Overview

Dataset statistics

Number of variables8
Number of observations103
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory68.3 B

Variable types

Categorical4
Text1
Numeric3

Dataset

Description함양군 관내 행정리별 인구현황 자료로 구성항목은 인구수, 세대수, 남자수, 여자수로 구성되어 있으며, 해당자료는 링크자료로 수정된 내용이 주기적으로 반영되는 자료임
Author경상남도 함양군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3064783

Alerts

시도명 has constant value ""Constant
시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
합계 is highly overall correlated with 남자수 and 1 other fieldsHigh correlation
남자수 is highly overall correlated with 합계 and 1 other fieldsHigh correlation
여자수 is highly overall correlated with 합계 and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-03-23 07:21:57.923643
Analysis finished2024-03-23 07:22:03.149603
Duration5.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
경상남도
103 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 103
100.0%

Length

2024-03-23T07:22:03.377866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:22:03.769617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 103
100.0%

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
함양군
103 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함양군 103
100.0%

Length

2024-03-23T07:22:04.398791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:22:04.712437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
함양군 103
100.0%

읍면명
Categorical

Distinct11
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size956.0 B
함양읍
15 
안의면
15 
휴천면
11 
지곡면
10 
마천면
9 
Other values (6)
43 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함양읍 15
14.6%
안의면 15
14.6%
휴천면 11
10.7%
지곡면 10
9.7%
마천면 9
8.7%
유림면 9
8.7%
수동면 8
7.8%
백전면 8
7.8%
병곡면 7
6.8%
서상면 6
 
5.8%

Length

2024-03-23T07:22:05.159960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
함양읍 15
14.6%
안의면 15
14.6%
휴천면 11
10.7%
지곡면 10
9.7%
마천면 9
8.7%
유림면 9
8.7%
수동면 8
7.8%
백전면 8
7.8%
병곡면 7
6.8%
서상면 6
 
5.8%

법정리명
Text

Distinct102
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-23T07:22:06.032282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters309
Distinct characters90
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

Unique101 ?
Unique (%)98.1%

Sample

1st row운림리
2nd row용평리
3rd row대덕리
4th row교산리
5th row신천리
ValueCountFrequency (%)
도천리 2
 
1.9%
석천리 1
 
1.0%
상원리 1
 
1.0%
하원리 1
 
1.0%
신안리 1
 
1.0%
대대리 1
 
1.0%
귀곡리 1
 
1.0%
봉산리 1
 
1.0%
초동리 1
 
1.0%
도림리 1
 
1.0%
Other values (92) 92
89.3%
2024-03-23T07:22:07.042904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 103
33.3%
산 13
 
4.2%
평 12
 
3.9%
천 8
 
2.6%
곡 7
 
2.3%
대 7
 
2.3%
백 7
 
2.3%
도 5
 
1.6%
운 5
 
1.6%
원 5
 
1.6%
Other values (80) 137
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 309
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 103
33.3%
산 13
 
4.2%
평 12
 
3.9%
천 8
 
2.6%
곡 7
 
2.3%
대 7
 
2.3%
백 7
 
2.3%
도 5
 
1.6%
운 5
 
1.6%
원 5
 
1.6%
Other values (80) 137
44.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 309
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 103
33.3%
산 13
 
4.2%
평 12
 
3.9%
천 8
 
2.6%
곡 7
 
2.3%
대 7
 
2.3%
백 7
 
2.3%
도 5
 
1.6%
운 5
 
1.6%
원 5
 
1.6%
Other values (80) 137
44.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 309
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 103
33.3%
산 13
 
4.2%
평 12
 
3.9%
천 8
 
2.6%
곡 7
 
2.3%
대 7
 
2.3%
백 7
 
2.3%
도 5
 
1.6%
운 5
 
1.6%
원 5
 
1.6%
Other values (80) 137
44.3%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct90
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean358.04854
Minimum66
Maximum8913
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:22:07.571991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile91.2
Q1165
median215
Q3280
95-th percentile821.1
Maximum8913
Range8847
Interquartile range (IQR)115

Descriptive statistics

Standard deviation895.29746
Coefficient of variation (CV)2.5004918
Kurtosis83.891612
Mean358.04854
Median Absolute Deviation (MAD)53
Skewness8.849894
Sum36879
Variance801557.54
MonotonicityNot monotonic
2024-03-23T07:22:08.183965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
206 3
 
2.9%
138 2
 
1.9%
145 2
 
1.9%
175 2
 
1.9%
236 2
 
1.9%
229 2
 
1.9%
254 2
 
1.9%
244 2
 
1.9%
239 2
 
1.9%
328 2
 
1.9%
Other values (80) 82
79.6%
ValueCountFrequency (%)
66 1
1.0%
67 1
1.0%
79 1
1.0%
89 1
1.0%
90 1
1.0%
91 1
1.0%
93 1
1.0%
94 1
1.0%
95 1
1.0%
102 1
1.0%
ValueCountFrequency (%)
8913 1
1.0%
2396 1
1.0%
1263 1
1.0%
924 1
1.0%
865 1
1.0%
850 1
1.0%
561 1
1.0%
554 1
1.0%
527 1
1.0%
481 1
1.0%

남자수
Real number (ℝ)

HIGH CORRELATION 

Distinct78
Distinct (%)75.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean173.68932
Minimum32
Maximum4289
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:22:08.703480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile46.1
Q175
median105
Q3135
95-th percentile408.9
Maximum4289
Range4257
Interquartile range (IQR)60

Descriptive statistics

Standard deviation431.17966
Coefficient of variation (CV)2.4824765
Kurtosis83.490521
Mean173.68932
Median Absolute Deviation (MAD)30
Skewness8.8214042
Sum17890
Variance185915.9
MonotonicityNot monotonic
2024-03-23T07:22:09.484779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
112 6
 
5.8%
88 3
 
2.9%
70 3
 
2.9%
75 3
 
2.9%
62 3
 
2.9%
132 2
 
1.9%
160 2
 
1.9%
118 2
 
1.9%
73 2
 
1.9%
44 2
 
1.9%
Other values (68) 75
72.8%
ValueCountFrequency (%)
32 1
1.0%
34 1
1.0%
40 1
1.0%
44 2
1.9%
46 1
1.0%
47 1
1.0%
48 1
1.0%
53 1
1.0%
54 1
1.0%
59 2
1.9%
ValueCountFrequency (%)
4289 1
1.0%
1155 1
1.0%
617 1
1.0%
463 1
1.0%
447 1
1.0%
423 1
1.0%
282 1
1.0%
254 1
1.0%
253 1
1.0%
234 1
1.0%

여자수
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)81.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184.35922
Minimum32
Maximum4624
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:22:09.986649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile45.2
Q179.5
median109
Q3146
95-th percentile406.9
Maximum4624
Range4592
Interquartile range (IQR)66.5

Descriptive statistics

Standard deviation464.23903
Coefficient of variation (CV)2.5181221
Kurtosis84.17465
Mean184.35922
Median Absolute Deviation (MAD)32
Skewness8.8695891
Sum18989
Variance215517.88
MonotonicityNot monotonic
2024-03-23T07:22:10.778966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
47 4
 
3.9%
100 3
 
2.9%
106 3
 
2.9%
124 2
 
1.9%
123 2
 
1.9%
72 2
 
1.9%
121 2
 
1.9%
101 2
 
1.9%
205 2
 
1.9%
110 2
 
1.9%
Other values (74) 79
76.7%
ValueCountFrequency (%)
32 1
 
1.0%
35 1
 
1.0%
39 1
 
1.0%
41 1
 
1.0%
42 1
 
1.0%
45 1
 
1.0%
47 4
3.9%
49 1
 
1.0%
53 1
 
1.0%
57 1
 
1.0%
ValueCountFrequency (%)
4624 1
1.0%
1241 1
1.0%
646 1
1.0%
461 1
1.0%
427 1
1.0%
418 1
1.0%
307 1
1.0%
274 1
1.0%
272 1
1.0%
247 1
1.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size956.0 B
2024-03-11
103 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-11
2nd row2024-03-11
3rd row2024-03-11
4th row2024-03-11
5th row2024-03-11

Common Values

ValueCountFrequency (%)
2024-03-11 103
100.0%

Length

2024-03-23T07:22:11.321077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:22:11.894909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-11 103
100.0%

Interactions

2024-03-23T07:22:01.282194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:21:58.754254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:21:59.867520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:22:01.819424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:21:59.221624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:22:00.510780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:22:02.181887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:21:59.516137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:22:00.886821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:22:12.064370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면명합계남자수여자수
읍면명1.0000.0000.0000.000
합계0.0001.0000.9961.000
남자수0.0000.9961.0000.996
여자수0.0001.0000.9961.000
2024-03-23T07:22:12.357572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계남자수여자수읍면명
합계1.0000.9870.9880.000
남자수0.9871.0000.9550.000
여자수0.9880.9551.0000.000
읍면명0.0000.0000.0001.000

Missing values

2024-03-23T07:22:02.503251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:22:02.998799image/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

시도명시군명읍면명법정리명합계남자수여자수데이터기준일자
0경상남도함양군함양읍운림리12636176462024-03-11
1경상남도함양군함양읍용평리2396115512412024-03-11
2경상남도함양군함양읍대덕리200911092024-03-11
3경상남도함양군함양읍교산리8913428946242024-03-11
4경상남도함양군함양읍신천리3281531752024-03-11
5경상남도함양군함양읍신관리3771861912024-03-11
6경상남도함양군함양읍백천리5542822722024-03-11
7경상남도함양군함양읍백연리8654474182024-03-11
8경상남도함양군함양읍이은리9244634612024-03-11
9경상남도함양군함양읍난평리2681381302024-03-11
시도명시군명읍면명법정리명합계남자수여자수데이터기준일자
93경상남도함양군백전면구산리8944452024-03-11
94경상남도함양군백전면오천리15581742024-03-11
95경상남도함양군백전면경백리2061021042024-03-11
96경상남도함양군병곡면옥계리206911152024-03-11
97경상남도함양군병곡면연덕리19194972024-03-11
98경상남도함양군병곡면송평리13264682024-03-11
99경상남도함양군병곡면도천리2441271172024-03-11
100경상남도함양군병곡면월암리16884842024-03-11
101경상남도함양군병곡면광평리2151121032024-03-11
102경상남도함양군병곡면원산리10962472024-03-11