Overview

Dataset statistics

Number of variables10
Number of observations120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.3 KiB
Average record size in memory88.1 B

Variable types

Text1
Numeric7
DateTime2

Dataset

Description2019년~2022년 진주시 읍면동별 인구통계에 관한 자료( 세대수, 내외국인인구수, 내국인인구수, 외국인인구수, 등록기준일자 항목 등) 제공입니다.
URLhttps://www.data.go.kr/data/3035977/fileData.do

Alerts

데이터작성기준일 has constant value ""Constant
세대수 is highly overall correlated with 내외국인_남자 인구 and 4 other fieldsHigh correlation
내외국인_남자 인구 is highly overall correlated with 세대수 and 4 other fieldsHigh correlation
내외국인_여자 인구 is highly overall correlated with 세대수 and 4 other fieldsHigh correlation
내국인_주민등록_남자 인구 is highly overall correlated with 세대수 and 4 other fieldsHigh correlation
내국인_주민등록_여자 인구 is highly overall correlated with 세대수 and 4 other fieldsHigh correlation
외국인_출입국등록신고_여자 is highly overall correlated with 세대수 and 4 other fieldsHigh correlation
세대수 has unique valuesUnique
내외국인_남자 인구 has unique valuesUnique
외국인_출입국등록신고_남자 has 2 (1.7%) zerosZeros

Reproduction

Analysis started2023-12-12 04:19:59.411429
Analysis finished2023-12-12 04:20:06.795040
Duration7.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동명
Text

Distinct57
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2023-12-12T13:20:06.997391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length4.45
Min length3

Characters and Unicode

Total characters534
Distinct characters45
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

Unique27 ?
Unique (%)22.5%

Sample

1st row문 산 읍
2nd row내 동 면
3rd row정 촌 면
4th row금 곡 면
5th row진 성 면
ValueCountFrequency (%)
동 42
 
14.9%
면 39
 
13.8%
대 12
 
4.3%
평 9
 
3.2%
상 9
 
3.2%
곡 9
 
3.2%
현 6
 
2.1%
금 6
 
2.1%
수 6
 
2.1%
문 6
 
2.1%
Other values (59) 138
48.9%
2023-12-12T13:20:07.463387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
30.3%
면 60
 
11.2%
동 60
 
11.2%
성 16
 
3.0%
대 16
 
3.0%
상 12
 
2.2%
곡 12
 
2.2%
평 12
 
2.2%
반 8
 
1.5%
이 8
 
1.5%
Other values (35) 168
31.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 372
69.7%
Space Separator 162
30.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 60
 
16.1%
동 60
 
16.1%
성 16
 
4.3%
대 16
 
4.3%
상 12
 
3.2%
곡 12
 
3.2%
평 12
 
3.2%
반 8
 
2.2%
이 8
 
2.2%
산 8
 
2.2%
Other values (34) 160
43.0%
Space Separator
ValueCountFrequency (%)
162
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 372
69.7%
Common 162
30.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 60
 
16.1%
동 60
 
16.1%
성 16
 
4.3%
대 16
 
4.3%
상 12
 
3.2%
곡 12
 
3.2%
평 12
 
3.2%
반 8
 
2.2%
이 8
 
2.2%
산 8
 
2.2%
Other values (34) 160
43.0%
Common
ValueCountFrequency (%)
162
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 372
69.7%
ASCII 162
30.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
100.0%
Hangul
ValueCountFrequency (%)
면 60
 
16.1%
동 60
 
16.1%
성 16
 
4.3%
대 16
 
4.3%
상 12
 
3.2%
곡 12
 
3.2%
평 12
 
3.2%
반 8
 
2.2%
이 8
 
2.2%
산 8
 
2.2%
Other values (34) 160
43.0%

세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5128.9083
Minimum563
Maximum14808
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:07.632425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum563
5-th percentile835.6
Q11252.75
median4613.5
Q37921.25
95-th percentile12854.3
Maximum14808
Range14245
Interquartile range (IQR)6668.5

Descriptive statistics

Standard deviation4104.8446
Coefficient of variation (CV)0.80033496
Kurtosis-0.89058514
Mean5128.9083
Median Absolute Deviation (MAD)3351.5
Skewness0.60734959
Sum615469
Variance16849749
MonotonicityNot monotonic
2023-12-12T13:20:07.861864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3628 1
 
0.8%
1670 1
 
0.8%
11589 1
 
0.8%
12851 1
 
0.8%
7912 1
 
0.8%
5223 1
 
0.8%
5261 1
 
0.8%
11144 1
 
0.8%
9288 1
 
0.8%
5508 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
563 1
0.8%
567 1
0.8%
568 1
0.8%
589 1
0.8%
827 1
0.8%
828 1
0.8%
836 1
0.8%
862 1
0.8%
885 1
0.8%
888 1
0.8%
ValueCountFrequency (%)
14808 1
0.8%
13855 1
0.8%
13639 1
0.8%
13374 1
0.8%
13172 1
0.8%
12917 1
0.8%
12851 1
0.8%
12379 1
0.8%
12298 1
0.8%
11589 1
0.8%

내외국인_남자 인구
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct120
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5803.95
Minimum482
Maximum16394
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:08.064756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum482
5-th percentile786.65
Q11155.75
median4900
Q310223.25
95-th percentile14059.25
Maximum16394
Range15912
Interquartile range (IQR)9067.5

Descriptive statistics

Standard deviation4914.228
Coefficient of variation (CV)0.84670405
Kurtosis-1.0114303
Mean5803.95
Median Absolute Deviation (MAD)3828.5
Skewness0.62595823
Sum696474
Variance24149636
MonotonicityNot monotonic
2023-12-12T13:20:08.273235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4221 1
 
0.8%
2118 1
 
0.8%
15481 1
 
0.8%
13930 1
 
0.8%
10201 1
 
0.8%
6030 1
 
0.8%
5653 1
 
0.8%
13345 1
 
0.8%
13651 1
 
0.8%
6423 1
 
0.8%
Other values (110) 110
91.7%
ValueCountFrequency (%)
482 1
0.8%
497 1
0.8%
504 1
0.8%
562 1
0.8%
745 1
0.8%
761 1
0.8%
788 1
0.8%
790 1
0.8%
804 1
0.8%
805 1
0.8%
ValueCountFrequency (%)
16394 1
0.8%
16344 1
0.8%
15481 1
0.8%
15254 1
0.8%
14996 1
0.8%
14558 1
0.8%
14033 1
0.8%
13987 1
0.8%
13930 1
0.8%
13748 1
0.8%

내외국인_여자 인구
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5897.1667
Minimum539
Maximum16953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:08.497777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum539
5-th percentile736.25
Q11246.5
median4746.5
Q310515.25
95-th percentile14510.2
Maximum16953
Range16414
Interquartile range (IQR)9268.75

Descriptive statistics

Standard deviation5041.4422
Coefficient of variation (CV)0.85489226
Kurtosis-1.0184634
Mean5897.1667
Median Absolute Deviation (MAD)3653.5
Skewness0.62722724
Sum707660
Variance25416139
MonotonicityNot monotonic
2023-12-12T13:20:08.661009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2029 2
 
1.7%
806 2
 
1.7%
3973 1
 
0.8%
13680 1
 
0.8%
11189 1
 
0.8%
6200 1
 
0.8%
6197 1
 
0.8%
14495 1
 
0.8%
13337 1
 
0.8%
5899 1
 
0.8%
Other values (108) 108
90.0%
ValueCountFrequency (%)
539 1
0.8%
550 1
0.8%
568 1
0.8%
621 1
0.8%
688 1
0.8%
722 1
0.8%
737 1
0.8%
763 1
0.8%
775 1
0.8%
778 1
0.8%
ValueCountFrequency (%)
16953 1
0.8%
16741 1
0.8%
15747 1
0.8%
15319 1
0.8%
15111 1
0.8%
14799 1
0.8%
14495 1
0.8%
14341 1
0.8%
14291 1
0.8%
14144 1
0.8%

내국인_주민등록_남자 인구
Real number (ℝ)

HIGH CORRELATION 

Distinct119
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5707.425
Minimum481
Maximum16355
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:08.840707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum481
5-th percentile717.8
Q11125.75
median4722.5
Q310173
95-th percentile14012.25
Maximum16355
Range15874
Interquartile range (IQR)9047.25

Descriptive statistics

Standard deviation4896.4142
Coefficient of variation (CV)0.8579025
Kurtosis-0.99914694
Mean5707.425
Median Absolute Deviation (MAD)3698
Skewness0.63545078
Sum684891
Variance23974872
MonotonicityNot monotonic
2023-12-12T13:20:09.036891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1039 2
 
1.7%
4021 1
 
0.8%
5327 1
 
0.8%
15446 1
 
0.8%
13556 1
 
0.8%
10150 1
 
0.8%
6020 1
 
0.8%
5636 1
 
0.8%
13325 1
 
0.8%
13632 1
 
0.8%
Other values (109) 109
90.8%
ValueCountFrequency (%)
481 1
0.8%
497 1
0.8%
504 1
0.8%
561 1
0.8%
700 1
0.8%
714 1
0.8%
718 1
0.8%
725 1
0.8%
752 1
0.8%
758 1
0.8%
ValueCountFrequency (%)
16355 1
0.8%
16314 1
0.8%
15446 1
0.8%
14937 1
0.8%
14850 1
0.8%
14188 1
0.8%
14003 1
0.8%
13891 1
0.8%
13690 1
0.8%
13632 1
0.8%

내국인_주민등록_여자 인구
Real number (ℝ)

HIGH CORRELATION 

Distinct118
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5833.925
Minimum525
Maximum16881
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:09.245457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum525
5-th percentile728.35
Q11202.5
median4688
Q310438.25
95-th percentile14410.7
Maximum16881
Range16356
Interquartile range (IQR)9235.75

Descriptive statistics

Standard deviation5001.3774
Coefficient of variation (CV)0.85729203
Kurtosis-1.0072208
Mean5833.925
Median Absolute Deviation (MAD)3610.5
Skewness0.63117726
Sum700071
Variance25013776
MonotonicityNot monotonic
2023-12-12T13:20:09.479610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2001 2
 
1.7%
1101 2
 
1.7%
5459 1
 
0.8%
15690 1
 
0.8%
13360 1
 
0.8%
11122 1
 
0.8%
6169 1
 
0.8%
6167 1
 
0.8%
14443 1
 
0.8%
13303 1
 
0.8%
Other values (108) 108
90.0%
ValueCountFrequency (%)
525 1
0.8%
539 1
0.8%
555 1
0.8%
604 1
0.8%
683 1
0.8%
716 1
0.8%
729 1
0.8%
753 1
0.8%
765 1
0.8%
767 1
0.8%
ValueCountFrequency (%)
16881 1
0.8%
16676 1
0.8%
15690 1
0.8%
15208 1
0.8%
15053 1
0.8%
14443 1
0.8%
14409 1
0.8%
14287 1
0.8%
14182 1
0.8%
14047 1
0.8%

외국인_출입국등록신고_남자
Real number (ℝ)

ZEROS 

Distinct82
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.525
Minimum0
Maximum557
Zeros2
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:09.634446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.95
Q123
median39.5
Q3118.75
95-th percentile375.5
Maximum557
Range557
Interquartile range (IQR)95.75

Descriptive statistics

Standard deviation121.28292
Coefficient of variation (CV)1.2564923
Kurtosis2.4774795
Mean96.525
Median Absolute Deviation (MAD)21.5
Skewness1.8036878
Sum11583
Variance14709.546
MonotonicityNot monotonic
2023-12-12T13:20:09.803395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39 4
 
3.3%
30 4
 
3.3%
17 4
 
3.3%
18 3
 
2.5%
29 3
 
2.5%
51 3
 
2.5%
31 3
 
2.5%
26 3
 
2.5%
23 3
 
2.5%
24 2
 
1.7%
Other values (72) 88
73.3%
ValueCountFrequency (%)
0 2
1.7%
1 2
1.7%
6 1
0.8%
8 1
0.8%
9 1
0.8%
10 1
0.8%
11 1
0.8%
12 1
0.8%
13 1
0.8%
14 1
0.8%
ValueCountFrequency (%)
557 1
0.8%
465 1
0.8%
439 1
0.8%
421 1
0.8%
418 1
0.8%
404 1
0.8%
374 1
0.8%
370 1
0.8%
332 1
0.8%
320 1
0.8%

외국인_출입국등록신고_여자
Real number (ℝ)

HIGH CORRELATION 

Distinct76
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.241667
Minimum5
Maximum417
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-12T13:20:09.959414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.95
Q122.75
median42
Q369
95-th percentile198.8
Maximum417
Range412
Interquartile range (IQR)46.25

Descriptive statistics

Standard deviation72.409201
Coefficient of variation (CV)1.1449604
Kurtosis9.6954615
Mean63.241667
Median Absolute Deviation (MAD)21
Skewness2.8938107
Sum7589
Variance5243.0924
MonotonicityNot monotonic
2023-12-12T13:20:10.471675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 7
 
5.8%
23 5
 
4.2%
10 5
 
4.2%
21 4
 
3.3%
97 3
 
2.5%
59 3
 
2.5%
109 3
 
2.5%
77 2
 
1.7%
99 2
 
1.7%
49 2
 
1.7%
Other values (66) 84
70.0%
ValueCountFrequency (%)
5 1
 
0.8%
6 2
 
1.7%
7 1
 
0.8%
8 2
 
1.7%
9 2
 
1.7%
10 5
4.2%
11 2
 
1.7%
13 1
 
0.8%
14 2
 
1.7%
15 1
 
0.8%
ValueCountFrequency (%)
417 1
0.8%
390 1
0.8%
342 1
0.8%
320 1
0.8%
217 1
0.8%
214 1
0.8%
198 1
0.8%
193 1
0.8%
165 1
0.8%
163 1
0.8%

등록기준일자
Date

Distinct4
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2019-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-12T13:20:10.618564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:10.734289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=4)

데이터작성기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
Minimum2023-05-18 00:00:00
Maximum2023-05-18 00:00:00
2023-12-12T13:20:10.853539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:10.971670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T13:20:05.535740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:59.818816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.761430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.690340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.594578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:03.783761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.663207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.682778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:19:59.949220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.924163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.815337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.722442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:03.891235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.768083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.837419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.084295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.069926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.948347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.848088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.026458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.901685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.983369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.232959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.202839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.079079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.972475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.143721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.024080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:06.102894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.372874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.336785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.220695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:03.098368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.274384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.158695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:06.230028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.514335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.457094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.353903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:03.545221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.438963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.297126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:06.351130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:00.638765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:01.585066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:02.486258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:03.681201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:04.540816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:20:05.417015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:20:11.079497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동명세대수내외국인_남자 인구내외국인_여자 인구내국인_주민등록_남자 인구내국인_주민등록_여자 인구외국인_출입국등록신고_남자외국인_출입국등록신고_여자등록기준일자
읍면동명1.0000.9850.9720.9880.9800.9790.9750.9240.000
세대수0.9851.0000.9550.9710.9610.9650.7470.7610.000
내외국인_남자 인구0.9720.9551.0000.9870.9980.9840.7410.7190.000
내외국인_여자 인구0.9880.9710.9871.0000.9920.9990.6530.6750.000
내국인_주민등록_남자 인구0.9800.9610.9980.9921.0000.9900.6640.6740.000
내국인_주민등록_여자 인구0.9790.9650.9840.9990.9901.0000.5790.6600.000
외국인_출입국등록신고_남자0.9750.7470.7410.6530.6640.5791.0000.8170.000
외국인_출입국등록신고_여자0.9240.7610.7190.6750.6740.6600.8171.0000.000
등록기준일자0.0000.0000.0000.0000.0000.0000.0000.0001.000
2023-12-12T13:20:11.267905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세대수내외국인_남자 인구내외국인_여자 인구내국인_주민등록_남자 인구내국인_주민등록_여자 인구외국인_출입국등록신고_남자외국인_출입국등록신고_여자
세대수1.0000.9820.9850.9830.9840.1530.822
내외국인_남자 인구0.9821.0000.9940.9970.9930.1400.782
내외국인_여자 인구0.9850.9941.0000.9971.0000.0850.769
내국인_주민등록_남자 인구0.9830.9970.9971.0000.9960.1050.776
내국인_주민등록_여자 인구0.9840.9931.0000.9961.0000.0780.764
외국인_출입국등록신고_남자0.1530.1400.0850.1050.0781.0000.465
외국인_출입국등록신고_여자0.8220.7820.7690.7760.7640.4651.000

Missing values

2023-12-12T13:20:06.502909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:20:06.716243image/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

읍면동명세대수내외국인_남자 인구내외국인_여자 인구내국인_주민등록_남자 인구내국인_주민등록_여자 인구외국인_출입국등록신고_남자외국인_출입국등록신고_여자등록기준일자데이터작성기준일
0문 산 읍36284221400940213915200942022-12-312023-05-18
1내 동 면1648205220291998200154282022-12-312023-05-18
2정 촌 면40284796435744644299332582022-12-312023-05-18
3금 곡 면1229107411251039110135242022-12-312023-05-18
4진 성 면107596795190993358182022-12-312023-05-18
5일반성면1384127113001252128119192022-12-312023-05-18
6이반성면100886278878976973192022-12-312023-05-18
7사 봉 면904982778718767264112022-12-312023-05-18
8지 수 면8287456887006834552022-12-312023-05-18
9대 곡 면17731679158815431535136532022-12-312023-05-18
읍면동명세대수내외국인_남자 인구내외국인_여자 인구내국인_주민등록_남자 인구내국인_주민등록_여자 인구외국인_출입국등록신고_남자외국인_출입국등록신고_여자등록기준일자데이터작성기준일
110상대동10075111681118010848109873201932019-12-312023-05-18
111하대동1119713987138951389113751961442019-12-312023-05-18
112상평동55597030637464736275557992019-12-312023-05-18
113초장동78081215511773121321174123322019-12-312023-05-18
114평거동109301403315111140031505330582019-12-312023-05-18
115신안동5298611966386103660416342019-12-312023-05-18
116이현동530266066700659766719292019-12-312023-05-18
117판문동81031098411892109291182955632019-12-312023-05-18
118가호동9928114091126510944108484654172019-12-312023-05-18
119충무공동74701029710319102751029622232019-12-312023-05-18