 9
5.9%
3340033 12
7.8%

행정동명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
다대1동
17 
장림1동
13 
하단2동
12 
감천1동
12 
괴정1동
12 
Other values (11)
87 

Length

Max length4
Median length4
Mean length3.9869281
Min length3

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row장림2동
2nd row하단1동
3rd row장림2동
4th row장림2동
5th row장림2동

Common Values

ValueCountFrequency (%)
다대1동 17
11.1%
장림1동 13
 
8.5%
하단2동 12
 
7.8%
감천1동 12
 
7.8%
괴정1동 12
 
7.8%
괴정2동 12
 
7.8%
장림2동 11
 
7.2%
괴정3동 10
 
6.5%
하단1동 9
 
5.9%
괴정4동 9
 
5.9%
Other values (6) 36
23.5%

Length

2023-12-11T02:16:57.798167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
다대1동 17
11.1%
장림1동 13
 
8.5%
하단2동 12
 
7.8%
감천1동 12
 
7.8%
괴정1동 12
 
7.8%
괴정2동 12
 
7.8%
장림2동 11
 
7.2%
괴정3동 10
 
6.5%
하단1동 9
 
5.9%
괴정4동 9
 
5.9%
Other values (6) 36
23.5%

시작번지
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct136
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean464.77124
Minimum0
Maximum1561
Zeros2
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T02:16:58.091307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.6
Q1111
median400
Q3701
95-th percentile1181.2
Maximum1561
Range1561
Interquartile range (IQR)590

Descriptive statistics

Standard deviation406.33068
Coefficient of variation (CV)0.87425952
Kurtosis-0.11629812
Mean464.77124
Median Absolute Deviation (MAD)293
Skewness0.81898477
Sum71110
Variance165104.62
MonotonicityNot monotonic
2023-12-11T02:16:58.400185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 6
 
3.9%
701 2
 
1.3%
316 2
 
1.3%
300 2
 
1.3%
80 2
 
1.3%
1000 2
 
1.3%
107 2
 
1.3%
120 2
 
1.3%
21 2
 
1.3%
550 2
 
1.3%
Other values (126) 129
84.3%
ValueCountFrequency (%)
0 2
 
1.3%
1 6
3.9%
2 1
 
0.7%
5 1
 
0.7%
8 1
 
0.7%
16 1
 
0.7%
17 1
 
0.7%
19 1
 
0.7%
21 2
 
1.3%
23 1
 
0.7%
ValueCountFrequency (%)
1561 1
0.7%
1553 1
0.7%
1551 1
0.7%
1549 1
0.7%
1522 1
0.7%
1239 1
0.7%
1238 1
0.7%
1210 1
0.7%
1162 1
0.7%
1146 1
0.7%

종료번지
Real number (ℝ)

HIGH CORRELATION 

Distinct135
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean986.55556
Minimum1
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T02:16:59.457084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile21.2
Q1143
median471
Q3870
95-th percentile4935.6
Maximum9999
Range9998
Interquartile range (IQR)727

Descriptive statistics

Standard deviation2159.6233
Coefficient of variation (CV)2.1890539
Kurtosis13.557669
Mean986.55556
Median Absolute Deviation (MAD)344
Skewness3.8457601
Sum150943
Variance4663972.9
MonotonicityNot monotonic
2023-12-11T02:16:59.829446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9999 8
 
5.2%
315 2
 
1.3%
20 2
 
1.3%
549 2
 
1.3%
149 2
 
1.3%
119 2
 
1.3%
106 2
 
1.3%
700 2
 
1.3%
999 2
 
1.3%
79 2
 
1.3%
Other values (125) 127
83.0%
ValueCountFrequency (%)
1 1
0.7%
4 1
0.7%
7 1
0.7%
14 1
0.7%
16 1
0.7%
18 1
0.7%
20 2
1.3%
22 1
0.7%
33 1
0.7%
34 1
0.7%
ValueCountFrequency (%)
9999 8
5.2%
1560 1
 
0.7%
1552 1
 
0.7%
1550 1
 
0.7%
1548 1
 
0.7%
1521 1
 
0.7%
1238 1
 
0.7%
1237 1
 
0.7%
1209 1
 
0.7%
1161 1
 
0.7%

Interactions

2023-12-11T02:16:54.938049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:52.149948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:53.082110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:54.018460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:55.139633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:52.373380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:53.306628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:54.244746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:55.348299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:52.640622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:53.554479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:54.499153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:55.562985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:52.861116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:53.795740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:16:54.737196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:17:00.091023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드법정동명행정동코드행정동명시작번지종료번지
법정동코드1.0001.0000.9791.0000.3980.514
법정동명1.0001.0000.9891.0000.3920.493
행정동코드0.9790.9891.0001.0000.4360.527
행정동명1.0001.0001.0001.0000.5070.578
시작번지0.3980.3920.4360.5071.0000.900
종료번지0.5140.4930.5270.5780.9001.000
2023-12-11T02:17:00.417870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명법정동명
행정동명1.0000.972
법정동명0.9721.000
2023-12-11T02:17:00.610145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드행정동코드시작번지종료번지법정동명행정동명
법정동코드1.0000.984-0.146-0.1101.0000.972
행정동코드0.9841.000-0.140-0.1080.9550.979
시작번지-0.146-0.1401.0000.9060.2020.229
종료번지-0.110-0.1080.9061.0000.3540.367
법정동명1.0000.9550.2020.3541.0000.972
행정동명0.9720.9790.2290.3670.9721.000

Missing values

2023-12-11T02:16:55.801540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:16:56.013413image/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

법정동코드법정동명행정동코드행정동명시작번지종료번지
02638010500장림동3340037장림2동1144
12638010300하단동3340032하단1동49239
22638010500장림동3340037장림2동200227
32638010500장림동3340037장림2동228310
42638010500장림동3340037장림2동330399
52638010500장림동3340037장림2동400419
62638010500장림동3340037장림2동420429
72638010500장림동3340037장림2동430490
82638010500장림동3340037장림2동491509
92638010500장림동3340037장림2동510581
법정동코드법정동명행정동코드행정동명시작번지종료번지
1432638010500장림동3340036장림1동190199
1442638010500장림동3340036장림1동311315
1452638010500장림동3340036장림1동316329
1462638010500장림동3340036장림1동640666
1472638010500장림동3340036장림1동667780
1482638010500장림동3340036장림1동781999
1492638010500장림동3340036장림1동10001037
1502638010500장림동3340036장림1동10661135
1512638010500장림동3340036장림1동11361145
1522638010500장림동3340036장림1동11469999