Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory76.5 B

Variable types

Text1
Numeric7

Dataset

Description동별 세대수, 인구수, 인구수(남), 인구수(여), 18세이상인구수, 18세이상인구수(남), 18세이상인구수(여)에 대한 현황입니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/3040550/fileData.do

Alerts

세대수 is highly overall correlated with 인구수 and 5 other fieldsHigh correlation
인구수 is highly overall correlated with 세대수 and 5 other fieldsHigh correlation
인구수(남) is highly overall correlated with 세대수 and 5 other fieldsHigh correlation
인구수(여) is highly overall correlated with 세대수 and 5 other fieldsHigh correlation
18세이상인구수 is highly overall correlated with 세대수 and 5 other fieldsHigh correlation
18세이상인구수(남) is highly overall correlated with 세대수 and 5 other fieldsHigh correlation
18세이상인구수(여) is highly overall correlated with 세대수 and 5 other fieldsHigh correlation
동별 has unique valuesUnique
세대수 has unique valuesUnique
인구수 has unique valuesUnique
인구수(남) has unique valuesUnique
인구수(여) has unique valuesUnique
18세이상인구수 has unique valuesUnique
18세이상인구수(남) has unique valuesUnique
18세이상인구수(여) has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:09:57.771925
Analysis finished2024-04-06 08:10:07.842812
Duration10.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동별
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-06T17:10:08.036430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.4583333
Min length2

Characters and Unicode

Total characters83
Distinct characters32
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

Unique24 ?
Unique (%)100.0%

Sample

1st row복수동
2nd row도마1동
3rd row도마2동
4th row정림동
5th row변동
ValueCountFrequency (%)
복수동 1
 
4.2%
도마1동 1
 
4.2%
만년동 1
 
4.2%
둔산2동 1
 
4.2%
둔산1동 1
 
4.2%
기성동 1
 
4.2%
관저2동 1
 
4.2%
관저1동 1
 
4.2%
도안동 1
 
4.2%
가수원동 1
 
4.2%
Other values (14) 14
58.3%
2024-04-06T17:10:08.568841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
28.9%
1 5
 
6.0%
2 5
 
6.0%
마 4
 
4.8%
평 3
 
3.6%
도 3
 
3.6%
산 3
 
3.6%
둔 3
 
3.6%
월 3
 
3.6%
저 2
 
2.4%
Other values (22) 28
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71
85.5%
Decimal Number 12
 
14.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
33.8%
마 4
 
5.6%
평 3
 
4.2%
도 3
 
4.2%
산 3
 
4.2%
둔 3
 
4.2%
월 3
 
4.2%
저 2
 
2.8%
가 2
 
2.8%
관 2
 
2.8%
Other values (19) 22
31.0%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71
85.5%
Common 12
 
14.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
33.8%
마 4
 
5.6%
평 3
 
4.2%
도 3
 
4.2%
산 3
 
4.2%
둔 3
 
4.2%
월 3
 
4.2%
저 2
 
2.8%
가 2
 
2.8%
관 2
 
2.8%
Other values (19) 22
31.0%
Common
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71
85.5%
ASCII 12
 
14.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
33.8%
마 4
 
5.6%
평 3
 
4.2%
도 3
 
4.2%
산 3
 
4.2%
둔 3
 
4.2%
월 3
 
4.2%
저 2
 
2.8%
가 2
 
2.8%
관 2
 
2.8%
Other values (19) 22
31.0%
ASCII
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%

세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9086.5
Minimum1833
Maximum19598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:08.807622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1833
5-th percentile4851.3
Q16719
median7800.5
Q311779.25
95-th percentile15004.4
Maximum19598
Range17765
Interquartile range (IQR)5060.25

Descriptive statistics

Standard deviation4063.6813
Coefficient of variation (CV)0.44722185
Kurtosis0.59721326
Mean9086.5
Median Absolute Deviation (MAD)1899.5
Skewness0.82012958
Sum218076
Variance16513506
MonotonicityNot monotonic
2024-04-06T17:10:09.065899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
8880 1
 
4.2%
6780 1
 
4.2%
7946 1
 
4.2%
6157 1
 
4.2%
14984 1
 
4.2%
5762 1
 
4.2%
1833 1
 
4.2%
19598 1
 
4.2%
6593 1
 
4.2%
13944 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1833 1
4.2%
4845 1
4.2%
4887 1
4.2%
5762 1
4.2%
6157 1
4.2%
6593 1
4.2%
6761 1
4.2%
6780 1
4.2%
6783 1
4.2%
7227 1
4.2%
ValueCountFrequency (%)
19598 1
4.2%
15008 1
4.2%
14984 1
4.2%
13944 1
4.2%
13590 1
4.2%
11894 1
4.2%
11741 1
4.2%
9749 1
4.2%
9651 1
4.2%
8880 1
4.2%

인구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19365.167
Minimum3451
Maximum48582
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:09.301034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3451
5-th percentile10507.75
Q113126.5
median17619.5
Q321968.5
95-th percentile36419.95
Maximum48582
Range45131
Interquartile range (IQR)8842

Descriptive statistics

Standard deviation9781.2337
Coefficient of variation (CV)0.50509422
Kurtosis2.568707
Mean19365.167
Median Absolute Deviation (MAD)4755.5
Skewness1.3901212
Sum464764
Variance95672534
MonotonicityNot monotonic
2024-04-06T17:10:09.517169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
21654 1
 
4.2%
13623 1
 
4.2%
19070 1
 
4.2%
12303 1
 
4.2%
35241 1
 
4.2%
16417 1
 
4.2%
3451 1
 
4.2%
48582 1
 
4.2%
14921 1
 
4.2%
36628 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
3451 1
4.2%
10435 1
4.2%
10920 1
4.2%
11307 1
4.2%
11934 1
4.2%
12303 1
4.2%
13401 1
4.2%
13623 1
4.2%
14921 1
4.2%
15310 1
4.2%
ValueCountFrequency (%)
48582 1
4.2%
36628 1
4.2%
35241 1
4.2%
26791 1
4.2%
24065 1
4.2%
22912 1
4.2%
21654 1
4.2%
21229 1
4.2%
20513 1
4.2%
19070 1
4.2%

인구수(남)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9504.6667
Minimum1774
Maximum23659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:09.823658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1774
5-th percentile5116.85
Q16399.25
median8717.5
Q310847.75
95-th percentile17830.95
Maximum23659
Range21885
Interquartile range (IQR)4448.5

Descriptive statistics

Standard deviation4744.3464
Coefficient of variation (CV)0.49915968
Kurtosis2.5398094
Mean9504.6667
Median Absolute Deviation (MAD)2277.5
Skewness1.3761003
Sum228112
Variance22508822
MonotonicityNot monotonic
2024-04-06T17:10:10.107044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10703 1
 
4.2%
6448 1
 
4.2%
9180 1
 
4.2%
6253 1
 
4.2%
17026 1
 
4.2%
8071 1
 
4.2%
1774 1
 
4.2%
23659 1
 
4.2%
7020 1
 
4.2%
17973 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1774 1
4.2%
5093 1
4.2%
5252 1
4.2%
5678 1
4.2%
6097 1
4.2%
6253 1
4.2%
6448 1
4.2%
6764 1
4.2%
7020 1
4.2%
7415 1
4.2%
ValueCountFrequency (%)
23659 1
4.2%
17973 1
4.2%
17026 1
4.2%
12858 1
4.2%
12126 1
4.2%
11003 1
4.2%
10796 1
4.2%
10703 1
4.2%
10006 1
4.2%
9474 1
4.2%

인구수(여)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9830.9167
Minimum1677
Maximum24923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:10.453921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1677
5-th percentile5229.8
Q16541.75
median8763
Q311190.5
95-th percentile18589
Maximum24923
Range23246
Interquartile range (IQR)4648.75

Descriptive statistics

Standard deviation5048.7981
Coefficient of variation (CV)0.51356331
Kurtosis2.5916951
Mean9830.9167
Median Absolute Deviation (MAD)2347.5
Skewness1.4102231
Sum235942
Variance25490362
MonotonicityNot monotonic
2024-04-06T17:10:10.715978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
10951 1
 
4.2%
7175 1
 
4.2%
9180 1
 
4.2%
6050 1
 
4.2%
18215 1
 
4.2%
8346 1
 
4.2%
1677 1
 
4.2%
24923 1
 
4.2%
7901 1
 
4.2%
18655 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1677 1
4.2%
5210 1
4.2%
5342 1
4.2%
5668 1
4.2%
6050 1
4.2%
6256 1
4.2%
6637 1
4.2%
7175 1
4.2%
7895 1
4.2%
7901 1
4.2%
ValueCountFrequency (%)
24923 1
4.2%
18655 1
4.2%
18215 1
4.2%
13933 1
4.2%
11939 1
4.2%
11909 1
4.2%
10951 1
4.2%
10507 1
4.2%
10433 1
4.2%
9590 1
4.2%

18세이상인구수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16531.042
Minimum3258
Maximum38986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:10.987638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3258
5-th percentile9287.5
Q111747
median15395
Q319341.5
95-th percentile29295.1
Maximum38986
Range35728
Interquartile range (IQR)7594.5

Descriptive statistics

Standard deviation7664.1061
Coefficient of variation (CV)0.46361907
Kurtosis2.1599225
Mean16531.042
Median Absolute Deviation (MAD)4023
Skewness1.2038642
Sum396745
Variance58738523
MonotonicityNot monotonic
2024-04-06T17:10:11.377833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
17805 1
 
4.2%
12126 1
 
4.2%
15904 1
 
4.2%
10678 1
 
4.2%
29635 1
 
4.2%
12282 1
 
4.2%
3258 1
 
4.2%
38986 1
 
4.2%
12826 1
 
4.2%
27369 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
3258 1
4.2%
9232 1
4.2%
9602 1
4.2%
10615 1
4.2%
10678 1
4.2%
11048 1
4.2%
11980 1
4.2%
12126 1
4.2%
12282 1
4.2%
12826 1
4.2%
ValueCountFrequency (%)
38986 1
4.2%
29635 1
4.2%
27369 1
4.2%
23661 1
4.2%
21717 1
4.2%
19571 1
4.2%
19265 1
4.2%
17805 1
4.2%
17081 1
4.2%
16997 1
4.2%

18세이상인구수(남)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8043.9167
Minimum1667
Maximum18789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:11.616980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1667
5-th percentile4491.95
Q15726.5
median7455.5
Q39451
95-th percentile13998.15
Maximum18789
Range17122
Interquartile range (IQR)3724.5

Descriptive statistics

Standard deviation3674.424
Coefficient of variation (CV)0.45679538
Kurtosis2.0796084
Mean8043.9167
Median Absolute Deviation (MAD)1830.5
Skewness1.1720674
Sum193054
Variance13501392
MonotonicityNot monotonic
2024-04-06T17:10:11.945886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
8781 1
 
4.2%
5689 1
 
4.2%
7496 1
 
4.2%
5418 1
 
4.2%
14133 1
 
4.2%
5920 1
 
4.2%
1667 1
 
4.2%
18789 1
 
4.2%
5936 1
 
4.2%
13234 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1667 1
4.2%
4475 1
4.2%
4588 1
4.2%
5237 1
4.2%
5418 1
4.2%
5689 1
4.2%
5739 1
4.2%
5920 1
4.2%
5936 1
4.2%
6003 1
4.2%
ValueCountFrequency (%)
18789 1
4.2%
14133 1
4.2%
13234 1
4.2%
11207 1
4.2%
10928 1
4.2%
9754 1
4.2%
9350 1
4.2%
8781 1
4.2%
8388 1
4.2%
8283 1
4.2%

18세이상인구수(여)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8487.125
Minimum1591
Maximum20197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-06T17:10:12.266351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1591
5-th percentile4774.85
Q15935.5
median7901.5
Q39688.5
95-th percentile15296.95
Maximum20197
Range18606
Interquartile range (IQR)3753

Descriptive statistics

Standard deviation4003.4663
Coefficient of variation (CV)0.47171054
Kurtosis2.1803116
Mean8487.125
Median Absolute Deviation (MAD)2007.5
Skewness1.2185409
Sum203691
Variance16027743
MonotonicityNot monotonic
2024-04-06T17:10:12.502166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
9024 1
 
4.2%
6437 1
 
4.2%
8408 1
 
4.2%
5260 1
 
4.2%
15502 1
 
4.2%
6362 1
 
4.2%
1591 1
 
4.2%
20197 1
 
4.2%
6890 1
 
4.2%
14135 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1591 1
4.2%
4757 1
4.2%
4876 1
4.2%
5014 1
4.2%
5260 1
4.2%
5811 1
4.2%
5977 1
4.2%
6362 1
4.2%
6437 1
4.2%
6890 1
4.2%
ValueCountFrequency (%)
20197 1
4.2%
15502 1
4.2%
14135 1
4.2%
12454 1
4.2%
10789 1
4.2%
10221 1
4.2%
9511 1
4.2%
9024 1
4.2%
8896 1
4.2%
8714 1
4.2%

Interactions

2024-04-06T17:10:06.342850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:58.173269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:59.329459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:00.687567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:01.878182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:03.247221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:04.622485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:06.505879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:58.329994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:59.493301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:00.872252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:02.155483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:03.436241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:04.879358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:06.672162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:58.464980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:59.659719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:01.032328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:02.327929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:03.621439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:05.082767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:06.885269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:58.613246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:59.911888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:01.171411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:02.491577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:03.770816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:05.259826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:07.024226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:58.749090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:00.088520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:01.339204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:02.661811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:03.937756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:05.809549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:07.158383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:58.940698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:00.288273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:01.510191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:02.873535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:04.146604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:05.984679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:07.305596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:59.131190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:00.478566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:01.692269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:03.035042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:04.354267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:10:06.166211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:10:12.671809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별세대수인구수인구수(남)인구수(여)18세이상인구수18세이상인구수(남)18세이상인구수(여)
동별1.0001.0001.0001.0001.0001.0001.0001.000
세대수1.0001.0000.8020.9340.8220.9530.9530.936
인구수1.0000.8021.0000.9640.9990.8800.8800.930
인구수(남)1.0000.9340.9641.0000.9510.9890.9890.993
인구수(여)1.0000.8220.9990.9511.0000.8670.8670.948
18세이상인구수1.0000.9530.8800.9890.8671.0001.0000.988
18세이상인구수(남)1.0000.9530.8800.9890.8671.0001.0000.988
18세이상인구수(여)1.0000.9360.9300.9930.9480.9880.9881.000
2024-04-06T17:10:12.905082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수인구수인구수(남)인구수(여)18세이상인구수18세이상인구수(남)18세이상인구수(여)
세대수1.0000.8880.9020.8680.9100.9370.902
인구수0.8881.0000.9950.9900.9910.9750.989
인구수(남)0.9020.9951.0000.9870.9920.9870.985
인구수(여)0.8680.9900.9871.0000.9880.9600.985
18세이상인구수0.9100.9910.9920.9881.0000.9830.997
18세이상인구수(남)0.9370.9750.9870.9600.9831.0000.976
18세이상인구수(여)0.9020.9890.9850.9850.9970.9761.000

Missing values

2024-04-06T17:10:07.536515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:10:07.756165image/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

동별세대수인구수인구수(남)인구수(여)18세이상인구수18세이상인구수(남)18세이상인구수(여)
0복수동88802165410703109511780587819024
1도마1동974918818947493441672083888332
2도마2동816816461825582061488674157471
3정림동676115310741578951350164397062
4변동678313401676466371198060035977
5용문동722711934567862561104852375811
6탄방동15008267911285813933236611120712454
7괴정동1174118778918895901699782838714
8가장동48871092052525668960245885014
9내동965122912110031190919571935010221
동별세대수인구수인구수(남)인구수(여)18세이상인구수18세이상인구수(남)18세이상인구수(여)
14월평3동76402051310006105071708181858896
15가수원동48451043550935342923244754757
16도안동13944366281797318655273691323414135
17관저1동659314921702079011282659366890
18관저2동19598485822365924923389861878920197
19기성동1833345117741677325816671591
20둔산1동576216417807183461228259206362
21둔산2동14984352411702618215296351413315502
22만년동615712303625360501067854185260
23둔산3동794619070918091801590474968408