Overview

Dataset statistics

Number of variables6
Number of observations93
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory53.4 B

Variable types

Numeric4
Categorical2

Dataset

Description부산광역시영도구_옥외광고물법정동행정동매칭_20211231
Author부산광역시 영도구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15072282

Alerts

법정동코드 is highly overall correlated with 행정동코드 and 3 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 3 other fieldsHigh correlation
종료번지 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동명 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 법정동코드 and 3 other fieldsHigh correlation
시작번지 has 18 (19.4%) zerosZeros

Reproduction

Analysis started2023-12-10 17:05:36.068191
Analysis finished2023-12-10 17:05:39.625322
Duration3.56 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6200118 × 109
Minimum2.6200101 × 109
Maximum2.6200121 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T02:05:39.749825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6200101 × 109
5-th percentile2.6200106 × 109
Q12.6200118 × 109
median2.6200121 × 109
Q32.6200121 × 109
95-th percentile2.6200121 × 109
Maximum2.6200121 × 109
Range2000
Interquartile range (IQR)300

Descriptive statistics

Standard deviation516.38194
Coefficient of variation (CV)1.9709145 × 10-7
Kurtosis2.7416881
Mean2.6200118 × 109
Median Absolute Deviation (MAD)0
Skewness-1.9731572
Sum2.436611 × 1011
Variance266650.3
MonotonicityNot monotonic
2023-12-11T02:05:39.966151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2620012100 47
50.5%
2620012000 21
22.6%
2620011800 5
 
5.4%
2620010900 3
 
3.2%
2620010100 1
 
1.1%
2620011300 1
 
1.1%
2620011900 1
 
1.1%
2620011700 1
 
1.1%
2620011600 1
 
1.1%
2620011500 1
 
1.1%
Other values (11) 11
 
11.8%
ValueCountFrequency (%)
2620010100 1
 
1.1%
2620010200 1
 
1.1%
2620010300 1
 
1.1%
2620010400 1
 
1.1%
2620010500 1
 
1.1%
2620010600 1
 
1.1%
2620010700 1
 
1.1%
2620010800 1
 
1.1%
2620010900 3
3.2%
2620011000 1
 
1.1%
ValueCountFrequency (%)
2620012100 47
50.5%
2620012000 21
22.6%
2620011900 1
 
1.1%
2620011800 5
 
5.4%
2620011700 1
 
1.1%
2620011600 1
 
1.1%
2620011500 1
 
1.1%
2620011400 1
 
1.1%
2620011300 1
 
1.1%
2620011200 1
 
1.1%

법정동명
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size876.0 B
동삼동
47 
청학동
21 
봉래동4가
5 
영선동2가
 
3
대교동2가
 
1
Other values (16)
16 

Length

Max length5
Median length3
Mean length3.5376344
Min length3

Unique

Unique17 ?
Unique (%)18.3%

Sample

1st row대교동1가
2nd row대교동2가
3rd row대평동1가
4th row대평동2가
5th row남항동1가

Common Values

ValueCountFrequency (%)
동삼동 47
50.5%
청학동 21
22.6%
봉래동4가 5
 
5.4%
영선동2가 3
 
3.2%
대교동2가 1
 
1.1%
대평동1가 1
 
1.1%
대평동2가 1
 
1.1%
남항동1가 1
 
1.1%
남항동2가 1
 
1.1%
남항동3가 1
 
1.1%
Other values (11) 11
 
11.8%

Length

2023-12-11T02:05:40.204324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동삼동 47
50.5%
청학동 21
22.6%
봉래동4가 5
 
5.4%
영선동2가 3
 
3.2%
신선동2가 1
 
1.1%
신선동1가 1
 
1.1%
봉래동5가 1
 
1.1%
봉래동3가 1
 
1.1%
봉래동2가 1
 
1.1%
봉래동1가 1
 
1.1%
Other values (11) 11
 
11.8%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3280040.5
Minimum3280028
Maximum3280078
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T02:05:40.408337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3280028
5-th percentile3280028
Q13280038
median3280040
Q33280041
95-th percentile3280078
Maximum3280078
Range50
Interquartile range (IQR)3

Descriptive statistics

Standard deviation10.727467
Coefficient of variation (CV)3.2705287 × 10-6
Kurtosis7.5066092
Mean3280040.5
Median Absolute Deviation (MAD)2
Skewness2.6385289
Sum3.0504377 × 108
Variance115.07854
MonotonicityNot monotonic
2023-12-11T02:05:40.607982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
3280040 27
29.0%
3280038 14
15.1%
3280042 14
15.1%
3280028 7
 
7.5%
3280034 7
 
7.5%
3280039 7
 
7.5%
3280078 6
 
6.5%
3280041 6
 
6.5%
3280029 3
 
3.2%
3280030 2
 
2.2%
ValueCountFrequency (%)
3280028 7
 
7.5%
3280029 3
 
3.2%
3280030 2
 
2.2%
3280034 7
 
7.5%
3280038 14
15.1%
3280039 7
 
7.5%
3280040 27
29.0%
3280041 6
 
6.5%
3280042 14
15.1%
3280078 6
 
6.5%
ValueCountFrequency (%)
3280078 6
 
6.5%
3280042 14
15.1%
3280041 6
 
6.5%
3280040 27
29.0%
3280039 7
 
7.5%
3280038 14
15.1%
3280034 7
 
7.5%
3280030 2
 
2.2%
3280029 3
 
3.2%
3280028 7
 
7.5%

행정동명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size876.0 B
동삼제1동
27 
청학제1동
14 
동삼제3동
14 
남항동
7 
청학제2동
7 
Other values (6)
24 

Length

Max length5
Median length5
Mean length4.7204301
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동삼제1동 27
29.0%
청학제1동 14
15.1%
동삼제3동 14
15.1%
남항동 7
 
7.5%
청학제2동 7
 
7.5%
신선동 6
 
6.5%
동삼제2동 6
 
6.5%
봉래제2동 4
 
4.3%
영선제1동 3
 
3.2%
봉래제1동 3
 
3.2%

Length

2023-12-11T02:05:40.814559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
동삼제1동 27
29.0%
청학제1동 14
15.1%
동삼제3동 14
15.1%
남항동 7
 
7.5%
청학제2동 7
 
7.5%
신선동 6
 
6.5%
동삼제2동 6
 
6.5%
봉래제2동 4
 
4.3%
영선제1동 3
 
3.2%
봉래제1동 3
 
3.2%

시작번지
Real number (ℝ)

ZEROS 

Distinct69
Distinct (%)74.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean233.82796
Minimum0
Maximum1131
Zeros18
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T02:05:41.044617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q189
median195
Q3244
95-th percentile1067.8
Maximum1131
Range1131
Interquartile range (IQR)155

Descriptive statistics

Standard deviation265.74336
Coefficient of variation (CV)1.136491
Kurtosis5.1804795
Mean233.82796
Median Absolute Deviation (MAD)66
Skewness2.2584716
Sum21746
Variance70619.535
MonotonicityNot monotonic
2023-12-11T02:05:41.278168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18
 
19.4%
1 3
 
3.2%
216 2
 
2.2%
225 2
 
2.2%
185 2
 
2.2%
226 2
 
2.2%
207 2
 
2.2%
82 1
 
1.1%
179 1
 
1.1%
175 1
 
1.1%
Other values (59) 59
63.4%
ValueCountFrequency (%)
0 18
19.4%
1 3
 
3.2%
61 1
 
1.1%
82 1
 
1.1%
89 1
 
1.1%
101 1
 
1.1%
109 1
 
1.1%
110 1
 
1.1%
121 1
 
1.1%
124 1
 
1.1%
ValueCountFrequency (%)
1131 1
1.1%
1124 1
1.1%
1123 1
1.1%
1094 1
1.1%
1090 1
1.1%
1053 1
1.1%
681 1
1.1%
474 1
1.1%
472 1
1.1%
470 1
1.1%

종료번지
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2489.6452
Minimum55
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2023-12-11T02:05:41.533230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55
5-th percentile105.8
Q1190
median230
Q31122
95-th percentile9999
Maximum9999
Range9944
Interquartile range (IQR)932

Descriptive statistics

Standard deviation4084.2197
Coefficient of variation (CV)1.6404827
Kurtosis-0.24182066
Mean2489.6452
Median Absolute Deviation (MAD)97
Skewness1.3216926
Sum231537
Variance16680851
MonotonicityNot monotonic
2023-12-11T02:05:41.781632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9999 21
 
22.6%
225 2
 
2.2%
215 2
 
2.2%
55 1
 
1.1%
183 1
 
1.1%
177 1
 
1.1%
222 1
 
1.1%
1052 1
 
1.1%
151 1
 
1.1%
83 1
 
1.1%
Other values (61) 61
65.6%
ValueCountFrequency (%)
55 1
1.1%
61 1
1.1%
83 1
1.1%
89 1
1.1%
101 1
1.1%
109 1
1.1%
110 1
1.1%
121 1
1.1%
124 1
1.1%
127 1
1.1%
ValueCountFrequency (%)
9999 21
22.6%
1127 1
 
1.1%
1123 1
 
1.1%
1122 1
 
1.1%
1093 1
 
1.1%
1089 1
 
1.1%
1052 1
 
1.1%
680 1
 
1.1%
473 1
 
1.1%
471 1
 
1.1%

Interactions

2023-12-11T02:05:38.718628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:36.454068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:37.136763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:37.729281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:38.872865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:36.624328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:37.303567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:37.859598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:39.027470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:36.788637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:37.471578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:38.001361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:39.173919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:36.965094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:37.607774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T02:05:38.551702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:05:41.948641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드법정동명행정동코드행정동명시작번지종료번지
법정동코드1.0001.0000.8050.9070.0000.690
법정동명1.0001.0000.9330.9420.0000.774
행정동코드0.8050.9331.0001.0000.3390.385
행정동명0.9070.9421.0001.0000.6420.699
시작번지0.0000.0000.3390.6421.0000.817
종료번지0.6900.7740.3850.6990.8171.000
2023-12-11T02:05:42.118987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명법정동명
행정동명1.0000.669
법정동명0.6691.000
2023-12-11T02:05:42.275080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드행정동코드시작번지종료번지법정동명행정동명
법정동코드1.0000.6500.352-0.6510.9310.688
행정동코드0.6501.0000.155-0.5020.7460.960
시작번지0.3520.1551.0000.0900.0000.376
종료번지-0.651-0.5020.0901.0000.4550.518
법정동명0.9310.7460.0000.4551.0000.669
행정동명0.6880.9600.3760.5180.6691.000

Missing values

2023-12-11T02:05:39.370881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:05:39.550586image/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
02620010100대교동1가3280028남항동09999
12620010200대교동2가3280028남항동09999
22620010300대평동1가3280028남항동09999
32620010400대평동2가3280028남항동09999
42620010500남항동1가3280028남항동09999
52620010600남항동2가3280028남항동09999
62620010700남항동3가3280028남항동09999
72620010800영선동1가3280029영선제1동09999
82620010900영선동2가3280029영선제1동1182
92620011000영선동3가3280030영선제2동09999
법정동코드법정동명행정동코드행정동명시작번지종료번지
832620012000청학동3280038청학제1동415416
842620012000청학동3280038청학제1동246247
852620010900영선동2가3280029영선제1동1859999
862620011800봉래동4가3280034봉래제2동207215
872620011800봉래동4가3280034봉래제2동2179999
882620012000청학동3280039청학제2동252254
892620012000청학동3280039청학제2동401411
902620012000청학동3280039청학제2동432466
912620012000청학동3280039청학제2동470471
922620012000청학동3280039청학제2동4749999