Overview

Dataset statistics

Number of variables11
Number of observations204
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.7 KiB
Average record size in memory98.6 B

Variable types

Numeric10
Categorical1

Dataset

Description경기도_시도별 등록장애인 집계현황(장애정도별)
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=QF8IPFEDF3VO3NB7NF3E24765665&infSeq=1

Alerts

기준년도 is highly overall correlated with 1급장애인수(명) and 7 other fieldsHigh correlation
합계(명) is highly overall correlated with 시도명High correlation
1급장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
2급장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
3급장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
4급장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
5급장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
6급장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
심한 장애인수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
심하지 않은 장애인수(명) is highly overall correlated with 기준년도 and 8 other fieldsHigh correlation
시도명 is highly overall correlated with 합계(명) and 7 other fieldsHigh correlation
합계(명) has unique valuesUnique
1급장애인수(명) has 85 (41.7%) zerosZeros
2급장애인수(명) has 85 (41.7%) zerosZeros
3급장애인수(명) has 85 (41.7%) zerosZeros
4급장애인수(명) has 85 (41.7%) zerosZeros
5급장애인수(명) has 85 (41.7%) zerosZeros
6급장애인수(명) has 85 (41.7%) zerosZeros
심한 장애인수(명) has 119 (58.3%) zerosZeros
심하지 않은 장애인수(명) has 119 (58.3%) zerosZeros

Reproduction

Analysis started2024-04-11 05:21:20.231887
Analysis finished2024-04-11 05:21:29.517756
Duration9.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:29.570834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12014.75
median2017.5
Q32020.25
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4605447
Coefficient of variation (CV)0.0017152638
Kurtosis-1.2171428
Mean2017.5
Median Absolute Deviation (MAD)3
Skewness0
Sum411570
Variance11.975369
MonotonicityDecreasing
2024-04-11T14:21:29.667789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2023 17
8.3%
2022 17
8.3%
2021 17
8.3%
2020 17
8.3%
2019 17
8.3%
2018 17
8.3%
2017 17
8.3%
2016 17
8.3%
2015 17
8.3%
2014 17
8.3%
Other values (2) 34
16.7%
ValueCountFrequency (%)
2012 17
8.3%
2013 17
8.3%
2014 17
8.3%
2015 17
8.3%
2016 17
8.3%
2017 17
8.3%
2018 17
8.3%
2019 17
8.3%
2020 17
8.3%
2021 17
8.3%
ValueCountFrequency (%)
2023 17
8.3%
2022 17
8.3%
2021 17
8.3%
2020 17
8.3%
2019 17
8.3%
2018 17
8.3%
2017 17
8.3%
2016 17
8.3%
2015 17
8.3%
2014 17
8.3%

시도명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
강원
 
12
경기
 
12
경남
 
12
경북
 
12
광주
 
12
Other values (12)
144 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원
2nd row경기
3rd row경남
4th row경북
5th row광주

Common Values

ValueCountFrequency (%)
강원 12
 
5.9%
경기 12
 
5.9%
경남 12
 
5.9%
경북 12
 
5.9%
광주 12
 
5.9%
대구 12
 
5.9%
대전 12
 
5.9%
부산 12
 
5.9%
서울 12
 
5.9%
세종 12
 
5.9%
Other values (7) 84
41.2%

Length

2024-04-11T14:21:29.760915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원 12
 
5.9%
세종 12
 
5.9%
충남 12
 
5.9%
제주 12
 
5.9%
전북 12
 
5.9%
전남 12
 
5.9%
인천 12
 
5.9%
울산 12
 
5.9%
서울 12
 
5.9%
경기 12
 
5.9%
Other values (7) 84
41.2%

합계(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean151132.85
Minimum7081
Maximum586421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:29.853048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7081
5-th percentile12875.15
Q171436.25
median129979
Q3169998.25
95-th percentile506322.25
Maximum586421
Range579340
Interquartile range (IQR)98562

Descriptive statistics

Standard deviation128723.01
Coefficient of variation (CV)0.85172095
Kurtosis3.3389938
Mean151132.85
Median Absolute Deviation (MAD)46521.5
Skewness1.9345843
Sum30831101
Variance1.6569614 × 1010
MonotonicityNot monotonic
2024-04-11T14:21:29.958501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100520 1
 
0.5%
115694 1
 
0.5%
141578 1
 
0.5%
130345 1
 
0.5%
34278 1
 
0.5%
126406 1
 
0.5%
94688 1
 
0.5%
98324 1
 
0.5%
512882 1
 
0.5%
179070 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
7081 1
0.5%
7202 1
0.5%
7943 1
0.5%
9079 1
0.5%
9845 1
0.5%
10623 1
0.5%
11404 1
0.5%
12046 1
0.5%
12346 1
0.5%
12630 1
0.5%
ValueCountFrequency (%)
586421 1
0.5%
584834 1
0.5%
578668 1
0.5%
569726 1
0.5%
559878 1
0.5%
547386 1
0.5%
533259 1
0.5%
522437 1
0.5%
512882 1
0.5%
508330 1
0.5%

1급장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct118
Distinct (%)57.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6849.6716
Minimum0
Maximum43515
Zeros85
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:30.265429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3909.5
Q39480.25
95-th percentile33272.15
Maximum43515
Range43515
Interquartile range (IQR)9480.25

Descriptive statistics

Standard deviation9803.8468
Coefficient of variation (CV)1.4312871
Kurtosis5.3599843
Mean6849.6716
Median Absolute Deviation (MAD)3909.5
Skewness2.2775732
Sum1397333
Variance96115412
MonotonicityNot monotonic
2024-04-11T14:21:30.365527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
41.7%
3342 2
 
1.0%
9340 2
 
1.0%
3881 1
 
0.5%
13670 1
 
0.5%
42107 1
 
0.5%
7992 1
 
0.5%
7606 1
 
0.5%
9396 1
 
0.5%
3317 1
 
0.5%
Other values (108) 108
52.9%
ValueCountFrequency (%)
0 85
41.7%
572 1
 
0.5%
593 1
 
0.5%
598 1
 
0.5%
703 1
 
0.5%
761 1
 
0.5%
798 1
 
0.5%
844 1
 
0.5%
3294 1
 
0.5%
3295 1
 
0.5%
ValueCountFrequency (%)
43515 1
0.5%
43247 1
0.5%
42597 1
0.5%
42568 1
0.5%
42268 1
0.5%
42107 1
0.5%
42047 1
0.5%
34851 1
0.5%
34261 1
0.5%
33813 1
0.5%

2급장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct119
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11623.794
Minimum0
Maximum71984
Zeros85
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:30.465244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6024
Q317259.5
95-th percentile52931.8
Maximum71984
Range71984
Interquartile range (IQR)17259.5

Descriptive statistics

Standard deviation16076.447
Coefficient of variation (CV)1.3830637
Kurtosis4.3817293
Mean11623.794
Median Absolute Deviation (MAD)6024
Skewness2.0530499
Sum2371254
Variance2.5845216 × 108
MonotonicityNot monotonic
2024-04-11T14:21:30.573601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
41.7%
52680 2
 
1.0%
53716 1
 
0.5%
23938 1
 
0.5%
25188 1
 
0.5%
66627 1
 
0.5%
13316 1
 
0.5%
12877 1
 
0.5%
17067 1
 
0.5%
4305 1
 
0.5%
Other values (109) 109
53.4%
ValueCountFrequency (%)
0 85
41.7%
1045 1
 
0.5%
1049 1
 
0.5%
1129 1
 
0.5%
1259 1
 
0.5%
1347 1
 
0.5%
1429 1
 
0.5%
1520 1
 
0.5%
4276 1
 
0.5%
4290 1
 
0.5%
ValueCountFrequency (%)
71984 1
0.5%
70569 1
0.5%
68948 1
0.5%
67591 1
0.5%
67019 1
0.5%
66673 1
0.5%
66627 1
0.5%
55775 1
0.5%
54519 1
0.5%
53716 1
0.5%

3급장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct120
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14932.51
Minimum0
Maximum92298
Zeros85
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:30.677869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8437
Q323002.5
95-th percentile65630
Maximum92298
Range92298
Interquartile range (IQR)23002.5

Descriptive statistics

Standard deviation20414.262
Coefficient of variation (CV)1.3671019
Kurtosis4.4717428
Mean14932.51
Median Absolute Deviation (MAD)8437
Skewness2.0449029
Sum3046232
Variance4.1674209 × 108
MonotonicityNot monotonic
2024-04-11T14:21:30.775980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
41.7%
1565 1
 
0.5%
30225 1
 
0.5%
31047 1
 
0.5%
86305 1
 
0.5%
18696 1
 
0.5%
17095 1
 
0.5%
22102 1
 
0.5%
5947 1
 
0.5%
22993 1
 
0.5%
Other values (110) 110
53.9%
ValueCountFrequency (%)
0 85
41.7%
1241 1
 
0.5%
1250 1
 
0.5%
1356 1
 
0.5%
1565 1
 
0.5%
1669 1
 
0.5%
1783 1
 
0.5%
1917 1
 
0.5%
5823 1
 
0.5%
5859 1
 
0.5%
ValueCountFrequency (%)
92298 1
0.5%
90114 1
0.5%
88666 1
0.5%
87519 1
0.5%
86638 1
0.5%
86305 1
0.5%
86181 1
0.5%
67501 1
0.5%
67001 1
0.5%
66419 1
0.5%

4급장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct119
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12967.407
Minimum0
Maximum78751
Zeros85
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:30.884240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6541
Q320558.25
95-th percentile58444.35
Maximum78751
Range78751
Interquartile range (IQR)20558.25

Descriptive statistics

Standard deviation17753.317
Coefficient of variation (CV)1.3690722
Kurtosis4.0857198
Mean12967.407
Median Absolute Deviation (MAD)6541
Skewness1.9883677
Sum2645351
Variance3.1518025 × 108
MonotonicityNot monotonic
2024-04-11T14:21:30.990264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
41.7%
14031 2
 
1.0%
25202 1
 
0.5%
26422 1
 
0.5%
26849 1
 
0.5%
73586 1
 
0.5%
15185 1
 
0.5%
18631 1
 
0.5%
5173 1
 
0.5%
20948 1
 
0.5%
Other values (109) 109
53.4%
ValueCountFrequency (%)
0 85
41.7%
1079 1
 
0.5%
1106 1
 
0.5%
1187 1
 
0.5%
1289 1
 
0.5%
1373 1
 
0.5%
1464 1
 
0.5%
1574 1
 
0.5%
5173 1
 
0.5%
5208 1
 
0.5%
ValueCountFrequency (%)
78751 1
0.5%
76399 1
0.5%
74761 1
0.5%
74190 1
0.5%
73586 1
0.5%
73327 1
0.5%
73250 1
0.5%
62213 1
0.5%
61077 1
0.5%
59771 1
0.5%

5급장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct120
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18366.123
Minimum0
Maximum117750
Zeros85
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:31.104894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10671
Q328685.5
95-th percentile83367.6
Maximum117750
Range117750
Interquartile range (IQR)28685.5

Descriptive statistics

Standard deviation25475.016
Coefficient of variation (CV)1.3870655
Kurtosis4.5794132
Mean18366.123
Median Absolute Deviation (MAD)10671
Skewness2.0823617
Sum3746689
Variance6.4897642 × 108
MonotonicityNot monotonic
2024-04-11T14:21:31.214365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
41.7%
1900 1
 
0.5%
35686 1
 
0.5%
39685 1
 
0.5%
106597 1
 
0.5%
22129 1
 
0.5%
19474 1
 
0.5%
26397 1
 
0.5%
6428 1
 
0.5%
28716 1
 
0.5%
Other values (110) 110
53.9%
ValueCountFrequency (%)
0 85
41.7%
1467 1
 
0.5%
1502 1
 
0.5%
1656 1
 
0.5%
1900 1
 
0.5%
2070 1
 
0.5%
2276 1
 
0.5%
2480 1
 
0.5%
6280 1
 
0.5%
6355 1
 
0.5%
ValueCountFrequency (%)
117750 1
0.5%
112962 1
0.5%
110037 1
0.5%
107271 1
0.5%
106706 1
0.5%
106597 1
0.5%
106227 1
0.5%
85870 1
0.5%
84835 1
0.5%
84535 1
0.5%

6급장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct119
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21729.618
Minimum0
Maximum143088
Zeros85
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:31.318358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median13708
Q331972.75
95-th percentile100741.2
Maximum143088
Range143088
Interquartile range (IQR)31972.75

Descriptive statistics

Standard deviation30808.746
Coefficient of variation (CV)1.4178227
Kurtosis5.3146753
Mean21729.618
Median Absolute Deviation (MAD)13708
Skewness2.2323843
Sum4432842
Variance9.4917881 × 108
MonotonicityNot monotonic
2024-04-11T14:21:31.422153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 85
41.7%
23658 2
 
1.0%
39896 1
 
0.5%
43091 1
 
0.5%
131242 1
 
0.5%
22342 1
 
0.5%
22529 1
 
0.5%
31128 1
 
0.5%
7819 1
 
0.5%
31516 1
 
0.5%
Other values (109) 109
53.4%
ValueCountFrequency (%)
0 85
41.7%
1652 1
 
0.5%
1727 1
 
0.5%
2017 1
 
0.5%
2363 1
 
0.5%
2625 1
 
0.5%
2873 1
 
0.5%
3069 1
 
0.5%
7389 1
 
0.5%
7609 1
 
0.5%
ValueCountFrequency (%)
143088 1
0.5%
139968 1
0.5%
137428 1
0.5%
134906 1
0.5%
133016 1
0.5%
131242 1
0.5%
129334 1
0.5%
101742 1
0.5%
101675 1
0.5%
101318 1
0.5%

심한 장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24332.064
Minimum0
Maximum215561
Zeros119
Zeros (%)58.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:31.529510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q338602.5
95-th percentile110083.3
Maximum215561
Range215561
Interquartile range (IQR)38602.5

Descriptive statistics

Standard deviation43339.027
Coefficient of variation (CV)1.7811488
Kurtosis8.0723945
Mean24332.064
Median Absolute Deviation (MAD)0
Skewness2.6801029
Sum4963741
Variance1.8782712 × 109
MonotonicityNot monotonic
2024-04-11T14:21:31.634172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 119
58.3%
37436 1
 
0.5%
27795 1
 
0.5%
50771 1
 
0.5%
53128 1
 
0.5%
18940 1
 
0.5%
4630 1
 
0.5%
148970 1
 
0.5%
67332 1
 
0.5%
28418 1
 
0.5%
Other values (76) 76
37.3%
ValueCountFrequency (%)
0 119
58.3%
4516 1
 
0.5%
4630 1
 
0.5%
4732 1
 
0.5%
4804 1
 
0.5%
4907 1
 
0.5%
14263 1
 
0.5%
14356 1
 
0.5%
14400 1
 
0.5%
14460 1
 
0.5%
ValueCountFrequency (%)
215561 1
0.5%
215402 1
0.5%
213806 1
0.5%
211870 1
0.5%
209835 1
0.5%
149906 1
0.5%
148970 1
0.5%
147861 1
0.5%
147334 1
0.5%
146174 1
0.5%

심하지 않은 장애인수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct86
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40331.662
Minimum0
Maximum370860
Zeros119
Zeros (%)58.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-11T14:21:31.738927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q363498.25
95-th percentile119120.9
Maximum370860
Range370860
Interquartile range (IQR)63498.25

Descriptive statistics

Standard deviation72426.67
Coefficient of variation (CV)1.795777
Kurtosis8.6975297
Mean40331.662
Median Absolute Deviation (MAD)0
Skewness2.7570199
Sum8227659
Variance5.2456226 × 109
MonotonicityNot monotonic
2024-04-11T14:21:31.859181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 119
58.3%
63084 1
 
0.5%
42266 1
 
0.5%
90171 1
 
0.5%
93193 1
 
0.5%
32182 1
 
0.5%
7716 1
 
0.5%
245220 1
 
0.5%
108961 1
 
0.5%
44435 1
 
0.5%
Other values (76) 76
37.3%
ValueCountFrequency (%)
0 119
58.3%
7530 1
 
0.5%
7716 1
 
0.5%
7898 1
 
0.5%
8037 1
 
0.5%
8059 1
 
0.5%
22024 1
 
0.5%
22299 1
 
0.5%
22458 1
 
0.5%
22476 1
 
0.5%
ValueCountFrequency (%)
370860 1
0.5%
369432 1
0.5%
364862 1
0.5%
357856 1
0.5%
350043 1
0.5%
245220 1
0.5%
244937 1
0.5%
244525 1
0.5%
244262 1
0.5%
243621 1
0.5%

Interactions

2024-04-11T14:21:28.602629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:21.697936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.578902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.361722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.014512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.896370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.578257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.330570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.076109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.945063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.673901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:21.817080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.661668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.428584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.080467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.961161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.660212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.401988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.150365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.009580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.744431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:21.999815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.745815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.496948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.146180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.032885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.748264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.482195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.219265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.090017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.808519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.060045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.809390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.563370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.205761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.089296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.821175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.557787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.285008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.154227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.878991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.127398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.886932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.630568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.273674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.156130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.897359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.635882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.362964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.223810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.940460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.191459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.992175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.688708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.334600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.216067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.967931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.695418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.426022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.283906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:29.015574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.263366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.074005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.757168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.408442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.287823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.042814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.766990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.496671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.352238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:29.084137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.346140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.138698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.822392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.481969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.363886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.116927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.839338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.710259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.415633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:29.163551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.436549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.213186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.888385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.557748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.448420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.187127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.914598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.786490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.479997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:29.231651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:22.497180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.273383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:23.948939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:24.646803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:25.514154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.249175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:26.982368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:27.865365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T14:21:28.535050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T14:21:31.956299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시도명합계(명)1급장애인수(명)2급장애인수(명)3급장애인수(명)4급장애인수(명)5급장애인수(명)6급장애인수(명)심한 장애인수(명)심하지 않은 장애인수(명)
기준년도1.0000.0000.0000.5170.5170.5200.5170.5030.5020.5120.538
시도명0.0001.0000.9530.8550.8880.8830.8880.8440.8420.7730.800
합계(명)0.0000.9531.0000.9180.7990.7900.8000.9260.9180.9180.815
1급장애인수(명)0.5170.8550.9181.0000.9720.9620.9620.9860.9960.5710.416
2급장애인수(명)0.5170.8880.7990.9721.0001.0000.9990.9650.9650.4160.631
3급장애인수(명)0.5200.8830.7900.9621.0001.0000.9980.9570.9550.4160.631
4급장애인수(명)0.5170.8880.8000.9620.9990.9981.0000.9520.9570.4160.631
5급장애인수(명)0.5030.8440.9260.9860.9650.9570.9521.0000.9860.5710.416
6급장애인수(명)0.5020.8420.9180.9960.9650.9550.9570.9861.0000.5710.416
심한 장애인수(명)0.5120.7730.9180.5710.4160.4160.4160.5710.5711.0000.965
심하지 않은 장애인수(명)0.5380.8000.8150.4160.6310.6310.6310.4160.4160.9651.000
2024-04-11T14:21:32.252866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도합계(명)1급장애인수(명)2급장애인수(명)3급장애인수(명)4급장애인수(명)5급장애인수(명)6급장애인수(명)심한 장애인수(명)심하지 않은 장애인수(명)시도명
기준년도1.0000.062-0.771-0.760-0.751-0.760-0.749-0.7420.8150.8210.000
합계(명)0.0621.0000.2900.2930.2940.2930.2940.2920.2540.2520.814
1급장애인수(명)-0.7710.2901.0000.9950.9960.9950.9940.996-0.846-0.8460.595
2급장애인수(명)-0.7600.2930.9951.0000.9990.9990.9990.996-0.846-0.8460.662
3급장애인수(명)-0.7510.2940.9960.9991.0000.9980.9990.998-0.846-0.8460.652
4급장애인수(명)-0.7600.2930.9950.9990.9981.0000.9990.995-0.846-0.8460.662
5급장애인수(명)-0.7490.2940.9940.9990.9990.9991.0000.997-0.846-0.8460.576
6급장애인수(명)-0.7420.2920.9960.9960.9980.9950.9971.000-0.846-0.8460.572
심한 장애인수(명)0.8150.254-0.846-0.846-0.846-0.846-0.846-0.8461.0000.9980.477
심하지 않은 장애인수(명)0.8210.252-0.846-0.846-0.846-0.846-0.846-0.8460.9981.0000.523
시도명0.0000.8140.5950.6620.6520.6620.5760.5720.4770.5231.000

Missing values

2024-04-11T14:21:29.336938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T14:21:29.466613image/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

기준년도시도명합계(명)1급장애인수(명)2급장애인수(명)3급장애인수(명)4급장애인수(명)5급장애인수(명)6급장애인수(명)심한 장애인수(명)심하지 않은 장애인수(명)
02023강원1005200000003743663084
12023경기586421000000215561370860
22023경남18882500000070543118282
32023경북17834100000064205114136
42023광주693140000002773341581
52023대구1305200000004701283508
62023대전714400000002806643374
72023부산17546700000066295109172
82023서울389795000000146174243621
92023세종1294400000049078037
기준년도시도명합계(명)1급장애인수(명)2급장애인수(명)3급장애인수(명)4급장애인수(명)5급장애인수(명)6급장애인수(명)심한 장애인수(명)심하지 않은 장애인수(명)
1942012부산17074313578236923040826001344094265500
1952012서울407528348515577567501622138587010131800
1962012세종70815931049124110791467165200
1972012울산489823943599484096621106751334000
1982012인천13346710876172192288720691283843341000
1992012전남14578810313204132380525898318693349000
2002012전북1330549631180382327521841292243104500
2012012제주3240533624276582352756280738900
2022012충남1248729680174012198919035264693029800
2032012충북941377889131531711714363197622185300