Overview

Dataset statistics

Number of variables6
Number of observations450
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory23.4 KiB
Average record size in memory53.3 B

Variable types

Categorical1
Numeric5

Dataset

Description시군별 세대인구(세대수, 남녀 인구수) 통계
Author강원도
URLhttps://www.data.go.kr/data/15050502/fileData.do

Alerts

세대수 (세대) is highly overall correlated with 인구 (명) and 3 other fieldsHigh correlation
인구 (명) is highly overall correlated with 세대수 (세대) and 3 other fieldsHigh correlation
인구 남 (명) is highly overall correlated with 세대수 (세대) and 3 other fieldsHigh correlation
인구 여 (명) is highly overall correlated with 세대수 (세대) and 3 other fieldsHigh correlation
시군명 is highly overall correlated with 세대수 (세대) and 3 other fieldsHigh correlation
인구 (명) has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:36:32.141097
Analysis finished2023-12-12 07:36:35.134351
Duration2.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size3.6 KiB
춘천시
 
25
원주시
 
25
강릉시
 
25
동해시
 
25
태백시
 
25
Other values (13)
325 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row춘천시
2nd row원주시
3rd row강릉시
4th row동해시
5th row태백시

Common Values

ValueCountFrequency (%)
춘천시 25
 
5.6%
원주시 25
 
5.6%
강릉시 25
 
5.6%
동해시 25
 
5.6%
태백시 25
 
5.6%
속초시 25
 
5.6%
삼척시 25
 
5.6%
홍천군 25
 
5.6%
횡성군 25
 
5.6%
영월군 25
 
5.6%
Other values (8) 200
44.4%

Length

2023-12-12T16:36:35.211775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
춘천시 25
 
5.6%
원주시 25
 
5.6%
고성군 25
 
5.6%
인제군 25
 
5.6%
양구군 25
 
5.6%
화천군 25
 
5.6%
철원군 25
 
5.6%
정선군 25
 
5.6%
평창군 25
 
5.6%
영월군 25
 
5.6%
Other values (8) 200
44.4%

해당연도
Real number (ℝ)

Distinct25
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007
Minimum1995
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T16:36:35.326655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1995
5-th percentile1996
Q12001
median2007
Q32013
95-th percentile2018
Maximum2019
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.2191283
Coefficient of variation (CV)0.0035969747
Kurtosis-1.2038772
Mean2007
Median Absolute Deviation (MAD)6
Skewness0
Sum903150
Variance52.115813
MonotonicityIncreasing
2023-12-12T16:36:35.473277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1995 18
 
4.0%
1996 18
 
4.0%
2019 18
 
4.0%
2018 18
 
4.0%
2017 18
 
4.0%
2016 18
 
4.0%
2015 18
 
4.0%
2014 18
 
4.0%
2013 18
 
4.0%
2012 18
 
4.0%
Other values (15) 270
60.0%
ValueCountFrequency (%)
1995 18
4.0%
1996 18
4.0%
1997 18
4.0%
1998 18
4.0%
1999 18
4.0%
2000 18
4.0%
2001 18
4.0%
2002 18
4.0%
2003 18
4.0%
2004 18
4.0%
ValueCountFrequency (%)
2019 18
4.0%
2018 18
4.0%
2017 18
4.0%
2016 18
4.0%
2015 18
4.0%
2014 18
4.0%
2013 18
4.0%
2012 18
4.0%
2011 18
4.0%
2010 18
4.0%

세대수 (세대)
Real number (ℝ)

HIGH CORRELATION 

Distinct447
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33102.24
Minimum7272
Maximum154583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T16:36:35.630651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7272
5-th percentile9156.55
Q114487
median19659.5
Q334220.25
95-th percentile109175.65
Maximum154583
Range147311
Interquartile range (IQR)19733.25

Descriptive statistics

Standard deviation31525.271
Coefficient of variation (CV)0.95236066
Kurtosis2.526852
Mean33102.24
Median Absolute Deviation (MAD)7748.5
Skewness1.8714789
Sum14896008
Variance9.9384272 × 108
MonotonicityNot monotonic
2023-12-12T16:36:35.792325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17529 2
 
0.4%
15377 2
 
0.4%
18968 2
 
0.4%
18668 1
 
0.2%
91332 1
 
0.2%
130617 1
 
0.2%
110596 1
 
0.2%
12783 1
 
0.2%
14248 1
 
0.2%
13935 1
 
0.2%
Other values (437) 437
97.1%
ValueCountFrequency (%)
7272 1
0.2%
7415 1
0.2%
7483 1
0.2%
7794 1
0.2%
7908 1
0.2%
7911 1
0.2%
7984 1
0.2%
8004 1
0.2%
8132 1
0.2%
8192 1
0.2%
ValueCountFrequency (%)
154583 1
0.2%
149166 1
0.2%
145521 1
0.2%
142136 1
0.2%
138380 1
0.2%
134487 1
0.2%
132207 1
0.2%
130617 1
0.2%
128436 1
0.2%
123983 1
0.2%

인구 (명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct450
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85263.391
Minimum21269
Maximum349215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T16:36:35.959158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21269
5-th percentile23942.9
Q133813.25
median48759.5
Q385727
95-th percentile276394.9
Maximum349215
Range327946
Interquartile range (IQR)51913.75

Descriptive statistics

Standard deviation82421.884
Coefficient of variation (CV)0.96667378
Kurtosis1.5738201
Mean85263.391
Median Absolute Deviation (MAD)21067
Skewness1.7126051
Sum38368526
Variance6.793367 × 109
MonotonicityNot monotonic
2023-12-12T16:36:36.113780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
232682 1
 
0.2%
23594 1
 
0.2%
217741 1
 
0.2%
323885 1
 
0.2%
273364 1
 
0.2%
27942 1
 
0.2%
30057 1
 
0.2%
31970 1
 
0.2%
22285 1
 
0.2%
24945 1
 
0.2%
Other values (440) 440
97.8%
ValueCountFrequency (%)
21269 1
0.2%
21303 1
0.2%
21323 1
0.2%
21401 1
0.2%
21480 1
0.2%
21692 1
0.2%
21843 1
0.2%
21995 1
0.2%
22285 1
0.2%
22527 1
0.2%
ValueCountFrequency (%)
349215 1
0.2%
344070 1
0.2%
341337 1
0.2%
337979 1
0.2%
332995 1
0.2%
327292 1
0.2%
324837 1
0.2%
323885 1
0.2%
320536 1
0.2%
314678 1
0.2%

인구 남 (명)
Real number (ℝ)

HIGH CORRELATION 

Distinct445
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42882.42
Minimum10991
Maximum173425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T16:36:36.253185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10991
5-th percentile12455.95
Q117533.25
median24868.5
Q342675.5
95-th percentile136975.1
Maximum173425
Range162434
Interquartile range (IQR)25142.25

Descriptive statistics

Standard deviation40706.927
Coefficient of variation (CV)0.94926841
Kurtosis1.5841363
Mean42882.42
Median Absolute Deviation (MAD)10655.5
Skewness1.7134906
Sum19297089
Variance1.6570539 × 109
MonotonicityNot monotonic
2023-12-12T16:36:36.407812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22612 2
 
0.4%
15242 2
 
0.4%
12735 2
 
0.4%
41260 2
 
0.4%
13078 2
 
0.4%
22866 1
 
0.2%
20478 1
 
0.2%
161117 1
 
0.2%
134874 1
 
0.2%
14282 1
 
0.2%
Other values (435) 435
96.7%
ValueCountFrequency (%)
10991 1
0.2%
11089 1
0.2%
11135 1
0.2%
11147 1
0.2%
11159 1
0.2%
11197 1
0.2%
11344 1
0.2%
11401 1
0.2%
11481 1
0.2%
11758 1
0.2%
ValueCountFrequency (%)
173425 1
0.2%
171048 1
0.2%
169742 1
0.2%
167854 1
0.2%
165547 1
0.2%
162734 1
0.2%
161588 1
0.2%
161117 1
0.2%
159522 1
0.2%
156741 1
0.2%

인구 여 (명)
Real number (ℝ)

HIGH CORRELATION 

Distinct448
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42380.971
Minimum10156
Maximum175790
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.1 KiB
2023-12-12T16:36:36.853820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10156
5-th percentile11210.6
Q116596
median23735
Q342978.5
95-th percentile139460.8
Maximum175790
Range165634
Interquartile range (IQR)26382.5

Descriptive statistics

Standard deviation41718.981
Coefficient of variation (CV)0.98438001
Kurtosis1.5641664
Mean42380.971
Median Absolute Deviation (MAD)10304
Skewness1.711542
Sum19071437
Variance1.7404734 × 109
MonotonicityNot monotonic
2023-12-12T16:36:36.998148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11153 2
 
0.4%
21240 2
 
0.4%
117109 1
 
0.2%
21243 1
 
0.2%
109423 1
 
0.2%
162768 1
 
0.2%
138490 1
 
0.2%
13660 1
 
0.2%
14422 1
 
0.2%
14956 1
 
0.2%
Other values (438) 438
97.3%
ValueCountFrequency (%)
10156 1
0.2%
10188 1
0.2%
10242 1
0.2%
10278 1
0.2%
10391 1
0.2%
10442 1
0.2%
10495 1
0.2%
10527 1
0.2%
10651 1
0.2%
10682 1
0.2%
ValueCountFrequency (%)
175790 1
0.2%
173022 1
0.2%
171595 1
0.2%
170125 1
0.2%
167448 1
0.2%
164558 1
0.2%
163249 1
0.2%
162768 1
0.2%
161014 1
0.2%
157937 1
0.2%

Interactions

2023-12-12T16:36:34.392293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.342244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.805998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.271261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.818673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.492736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.430186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.894228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.369017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.971618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.611831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.533149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.984019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.465962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.086266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.708020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.624755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.070225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.556723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.186236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.807184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:32.710883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.168994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:33.722825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:36:34.296985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T16:36:37.090833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명해당연도세대수 (세대)인구 (명)인구 남 (명)인구 여 (명)
시군명1.0000.0000.9060.9180.9160.920
해당연도0.0001.0000.2670.1030.0920.088
세대수 (세대)0.9060.2671.0000.8910.8900.892
인구 (명)0.9180.1030.8911.0001.0001.000
인구 남 (명)0.9160.0920.8901.0001.0001.000
인구 여 (명)0.9200.0880.8921.0001.0001.000
2023-12-12T16:36:37.221458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
해당연도세대수 (세대)인구 (명)인구 남 (명)인구 여 (명)시군명
해당연도1.0000.202-0.099-0.087-0.1120.000
세대수 (세대)0.2021.0000.9370.9400.9340.551
인구 (명)-0.0990.9371.0000.9990.9990.704
인구 남 (명)-0.0870.9400.9991.0000.9980.700
인구 여 (명)-0.1120.9340.9990.9981.0000.710
시군명0.0000.5510.7040.7000.7101.000

Missing values

2023-12-12T16:36:34.959769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:36:35.089048image/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

시군명해당연도세대수 (세대)인구 (명)인구 남 (명)인구 여 (명)
0춘천시199570774232682115573117109
1원주시199570874237537118552118985
2강릉시199567106223539111304112235
3동해시1995299881002775041649861
4태백시199518773648503310231748
5속초시199525750806254003340592
6삼척시199526424900054557244433
7홍천군199522226759243853337391
8횡성군199514331487732485123922
9영월군199516510533982689626502
시군명해당연도세대수 (세대)인구 (명)인구 남 (명)인구 여 (명)
440횡성군201922832465752378522790
441영월군201921044391272014318984
442평창군201921379421062155020556
443정선군201919974372711936017911
444철원군201921216455842376721817
445화천군201912603249171349511422
446양구군201910840227641208210682
447인제군201915583316721714314529
448고성군201914445272601411413146
449양양군201914081277261409913627