Overview

Dataset statistics

Number of variables8
Number of observations186
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.0 KiB
Average record size in memory71.7 B

Variable types

Numeric6
Categorical2

Dataset

Description경기도_시군분석마트외국인기본
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=MKY5DQFFMTW9N4GGCVUU33701198&infSeq=1

Alerts

년도 is highly overall correlated with 생성일자High correlation
시군코드 is highly overall correlated with 시군명High correlation
등록외국인수 is highly overall correlated with 등록외국인남자수 and 3 other fieldsHigh correlation
등록외국인남자수 is highly overall correlated with 등록외국인수 and 3 other fieldsHigh correlation
등록외국인여자수 is highly overall correlated with 등록외국인수 and 3 other fieldsHigh correlation
등록외국인여자2030수 is highly overall correlated with 등록외국인수 and 3 other fieldsHigh correlation
시군명 is highly overall correlated with 시군코드 and 4 other fieldsHigh correlation
생성일자 is highly overall correlated with 년도High correlation
등록외국인남자수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:33:53.230122
Analysis finished2023-12-10 21:33:56.532220
Duration3.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.5
Minimum2012
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:33:56.903701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12013
median2014.5
Q32016
95-th percentile2017
Maximum2017
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7124347
Coefficient of variation (CV)0.00085005443
Kurtosis-1.2703798
Mean2014.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum374697
Variance2.9324324
MonotonicityNot monotonic
2023-12-11T06:33:57.015671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2012 31
16.7%
2013 31
16.7%
2014 31
16.7%
2015 31
16.7%
2017 31
16.7%
2016 31
16.7%
ValueCountFrequency (%)
2012 31
16.7%
2013 31
16.7%
2014 31
16.7%
2015 31
16.7%
2016 31
16.7%
2017 31
16.7%
ValueCountFrequency (%)
2017 31
16.7%
2016 31
16.7%
2015 31
16.7%
2014 31
16.7%
2013 31
16.7%
2012 31
16.7%

시군코드
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4142.4194
Minimum4111
Maximum4183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:33:57.163508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4111
5-th percentile4113
Q14125
median4141
Q34159
95-th percentile4182
Maximum4183
Range72
Interquartile range (IQR)34

Descriptive statistics

Standard deviation20.597729
Coefficient of variation (CV)0.004972391
Kurtosis-0.84000522
Mean4142.4194
Median Absolute Deviation (MAD)16
Skewness0.34779322
Sum770490
Variance424.26643
MonotonicityNot monotonic
2023-12-11T06:33:57.345212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4111 6
 
3.2%
4113 6
 
3.2%
4183 6
 
3.2%
4182 6
 
3.2%
4180 6
 
3.2%
4167 6
 
3.2%
4165 6
 
3.2%
4163 6
 
3.2%
4161 6
 
3.2%
4159 6
 
3.2%
Other values (21) 126
67.7%
ValueCountFrequency (%)
4111 6
3.2%
4113 6
3.2%
4115 6
3.2%
4117 6
3.2%
4119 6
3.2%
4121 6
3.2%
4122 6
3.2%
4125 6
3.2%
4127 6
3.2%
4128 6
3.2%
ValueCountFrequency (%)
4183 6
3.2%
4182 6
3.2%
4180 6
3.2%
4167 6
3.2%
4165 6
3.2%
4163 6
3.2%
4161 6
3.2%
4159 6
3.2%
4157 6
3.2%
4155 6
3.2%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
수원시
 
6
성남시
 
6
의정부시
 
6
안양시
 
6
부천시
 
6
Other values (26)
156 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수원시
2nd row성남시
3rd row의정부시
4th row안양시
5th row부천시

Common Values

ValueCountFrequency (%)
수원시 6
 
3.2%
성남시 6
 
3.2%
의정부시 6
 
3.2%
안양시 6
 
3.2%
부천시 6
 
3.2%
광명시 6
 
3.2%
평택시 6
 
3.2%
동두천시 6
 
3.2%
안산시 6
 
3.2%
고양시 6
 
3.2%
Other values (21) 126
67.7%

Length

2023-12-11T06:33:57.522593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
수원시 6
 
3.2%
의왕시 6
 
3.2%
가평군 6
 
3.2%
연천군 6
 
3.2%
여주시 6
 
3.2%
포천시 6
 
3.2%
양주시 6
 
3.2%
광주시 6
 
3.2%
화성시 6
 
3.2%
김포시 6
 
3.2%
Other values (21) 126
67.7%

등록외국인수
Real number (ℝ)

HIGH CORRELATION 

Distinct183
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11184.667
Minimum211
Maximum55719
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:33:57.674701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum211
5-th percentile913
Q12908.25
median7246
Q315639.5
95-th percentile36122.25
Maximum55719
Range55508
Interquartile range (IQR)12731.25

Descriptive statistics

Standard deviation11714.653
Coefficient of variation (CV)1.0473851
Kurtosis3.3905463
Mean11184.667
Median Absolute Deviation (MAD)5450.5
Skewness1.8217124
Sum2080348
Variance1.372331 × 108
MonotonicityNot monotonic
2023-12-11T06:33:57.840183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1077 2
 
1.1%
7254 2
 
1.1%
3512 2
 
1.1%
27697 1
 
0.5%
21345 1
 
0.5%
3015 1
 
0.5%
892 1
 
0.5%
1469 1
 
0.5%
37852 1
 
0.5%
16936 1
 
0.5%
Other values (173) 173
93.0%
ValueCountFrequency (%)
211 1
0.5%
235 1
0.5%
274 1
0.5%
292 1
0.5%
297 1
0.5%
310 1
0.5%
729 1
0.5%
760 1
0.5%
791 1
0.5%
892 1
0.5%
ValueCountFrequency (%)
55719 1
0.5%
54497 1
0.5%
53755 1
0.5%
53733 1
0.5%
49249 1
0.5%
43465 1
0.5%
37852 1
0.5%
37351 1
0.5%
37183 1
0.5%
36516 1
0.5%

등록외국인남자수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct186
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6685.0161
Minimum95
Maximum31522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:33:58.000202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum95
5-th percentile456.25
Q11488.5
median4114.5
Q39040.25
95-th percentile22886.5
Maximum31522
Range31427
Interquartile range (IQR)7551.75

Descriptive statistics

Standard deviation7074.5544
Coefficient of variation (CV)1.0582704
Kurtosis2.6347983
Mean6685.0161
Median Absolute Deviation (MAD)3430
Skewness1.686805
Sum1243413
Variance50049320
MonotonicityNot monotonic
2023-12-11T06:33:58.186788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13781 1
 
0.5%
11070 1
 
0.5%
9489 1
 
0.5%
1905 1
 
0.5%
604 1
 
0.5%
457 1
 
0.5%
679 1
 
0.5%
20086 1
 
0.5%
8424 1
 
0.5%
1906 1
 
0.5%
Other values (176) 176
94.6%
ValueCountFrequency (%)
95 1
0.5%
101 1
0.5%
117 1
0.5%
133 1
0.5%
137 1
0.5%
147 1
0.5%
382 1
0.5%
409 1
0.5%
436 1
0.5%
456 1
0.5%
ValueCountFrequency (%)
31522 1
0.5%
30853 1
0.5%
30839 1
0.5%
30610 1
0.5%
28374 1
0.5%
26862 1
0.5%
25587 1
0.5%
24995 1
0.5%
24802 1
0.5%
23612 1
0.5%

등록외국인여자수
Real number (ℝ)

HIGH CORRELATION 

Distinct185
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4499.6505
Minimum116
Maximum24197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:33:58.372718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116
5-th percentile281.25
Q11169.5
median2777
Q36019.75
95-th percentile16563.5
Maximum24197
Range24081
Interquartile range (IQR)4850.25

Descriptive statistics

Standard deviation4963.3138
Coefficient of variation (CV)1.1030443
Kurtosis4.4294121
Mean4499.6505
Median Absolute Deviation (MAD)1952.5
Skewness2.0739635
Sum836935
Variance24634484
MonotonicityNot monotonic
2023-12-11T06:33:58.554040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
611 2
 
1.1%
13916 1
 
0.5%
3538 1
 
0.5%
2709 1
 
0.5%
1110 1
 
0.5%
288 1
 
0.5%
620 1
 
0.5%
790 1
 
0.5%
17766 1
 
0.5%
8512 1
 
0.5%
Other values (175) 175
94.1%
ValueCountFrequency (%)
116 1
0.5%
134 1
0.5%
157 1
0.5%
159 1
0.5%
160 1
0.5%
163 1
0.5%
263 1
0.5%
267 1
0.5%
274 1
0.5%
279 1
0.5%
ValueCountFrequency (%)
24197 1
0.5%
23658 1
0.5%
23145 1
0.5%
22880 1
0.5%
20875 1
0.5%
18470 1
0.5%
18213 1
0.5%
17837 1
0.5%
17766 1
0.5%
17112 1
0.5%

등록외국인여자2030수
Real number (ℝ)

HIGH CORRELATION 

Distinct180
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2137.5538
Minimum57
Maximum9692
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2023-12-11T06:33:58.714696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57
5-th percentile161.25
Q1758.25
median1523.5
Q33025.75
95-th percentile7037.75
Maximum9692
Range9635
Interquartile range (IQR)2267.5

Descriptive statistics

Standard deviation2089.4362
Coefficient of variation (CV)0.97748944
Kurtosis2.7654121
Mean2137.5538
Median Absolute Deviation (MAD)1039
Skewness1.7088319
Sum397585
Variance4365743.8
MonotonicityNot monotonic
2023-12-11T06:33:58.912920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
162 2
 
1.1%
3988 2
 
1.1%
285 2
 
1.1%
350 2
 
1.1%
343 2
 
1.1%
1630 2
 
1.1%
6071 1
 
0.5%
1674 1
 
0.5%
265 1
 
0.5%
500 1
 
0.5%
Other values (170) 170
91.4%
ValueCountFrequency (%)
57 1
0.5%
68 1
0.5%
79 1
0.5%
87 1
0.5%
96 1
0.5%
98 1
0.5%
141 1
0.5%
148 1
0.5%
160 1
0.5%
161 1
0.5%
ValueCountFrequency (%)
9692 1
0.5%
9610 1
0.5%
9512 1
0.5%
9007 1
0.5%
8615 1
0.5%
8151 1
0.5%
7351 1
0.5%
7220 1
0.5%
7165 1
0.5%
7110 1
0.5%

생성일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
20180315
155 
20190131
31 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20180315
2nd row20180315
3rd row20180315
4th row20180315
5th row20180315

Common Values

ValueCountFrequency (%)
20180315 155
83.3%
20190131 31
 
16.7%

Length

2023-12-11T06:33:59.061203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:33:59.159581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20180315 155
83.3%
20190131 31
 
16.7%

Interactions

2023-12-11T06:33:55.812934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:53.532338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.016987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.448410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.871675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.337455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.910024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:53.612710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.089267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.516431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.960756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.423376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:56.006213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:53.693450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.164518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.592618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.055072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.499372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:56.079058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:53.788881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.235356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.661593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.120151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.571997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:56.158118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:53.881482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.307574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.734855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.191985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.643291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:56.233943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:53.951633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.379225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:54.799117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.259337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:33:55.714329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:33:59.252974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도시군코드시군명등록외국인수등록외국인남자수등록외국인여자수등록외국인여자2030수생성일자
년도1.0000.0000.0000.0000.0000.0000.0001.000
시군코드0.0001.0001.0000.5730.5480.7290.7980.000
시군명0.0001.0001.0000.9060.9040.9280.9520.000
등록외국인수0.0000.5730.9061.0000.9680.9710.9540.000
등록외국인남자수0.0000.5480.9040.9681.0000.9350.9270.000
등록외국인여자수0.0000.7290.9280.9710.9351.0000.9640.000
등록외국인여자2030수0.0000.7980.9520.9540.9270.9641.0000.000
생성일자1.0000.0000.0000.0000.0000.0000.0001.000
2023-12-11T06:33:59.365378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
생성일자시군명
생성일자1.0000.000
시군명0.0001.000
2023-12-11T06:33:59.475008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도시군코드등록외국인수등록외국인남자수등록외국인여자수등록외국인여자2030수시군명생성일자
년도1.0000.0000.0830.0960.0850.0480.0000.989
시군코드0.0001.000-0.290-0.195-0.444-0.3490.9360.000
등록외국인수0.083-0.2901.0000.9880.9570.9730.5740.000
등록외국인남자수0.096-0.1950.9881.0000.9130.9460.5680.000
등록외국인여자수0.085-0.4440.9570.9131.0000.9730.6260.000
등록외국인여자2030수0.048-0.3490.9730.9460.9731.0000.6960.000
시군명0.0000.9360.5740.5680.6260.6961.0000.000
생성일자0.9890.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T06:33:56.355281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:33:56.487989image/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

년도시군코드시군명등록외국인수등록외국인남자수등록외국인여자수등록외국인여자2030수생성일자
020124111수원시276971378113916607120180315
120124113성남시1565672078449369920180315
220124115의정부시361314762137108220180315
320124117안양시681832033615166120180315
420124119부천시1600580417964377320180315
520124121광명시444420292415101520180315
620124122평택시1303280195013278520180315
720124125동두천시24911239125289320180315
820124127안산시434652499518470815120180315
920124128고양시1130455585746268620180315
년도시군코드시군명등록외국인수등록외국인남자수등록외국인여자수등록외국인여자2030수생성일자
17620164155안성시985164743377177720190131
17720164157김포시17835141423693177320190131
17820164159화성시34685255879098502420190131
17920164161광주시1211483533761196620190131
18020164163양주시72985636166291020190131
18120164165포천시1254997662783172920190131
18220164167여주시30651923114273820190131
18320164180연천군97969028916220190131
18420164182가평군106945861126220190131
18520164183양평군151369282153920190131