Overview

Dataset statistics

Number of variables14
Number of observations321
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.1 KiB
Average record size in memory121.4 B

Variable types

Categorical5
Numeric9

Dataset

Description대구광역시 북구 관내 유형별, 동별 장애인등록현황 정보(성별, 장애 정도, 장애 유형 등으로 분류함)를 제공합니다
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15030561/fileData.do

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
데이터기준일자 has constant value ""Constant
남성 여성-합계 is highly overall correlated with 남성 and 7 other fieldsHigh correlation
남성 is highly overall correlated with 남성 여성-합계 and 7 other fieldsHigh correlation
여성 is highly overall correlated with 남성 여성-합계 and 7 other fieldsHigh correlation
심한 장애-소계 is highly overall correlated with 남성 여성-합계 and 4 other fieldsHigh correlation
심한 장애-남성 is highly overall correlated with 남성 여성-합계 and 4 other fieldsHigh correlation
심한 장애-여성 is highly overall correlated with 남성 여성-합계 and 4 other fieldsHigh correlation
심하지 않은 장애-소계 is highly overall correlated with 남성 여성-합계 and 4 other fieldsHigh correlation
심하지 않은 장애-남성 is highly overall correlated with 남성 여성-합계 and 4 other fieldsHigh correlation
심하지 않은 장애-여성 is highly overall correlated with 남성 여성-합계 and 4 other fieldsHigh correlation
남성 has 8 (2.5%) zerosZeros
여성 has 53 (16.5%) zerosZeros
심한 장애-소계 has 46 (14.3%) zerosZeros
심한 장애-남성 has 58 (18.1%) zerosZeros
심한 장애-여성 has 99 (30.8%) zerosZeros
심하지 않은 장애-소계 has 98 (30.5%) zerosZeros
심하지 않은 장애-남성 has 113 (35.2%) zerosZeros
심하지 않은 장애-여성 has 138 (43.0%) zerosZeros

Reproduction

Analysis started2024-03-15 00:53:29.021670
Analysis finished2024-03-15 00:53:49.467683
Duration20.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
대구광역시
321 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구광역시 321
100.0%

Length

2024-03-15T09:53:49.581769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:53:49.754163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 321
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
북구
321 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
북구 321
100.0%

Length

2024-03-15T09:53:49.929980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:53:50.153240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
북구 321
100.0%

읍면동
Categorical

Distinct23
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
국우동
 
16
동천동
 
15
침산2동
 
15
침산3동
 
15
산격1동
 
15
Other values (18)
245 

Length

Max length5
Median length4
Mean length3.5576324
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국우동 16
 
5.0%
동천동 15
 
4.7%
침산2동 15
 
4.7%
침산3동 15
 
4.7%
산격1동 15
 
4.7%
읍내동 15
 
4.7%
관음동 15
 
4.7%
산격4동 15
 
4.7%
태전2동 15
 
4.7%
태전1동 15
 
4.7%
Other values (13) 170
53.0%

Length

2024-03-15T09:53:50.424581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
국우동 16
 
5.0%
침산2동 15
 
4.7%
침산3동 15
 
4.7%
산격1동 15
 
4.7%
읍내동 15
 
4.7%
관음동 15
 
4.7%
산격4동 15
 
4.7%
태전2동 15
 
4.7%
태전1동 15
 
4.7%
관문동 15
 
4.7%
Other values (13) 170
53.0%

장애유형
Categorical

Distinct15
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
지체
23 
시각
23 
청각
23 
언어
23 
지적
23 
Other values (10)
206 

Length

Max length5
Median length2
Mean length2.3831776
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지체 23
 
7.2%
시각 23
 
7.2%
청각 23
 
7.2%
언어 23
 
7.2%
지적 23
 
7.2%
뇌병변 23
 
7.2%
자폐성 23
 
7.2%
정신 23
 
7.2%
신장 23
 
7.2%
23
 
7.2%
Other values (5) 91
28.3%

Length

2024-03-15T09:53:50.683711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지체 23
 
7.2%
시각 23
 
7.2%
청각 23
 
7.2%
언어 23
 
7.2%
지적 23
 
7.2%
뇌병변 23
 
7.2%
자폐성 23
 
7.2%
정신 23
 
7.2%
신장 23
 
7.2%
23
 
7.2%
Other values (5) 91
28.3%

남성 여성-합계
Real number (ℝ)

HIGH CORRELATION 

Distinct131
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.495327
Minimum1
Maximum701
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:51.135061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median20
Q386
95-th percentile299
Maximum701
Range700
Interquartile range (IQR)83

Descriptive statistics

Standard deviation116.7704
Coefficient of variation (CV)1.6802626
Kurtosis8.7907687
Mean69.495327
Median Absolute Deviation (MAD)18
Skewness2.8036826
Sum22308
Variance13635.326
MonotonicityNot monotonic
2024-03-15T09:53:51.548283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 35
 
10.9%
3 26
 
8.1%
1 24
 
7.5%
4 11
 
3.4%
6 10
 
3.1%
7 9
 
2.8%
13 8
 
2.5%
5 6
 
1.9%
8 6
 
1.9%
9 5
 
1.6%
Other values (121) 181
56.4%
ValueCountFrequency (%)
1 24
7.5%
2 35
10.9%
3 26
8.1%
4 11
 
3.4%
5 6
 
1.9%
6 10
 
3.1%
7 9
 
2.8%
8 6
 
1.9%
9 5
 
1.6%
10 1
 
0.3%
ValueCountFrequency (%)
701 1
0.3%
681 1
0.3%
555 1
0.3%
550 1
0.3%
548 1
0.3%
537 1
0.3%
524 1
0.3%
483 1
0.3%
436 1
0.3%
419 1
0.3%

남성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct104
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.866044
Minimum0
Maximum469
Zeros8
Zeros (%)2.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:51.977132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median13
Q353
95-th percentile164
Maximum469
Range469
Interquartile range (IQR)51

Descriptive statistics

Standard deviation70.46713
Coefficient of variation (CV)1.7243443
Kurtosis11.775036
Mean40.866044
Median Absolute Deviation (MAD)12
Skewness3.1706694
Sum13118
Variance4965.6164
MonotonicityNot monotonic
2024-03-15T09:53:52.412132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 43
 
13.4%
2 32
 
10.0%
6 15
 
4.7%
3 13
 
4.0%
4 12
 
3.7%
5 11
 
3.4%
0 8
 
2.5%
11 7
 
2.2%
20 6
 
1.9%
23 6
 
1.9%
Other values (94) 168
52.3%
ValueCountFrequency (%)
0 8
 
2.5%
1 43
13.4%
2 32
10.0%
3 13
 
4.0%
4 12
 
3.7%
5 11
 
3.4%
6 15
 
4.7%
7 4
 
1.2%
8 5
 
1.6%
9 5
 
1.6%
ValueCountFrequency (%)
469 1
0.3%
436 1
0.3%
349 1
0.3%
347 1
0.3%
343 1
0.3%
333 1
0.3%
328 1
0.3%
291 1
0.3%
264 1
0.3%
252 1
0.3%

여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct93
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.629283
Minimum0
Maximum245
Zeros53
Zeros (%)16.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:52.867372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q338
95-th percentile146
Maximum245
Range245
Interquartile range (IQR)37

Descriptive statistics

Standard deviation47.42385
Coefficient of variation (CV)1.6564805
Kurtosis5.476382
Mean28.629283
Median Absolute Deviation (MAD)6
Skewness2.3685222
Sum9190
Variance2249.0215
MonotonicityNot monotonic
2024-03-15T09:53:53.198720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 53
 
16.5%
1 47
 
14.6%
2 29
 
9.0%
3 12
 
3.7%
6 11
 
3.4%
4 8
 
2.5%
5 7
 
2.2%
19 6
 
1.9%
15 5
 
1.6%
12 5
 
1.6%
Other values (83) 138
43.0%
ValueCountFrequency (%)
0 53
16.5%
1 47
14.6%
2 29
9.0%
3 12
 
3.7%
4 8
 
2.5%
5 7
 
2.2%
6 11
 
3.4%
7 3
 
0.9%
8 4
 
1.2%
9 2
 
0.6%
ValueCountFrequency (%)
245 1
0.3%
232 1
0.3%
217 1
0.3%
209 1
0.3%
206 1
0.3%
201 1
0.3%
192 1
0.3%
184 1
0.3%
181 1
0.3%
173 1
0.3%

심한 장애-소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct84
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.862928
Minimum0
Maximum249
Zeros46
Zeros (%)14.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:53.459472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q335
95-th percentile100
Maximum249
Range249
Interquartile range (IQR)34

Descriptive statistics

Standard deviation34.190549
Coefficient of variation (CV)1.3751618
Kurtosis7.7824166
Mean24.862928
Median Absolute Deviation (MAD)11
Skewness2.349468
Sum7981
Variance1168.9937
MonotonicityNot monotonic
2024-03-15T09:53:53.904159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 46
 
14.3%
1 39
 
12.1%
2 27
 
8.4%
3 10
 
3.1%
9 8
 
2.5%
5 8
 
2.5%
22 7
 
2.2%
20 6
 
1.9%
4 6
 
1.9%
37 6
 
1.9%
Other values (74) 158
49.2%
ValueCountFrequency (%)
0 46
14.3%
1 39
12.1%
2 27
8.4%
3 10
 
3.1%
4 6
 
1.9%
5 8
 
2.5%
6 5
 
1.6%
7 6
 
1.9%
8 1
 
0.3%
9 8
 
2.5%
ValueCountFrequency (%)
249 1
0.3%
181 1
0.3%
145 1
0.3%
138 1
0.3%
131 1
0.3%
126 1
0.3%
125 1
0.3%
124 1
0.3%
123 1
0.3%
115 1
0.3%

심한 장애-남성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct62
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.794393
Minimum0
Maximum144
Zeros58
Zeros (%)18.1%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:54.323429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median7
Q320
95-th percentile60
Maximum144
Range144
Interquartile range (IQR)19

Descriptive statistics

Standard deviation20.584159
Coefficient of variation (CV)1.3913487
Kurtosis7.7934823
Mean14.794393
Median Absolute Deviation (MAD)7
Skewness2.4112487
Sum4749
Variance423.70759
MonotonicityNot monotonic
2024-03-15T09:53:54.679752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 58
18.1%
1 44
 
13.7%
2 24
 
7.5%
3 10
 
3.1%
7 10
 
3.1%
9 9
 
2.8%
4 8
 
2.5%
6 8
 
2.5%
15 8
 
2.5%
17 7
 
2.2%
Other values (52) 135
42.1%
ValueCountFrequency (%)
0 58
18.1%
1 44
13.7%
2 24
7.5%
3 10
 
3.1%
4 8
 
2.5%
5 5
 
1.6%
6 8
 
2.5%
7 10
 
3.1%
8 6
 
1.9%
9 9
 
2.8%
ValueCountFrequency (%)
144 1
0.3%
117 1
0.3%
89 2
0.6%
88 1
0.3%
79 1
0.3%
75 1
0.3%
71 2
0.6%
70 2
0.6%
69 1
0.3%
62 2
0.6%

심한 장애-여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct50
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.068536
Minimum0
Maximum105
Zeros99
Zeros (%)30.8%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:55.040556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q315
95-th percentile38
Maximum105
Range105
Interquartile range (IQR)15

Descriptive statistics

Standard deviation14.302152
Coefficient of variation (CV)1.4204798
Kurtosis7.7416602
Mean10.068536
Median Absolute Deviation (MAD)4
Skewness2.3177217
Sum3232
Variance204.55154
MonotonicityNot monotonic
2024-03-15T09:53:55.517258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 99
30.8%
1 35
 
10.9%
2 13
 
4.0%
10 11
 
3.4%
6 11
 
3.4%
4 11
 
3.4%
7 10
 
3.1%
13 10
 
3.1%
3 8
 
2.5%
25 7
 
2.2%
Other values (40) 106
33.0%
ValueCountFrequency (%)
0 99
30.8%
1 35
 
10.9%
2 13
 
4.0%
3 8
 
2.5%
4 11
 
3.4%
5 7
 
2.2%
6 11
 
3.4%
7 10
 
3.1%
8 6
 
1.9%
9 5
 
1.6%
ValueCountFrequency (%)
105 1
0.3%
65 2
0.6%
64 1
0.3%
56 2
0.6%
53 1
0.3%
51 1
0.3%
49 1
0.3%
48 1
0.3%
45 1
0.3%
44 1
0.3%

심하지 않은 장애-소계
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct94
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.632399
Minimum0
Maximum577
Zeros98
Zeros (%)30.5%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:55.780975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q331
95-th percentile269
Maximum577
Range577
Interquartile range (IQR)31

Descriptive statistics

Standard deviation95.595316
Coefficient of variation (CV)2.1418368
Kurtosis8.8133084
Mean44.632399
Median Absolute Deviation (MAD)3
Skewness2.896545
Sum14327
Variance9138.4644
MonotonicityNot monotonic
2024-03-15T09:53:56.114944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 98
30.5%
1 35
 
10.9%
2 21
 
6.5%
3 19
 
5.9%
4 10
 
3.1%
11 7
 
2.2%
7 7
 
2.2%
8 6
 
1.9%
5 6
 
1.9%
6 4
 
1.2%
Other values (84) 108
33.6%
ValueCountFrequency (%)
0 98
30.5%
1 35
 
10.9%
2 21
 
6.5%
3 19
 
5.9%
4 10
 
3.1%
5 6
 
1.9%
6 4
 
1.2%
7 7
 
2.2%
8 6
 
1.9%
9 3
 
0.9%
ValueCountFrequency (%)
577 1
0.3%
536 1
0.3%
445 1
0.3%
431 1
0.3%
425 1
0.3%
410 1
0.3%
369 1
0.3%
368 1
0.3%
360 1
0.3%
341 1
0.3%

심하지 않은 장애-남성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct84
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.071651
Minimum0
Maximum381
Zeros113
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:56.386725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q318
95-th percentile146
Maximum381
Range381
Interquartile range (IQR)18

Descriptive statistics

Standard deviation57.060915
Coefficient of variation (CV)2.1886191
Kurtosis11.745502
Mean26.071651
Median Absolute Deviation (MAD)2
Skewness3.2242233
Sum8369
Variance3255.948
MonotonicityNot monotonic
2024-03-15T09:53:56.845304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 113
35.2%
1 39
 
12.1%
2 17
 
5.3%
3 17
 
5.3%
4 11
 
3.4%
6 9
 
2.8%
5 7
 
2.2%
9 5
 
1.6%
8 5
 
1.6%
17 4
 
1.2%
Other values (74) 94
29.3%
ValueCountFrequency (%)
0 113
35.2%
1 39
 
12.1%
2 17
 
5.3%
3 17
 
5.3%
4 11
 
3.4%
5 7
 
2.2%
6 9
 
2.8%
7 4
 
1.2%
8 5
 
1.6%
9 5
 
1.6%
ValueCountFrequency (%)
381 1
0.3%
347 1
0.3%
272 1
0.3%
270 1
0.3%
259 1
0.3%
258 1
0.3%
221 1
0.3%
216 1
0.3%
215 1
0.3%
213 1
0.3%

심하지 않은 장애-여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct73
Distinct (%)22.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.560748
Minimum0
Maximum196
Zeros138
Zeros (%)43.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-15T09:53:57.285138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q311
95-th percentile113
Maximum196
Range196
Interquartile range (IQR)11

Descriptive statistics

Standard deviation39.402136
Coefficient of variation (CV)2.1228744
Kurtosis5.9450602
Mean18.560748
Median Absolute Deviation (MAD)1
Skewness2.5630628
Sum5958
Variance1552.5283
MonotonicityNot monotonic
2024-03-15T09:53:57.760669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 138
43.0%
1 43
 
13.4%
2 23
 
7.2%
4 7
 
2.2%
6 7
 
2.2%
3 6
 
1.9%
9 5
 
1.6%
5 5
 
1.6%
16 3
 
0.9%
13 3
 
0.9%
Other values (63) 81
25.2%
ValueCountFrequency (%)
0 138
43.0%
1 43
 
13.4%
2 23
 
7.2%
3 6
 
1.9%
4 7
 
2.2%
5 5
 
1.6%
6 7
 
2.2%
7 1
 
0.3%
8 3
 
0.9%
9 5
 
1.6%
ValueCountFrequency (%)
196 1
0.3%
189 1
0.3%
175 1
0.3%
172 1
0.3%
155 2
0.6%
153 2
0.6%
152 1
0.3%
148 1
0.3%
142 2
0.6%
139 1
0.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2023-12-31
321 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12-31
2nd row2023-12-31
3rd row2023-12-31
4th row2023-12-31
5th row2023-12-31

Common Values

ValueCountFrequency (%)
2023-12-31 321
100.0%

Length

2024-03-15T09:53:58.189328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:53:58.512629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-12-31 321
100.0%

Interactions

2024-03-15T09:53:47.117780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:30.078014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:32.006588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:34.184939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:36.856555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:39.529272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:41.874053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:43.645492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:45.502577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:47.289687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:30.324888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:32.216957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:34.464976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:37.130724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:39.808446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:42.033726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:43.811906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:45.678199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:47.469848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:30.470724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:32.349239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:34.763905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:37.510298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:40.059561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:42.175487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:43.957286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:45.835256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:47.651771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:30.627183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:32.589639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:35.170070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:37.826582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:40.341679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:42.331081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:44.211898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:45.991182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:47.909518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:30.798708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:32.833320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:35.369623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:38.120564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:40.656061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:42.708746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:44.372272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:46.152524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:48.082302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:31.078779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:33.091861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:35.638501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:38.418785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:40.955569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:42.946233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:44.542511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:46.341506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:48.240885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:31.340419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:33.337059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:35.901724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:38.693547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:41.227594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:43.096951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:44.697568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:46.580899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:48.414532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:31.601555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:33.589397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:36.188233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:38.951445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:41.436476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:43.254606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:44.863689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:46.759796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:48.595929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:31.801849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:33.907580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:36.577062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:39.253814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:41.630251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:43.473767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:45.221830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T09:53:46.937462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:53:58.666311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동장애유형남성 여성-합계남성여성심한 장애-소계심한 장애-남성심한 장애-여성심하지 않은 장애-소계심하지 않은 장애-남성심하지 않은 장애-여성
읍면동1.0000.0000.0000.0000.0000.0000.0000.3890.0000.0000.000
장애유형0.0001.0000.7140.7080.7260.6090.6500.5660.7460.7140.753
남성 여성-합계0.0000.7141.0000.9830.9350.6630.8890.6170.9930.9750.900
남성0.0000.7080.9831.0000.8910.6860.8930.6340.9750.9890.870
여성0.0000.7260.9350.8911.0000.7040.7670.6670.9040.8820.979
심한 장애-소계0.0000.6090.6630.6860.7041.0000.9400.9680.6320.6070.619
심한 장애-남성0.0000.6500.8890.8930.7670.9401.0000.8500.8750.8740.732
심한 장애-여성0.3890.5660.6170.6340.6670.9680.8501.0000.5290.5320.499
심하지 않은 장애-소계0.0000.7460.9930.9750.9040.6320.8750.5291.0000.9900.917
심하지 않은 장애-남성0.0000.7140.9750.9890.8820.6070.8740.5320.9901.0000.878
심하지 않은 장애-여성0.0000.7530.9000.8700.9790.6190.7320.4990.9170.8781.000
2024-03-15T09:53:59.107106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장애유형읍면동
장애유형1.0000.000
읍면동0.0001.000
2024-03-15T09:53:59.266361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
남성 여성-합계남성여성심한 장애-소계심한 장애-남성심한 장애-여성심하지 않은 장애-소계심하지 않은 장애-남성심하지 않은 장애-여성읍면동장애유형
남성 여성-합계1.0000.9870.9620.8700.8410.8800.6310.6390.6770.0000.384
남성0.9871.0000.9200.8710.8570.8540.6110.6360.6390.0000.379
여성0.9620.9201.0000.8380.7840.9010.6290.6120.7130.0000.366
심한 장애-소계0.8700.8710.8381.0000.9830.9540.2730.2890.3490.0000.310
심한 장애-남성0.8410.8570.7840.9831.0000.8970.2320.2500.3100.0000.328
심한 장애-여성0.8800.8540.9010.9540.8971.0000.3500.3580.4190.1670.279
심하지 않은 장애-소계0.6310.6110.6290.2730.2320.3501.0000.9820.9480.0000.417
심하지 않은 장애-남성0.6390.6360.6120.2890.2500.3580.9821.0000.8950.0000.384
심하지 않은 장애-여성0.6770.6390.7130.3490.3100.4190.9480.8951.0000.0000.393
읍면동0.0000.0000.0000.0000.0000.1670.0000.0000.0001.0000.000
장애유형0.3840.3790.3660.3100.3280.2790.4170.3840.3930.0001.000

Missing values

2024-03-15T09:53:48.917876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:53:49.331991image/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

시도시군구읍면동장애유형남성 여성-합계남성여성심한 장애-소계심한 장애-남성심한 장애-여성심하지 않은 장애-소계심하지 않은 장애-남성심하지 않은 장애-여성데이터기준일자
0대구광역시북구고성동지체150797129191012160612023-12-31
1대구광역시북구고성동시각3520154223118132023-12-31
2대구광역시북구고성동청각79314812666725422023-12-31
3대구광역시북구고성동언어3302201102023-12-31
4대구광역시북구고성동지적2312112312110002023-12-31
5대구광역시북구고성동뇌병변271512169711652023-12-31
6대구광역시북구고성동자폐성2112110002023-12-31
7대구광역시북구고성동정신5325320002023-12-31
8대구광역시북구고성동신장1611512934222023-12-31
9대구광역시북구고성동심장2202200002023-12-31
시도시군구읍면동장애유형남성 여성-합계남성여성심한 장애-소계심한 장애-남성심한 장애-여성심하지 않은 장애-소계심하지 않은 장애-남성심하지 않은 장애-여성데이터기준일자
311대구광역시북구국우동뇌병변13076546842266234282023-12-31
312대구광역시북구국우동자폐성26233262330002023-12-31
313대구광역시북구국우동정신5022285022280002023-12-31
314대구광역시북구국우동신장74403456312518992023-12-31
315대구광역시북구국우동심장2202200002023-12-31
316대구광역시북구국우동호흡기4224220002023-12-31
317대구광역시북구국우동13112000131122023-12-31
318대구광역시북구국우동안면2201101102023-12-31
319대구광역시북구국우동장루.요루8441107342023-12-31
320대구광역시북구국우동뇌전증6422114312023-12-31