Overview

Dataset statistics

Number of variables7
Number of observations1133
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory67.6 KiB
Average record size in memory61.1 B

Variable types

Categorical2
Text1
Numeric4

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 인구천명당특허등록(건), 제1설정등록(건), 공동설정등록(건), 총인구수(명)로 구성되어 있습니다. 김해시 중심의 통계지수로서, 데이터 수집, 가공 등의 어려움으로 김해시 외 지역의 정보는 누락될 수 있습니다.
Author경상남도 김해시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15110112

Alerts

인구천명당특허등록(건) is highly overall correlated with 제1설정등록(건) and 2 other fieldsHigh correlation
제1설정등록(건) is highly overall correlated with 인구천명당특허등록(건) and 2 other fieldsHigh correlation
공동설정등록(건) is highly overall correlated with 인구천명당특허등록(건) and 2 other fieldsHigh correlation
총인구수(명) is highly overall correlated with 인구천명당특허등록(건) and 2 other fieldsHigh correlation

Reproduction

Analysis started2023-12-11 00:15:21.830834
Analysis finished2023-12-11 00:15:24.112700
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2017
227 
2019
227 
2020
227 
2021
227 
2018
225 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2017 227
20.0%
2019 227
20.0%
2020 227
20.0%
2021 227
20.0%
2018 225
19.9%

Length

2023-12-11T09:15:24.172104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:15:24.359212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 227
20.0%
2019 227
20.0%
2020 227
20.0%
2021 227
20.0%
2018 225
19.9%

시도명
Categorical

Distinct16
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
경기도
155 
서울특별시
125 
경상북도
112 
전라남도
110 
강원도
90 
Other values (11)
541 

Length

Max length7
Median length5
Mean length4.1332745
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 155
13.7%
서울특별시 125
11.0%
경상북도 112
9.9%
전라남도 110
9.7%
강원도 90
7.9%
경상남도 90
7.9%
부산광역시 80
7.1%
충청남도 75
6.6%
전라북도 70
6.2%
충청북도 55
 
4.9%
Other values (6) 171
15.1%

Length

2023-12-11T09:15:24.507869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 155
13.7%
서울특별시 125
11.0%
경상북도 112
9.9%
전라남도 110
9.7%
강원도 90
7.9%
경상남도 90
7.9%
부산광역시 80
7.1%
충청남도 75
6.6%
전라북도 70
6.2%
충청북도 55
 
4.9%
Other values (6) 171
15.1%
Distinct205
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size9.0 KiB
2023-12-11T09:15:24.859977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9285084
Min length2

Characters and Unicode

Total characters3318
Distinct characters130
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

Unique0 ?
Unique (%)0.0%

Sample

1st row종로구
2nd row중구
3rd row용산구
4th row성동구
5th row광진구
ValueCountFrequency (%)
동구 30
 
2.6%
중구 30
 
2.6%
서구 25
 
2.2%
남구 21
 
1.9%
북구 20
 
1.8%
고성군 10
 
0.9%
강서구 10
 
0.9%
김제시 5
 
0.4%
진안군 5
 
0.4%
완주군 5
 
0.4%
Other values (195) 972
85.8%
2023-12-11T09:15:25.328749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
422
 
12.7%
390
 
11.8%
366
 
11.0%
110
 
3.3%
100
 
3.0%
90
 
2.7%
89
 
2.7%
85
 
2.6%
80
 
2.4%
65
 
2.0%
Other values (120) 1521
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3318
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
422
 
12.7%
390
 
11.8%
366
 
11.0%
110
 
3.3%
100
 
3.0%
90
 
2.7%
89
 
2.7%
85
 
2.6%
80
 
2.4%
65
 
2.0%
Other values (120) 1521
45.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3318
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
422
 
12.7%
390
 
11.8%
366
 
11.0%
110
 
3.3%
100
 
3.0%
90
 
2.7%
89
 
2.7%
85
 
2.6%
80
 
2.4%
65
 
2.0%
Other values (120) 1521
45.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3318
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
422
 
12.7%
390
 
11.8%
366
 
11.0%
110
 
3.3%
100
 
3.0%
90
 
2.7%
89
 
2.7%
85
 
2.6%
80
 
2.4%
65
 
2.0%
Other values (120) 1521
45.8%

인구천명당특허등록(건)
Real number (ℝ)

HIGH CORRELATION 

Distinct498
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0235569
Minimum0.18
Maximum43.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-11T09:15:25.463553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.18
5-th percentile0.576
Q11.07
median1.89
Q33.34
95-th percentile8.318
Maximum43.69
Range43.51
Interquartile range (IQR)2.27

Descriptive statistics

Standard deviation4.2747486
Coefficient of variation (CV)1.4138145
Kurtosis37.614659
Mean3.0235569
Median Absolute Deviation (MAD)0.97
Skewness5.4466238
Sum3425.69
Variance18.273476
MonotonicityNot monotonic
2023-12-11T09:15:25.611117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.77 11
 
1.0%
0.94 10
 
0.9%
0.78 8
 
0.7%
1.36 8
 
0.7%
1.06 8
 
0.7%
2.13 8
 
0.7%
0.86 8
 
0.7%
2.22 8
 
0.7%
0.66 7
 
0.6%
2.66 7
 
0.6%
Other values (488) 1050
92.7%
ValueCountFrequency (%)
0.18 1
0.1%
0.25 1
0.1%
0.26 1
0.1%
0.27 1
0.1%
0.28 1
0.1%
0.3 1
0.1%
0.32 1
0.1%
0.33 2
0.2%
0.34 2
0.2%
0.35 1
0.1%
ValueCountFrequency (%)
43.69 1
0.1%
42.47 1
0.1%
41.13 1
0.1%
37.95 1
0.1%
33.63 1
0.1%
32.27 1
0.1%
31.9 1
0.1%
31.58 1
0.1%
31.44 1
0.1%
31.33 1
0.1%

제1설정등록(건)
Real number (ℝ)

HIGH CORRELATION 

Distinct544
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean425.71315
Minimum1
Maximum8231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-11T09:15:25.748305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q131
median126
Q3470
95-th percentile1534.2
Maximum8231
Range8230
Interquartile range (IQR)439

Descriptive statistics

Standard deviation896.60775
Coefficient of variation (CV)2.1061312
Kurtosis30.281881
Mean425.71315
Median Absolute Deviation (MAD)111
Skewness4.9866686
Sum482333
Variance803905.46
MonotonicityNot monotonic
2023-12-11T09:15:25.886358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27 17
 
1.5%
22 14
 
1.2%
13 13
 
1.1%
8 13
 
1.1%
20 12
 
1.1%
12 12
 
1.1%
19 12
 
1.1%
18 12
 
1.1%
21 11
 
1.0%
25 11
 
1.0%
Other values (534) 1006
88.8%
ValueCountFrequency (%)
1 1
 
0.1%
2 5
 
0.4%
3 7
0.6%
4 7
0.6%
5 9
0.8%
6 5
 
0.4%
7 11
1.0%
8 13
1.1%
9 10
0.9%
10 8
0.7%
ValueCountFrequency (%)
8231 1
0.1%
7922 1
0.1%
7829 1
0.1%
7502 1
0.1%
7281 1
0.1%
6916 1
0.1%
5830 1
0.1%
5701 1
0.1%
5383 1
0.1%
5321 1
0.1%

공동설정등록(건)
Real number (ℝ)

HIGH CORRELATION 

Distinct596
Distinct (%)52.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean482.44042
Minimum2
Maximum8349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-11T09:15:26.023341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile11
Q138
median162
Q3536
95-th percentile1732
Maximum8349
Range8347
Interquartile range (IQR)498

Descriptive statistics

Standard deviation965.66242
Coefficient of variation (CV)2.00162
Kurtosis26.62046
Mean482.44042
Median Absolute Deviation (MAD)140
Skewness4.6876265
Sum546605
Variance932503.91
MonotonicityNot monotonic
2023-12-11T09:15:26.188700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31 15
 
1.3%
26 15
 
1.3%
15 14
 
1.2%
36 13
 
1.1%
20 12
 
1.1%
23 12
 
1.1%
14 11
 
1.0%
11 11
 
1.0%
33 10
 
0.9%
28 9
 
0.8%
Other values (586) 1011
89.2%
ValueCountFrequency (%)
2 1
 
0.1%
3 5
0.4%
4 5
0.4%
5 5
0.4%
6 5
0.4%
7 8
0.7%
8 4
 
0.4%
9 8
0.7%
10 7
0.6%
11 11
1.0%
ValueCountFrequency (%)
8349 1
0.1%
8268 1
0.1%
8082 1
0.1%
7737 1
0.1%
7620 1
0.1%
7071 1
0.1%
6288 1
0.1%
5944 1
0.1%
5883 1
0.1%
5823 1
0.1%

총인구수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct1132
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean225582.87
Minimum8867
Maximum1202628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.1 KiB
2023-12-11T09:15:26.351730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8867
5-th percentile27191.4
Q152937
median148113
Q3339996
95-th percentile654602.4
Maximum1202628
Range1193761
Interquartile range (IQR)287059

Descriptive statistics

Standard deviation221903.63
Coefficient of variation (CV)0.98369004
Kurtosis3.2392488
Mean225582.87
Median Absolute Deviation (MAD)107589
Skewness1.6740209
Sum2.555854 × 108
Variance4.9241219 × 1010
MonotonicityNot monotonic
2023-12-11T09:15:26.488028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122499 2
 
0.2%
154770 1
 
0.1%
940064 1
 
0.1%
94353 1
 
0.1%
537307 1
 
0.1%
298599 1
 
0.1%
818383 1
 
0.1%
550027 1
 
0.1%
461710 1
 
0.1%
1186078 1
 
0.1%
Other values (1122) 1122
99.0%
ValueCountFrequency (%)
8867 1
0.1%
9077 1
0.1%
9617 1
0.1%
16320 1
0.1%
16692 1
0.1%
16993 1
0.1%
17479 1
0.1%
20342 1
0.1%
20455 1
0.1%
20566 1
0.1%
ValueCountFrequency (%)
1202628 1
0.1%
1201166 1
0.1%
1194465 1
0.1%
1186078 1
0.1%
1183714 1
0.1%
1079353 1
0.1%
1079216 1
0.1%
1077508 1
0.1%
1074176 1
0.1%
1066351 1
0.1%

Interactions

2023-12-11T09:15:23.536560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:15:22.185040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:15:22.532139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:15:23.129999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:15:23.630770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:15:22.281232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/