Overview

Dataset statistics

Number of variables11
Number of observations170
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.2 KiB
Average record size in memory97.8 B

Variable types

Categorical2
Numeric9

Dataset

Description울산광역시 울주군 장애인 등록 현황에 대한 데이터로 장애인유형별(지체,시각,청각,언어,지적,자폐성,뇌변병,정신 등) 등록자료를 읍면별로를 제공합니다.
URLhttps://www.data.go.kr/data/15102402/fileData.do

Alerts

합계 is highly overall correlated with 남성 and 7 other fieldsHigh correlation
남성 is highly overall correlated with 합계 and 7 other fieldsHigh correlation
여성 is highly overall correlated with 합계 and 7 other fieldsHigh correlation
소계(심한 장애) is highly overall correlated with 합계 and 4 other fieldsHigh correlation
남성(심한 장애) is highly overall correlated with 합계 and 4 other fieldsHigh correlation
여성(심한 장애) is highly overall correlated with 합계 and 4 other fieldsHigh correlation
소계(심하지 않은 장애) is highly overall correlated with 합계 and 4 other fieldsHigh correlation
남성(심하지 않은 장애) is highly overall correlated with 합계 and 4 other fieldsHigh correlation
여성(심하지 않은 장애) is highly overall correlated with 합계 and 4 other fieldsHigh correlation
남성 has 5 (2.9%) zerosZeros
여성 has 29 (17.1%) zerosZeros
소계(심한 장애) has 24 (14.1%) zerosZeros
남성(심한 장애) has 33 (19.4%) zerosZeros
여성(심한 장애) has 49 (28.8%) zerosZeros
소계(심하지 않은 장애) has 60 (35.3%) zerosZeros
남성(심하지 않은 장애) has 65 (38.2%) zerosZeros
여성(심하지 않은 장애) has 81 (47.6%) zerosZeros

Reproduction

Analysis started2023-12-12 06:08:24.997565
Analysis finished2023-12-12 06:08:33.796376
Duration8.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct12
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
범서읍
15 
온산읍
15 
언양읍
15 
삼남읍
15 
두동면
15 
Other values (7)
95 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
범서읍 15
8.8%
온산읍 15
8.8%
언양읍 15
8.8%
삼남읍 15
8.8%
두동면 15
8.8%
온양읍 14
8.2%
청량읍 14
8.2%
서생면 14
8.2%
웅촌면 14
8.2%
두서면 14
8.2%
Other values (2) 25
14.7%

Length

2023-12-12T15:08:33.880989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
범서읍 15
8.8%
온산읍 15
8.8%
언양읍 15
8.8%
삼남읍 15
8.8%
두동면 15
8.8%
온양읍 14
8.2%
청량읍 14
8.2%
서생면 14
8.2%
웅촌면 14
8.2%
두서면 14
8.2%
Other values (2) 25
14.7%

장애유형
Categorical

Distinct15
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
지체
12 
시각
12 
청각
12 
언어
12 
지적
12 
Other values (10)
110 

Length

Max length5
Median length2
Mean length2.4117647
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지체
2nd row시각
3rd row청각
4th row언어
5th row지적

Common Values

ValueCountFrequency (%)
지체 12
 
7.1%
시각 12
 
7.1%
청각 12
 
7.1%
언어 12
 
7.1%
지적 12
 
7.1%
뇌병변 12
 
7.1%
자폐성 12
 
7.1%
정신 12
 
7.1%
신장 12
 
7.1%
호흡기 12
 
7.1%
Other values (5) 50
29.4%

Length

2023-12-12T15:08:34.064276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지체 12
 
7.1%
시각 12
 
7.1%
청각 12
 
7.1%
언어 12
 
7.1%
지적 12
 
7.1%
뇌병변 12
 
7.1%
자폐성 12
 
7.1%
정신 12
 
7.1%
신장 12
 
7.1%
호흡기 12
 
7.1%
Other values (5) 50
29.4%

합계
Real number (ℝ)

HIGH CORRELATION 

Distinct84
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.323529
Minimum1
Maximum1107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:34.239092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13.25
median13.5
Q381.5
95-th percentile275.85
Maximum1107
Range1106
Interquartile range (IQR)78.25

Descriptive statistics

Standard deviation138.81918
Coefficient of variation (CV)1.9740076
Kurtosis22.092997
Mean70.323529
Median Absolute Deviation (MAD)12.5
Skewness4.1140516
Sum11955
Variance19270.765
MonotonicityNot monotonic
2023-12-12T15:08:34.432308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 16
 
9.4%
3 14
 
8.2%
2 13
 
7.6%
7 7
 
4.1%
5 6
 
3.5%
11 6
 
3.5%
10 5
 
2.9%
4 4
 
2.4%
9 4
 
2.4%
8 3
 
1.8%
Other values (74) 92
54.1%
ValueCountFrequency (%)
1 16
9.4%
2 13
7.6%
3 14
8.2%
4 4
 
2.4%
5 6
 
3.5%
6 2
 
1.2%
7 7
4.1%
8 3
 
1.8%
9 4
 
2.4%
10 5
 
2.9%
ValueCountFrequency (%)
1107 1
0.6%
659 1
0.6%
626 1
0.6%
568 1
0.6%
527 1
0.6%
466 1
0.6%
395 1
0.6%
300 1
0.6%
288 1
0.6%
261 1
0.6%

남성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.576471
Minimum0
Maximum695
Zeros5
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:34.588768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median9
Q344.5
95-th percentile159.5
Maximum695
Range695
Interquartile range (IQR)41.5

Descriptive statistics

Standard deviation85.377183
Coefficient of variation (CV)2.0534976
Kurtosis24.319621
Mean41.576471
Median Absolute Deviation (MAD)8
Skewness4.3537488
Sum7068
Variance7289.2633
MonotonicityNot monotonic
2023-12-12T15:08:34.736635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 23
 
13.5%
3 13
 
7.6%
2 12
 
7.1%
5 8
 
4.7%
9 7
 
4.1%
8 7
 
4.1%
6 5
 
2.9%
4 5
 
2.9%
7 5
 
2.9%
0 5
 
2.9%
Other values (57) 80
47.1%
ValueCountFrequency (%)
0 5
 
2.9%
1 23
13.5%
2 12
7.1%
3 13
7.6%
4 5
 
2.9%
5 8
 
4.7%
6 5
 
2.9%
7 5
 
2.9%
8 7
 
4.1%
9 7
 
4.1%
ValueCountFrequency (%)
695 1
0.6%
388 1
0.6%
379 1
0.6%
376 1
0.6%
344 1
0.6%
298 1
0.6%
218 1
0.6%
181 1
0.6%
164 1
0.6%
154 1
0.6%

여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct67
Distinct (%)39.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.747059
Minimum0
Maximum412
Zeros29
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:34.883796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q336
95-th percentile118.55
Maximum412
Range412
Interquartile range (IQR)35

Descriptive statistics

Standard deviation54.097552
Coefficient of variation (CV)1.8818465
Kurtosis18.554353
Mean28.747059
Median Absolute Deviation (MAD)5
Skewness3.7355262
Sum4887
Variance2926.5451
MonotonicityNot monotonic
2023-12-12T15:08:35.001085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 29
17.1%
1 20
 
11.8%
2 14
 
8.2%
4 13
 
7.6%
3 8
 
4.7%
6 5
 
2.9%
5 4
 
2.4%
17 4
 
2.4%
41 2
 
1.2%
30 2
 
1.2%
Other values (57) 69
40.6%
ValueCountFrequency (%)
0 29
17.1%
1 20
11.8%
2 14
8.2%
3 8
 
4.7%
4 13
7.6%
5 4
 
2.4%
6 5
 
2.9%
7 1
 
0.6%
8 2
 
1.2%
9 2
 
1.2%
ValueCountFrequency (%)
412 1
0.6%
283 1
0.6%
238 1
0.6%
189 1
0.6%
183 1
0.6%
177 1
0.6%
168 1
0.6%
124 1
0.6%
119 1
0.6%
118 1
0.6%

소계(심한 장애)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)40.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.617647
Minimum0
Maximum224
Zeros24
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:35.164938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q335.5
95-th percentile114.1
Maximum224
Range224
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation42.791095
Coefficient of variation (CV)1.5494113
Kurtosis6.6312901
Mean27.617647
Median Absolute Deviation (MAD)9
Skewness2.4449154
Sum4695
Variance1831.0778
MonotonicityNot monotonic
2023-12-12T15:08:35.290492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24
 
14.1%
2 16
 
9.4%
1 15
 
8.8%
3 8
 
4.7%
7 5
 
2.9%
5 5
 
2.9%
10 5
 
2.9%
20 4
 
2.4%
6 4
 
2.4%
16 4
 
2.4%
Other values (59) 80
47.1%
ValueCountFrequency (%)
0 24
14.1%
1 15
8.8%
2 16
9.4%
3 8
 
4.7%
4 4
 
2.4%
5 5
 
2.9%
6 4
 
2.4%
7 5
 
2.9%
8 2
 
1.2%
9 3
 
1.8%
ValueCountFrequency (%)
224 1
0.6%
220 1
0.6%
200 1
0.6%
190 1
0.6%
151 1
0.6%
128 1
0.6%
122 1
0.6%
118 1
0.6%
115 1
0.6%
113 1
0.6%

남성(심한 장애)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)31.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.294118
Minimum0
Maximum142
Zeros33
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:35.407810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q318.75
95-th percentile68.95
Maximum142
Range142
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation26.102585
Coefficient of variation (CV)1.6019637
Kurtosis7.6500487
Mean16.294118
Median Absolute Deviation (MAD)5
Skewness2.6012205
Sum2770
Variance681.34494
MonotonicityNot monotonic
2023-12-12T15:08:35.830654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33
19.4%
1 22
 
12.9%
3 9
 
5.3%
2 9
 
5.3%
5 8
 
4.7%
9 7
 
4.1%
15 5
 
2.9%
6 5
 
2.9%
4 5
 
2.9%
7 5
 
2.9%
Other values (44) 62
36.5%
ValueCountFrequency (%)
0 33
19.4%
1 22
12.9%
2 9
 
5.3%
3 9
 
5.3%
4 5
 
2.9%
5 8
 
4.7%
6 5
 
2.9%
7 5
 
2.9%
8 5
 
2.9%
9 7
 
4.1%
ValueCountFrequency (%)
142 1
0.6%
138 1
0.6%
124 1
0.6%
115 1
0.6%
82 1
0.6%
81 1
0.6%
78 1
0.6%
76 1
0.6%
73 1
0.6%
64 1
0.6%

여성(심한 장애)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.323529
Minimum0
Maximum86
Zeros49
Zeros (%)28.8%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:35.983640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q314.75
95-th percentile43.1
Maximum86
Range86
Interquartile range (IQR)14.75

Descriptive statistics

Standard deviation17.359275
Coefficient of variation (CV)1.5330268
Kurtosis5.5244828
Mean11.323529
Median Absolute Deviation (MAD)3
Skewness2.2771959
Sum1925
Variance301.34441
MonotonicityNot monotonic
2023-12-12T15:08:36.138869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 49
28.8%
2 17
 
10.0%
1 15
 
8.8%
4 7
 
4.1%
12 6
 
3.5%
3 6
 
3.5%
6 5
 
2.9%
13 5
 
2.9%
9 4
 
2.4%
8 4
 
2.4%
Other values (37) 52
30.6%
ValueCountFrequency (%)
0 49
28.8%
1 15
 
8.8%
2 17
 
10.0%
3 6
 
3.5%
4 7
 
4.1%
5 3
 
1.8%
6 5
 
2.9%
7 1
 
0.6%
8 4
 
2.4%
9 4
 
2.4%
ValueCountFrequency (%)
86 1
0.6%
85 1
0.6%
78 1
0.6%
73 1
0.6%
66 1
0.6%
64 1
0.6%
60 1
0.6%
45 1
0.6%
44 1
0.6%
42 1
0.6%

소계(심하지 않은 장애)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct56
Distinct (%)32.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.705882
Minimum0
Maximum887
Zeros60
Zeros (%)35.3%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:36.271318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q326
95-th percentile218.6
Maximum887
Range887
Interquartile range (IQR)26

Descriptive statistics

Standard deviation111.17275
Coefficient of variation (CV)2.6032187
Kurtosis24.586883
Mean42.705882
Median Absolute Deviation (MAD)3
Skewness4.480893
Sum7260
Variance12359.38
MonotonicityNot monotonic
2023-12-12T15:08:36.400063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60
35.3%
1 16
 
9.4%
3 9
 
5.3%
2 7
 
4.1%
4 7
 
4.1%
11 5
 
2.9%
8 5
 
2.9%
10 4
 
2.4%
27 3
 
1.8%
7 3
 
1.8%
Other values (46) 51
30.0%
ValueCountFrequency (%)
0 60
35.3%
1 16
 
9.4%
2 7
 
4.1%
3 9
 
5.3%
4 7
 
4.1%
5 2
 
1.2%
6 1
 
0.6%
7 3
 
1.8%
8 5
 
2.9%
9 1
 
0.6%
ValueCountFrequency (%)
887 1
0.6%
537 1
0.6%
511 1
0.6%
455 1
0.6%
422 1
0.6%
388 1
0.6%
292 1
0.6%
249 1
0.6%
224 1
0.6%
212 1
0.6%

남성(심하지 않은 장애)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.282353
Minimum0
Maximum553
Zeros65
Zeros (%)38.2%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:36.553046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q314.75
95-th percentile121.55
Maximum553
Range553
Interquartile range (IQR)14.75

Descriptive statistics

Standard deviation67.443706
Coefficient of variation (CV)2.6676198
Kurtosis27.091007
Mean25.282353
Median Absolute Deviation (MAD)2
Skewness4.7071265
Sum4298
Variance4548.6535
MonotonicityNot monotonic
2023-12-12T15:08:36.695575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 65
38.2%
1 18
 
10.6%
2 10
 
5.9%
3 8
 
4.7%
5 7
 
4.1%
7 5
 
2.9%
8 3
 
1.8%
79 3
 
1.8%
24 3
 
1.8%
6 3
 
1.8%
Other values (38) 45
26.5%
ValueCountFrequency (%)
0 65
38.2%
1 18
 
10.6%
2 10
 
5.9%
3 8
 
4.7%
4 2
 
1.2%
5 7
 
4.1%
6 3
 
1.8%
7 5
 
2.9%
8 3
 
1.8%
9 1
 
0.6%
ValueCountFrequency (%)
553 1
0.6%
312 1
0.6%
297 1
0.6%
295 1
0.6%
271 1
0.6%
241 1
0.6%
160 1
0.6%
147 1
0.6%
122 1
0.6%
121 1
0.6%

여성(심하지 않은 장애)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct44
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.423529
Minimum0
Maximum334
Zeros81
Zeros (%)47.6%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-12-12T15:08:36.849907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q38.75
95-th percentile97.05
Maximum334
Range334
Interquartile range (IQR)8.75

Descriptive statistics

Standard deviation44.179268
Coefficient of variation (CV)2.5356096
Kurtosis21.141149
Mean17.423529
Median Absolute Deviation (MAD)1
Skewness4.1673379
Sum2962
Variance1951.8077
MonotonicityNot monotonic
2023-12-12T15:08:36.995291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0 81
47.6%
1 13
 
7.6%
2 10
 
5.9%
3 9
 
5.3%
4 6
 
3.5%
5 5
 
2.9%
16 3
 
1.8%
30 2
 
1.2%
22 2
 
1.2%
65 2
 
1.2%
Other values (34) 37
21.8%
ValueCountFrequency (%)
0 81
47.6%
1 13
 
7.6%
2 10
 
5.9%
3 9
 
5.3%
4 6
 
3.5%
5 5
 
2.9%
6 1
 
0.6%
7 1
 
0.6%
8 1
 
0.6%
9 1
 
0.6%
ValueCountFrequency (%)
334 1
0.6%
242 1
0.6%
199 1
0.6%
158 1
0.6%
151 1
0.6%
147 1
0.6%
132 1
0.6%
102 2
1.2%
91 1
0.6%
79 1
0.6%

Interactions

2023-12-12T15:08:32.468835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.393773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.124380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.910200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.648257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.465775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:29.865116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.613503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.499441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.569623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.464730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.201213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.985423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.724627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.592335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:29.943839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.697146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.609737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.688847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.552078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.283304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.065550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.816026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.717700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.035897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.786950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.710382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.784672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.629276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.360807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.139282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.919356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.809018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.115695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.872629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.791670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.885126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.701510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.444407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.225249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.998360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.909914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.195198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.992400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.890721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:33.001063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.780194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.549995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.334490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.085227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:29.025533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.282034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.110695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.051998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:33.107807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.857895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.631446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.418470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.168980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:29.127382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.353101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.206983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.156019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:33.221071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:25.953697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.714079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.490416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.274161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:29.615048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.429549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.297521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.253989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:33.336861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.038358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:26.811566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:27.568575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:28.375541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:29.749022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:30.513304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:31.385320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:08:32.363537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:08:37.098805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동장애유형합계남성여성소계(심한 장애)남성(심한 장애)여성(심한 장애)소계(심하지 않은 장애)남성(심하지 않은 장애)여성(심하지 않은 장애)
읍면동1.0000.0000.0000.0000.0000.0000.0000.2630.0000.0000.000
장애유형0.0001.0000.5750.5930.5080.5590.6220.5520.5960.6250.557
합계0.0000.5751.0000.9980.9110.7930.7670.7450.9670.9510.904
남성0.0000.5930.9981.0000.9000.7760.7660.7020.9800.9680.915
여성0.0000.5080.9110.9001.0000.7680.8860.7030.9810.8990.992
소계(심한 장애)0.0000.5590.7930.7760.7681.0000.9410.8970.7570.8130.760
남성(심한 장애)0.0000.6220.7670.7660.8860.9411.0000.8410.8720.7540.877
여성(심한 장애)0.2630.5520.7450.7020.7030.8970.8411.0000.6840.6360.642
소계(심하지 않은 장애)0.0000.5960.9670.9800.9810.7570.8720.6841.0000.9980.990
남성(심하지 않은 장애)0.0000.6250.9510.9680.8990.8130.7540.6360.9981.0000.948
여성(심하지 않은 장애)0.0000.5570.9040.9150.9920.7600.8770.6420.9900.9481.000
2023-12-12T15:08:37.224503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장애유형읍면동
장애유형1.0000.000
읍면동0.0001.000
2023-12-12T15:08:37.369966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계남성여성소계(심한 장애)남성(심한 장애)여성(심한 장애)소계(심하지 않은 장애)남성(심하지 않은 장애)여성(심하지 않은 장애)읍면동장애유형
합계1.0000.9840.9660.8950.8540.8910.6090.6200.6560.0000.296
남성0.9841.0000.9160.8860.8720.8520.5910.6170.6230.0000.309
여성0.9660.9161.0000.8680.7990.9160.6110.6020.6870.0000.239
소계(심한 장애)0.8950.8860.8681.0000.9740.9560.2970.3130.3750.0000.260
남성(심한 장애)0.8540.8720.7990.9741.0000.8810.2530.2710.3330.0000.316
여성(심한 장애)0.8910.8520.9160.9560.8811.0000.3500.3610.4110.1110.236
소계(심하지 않은 장애)0.6090.5910.6110.2970.2530.3501.0000.9850.9500.0000.297
남성(심하지 않은 장애)0.6200.6170.6020.3130.2710.3610.9851.0000.9090.0000.340
여성(심하지 않은 장애)0.6560.6230.6870.3750.3330.4110.9500.9091.0000.0000.270
읍면동0.0000.0000.0000.0000.0000.1110.0000.0000.0001.0000.000
장애유형0.2960.3090.2390.2600.3160.2360.2970.3400.2700.0001.000

Missing values

2023-12-12T15:08:33.485314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:08:33.716259image/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

읍면동장애유형합계남성여성소계(심한 장애)남성(심한 장애)여성(심한 장애)소계(심하지 않은 장애)남성(심하지 않은 장애)여성(심하지 않은 장애)
0범서읍지체110769541222014278887553334
1범서읍시각2041317341241716310756
2범서읍청각3952181771035845292160132
3범서읍언어281711171161165
4범서읍지적2241388622413886000
5범서읍뇌병변25713911815178731066145
6범서읍자폐성4435944359000
7범서읍정신542430532330110
8범서읍신장1096940694128402812
9범서읍심장12391138101
읍면동장애유형합계남성여성소계(심한 장애)남성(심한 장애)여성(심한 장애)소계(심하지 않은 장애)남성(심하지 않은 장애)여성(심하지 않은 장애)
160삼동면청각311417431271116
161삼동면언어101101000
162삼동면지적14861486000
163삼동면뇌병변1275853422
164삼동면자폐성110110000
165삼동면정신10641064000
166삼동면신장312202110
167삼동면호흡기220220000
168삼동면220000220
169삼동면장루.요루211000211