Overview

Dataset statistics

Number of variables6
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory58.3 B

Variable types

Numeric4
Text1
DateTime1

Dataset

Description1. 2010년 12월 31일 강릉시 읍면동(21개) 1인가구 수
Author강원도 강릉시
URLhttps://www.data.go.kr/data/15100426/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 is highly overall correlated with 2010년High correlation
2010년 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
2015년 is highly overall correlated with 2010년 and 1 other fieldsHigh correlation
2020년 is highly overall correlated with 2010년 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
읍면동 has unique valuesUnique
2010년 has unique valuesUnique
2015년 has unique valuesUnique
2020년 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:50:40.535166
Analysis finished2023-12-12 12:50:42.505960
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T21:50:42.569654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2023-12-12T21:50:42.710577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

읍면동
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-12T21:50:42.910442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.1428571
Min length3

Characters and Unicode

Total characters66
Distinct characters33
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row주문진읍
2nd row성산면
3rd row왕산면
4th row구정면
5th row강동면
ValueCountFrequency (%)
주문진읍 1
 
4.8%
교1동 1
 
4.8%
성덕동 1
 
4.8%
강남동 1
 
4.8%
내곡동 1
 
4.8%
송정동 1
 
4.8%
초당동 1
 
4.8%
포남2동 1
 
4.8%
포남1동 1
 
4.8%
교2동 1
 
4.8%
Other values (11) 11
52.4%
2023-12-12T21:50:43.262593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 14
21.2%
면 7
 
10.6%
포 3
 
4.5%
남 3
 
4.5%
강 2
 
3.0%
1 2
 
3.0%
2 2
 
3.0%
곡 2
 
3.0%
천 2
 
3.0%
옥 2
 
3.0%
Other values (23) 27
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62
93.9%
Decimal Number 4
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 14
22.6%
면 7
 
11.3%
포 3
 
4.8%
남 3
 
4.8%
강 2
 
3.2%
곡 2
 
3.2%
천 2
 
3.2%
옥 2
 
3.2%
교 2
 
3.2%
정 2
 
3.2%
Other values (21) 23
37.1%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62
93.9%
Common 4
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 14
22.6%
면 7
 
11.3%
포 3
 
4.8%
남 3
 
4.8%
강 2
 
3.2%
곡 2
 
3.2%
천 2
 
3.2%
옥 2
 
3.2%
교 2
 
3.2%
정 2
 
3.2%
Other values (21) 23
37.1%
Common
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62
93.9%
ASCII 4
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 14
22.6%
면 7
 
11.3%
포 3
 
4.8%
남 3
 
4.8%
강 2
 
3.2%
곡 2
 
3.2%
천 2
 
3.2%
옥 2
 
3.2%
교 2
 
3.2%
정 2
 
3.2%
Other values (21) 23
37.1%
ASCII
ValueCountFrequency (%)
1 2
50.0%
2 2
50.0%

2010년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3542.381
Minimum409
Maximum11083
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T21:50:43.392721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum409
5-th percentile553
Q11099
median2417
Q34330
95-th percentile10939
Maximum11083
Range10674
Interquartile range (IQR)3231

Descriptive statistics

Standard deviation3264.5444
Coefficient of variation (CV)0.92156785
Kurtosis0.8684032
Mean3542.381
Median Absolute Deviation (MAD)1588
Skewness1.3008146
Sum74390
Variance10657250
MonotonicityNot monotonic
2023-12-12T21:50:43.521254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
3857 1
 
4.8%
565 1
 
4.8%
2173 1
 
4.8%
11083 1
 
4.8%
8421 1
 
4.8%
4330 1
 
4.8%
2833 1
 
4.8%
2417 1
 
4.8%
6712 1
 
4.8%
5218 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
409 1
4.8%
553 1
4.8%
565 1
4.8%
829 1
4.8%
837 1
4.8%
1099 1
4.8%
1269 1
4.8%
1314 1
4.8%
2173 1
4.8%
2202 1
4.8%
ValueCountFrequency (%)
11083 1
4.8%
10939 1
4.8%
8421 1
4.8%
6712 1
4.8%
5218 1
4.8%
4330 1
4.8%
4067 1
4.8%
3857 1
4.8%
3263 1
4.8%
2833 1
4.8%

2015년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1696.7619
Minimum412
Maximum4145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T21:50:43.656482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum412
5-th percentile665
Q1890
median1340
Q32332
95-th percentile3317
Maximum4145
Range3733
Interquartile range (IQR)1442

Descriptive statistics

Standard deviation1034.4403
Coefficient of variation (CV)0.60965556
Kurtosis-0.025709811
Mean1696.7619
Median Absolute Deviation (MAD)557
Skewness0.92967958
Sum35632
Variance1070066.8
MonotonicityNot monotonic
2023-12-12T21:50:44.101702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
4145 1
 
4.8%
673 1
 
4.8%
1340 1
 
4.8%
3317 1
 
4.8%
2800 1
 
4.8%
2708 1
 
4.8%
783 1
 
4.8%
865 1
 
4.8%
2332 1
 
4.8%
2094 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
412 1
4.8%
665 1
4.8%
673 1
4.8%
783 1
4.8%
865 1
4.8%
890 1
4.8%
944 1
4.8%
1110 1
4.8%
1198 1
4.8%
1290 1
4.8%
ValueCountFrequency (%)
4145 1
4.8%
3317 1
4.8%
3288 1
4.8%
2800 1
4.8%
2708 1
4.8%
2332 1
4.8%
2094 1
4.8%
1703 1
4.8%
1588 1
4.8%
1487 1
4.8%

2020년
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2037.2857
Minimum446
Maximum4664
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-12T21:50:44.251909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum446
5-th percentile711
Q11072
median1696
Q32928
95-th percentile4255
Maximum4664
Range4218
Interquartile range (IQR)1856

Descriptive statistics

Standard deviation1260.8296
Coefficient of variation (CV)0.61887717
Kurtosis-0.62057837
Mean2037.2857
Median Absolute Deviation (MAD)738
Skewness0.73736293
Sum42783
Variance1589691.3
MonotonicityNot monotonic
2023-12-12T21:50:44.425445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
4664 1
 
4.8%
711 1
 
4.8%
2026 1
 
4.8%
3991 1
 
4.8%
3138 1
 
4.8%
3175 1
 
4.8%
1113 1
 
4.8%
1022 1
 
4.8%
2928 1
 
4.8%
2423 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
446 1
4.8%
711 1
4.8%
787 1
4.8%
958 1
4.8%
1022 1
4.8%
1072 1
4.8%
1113 1
4.8%
1141 1
4.8%
1158 1
4.8%
1474 1
4.8%
ValueCountFrequency (%)
4664 1
4.8%
4255 1
4.8%
3991 1
4.8%
3175 1
4.8%
3138 1
4.8%
2928 1
4.8%
2904 1
4.8%
2423 1
4.8%
2026 1
4.8%
1701 1
4.8%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2022-05-23 00:00:00
Maximum2022-05-23 00:00:00
2023-12-12T21:50:44.543383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:44.689296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T21:50:41.987389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:40.754482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.214263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.600149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:42.083513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:40.878571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.338049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.703252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:42.166214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:40.990199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.441540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.789029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:42.258080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.106053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.527441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:50:41.891752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:50:44.766959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동2010년2015년2020년
연번1.0001.0000.0000.0000.000
읍면동1.0001.0001.0001.0001.000
2010년0.0001.0001.0000.8670.703
2015년0.0001.0000.8671.0000.958
2020년0.0001.0000.7030.9581.000
2023-12-12T21:50:44.873304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번2010년2015년2020년
연번1.0000.6860.4120.456
2010년0.6861.0000.8600.843
2015년0.4120.8601.0000.973
2020년0.4560.8430.9731.000

Missing values

2023-12-12T21:50:42.349258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:50:42.457814image/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

연번읍면동2010년2015년2020년기준일자
01주문진읍3857414546642022-05-23
12성산면5656737112022-05-23
23왕산면4094124462022-05-23
34구정면5536657872022-05-23
45강동면1099119811582022-05-23
56옥계면8298909582022-05-23
67사천면83794410722022-05-23
78연곡면1269129014742022-05-23
89홍제동1314148729042022-05-23
910중앙동3263170317012022-05-23
연번읍면동2010년2015년2020년기준일자
1112교1동10939328842552022-05-23
1213교2동4067158816962022-05-23
1314포남1동5218209424232022-05-23
1415포남2동6712233229282022-05-23
1516초당동241786510222022-05-23
1617송정동283378311132022-05-23
1718내곡동4330270831752022-05-23
1819강남동8421280031382022-05-23
1920성덕동11083331739912022-05-23
2021경포동2173134020262022-05-23