Overview

Dataset statistics

Number of variables9
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory85.5 B

Variable types

Text1
Numeric8

Dataset

Description경주시 읍면동 별로 한국인배우자, 결혼이민자, 귀화자, 자녀, 동거인정보를 나타낸 경주시 다문화가족 현황입니다.
URLhttps://www.data.go.kr/data/15104053/fileData.do

Alerts

합계 is highly overall correlated with 한국인배우자 and 6 other fieldsHigh correlation
한국인배우자 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
결혼이민자 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
귀화자 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
자녀외국출생 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
자녀국내출생 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
동거인내국인 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
동거인외국인 is highly overall correlated with 합계 and 6 other fieldsHigh correlation
구분 has unique valuesUnique
합계 has unique valuesUnique
귀화자 has 1 (4.2%) zerosZeros
자녀외국출생 has 7 (29.2%) zerosZeros
동거인외국인 has 3 (12.5%) zerosZeros

Reproduction

Analysis started2023-12-12 17:04:00.298883
Analysis finished2023-12-12 17:04:07.195432
Duration6.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T02:04:07.314314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0416667
Min length4

Characters and Unicode

Total characters121
Distinct characters39
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 row 경주시
2nd row 감포읍
3rd row 안강읍
4th row 건천읍
5th row 외동읍
ValueCountFrequency (%)
경주시 1
 
4.2%
감포읍 1
 
4.2%
황오동 1
 
4.2%
보덕동 1
 
4.2%
불국동 1
 
4.2%
동천동 1
 
4.2%
황성동 1
 
4.2%
용강동 1
 
4.2%
선도동 1
 
4.2%
월성동 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T02:04:07.649119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
39.7%
동 14
 
11.6%
면 8
 
6.6%
읍 4
 
3.3%
성 3
 
2.5%
황 3
 
2.5%
강 3
 
2.5%
천 3
 
2.5%
남 3
 
2.5%
건 2
 
1.7%
Other values (29) 30
24.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
60.3%
Space Separator 48
39.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 14
19.2%
면 8
 
11.0%
읍 4
 
5.5%
성 3
 
4.1%
황 3
 
4.1%
강 3
 
4.1%
천 3
 
4.1%
남 3
 
4.1%
건 2
 
2.7%
내 2
 
2.7%
Other values (28) 28
38.4%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
60.3%
Common 48
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 14
19.2%
면 8
 
11.0%
읍 4
 
5.5%
성 3
 
4.1%
황 3
 
4.1%
강 3
 
4.1%
천 3
 
4.1%
남 3
 
4.1%
건 2
 
2.7%
내 2
 
2.7%
Other values (28) 28
38.4%
Common
ValueCountFrequency (%)
48
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
60.3%
ASCII 48
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
100.0%
Hangul
ValueCountFrequency (%)
동 14
19.2%
면 8
 
11.0%
읍 4
 
5.5%
성 3
 
4.1%
황 3
 
4.1%
강 3
 
4.1%
천 3
 
4.1%
남 3
 
4.1%
건 2
 
2.7%
내 2
 
2.7%
Other values (28) 28
38.4%

합계
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean524
Minimum20
Maximum6288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:07.778386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile81.85
Q1121.75
median173.5
Q3375.25
95-th percentile1295.1
Maximum6288
Range6268
Interquartile range (IQR)253.5

Descriptive statistics

Standard deviation1259.8232
Coefficient of variation (CV)2.4042427
Kurtosis21.32956
Mean524
Median Absolute Deviation (MAD)74
Skewness4.5360382
Sum12576
Variance1587154.4
MonotonicityNot monotonic
2023-12-13T02:04:07.884351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
6288 1
 
4.2%
126 1
 
4.2%
113 1
 
4.2%
124 1
 
4.2%
20 1
 
4.2%
240 1
 
4.2%
433 1
 
4.2%
405 1
 
4.2%
370 1
 
4.2%
282 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
20 1
4.2%
79 1
4.2%
98 1
4.2%
101 1
4.2%
113 1
4.2%
115 1
4.2%
124 1
4.2%
126 1
4.2%
134 1
4.2%
145 1
4.2%
ValueCountFrequency (%)
6288 1
4.2%
1407 1
4.2%
661 1
4.2%
433 1
4.2%
405 1
4.2%
391 1
4.2%
370 1
4.2%
324 1
4.2%
282 1
4.2%
240 1
4.2%

한국인배우자
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.666667
Minimum3
Maximum872
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:08.022874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile9.6
Q116.5
median23
Q354
95-th percentile156.4
Maximum872
Range869
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation173.97118
Coefficient of variation (CV)2.3940988
Kurtosis21.743082
Mean72.666667
Median Absolute Deviation (MAD)12
Skewness4.5845364
Sum1744
Variance30265.971
MonotonicityNot monotonic
2023-12-13T02:04:08.134882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
21 2
 
8.3%
18 2
 
8.3%
13 2
 
8.3%
872 1
 
4.2%
40 1
 
4.2%
15 1
 
4.2%
9 1
 
4.2%
3 1
 
4.2%
37 1
 
4.2%
61 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
3 1
4.2%
9 1
4.2%
13 2
8.3%
14 1
4.2%
15 1
4.2%
17 1
4.2%
18 2
8.3%
20 1
4.2%
21 2
8.3%
25 1
4.2%
ValueCountFrequency (%)
872 1
4.2%
166 1
4.2%
102 1
4.2%
67 1
4.2%
61 1
4.2%
60 1
4.2%
52 1
4.2%
48 1
4.2%
40 1
4.2%
37 1
4.2%

결혼이민자
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.416667
Minimum4
Maximum1037
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:08.282299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile7.75
Q113.75
median26
Q357.5
95-th percentile286.1
Maximum1037
Range1033
Interquartile range (IQR)43.75

Descriptive statistics

Standard deviation212.1025
Coefficient of variation (CV)2.4544166
Kurtosis19.442479
Mean86.416667
Median Absolute Deviation (MAD)14.5
Skewness4.3102896
Sum2074
Variance44987.471
MonotonicityNot monotonic
2023-12-13T02:04:08.447520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
13 3
 
12.5%
27 2
 
8.3%
20 2
 
8.3%
1037 1
 
4.2%
75 1
 
4.2%
4 1
 
4.2%
41 1
 
4.2%
65 1
 
4.2%
68 1
 
4.2%
55 1
 
4.2%
Other values (10) 10
41.7%
ValueCountFrequency (%)
4 1
 
4.2%
7 1
 
4.2%
12 1
 
4.2%
13 3
12.5%
14 1
 
4.2%
20 2
8.3%
22 1
 
4.2%
23 1
 
4.2%
25 1
 
4.2%
27 2
8.3%
ValueCountFrequency (%)
1037 1
4.2%
323 1
4.2%
77 1
4.2%
75 1
4.2%
68 1
4.2%
65 1
4.2%
55 1
4.2%
47 1
4.2%
46 1
4.2%
41 1
4.2%

귀화자
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.333333
Minimum0
Maximum928
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:08.613357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.6
Q113
median23.5
Q344.75
95-th percentile246.6
Maximum928
Range928
Interquartile range (IQR)31.75

Descriptive statistics

Standard deviation189.18927
Coefficient of variation (CV)2.446413
Kurtosis19.719475
Mean77.333333
Median Absolute Deviation (MAD)11.5
Skewness4.3385251
Sum1856
Variance35792.58
MonotonicityNot monotonic
2023-12-13T02:04:08.765226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
13 3
 
12.5%
15 2
 
8.3%
12 2
 
8.3%
65 1
 
4.2%
23 1
 
4.2%
0 1
 
4.2%
34 1
 
4.2%
70 1
 
4.2%
44 1
 
4.2%
47 1
 
4.2%
Other values (10) 10
41.7%
ValueCountFrequency (%)
0 1
 
4.2%
8 1
 
4.2%
12 2
8.3%
13 3
12.5%
15 2
8.3%
20 1
 
4.2%
22 1
 
4.2%
23 1
 
4.2%
24 1
 
4.2%
32 1
 
4.2%
ValueCountFrequency (%)
928 1
4.2%
273 1
4.2%
97 1
4.2%
70 1
4.2%
65 1
4.2%
47 1
4.2%
44 1
4.2%
39 1
4.2%
37 1
4.2%
34 1
4.2%

자녀외국출생
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5833333
Minimum0
Maximum55
Zeros7
Zeros (%)29.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:08.901378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile13.65
Maximum55
Range55
Interquartile range (IQR)4

Descriptive statistics

Standard deviation11.2169
Coefficient of variation (CV)2.4473236
Kurtosis19.667358
Mean4.5833333
Median Absolute Deviation (MAD)1
Skewness4.3117347
Sum110
Variance125.81884
MonotonicityNot monotonic
2023-12-13T02:04:09.027031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 7
29.2%
1 6
25.0%
4 4
16.7%
2 2
 
8.3%
55 1
 
4.2%
3 1
 
4.2%
15 1
 
4.2%
5 1
 
4.2%
6 1
 
4.2%
ValueCountFrequency (%)
0 7
29.2%
1 6
25.0%
2 2
 
8.3%
3 1
 
4.2%
4 4
16.7%
5 1
 
4.2%
6 1
 
4.2%
15 1
 
4.2%
55 1
 
4.2%
ValueCountFrequency (%)
55 1
 
4.2%
15 1
 
4.2%
6 1
 
4.2%
5 1
 
4.2%
4 4
16.7%
3 1
 
4.2%
2 2
 
8.3%
1 6
25.0%
0 7
29.2%

자녀국내출생
Real number (ℝ)

HIGH CORRELATION 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean145.91667
Minimum4
Maximum1751
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:09.161811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile21.45
Q132.75
median55
Q393
95-th percentile339.2
Maximum1751
Range1747
Interquartile range (IQR)60.25

Descriptive statistics

Standard deviation350.11935
Coefficient of variation (CV)2.3994473
Kurtosis21.522697
Mean145.91667
Median Absolute Deviation (MAD)29
Skewness4.5582137
Sum3502
Variance122583.56
MonotonicityNot monotonic
2023-12-13T02:04:09.309458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
88 2
 
8.3%
26 2
 
8.3%
1751 1
 
4.2%
34 1
 
4.2%
29 1
 
4.2%
4 1
 
4.2%
62 1
 
4.2%
127 1
 
4.2%
118 1
 
4.2%
108 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
4 1
4.2%
21 1
4.2%
24 1
4.2%
26 2
8.3%
29 1
4.2%
34 1
4.2%
38 1
4.2%
41 1
4.2%
45 1
4.2%
48 1
4.2%
ValueCountFrequency (%)
1751 1
4.2%
362 1
4.2%
210 1
4.2%
127 1
4.2%
118 1
4.2%
108 1
4.2%
88 2
8.3%
82 1
4.2%
62 1
4.2%
60 1
4.2%

동거인내국인
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.41667
Minimum9
Maximum1493
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:09.470829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile21.2
Q136.75
median53
Q391.75
95-th percentile202.65
Maximum1493
Range1484
Interquartile range (IQR)55

Descriptive statistics

Standard deviation295.02305
Coefficient of variation (CV)2.3712503
Kurtosis22.720618
Mean124.41667
Median Absolute Deviation (MAD)21
Skewness4.716877
Sum2986
Variance87038.601
MonotonicityNot monotonic
2023-12-13T02:04:09.631329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
37 2
 
8.3%
1493 1
 
4.2%
29 1
 
4.2%
44 1
 
4.2%
9 1
 
4.2%
57 1
 
4.2%
101 1
 
4.2%
94 1
 
4.2%
99 1
 
4.2%
71 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
9 1
4.2%
20 1
4.2%
28 1
4.2%
29 1
4.2%
35 1
4.2%
36 1
4.2%
37 2
8.3%
39 1
4.2%
44 1
4.2%
47 1
4.2%
ValueCountFrequency (%)
1493 1
4.2%
210 1
4.2%
161 1
4.2%
101 1
4.2%
99 1
4.2%
94 1
4.2%
91 1
4.2%
80 1
4.2%
71 1
4.2%
61 1
4.2%

동거인외국인
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct14
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.666667
Minimum0
Maximum152
Zeros3
Zeros (%)12.5%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T02:04:09.768465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3.5
Q37.25
95-th percentile52.3
Maximum152
Range152
Interquartile range (IQR)6.25

Descriptive statistics

Standard deviation31.94243
Coefficient of variation (CV)2.5217708
Kurtosis17.249027
Mean12.666667
Median Absolute Deviation (MAD)2.5
Skewness4.04241
Sum304
Variance1020.3188
MonotonicityNot monotonic
2023-12-13T02:04:09.930810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 4
16.7%
1 4
16.7%
5 3
12.5%
0 3
12.5%
152 1
 
4.2%
10 1
 
4.2%
58 1
 
4.2%
3 1
 
4.2%
4 1
 
4.2%
6 1
 
4.2%
Other values (4) 4
16.7%
ValueCountFrequency (%)
0 3
12.5%
1 4
16.7%
2 4
16.7%
3 1
 
4.2%
4 1
 
4.2%
5 3
12.5%
6 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
ValueCountFrequency (%)
152 1
 
4.2%
58 1
 
4.2%
20 1
 
4.2%
10 1
 
4.2%
9 1
 
4.2%
8 1
 
4.2%
7 1
 
4.2%
6 1
 
4.2%
5 3
12.5%
4 1
 
4.2%

Interactions

2023-12-13T02:04:06.305822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:00.542522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.417969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.154493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.997497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.751546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.575886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.660507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.401923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:00.648628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.513319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.252945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.080179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.864885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.676106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.746399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.472347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:00.740651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.604306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.330453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.154818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.953210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.788056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.816255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.552801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:00.850180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.704302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.431634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.228298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.044431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.891222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.891170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.623306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:00.948191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.790519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.518851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.297238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.126070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.990269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.984362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.733112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.058583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.874166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.607468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.411488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.219807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.095004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.058625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.823503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.177993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.958690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.697164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.532732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.332780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.183579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.141876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.909748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:01.293069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.064918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:02.865702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:03.627492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:04.465889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:05.578473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:04:06.225300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:04:10.028528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분합계한국인배우자결혼이민자귀화자자녀외국출생자녀국내출생동거인내국인동거인외국인
구분1.0001.0001.0001.0001.0001.0001.0001.0001.000
합계1.0001.0001.0001.0001.0000.9751.0001.0000.975
한국인배우자1.0001.0001.0000.9841.0000.7801.0001.0000.780
결혼이민자1.0001.0000.9841.0001.0001.0001.0000.9841.000
귀화자1.0001.0001.0001.0001.0000.9751.0001.0000.975
자녀외국출생1.0000.9750.7801.0000.9751.0000.9750.7800.975
자녀국내출생1.0001.0001.0001.0001.0000.9751.0001.0000.975
동거인내국인1.0001.0001.0000.9841.0000.7801.0001.0000.780
동거인외국인1.0000.9750.7801.0000.9750.9750.9750.7801.000
2023-12-13T02:04:10.167249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계한국인배우자결혼이민자귀화자자녀외국출생자녀국내출생동거인내국인동거인외국인
합계1.0000.9770.9470.9310.8030.9890.9680.850
한국인배우자0.9771.0000.8890.8950.7870.9850.9450.867
결혼이민자0.9470.8891.0000.9170.8450.9070.9310.838
귀화자0.9310.8950.9171.0000.8040.9090.8700.869
자녀외국출생0.8030.7870.8450.8041.0000.8060.7630.749
자녀국내출생0.9890.9850.9070.9090.8061.0000.9590.839
동거인내국인0.9680.9450.9310.8700.7630.9591.0000.815
동거인외국인0.8500.8670.8380.8690.7490.8390.8151.000

Missing values

2023-12-13T02:04:07.007085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:04:07.138871image/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

구분합계한국인배우자결혼이민자귀화자자녀외국출생자녀국내출생동거인내국인동거인외국인
0경주시628887210379285517511493152
1감포읍10113148226362
2안강읍6611027797421016110
3건천읍225322737360615
4외동읍14071663232731536221058
5양남면168212522048493
6내남면145201220052392
7산내면7914713021204
8서면98131312024351
9현곡면324604639588806
구분합계한국인배우자결혼이민자귀화자자녀외국출생자녀국내출생동거인내국인동거인외국인
14성건동3914875654889120
15월성동179252313158581
16선도동282404732182719
17용강동3705255474108995
18황성동4056768446118948
19동천동43361657021271017
20불국동240374134462575
21보덕동203400490
22황오동12492723126371
23황남동113151312029440