Overview

Dataset statistics

Number of variables5
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory507.8 KiB
Average record size in memory52.0 B

Variable types

Numeric3
Categorical2

Dataset

Description외국인연령별인구현황입니다. 행정동, 성별, 연령, 인원수 정보를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/bigdata/collect/view.chungnam?menuCd=DOM_000000201001001000&apiIdx=103

Alerts

인원수 has 772 (7.7%) zerosZeros

Reproduction

Analysis started2024-01-09 21:19:12.654641
Analysis finished2024-01-09 21:19:13.750952
Duration1.1 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분기
Real number (ℝ)

Distinct35
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20191.926
Minimum20151
Maximum20233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:19:13.798779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20151
5-th percentile20152
Q120171
median20192
Q320213
95-th percentile20232
Maximum20233
Range82
Interquartile range (IQR)42

Descriptive statistics

Standard deviation25.413807
Coefficient of variation (CV)0.0012586123
Kurtosis-1.2304074
Mean20191.926
Median Absolute Deviation (MAD)21
Skewness-0.012452834
Sum2.0191926 × 108
Variance645.86157
MonotonicityNot monotonic
2024-01-10T06:19:14.109989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
20223 337
 
3.4%
20224 329
 
3.3%
20221 317
 
3.2%
20184 310
 
3.1%
20232 305
 
3.0%
20222 300
 
3.0%
20214 295
 
2.9%
20231 294
 
2.9%
20182 292
 
2.9%
20152 288
 
2.9%
Other values (25) 6933
69.3%
ValueCountFrequency (%)
20151 287
2.9%
20152 288
2.9%
20153 276
2.8%
20154 280
2.8%
20161 269
2.7%
20162 266
2.7%
20163 279
2.8%
20164 284
2.8%
20171 282
2.8%
20172 272
2.7%
ValueCountFrequency (%)
20233 283
2.8%
20232 305
3.0%
20231 294
2.9%
20224 329
3.3%
20223 337
3.4%
20222 300
3.0%
20221 317
3.2%
20214 295
2.9%
20213 272
2.7%
20212 281
2.8%

행정동코드
Real number (ℝ)

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4450075 × 109
Minimum4.4131 × 109
Maximum4.4825 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:19:14.191657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.4131 × 109
5-th percentile4.4131 × 109
Q14.42 × 109
median4.425 × 109
Q34.479 × 109
95-th percentile4.4825 × 109
Maximum4.4825 × 109
Range69400000
Interquartile range (IQR)59000000

Descriptive statistics

Standard deviation29348130
Coefficient of variation (CV)0.0066024928
Kurtosis-1.8636556
Mean4.4450075 × 109
Median Absolute Deviation (MAD)11700000
Skewness0.23564632
Sum4.4450075 × 1013
Variance8.6131274 × 1014
MonotonicityNot monotonic
2024-01-10T06:19:14.282427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
4421000000 652
 
6.5%
4481000000 644
 
6.4%
4420000000 642
 
6.4%
4479000000 639
 
6.4%
4425000000 638
 
6.4%
4413100000 632
 
6.3%
4471000000 630
 
6.3%
4477000000 628
 
6.3%
4423000000 628
 
6.3%
4413300000 619
 
6.2%
Other values (6) 3648
36.5%
ValueCountFrequency (%)
4413100000 632
6.3%
4413300000 619
6.2%
4415000000 604
6.0%
4418000000 618
6.2%
4420000000 642
6.4%
4421000000 652
6.5%
4423000000 628
6.3%
4425000000 638
6.4%
4427000000 614
6.1%
4471000000 630
6.3%
ValueCountFrequency (%)
4482500000 613
6.1%
4481000000 644
6.4%
4480000000 612
6.1%
4479000000 639
6.4%
4477000000 628
6.3%
4476000000 587
5.9%
4471000000 630
6.3%
4427000000 614
6.1%
4425000000 638
6.4%
4423000000 628
6.3%

성별코드
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5001 
2
4999 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 5001
50.0%
2 4999
50.0%

Length

2024-01-10T06:19:14.382517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:19:14.454213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5001
50.0%
2 4999
50.0%

연령(외국인)
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
60~64
 
617
65~69
 
606
25~29
 
600
40~44
 
590
10~14
 
590
Other values (14)
6997 

Length

Max length5
Median length5
Mean length4.687
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30~34
2nd row75~79
3rd row60~64
4th row10~14
5th row75~79

Common Values

ValueCountFrequency (%)
60~64 617
 
6.2%
65~69 606
 
6.1%
25~29 600
 
6.0%
40~44 590
 
5.9%
10~14 590
 
5.9%
55~59 586
 
5.9%
50~54 583
 
5.8%
0~4 581
 
5.8%
75~79 579
 
5.8%
80이상 578
 
5.8%
Other values (9) 4090
40.9%

Length

2024-01-10T06:19:14.540834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
60~64 617
 
6.2%
65~69 606
 
6.1%
25~29 600
 
6.0%
40~44 590
 
5.9%
10~14 590
 
5.9%
55~59 586
 
5.9%
50~54 583
 
5.8%
0~4 581
 
5.8%
75~79 579
 
5.8%
80이상 578
 
5.8%
Other values (9) 4090
40.9%

인원수
Real number (ℝ)

ZEROS 

Distinct877
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean118.0422
Minimum0
Maximum2204
Zeros772
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-01-10T06:19:14.649195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median27
Q3122
95-th percentile538.05
Maximum2204
Range2204
Interquartile range (IQR)118

Descriptive statistics

Standard deviation229.79173
Coefficient of variation (CV)1.9466913
Kurtosis21.367857
Mean118.0422
Median Absolute Deviation (MAD)26
Skewness3.9675485
Sum1180422
Variance52804.237
MonotonicityNot monotonic
2024-01-10T06:19:14.754631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 772
 
7.7%
1 702
 
7.0%
2 557
 
5.6%
3 358
 
3.6%
4 320
 
3.2%
5 228
 
2.3%
6 191
 
1.9%
7 188
 
1.9%
8 172
 
1.7%
9 142
 
1.4%
Other values (867) 6370
63.7%
ValueCountFrequency (%)
0 772
7.7%
1 702
7.0%
2 557
5.6%
3 358
3.6%
4 320
3.2%
5 228
 
2.3%
6 191
 
1.9%
7 188
 
1.9%
8 172
 
1.7%
9 142
 
1.4%
ValueCountFrequency (%)
2204 1
< 0.1%
2196 1
< 0.1%
2178 1
< 0.1%
2172 1
< 0.1%
2171 1
< 0.1%
2160 2
< 0.1%
2150 1
< 0.1%
2091 1
< 0.1%
2082 1
< 0.1%
2066 1
< 0.1%

Interactions

2024-01-10T06:19:13.413046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:12.976310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.183261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.486446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.037898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.254673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.562854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.121389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:19:13.334752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T06:19:14.825997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분기행정동코드성별코드연령(외국인)인원수
분기1.0000.0000.0000.2470.035
행정동코드0.0001.0000.0000.0000.395
성별코드0.0000.0001.0000.0000.153
연령(외국인)0.2470.0000.0001.0000.447
인원수0.0350.3950.1530.4471.000
2024-01-10T06:19:14.902391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별코드연령(외국인)
성별코드1.0000.000
연령(외국인)0.0001.000
2024-01-10T06:19:14.970173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분기행정동코드인원수성별코드연령(외국인)
분기1.000-0.0010.0290.0000.095
행정동코드-0.0011.000-0.2870.0000.000
인원수0.029-0.2871.0000.1170.184
성별코드0.0000.0000.1171.0000.000
연령(외국인)0.0950.0000.1840.0001.000

Missing values

2024-01-10T06:19:13.644811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T06:19:13.718181image/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

분기행정동코드성별코드연령(외국인)인원수
18774202334413100000230~34450
6645201814418000000175~792
6132201744420000000160~64116
7090201824413100000210~1432
8787201914415000000175~790
16281202224477000000215~193
567220173442300000025~911
4067201644425000000225~2917
17406202244471000000135~391481
1171320202442700000020~457
분기행정동코드성별코드연령(외국인)인원수
12737202044423000000225~29482
12127202034420000000235~39767
10722201944477000000160~6410
13630202124413100000265~6924
7553201824481000000130~34368
6717201814421000000215~1952
5336201724479000000275~791
8078201834480000000220~2489
18069202314477000000270~742
18535202324471000000225~29363