Overview

Dataset statistics

Number of variables7
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory693.4 KiB
Average record size in memory71.0 B

Variable types

Categorical2
Numeric5

Dataset

Description전입인구(전입지행정동, 전출지행정동, 연령, 성별, 전입사유, 인구수) 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=94

Alerts

연령코드 has 129 (1.3%) zerosZeros

Reproduction

Analysis started2024-01-09 20:29:11.430144
Analysis finished2024-01-09 20:29:14.888330
Duration3.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
201002
5143 
201001
4306 
201003
551 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row201002
2nd row201002
3rd row201002
4th row201002
5th row201001

Common Values

ValueCountFrequency (%)
201002 5143
51.4%
201001 4306
43.1%
201003 551
 
5.5%

Length

2024-01-10T05:29:14.961018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:29:15.041814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
201002 5143
51.4%
201001 4306
43.1%
201003 551
 
5.5%

전입지행정동코드
Real number (ℝ)

Distinct431
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9957435 × 109
Minimum1.111 × 109
Maximum5.013 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:29:15.142562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111 × 109
5-th percentile1.156 × 109
Q14.15 × 109
median4.413357 × 109
Q34.423052 × 109
95-th percentile4.483032 × 109
Maximum5.013 × 109
Range3.902 × 109
Interquartile range (IQR)2.73052 × 108

Descriptive statistics

Standard deviation9.5503509 × 108
Coefficient of variation (CV)0.23901311
Kurtosis3.4527696
Mean3.9957435 × 109
Median Absolute Deviation (MAD)36357000
Skewness-2.1642435
Sum3.9957435 × 1013
Variance9.1209202 × 1017
MonotonicityNot monotonic
2024-01-10T05:29:15.272116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4413357000 290
 
2.9%
4413158000 258
 
2.6%
3017000000 203
 
2.0%
4413157000 202
 
2.0%
4483025000 200
 
2.0%
4413356000 199
 
2.0%
4420025300 193
 
1.9%
4473025000 160
 
1.6%
4413354000 158
 
1.6%
4425033000 137
 
1.4%
Other values (421) 8000
80.0%
ValueCountFrequency (%)
1111000000 23
0.2%
1114000000 10
 
0.1%
1117000000 23
0.2%
1120000000 23
0.2%
1121500000 39
0.4%
1123000000 19
0.2%
1126000000 21
0.2%
1129000000 37
0.4%
1130500000 17
0.2%
1132000000 28
0.3%
ValueCountFrequency (%)
5013000000 1
 
< 0.1%
5011000000 9
0.1%
4889000000 1
 
< 0.1%
4888000000 2
 
< 0.1%
4887000000 1
 
< 0.1%
4886000000 1
 
< 0.1%
4885000000 1
 
< 0.1%
4874000000 2
 
< 0.1%
4873000000 2
 
< 0.1%
4833000000 10
0.1%

전출지행정동코드
Real number (ℝ)

Distinct425
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.1267798 × 109
Minimum1.111 × 109
Maximum5.013 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:29:15.399077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.111 × 109
5-th percentile2.53915 × 109
Q14.413125 × 109
median4.415057 × 109
Q34.425033 × 109
95-th percentile4.483038 × 109
Maximum5.013 × 109
Range3.902 × 109
Interquartile range (IQR)11908000

Descriptive statistics

Standard deviation8.0429849 × 108
Coefficient of variation (CV)0.19489736
Kurtosis6.8952728
Mean4.1267798 × 109
Median Absolute Deviation (MAD)9974500
Skewness-2.7684991
Sum4.1267798 × 1013
Variance6.4689606 × 1017
MonotonicityNot monotonic
2024-01-10T05:29:15.539094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4413357000 221
 
2.2%
4413159000 182
 
1.8%
4413354000 181
 
1.8%
4420025300 173
 
1.7%
3017000000 167
 
1.7%
4413356000 166
 
1.7%
4413157000 156
 
1.6%
4483025000 142
 
1.4%
4425033000 134
 
1.3%
3020000000 129
 
1.3%
Other values (415) 8349
83.5%
ValueCountFrequency (%)
1111000000 10
 
0.1%
1114000000 5
 
0.1%
1117000000 8
 
0.1%
1120000000 16
0.2%
1121500000 18
0.2%
1123000000 16
0.2%
1126000000 14
0.1%
1129000000 26
0.3%
1130500000 10
 
0.1%
1132000000 13
0.1%
ValueCountFrequency (%)
5013000000 2
 
< 0.1%
5011000000 17
0.2%
4888000000 2
 
< 0.1%
4887000000 3
 
< 0.1%
4885000000 3
 
< 0.1%
4884000000 1
 
< 0.1%
4882000000 3
 
< 0.1%
4874000000 1
 
< 0.1%
4873000000 4
 
< 0.1%
4833000000 13
0.1%

연령코드
Real number (ℝ)

ZEROS 

Distinct98
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.6004
Minimum0
Maximum100
Zeros129
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:29:15.721159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4
Q118
median30
Q343
95-th percentile67
Maximum100
Range100
Interquartile range (IQR)25

Descriptive statistics

Standard deviation18.609711
Coefficient of variation (CV)0.58890746
Kurtosis-0.026782755
Mean31.6004
Median Absolute Deviation (MAD)12
Skewness0.48021359
Sum316004
Variance346.32135
MonotonicityNot monotonic
2024-01-10T05:29:15.867946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 302
 
3.0%
27 281
 
2.8%
29 275
 
2.8%
26 260
 
2.6%
30 232
 
2.3%
25 226
 
2.3%
12 212
 
2.1%
36 212
 
2.1%
35 208
 
2.1%
41 207
 
2.1%
Other values (88) 7585
75.8%
ValueCountFrequency (%)
0 129
1.3%
1 116
1.2%
2 131
1.3%
3 123
1.2%
4 123
1.2%
5 115
1.1%
6 205
2.1%
7 142
1.4%
8 142
1.4%
9 147
1.5%
ValueCountFrequency (%)
100 1
 
< 0.1%
99 1
 
< 0.1%
97 1
 
< 0.1%
94 2
 
< 0.1%
93 2
 
< 0.1%
92 3
< 0.1%
91 3
< 0.1%
90 1
 
< 0.1%
89 3
< 0.1%
88 6
0.1%

성별코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5002 
2
4998 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 5002
50.0%
2 4998
50.0%

Length

2024-01-10T05:29:15.980745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:29:16.062880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5002
50.0%
2 4998
50.0%

전입사유코드
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6441
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:29:16.147558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.9794165
Coefficient of variation (CV)0.8176001
Kurtosis-0.53910587
Mean3.6441
Median Absolute Deviation (MAD)2
Skewness1.0396899
Sum36441
Variance8.8769229
MonotonicityNot monotonic
2024-01-10T05:29:16.261624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 2705
27.1%
3 2222
22.2%
2 2173
21.7%
9 2171
21.7%
4 572
 
5.7%
6 112
 
1.1%
5 45
 
0.4%
ValueCountFrequency (%)
1 2705
27.1%
2 2173
21.7%
3 2222
22.2%
4 572
 
5.7%
5 45
 
0.4%
6 112
 
1.1%
9 2171
21.7%
ValueCountFrequency (%)
9 2171
21.7%
6 112
 
1.1%
5 45
 
0.4%
4 572
 
5.7%
3 2222
22.2%
2 2173
21.7%
1 2705
27.1%

인구수
Real number (ℝ)

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0256
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T05:29:16.382846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.19273908
Coefficient of variation (CV)0.18792812
Kurtosis144.17812
Mean1.0256
Median Absolute Deviation (MAD)0
Skewness10.21691
Sum10256
Variance0.037148355
MonotonicityNot monotonic
2024-01-10T05:29:16.495627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 9788
97.9%
2 180
 
1.8%
3 24
 
0.2%
4 5
 
0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
1 9788
97.9%
2 180
 
1.8%
3 24
 
0.2%
4 5
 
0.1%
5 2
 
< 0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 2
 
< 0.1%
4 5
 
0.1%
3 24
 
0.2%
2 180
 
1.8%
1 9788
97.9%

Interactions

2024-01-10T05:29:14.271418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.042499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.506769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.274161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.778785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.363066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.132217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.904572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.375212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.898574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.455802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.228846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.994995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.465745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.010817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.541676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.314029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.085782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.559453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.095076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.626428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:12.412005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.183673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:13.675607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T05:29:14.185166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T05:29:16.584978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월전입지행정동코드전출지행정동코드연령코드성별코드전입사유코드인구수
기준연월1.0000.4770.1480.1180.0080.0800.011
전입지행정동코드0.4771.0000.4000.0920.0110.1210.042
전출지행정동코드0.1480.4001.0000.0800.0040.2200.000
연령코드0.1180.0920.0801.0000.1190.2450.053
성별코드0.0080.0110.0040.1191.0000.0880.028
전입사유코드0.0800.1210.2200.2450.0881.0000.053
인구수0.0110.0420.0000.0530.0280.0531.000
2024-01-10T05:29:16.698481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별코드기준연월
성별코드1.0000.014
기준연월0.0141.000
2024-01-10T05:29:16.801269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전입지행정동코드전출지행정동코드연령코드전입사유코드인구수기준연월성별코드
전입지행정동코드1.000-0.1050.011-0.0410.0320.3670.009
전출지행정동코드-0.1051.000-0.0290.008-0.0070.1000.004
연령코드0.011-0.0291.0000.032-0.0580.0650.094
전입사유코드-0.0410.0080.0321.0000.0370.0530.094
인구수0.032-0.007-0.0580.0371.0000.0040.020
기준연월0.3670.1000.0650.0530.0041.0000.014
성별코드0.0090.0040.0940.0940.0200.0141.000

Missing values

2024-01-10T05:29:14.727743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:29:14.835413image/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

기준연월전입지행정동코드전출지행정동코드연령코드성별코드전입사유코드인구수
60291201002441505700044150550008121
377212010021132000000448002530010121
474372010024165000000442503300018191
735872010024473036000441315200058211
23678201001442006100044200590002132
817632010031120000000447103200020211
360292010014518000000441335200030291
24381201001442103100044210510007241
505702010024413156000441335100036111
439672010024111700000447103700050221
기준연월전입지행정동코드전출지행정동코드연령코드성별코드전입사유코드인구수
461032010024139000000441803600026191
37839201002113500000044800350003231
44432010013017000000447603200055231
842462010031174000000441315900054111
329052010014481032000448103500051211
26033201001442105500041410000003211
689922010024423031000442302500048121
56322010014113100000442002530023211
4692010011129000000441505700021191
360192010014514000000448102500026291