Overview

Dataset statistics

Number of variables6
Number of observations684
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.9 KiB
Average record size in memory52.2 B

Variable types

Categorical2
Text1
Numeric3

Dataset

Description김해시에서 통계기반 도시현황 파악을 위해 개발한 통계지수 중 하나로서, 통계연도, 시도명, 시군구명, 인구 천명당 종사자수(명), 종사자수(명), 주민등록인구(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=15110109

Alerts

종사자수(명) is highly overall correlated with 주민등록인구(명)High correlation
주민등록인구(명) is highly overall correlated with 종사자수(명)High correlation
주민등록인구(명) has unique valuesUnique

Reproduction

Analysis started2023-12-10 23:30:10.530006
Analysis finished2023-12-10 23:30:11.777282
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

통계연도
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2017
228 
2018
228 
2019
228 

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 228
33.3%
2018 228
33.3%
2019 228
33.3%

Length

2023-12-11T08:30:11.831642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T08:30:11.925628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 228
33.3%
2018 228
33.3%
2019 228
33.3%

시도명
Categorical

Distinct16
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
경기도
93 
서울특별시
75 
경상북도
69 
전라남도
66 
강원도
54 
Other values (11)
327 

Length

Max length7
Median length5
Mean length4.1359649
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 93
13.6%
서울특별시 75
11.0%
경상북도 69
10.1%
전라남도 66
9.6%
강원도 54
7.9%
경상남도 54
7.9%
부산광역시 48
7.0%
충청남도 45
6.6%
전라북도 42
 
6.1%
충청북도 33
 
4.8%
Other values (6) 105
15.4%

Length

2023-12-11T08:30:12.039330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 93
13.6%
서울특별시 75
11.0%
경상북도 69
10.1%
전라남도 66
9.6%
강원도 54
7.9%
경상남도 54
7.9%
부산광역시 48
7.0%
충청남도 45
6.6%
전라북도 42
 
6.1%
충청북도 33
 
4.8%
Other values (6) 105
15.4%
Distinct206
Distinct (%)30.1%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2023-12-11T08:30:12.303618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9312865
Min length2

Characters and Unicode

Total characters2005
Distinct characters132
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 18
 
2.6%
중구 18
 
2.6%
서구 15
 
2.2%
남구 13
 
1.9%
북구 12
 
1.8%
고성군 6
 
0.9%
강서구 6
 
0.9%
완주군 3
 
0.4%
무주군 3
 
0.4%
진안군 3
 
0.4%
Other values (196) 587
85.8%
2023-12-11T08:30:12.706781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
255
 
12.7%
234
 
11.7%
222
 
11.1%
66
 
3.3%
60
 
3.0%
54
 
2.7%
54
 
2.7%
51
 
2.5%
48
 
2.4%
39
 
1.9%
Other values (122) 922
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2005
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
255
 
12.7%
234
 
11.7%
222
 
11.1%
66
 
3.3%
60
 
3.0%
54
 
2.7%
54
 
2.7%
51
 
2.5%
48
 
2.4%
39
 
1.9%
Other values (122) 922
46.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2005
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
255
 
12.7%
234
 
11.7%
222
 
11.1%
66
 
3.3%
60
 
3.0%
54
 
2.7%
54
 
2.7%
51
 
2.5%
48
 
2.4%
39
 
1.9%
Other values (122) 922
46.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2005
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
255
 
12.7%
234
 
11.7%
222
 
11.1%
66
 
3.3%
60
 
3.0%
54
 
2.7%
54
 
2.7%
51
 
2.5%
48
 
2.4%
39
 
1.9%
Other values (122) 922
46.0%
Distinct627
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean438.17997
Minimum182.5
Maximum3111.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-11T08:30:13.079499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182.5
5-th percentile254.69
Q1330.775
median387.1
Q3455.225
95-th percentile756.425
Maximum3111.4
Range2928.9
Interquartile range (IQR)124.45

Descriptive statistics

Standard deviation260.05478
Coefficient of variation (CV)0.59348851
Kurtosis51.176149
Mean438.17997
Median Absolute Deviation (MAD)59.25
Skewness6.0657657
Sum299715.1
Variance67628.487
MonotonicityNot monotonic
2023-12-11T08:30:13.212915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
415.3 3
 
0.4%
388.6 3
 
0.4%
294.9 3
 
0.4%
391.5 2
 
0.3%
442.2 2
 
0.3%
381.0 2
 
0.3%
417.2 2
 
0.3%
430.9 2
 
0.3%
359.7 2
 
0.3%
380.0 2
 
0.3%
Other values (617) 661
96.6%
ValueCountFrequency (%)
182.5 1
0.1%
186.4 1
0.1%
195.1 1
0.1%
196.1 1
0.1%
203.2 1
0.1%
204.9 1
0.1%
209.0 1
0.1%
212.6 1
0.1%
218.3 1
0.1%
218.8 1
0.1%
ValueCountFrequency (%)
3111.4 1
0.1%
3106.2 1
0.1%
3075.7 1
0.1%
1736.1 1
0.1%
1731.4 1
0.1%
1721.5 1
0.1%
1614.4 1
0.1%
1593.3 1
0.1%
1575.4 1
0.1%
1281.9 1
0.1%

종사자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct682
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96848.143
Minimum4352
Maximum698840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-11T08:30:13.333554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4352
5-th percentile9559.9
Q120306.75
median66571
Q3125200
95-th percentile321373.65
Maximum698840
Range694488
Interquartile range (IQR)104893.25

Descriptive statistics

Standard deviation104392.79
Coefficient of variation (CV)1.0779019
Kurtosis6.0866056
Mean96848.143
Median Absolute Deviation (MAD)48069
Skewness2.1511204
Sum66244130
Variance1.0897856 × 1010
MonotonicityNot monotonic
2023-12-11T08:30:13.477859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
108991 2
 
0.3%
20579 2
 
0.3%
268702 1
 
0.1%
178243 1
 
0.1%
20391 1
 
0.1%
12868 1
 
0.1%
206438 1
 
0.1%
70504 1
 
0.1%
260446 1
 
0.1%
392568 1
 
0.1%
Other values (672) 672
98.2%
ValueCountFrequency (%)
4352 1
0.1%
4377 1
0.1%
4473 1
0.1%
4491 1
0.1%
4573 1
0.1%
4879 1
0.1%
6332 1
0.1%
6541 1
0.1%
6717 1
0.1%
6765 1
0.1%
ValueCountFrequency (%)
698840 1
0.1%
694136 1
0.1%
679047 1
0.1%
492031 1
0.1%
467627 1
0.1%
462083 1
0.1%
460383 1
0.1%
452114 1
0.1%
450741 1
0.1%
449870 1
0.1%

주민등록인구(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct684
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean225905.94
Minimum9617
Maximum1202628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.1 KiB
2023-12-11T08:30:13.616431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9617
5-th percentile27273.05
Q153289.75
median150588.5
Q3344094
95-th percentile651065.05
Maximum1202628
Range1193011
Interquartile range (IQR)290804.25

Descriptive statistics

Standard deviation220994.29
Coefficient of variation (CV)0.97825799
Kurtosis3.220078
Mean225905.94
Median Absolute Deviation (MAD)108500.5
Skewness1.6595777
Sum1.5451966 × 108
Variance4.8838477 × 1010
MonotonicityNot monotonic
2023-12-11T08:30:13.750070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
154770 1
 
0.1%
351350 1
 
0.1%
62455 1
 
0.1%
45916 1
 
0.1%
485946 1
 
0.1%
181245 1
 
0.1%
151290 1
 
0.1%
126171 1
 
0.1%
228670 1
 
0.1%
300889 1
 
0.1%
Other values (674) 674
98.5%
ValueCountFrequency (%)
9617 1
0.1%
9832 1
0.1%
9975 1
0.1%
16993 1
0.1%
17356 1
0.1%
17479 1
0.1%
20566 1
0.1%
21036 1
0.1%
21573 1
0.1%
22441 1
0.1%
ValueCountFrequency (%)
1202628 1
0.1%
1201166 1
0.1%
1194465 1
0.1%
1066351 1
0.1%
1059609 1
0.1%
1057032 1
0.1%
1053601 1
0.1%
1044740 1
0.1%
1044189 1
0.1%
1041983 1
0.1%

Interactions

2023-12-11T08:30:11.337474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:30:10.789839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:30:11.070792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T08:30:11.432531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/