Overview

Dataset statistics

Number of variables13
Number of observations7121
Missing cells245
Missing cells (%)0.3%
Duplicate rows7
Duplicate rows (%)0.1%
Total size in memory785.9 KiB
Average record size in memory113.0 B

Variable types

Categorical3
Text1
Numeric9

Dataset

Description경기도 내 등록장애인 집계현황(읍면동별, 유형별, 정도별)
Author가평군
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=7USTQ8KGZPR5QQUAZ4EN31312072&infSeq=1

Alerts

Dataset has 7 (0.1%) duplicate rowsDuplicates
시군명 is highly overall correlated with 구명High correlation
구명 is highly overall correlated with 시군명High correlation
등록장애인수(합계) is highly overall correlated with 등록장애인수(남성) and 7 other fieldsHigh correlation
등록장애인수(남성) is highly overall correlated with 등록장애인수(합계) and 7 other fieldsHigh correlation
등록장애인수(여성) is highly overall correlated with 등록장애인수(합계) and 7 other fieldsHigh correlation
심한장애인수(합계) is highly overall correlated with 등록장애인수(합계) and 4 other fieldsHigh correlation
심한장애인수(남성) is highly overall correlated with 등록장애인수(합계) and 4 other fieldsHigh correlation
심한장애인수(여성) is highly overall correlated with 등록장애인수(합계) and 4 other fieldsHigh correlation
심하지않은장애인수(합계) is highly overall correlated with 등록장애인수(합계) and 4 other fieldsHigh correlation
심하지않은장애인수(남성) is highly overall correlated with 등록장애인수(합계) and 4 other fieldsHigh correlation
심하지않은장애인수(여성) is highly overall correlated with 등록장애인수(합계) and 4 other fieldsHigh correlation
등록장애인수(합계) is highly skewed (γ1 = 23.36471872)Skewed
등록장애인수(남성) is highly skewed (γ1 = 24.83145173)Skewed
등록장애인수(여성) is highly skewed (γ1 = 21.07650736)Skewed
심하지않은장애인수(합계) is highly skewed (γ1 = 27.57962027)Skewed
심하지않은장애인수(남성) is highly skewed (γ1 = 28.83043549)Skewed
심하지않은장애인수(여성) is highly skewed (γ1 = 25.56114394)Skewed
등록장애인수(남성) has 356 (5.0%) zerosZeros
등록장애인수(여성) has 920 (12.9%) zerosZeros
심한장애인수(합계) has 1045 (14.7%) zerosZeros
심한장애인수(남성) has 1416 (19.9%) zerosZeros
심한장애인수(여성) has 1962 (27.6%) zerosZeros
심하지않은장애인수(합계) has 2134 (30.0%) zerosZeros
심하지않은장애인수(남성) has 2470 (34.7%) zerosZeros
심하지않은장애인수(여성) has 2905 (40.8%) zerosZeros

Reproduction

Analysis started2024-05-10 21:06:33.971995
Analysis finished2024-05-10 21:07:02.464929
Duration28.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size55.8 KiB
성남시
686 
고양시
673 
수원시
622 
화성시
443 
안양시
429 
Other values (25)
4268 

Length

Max length4
Median length3
Mean length3.0834153
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
성남시 686
 
9.6%
고양시 673
 
9.5%
수원시 622
 
8.7%
화성시 443
 
6.2%
안양시 429
 
6.0%
안산시 379
 
5.3%
평택시 345
 
4.8%
파주시 278
 
3.9%
남양주시 273
 
3.8%
시흥시 271
 
3.8%
Other values (20) 2722
38.2%

Length

2024-05-10T21:07:02.711852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성남시 686
 
9.6%
고양시 673
 
9.5%
수원시 622
 
8.7%
화성시 443
 
6.2%
안양시 429
 
6.0%
안산시 379
 
5.3%
평택시 345
 
4.8%
파주시 278
 
3.9%
남양주시 273
 
3.8%
시흥시 271
 
3.8%
Other values (20) 2722
38.2%

구명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size55.8 KiB
<NA>
3776 
덕양구
 
323
분당구
 
300
남양주시
 
273
광명시
 
248
Other values (15)
2201 

Length

Max length4
Median length4
Mean length3.6177503
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 3776
53.0%
덕양구 323
 
4.5%
분당구 300
 
4.2%
남양주시 273
 
3.8%
광명시 248
 
3.5%
동안구 236
 
3.3%
수정구 228
 
3.2%
상록구 196
 
2.8%
만안구 193
 
2.7%
단원구 183
 
2.6%
Other values (10) 1165
 
16.4%

Length

2024-05-10T21:07:03.113252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 3776
53.0%
덕양구 323
 
4.5%
분당구 300
 
4.2%
남양주시 273
 
3.8%
광명시 248
 
3.5%
동안구 236
 
3.3%
수정구 228
 
3.2%
상록구 196
 
2.8%
만안구 193
 
2.7%
단원구 183
 
2.6%
Other values (10) 1165
 
16.4%
Distinct535
Distinct (%)7.5%
Missing0
Missing (%)0.0%
Memory size55.8 KiB
2024-05-10T21:07:03.890382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4262042
Min length2

Characters and Unicode

Total characters24398
Distinct characters207
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

Unique51 ?
Unique (%)0.7%

Sample

1st row가평읍
2nd row가평읍
3rd row가평읍
4th row가평읍
5th row가평읍
ValueCountFrequency (%)
중앙동 104
 
1.5%
금곡동 45
 
0.6%
부곡동 32
 
0.4%
청평면 31
 
0.4%
반월동 31
 
0.4%
정자2동 30
 
0.4%
능곡동 30
 
0.4%
풍산동 30
 
0.4%
위례동 29
 
0.4%
대야동 29
 
0.4%
Other values (525) 6730
94.5%
2024-05-10T21:07:04.987908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5764
23.6%
1126
 
4.6%
1 1012
 
4.1%
2 1007
 
4.1%
535
 
2.2%
459
 
1.9%
457
 
1.9%
3 422
 
1.7%
383
 
1.6%
337
 
1.4%
Other values (197) 12896
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21565
88.4%
Decimal Number 2833
 
11.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5764
26.7%
1126
 
5.2%
535
 
2.5%
459
 
2.1%
457
 
2.1%
383
 
1.8%
337
 
1.6%
306
 
1.4%
291
 
1.3%
291
 
1.3%
Other values (187) 11616
53.9%
Decimal Number
ValueCountFrequency (%)
1 1012
35.7%
2 1007
35.5%
3 422
14.9%
4 159
 
5.6%
5 62
 
2.2%
6 61
 
2.2%
7 47
 
1.7%
9 32
 
1.1%
8 29
 
1.0%
0 2
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21565
88.4%
Common 2833
 
11.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5764
26.7%
1126
 
5.2%
535
 
2.5%
459
 
2.1%
457
 
2.1%
383
 
1.8%
337
 
1.6%
306
 
1.4%
291
 
1.3%
291
 
1.3%
Other values (187) 11616
53.9%
Common
ValueCountFrequency (%)
1 1012
35.7%
2 1007
35.5%
3 422
14.9%
4 159
 
5.6%
5 62
 
2.2%
6 61
 
2.2%
7 47
 
1.7%
9 32
 
1.1%
8 29
 
1.0%
0 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21565
88.4%
ASCII 2833
 
11.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5764
26.7%
1126
 
5.2%
535
 
2.5%
459
 
2.1%
457
 
2.1%
383
 
1.8%
337
 
1.6%
306
 
1.4%
291
 
1.3%
291
 
1.3%
Other values (187) 11616
53.9%
ASCII
ValueCountFrequency (%)
1 1012
35.7%
2 1007
35.5%
3 422
14.9%
4 159
 
5.6%
5 62
 
2.2%
6 61
 
2.2%
7 47
 
1.7%
9 32
 
1.1%
8 29
 
1.0%
0 2
 
0.1%

장애유형
Categorical

Distinct18
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size55.8 KiB
신장
544 
지체
495 
뇌병변
494 
청각
494 
시각
494 
Other values (13)
4600 

Length

Max length6
Median length2
Mean length2.3908159
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row소계
2nd row장루.요루
3rd row안면
4th row
5th row호흡기

Common Values

ValueCountFrequency (%)
신장 544
 
7.6%
지체 495
 
7.0%
뇌병변 494
 
6.9%
청각 494
 
6.9%
시각 494
 
6.9%
지적 493
 
6.9%
정신 492
 
6.9%
자폐성 482
 
6.8%
언어 481
 
6.8%
478
 
6.7%
Other values (8) 2174
30.5%

Length

2024-05-10T21:07:05.371657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신장 544
 
7.6%
지체 495
 
6.9%
뇌병변 494
 
6.9%
청각 494
 
6.9%
시각 494
 
6.9%
지적 493
 
6.9%
정신 492
 
6.9%
자폐성 482
 
6.8%
언어 481
 
6.7%
478
 
6.7%
Other values (9) 2180
30.6%

등록장애인수(합계)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct673
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean96.798483
Minimum0
Maximum16602
Zeros66
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:05.768729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median19
Q382
95-th percentile420
Maximum16602
Range16602
Interquartile range (IQR)77

Descriptive statistics

Standard deviation320.62794
Coefficient of variation (CV)3.312324
Kurtosis1031.3904
Mean96.798483
Median Absolute Deviation (MAD)17
Skewness23.364719
Sum689302
Variance102802.28
MonotonicityNot monotonic
2024-05-10T21:07:06.224458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 556
 
7.8%
2 439
 
6.2%
3 398
 
5.6%
4 316
 
4.4%
5 279
 
3.9%
6 231
 
3.2%
7 200
 
2.8%
8 166
 
2.3%
9 144
 
2.0%
10 121
 
1.7%
Other values (663) 4271
60.0%
ValueCountFrequency (%)
0 66
 
0.9%
1 556
7.8%
2 439
6.2%
3 398
5.6%
4 316
4.4%
5 279
3.9%
6 231
3.2%
7 200
 
2.8%
8 166
 
2.3%
9 144
 
2.0%
ValueCountFrequency (%)
16602 1
< 0.1%
6243 1
< 0.1%
4934 1
< 0.1%
3859 1
< 0.1%
3569 1
< 0.1%
3438 1
< 0.1%
3434 1
< 0.1%
3368 1
< 0.1%
3365 1
< 0.1%
3334 1
< 0.1%

등록장애인수(남성)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct520
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.727005
Minimum0
Maximum10393
Zeros356
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:06.995127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median12
Q348
95-th percentile257
Maximum10393
Range10393
Interquartile range (IQR)45

Descriptive statistics

Standard deviation194.72179
Coefficient of variation (CV)3.3731491
Kurtosis1151.7699
Mean57.727005
Median Absolute Deviation (MAD)11
Skewness24.831452
Sum411074
Variance37916.577
MonotonicityNot monotonic
2024-05-10T21:07:07.380513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 663
 
9.3%
2 550
 
7.7%
3 430
 
6.0%
0 356
 
5.0%
4 336
 
4.7%
5 266
 
3.7%
6 237
 
3.3%
7 166
 
2.3%
8 147
 
2.1%
9 128
 
1.8%
Other values (510) 3842
54.0%
ValueCountFrequency (%)
0 356
5.0%
1 663
9.3%
2 550
7.7%
3 430
6.0%
4 336
4.7%
5 266
3.7%
6 237
 
3.3%
7 166
 
2.3%
8 147
 
2.1%
9 128
 
1.8%
ValueCountFrequency (%)
10393 1
< 0.1%
3383 1
< 0.1%
2908 1
< 0.1%
2369 1
< 0.1%
2177 1
< 0.1%
2127 1
< 0.1%
2060 1
< 0.1%
2026 2
< 0.1%
1979 1
< 0.1%
1865 1
< 0.1%

등록장애인수(여성)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct403
Distinct (%)5.7%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean39.192351
Minimum0
Maximum6209
Zeros920
Zeros (%)12.9%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:07.746498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q334
95-th percentile170.75
Maximum6209
Range6209
Interquartile range (IQR)33

Descriptive statistics

Standard deviation126.98612
Coefficient of variation (CV)3.2400741
Kurtosis848.47924
Mean39.192351
Median Absolute Deviation (MAD)6
Skewness21.076507
Sum277717
Variance16125.475
MonotonicityNot monotonic
2024-05-10T21:07:08.108560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1017
 
14.3%
0 920
 
12.9%
2 614
 
8.6%
3 417
 
5.9%
4 272
 
3.8%
5 207
 
2.9%
6 143
 
2.0%
7 112
 
1.6%
8 99
 
1.4%
10 93
 
1.3%
Other values (393) 3192
44.8%
ValueCountFrequency (%)
0 920
12.9%
1 1017
14.3%
2 614
8.6%
3 417
5.9%
4 272
 
3.8%
5 207
 
2.9%
6 143
 
2.0%
7 112
 
1.6%
8 99
 
1.4%
9 81
 
1.1%
ValueCountFrequency (%)
6209 1
< 0.1%
2860 1
< 0.1%
2026 1
< 0.1%
1490 1
< 0.1%
1459 1
< 0.1%
1392 1
< 0.1%
1374 1
< 0.1%
1339 1
< 0.1%
1308 1
< 0.1%
1254 1
< 0.1%

심한장애인수(합계)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct333
Distinct (%)4.7%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean35.682755
Minimum0
Maximum3372
Zeros1045
Zeros (%)14.7%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:08.495000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q338
95-th percentile124
Maximum3372
Range3372
Interquartile range (IQR)37

Descriptive statistics

Standard deviation101.36695
Coefficient of variation (CV)2.8407826
Kurtosis331.08945
Mean35.682755
Median Absolute Deviation (MAD)11
Skewness14.144424
Sum252848
Variance10275.259
MonotonicityNot monotonic
2024-05-10T21:07:08.902675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1045
 
14.7%
1 796
 
11.2%
2 414
 
5.8%
3 300
 
4.2%
4 211
 
3.0%
5 175
 
2.5%
6 136
 
1.9%
7 129
 
1.8%
8 115
 
1.6%
9 106
 
1.5%
Other values (323) 3659
51.4%
ValueCountFrequency (%)
0 1045
14.7%
1 796
11.2%
2 414
 
5.8%
3 300
 
4.2%
4 211
 
3.0%
5 175
 
2.5%
6 136
 
1.9%
7 129
 
1.8%
8 115
 
1.6%
9 106
 
1.5%
ValueCountFrequency (%)
3372 1
< 0.1%
2974 1
< 0.1%
1995 1
< 0.1%
1686 1
< 0.1%
1439 1
< 0.1%
1412 1
< 0.1%
1360 1
< 0.1%
1262 1
< 0.1%
1224 1
< 0.1%
1222 1
< 0.1%

심한장애인수(남성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct251
Distinct (%)3.5%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean21.530765
Minimum0
Maximum2279
Zeros1416
Zeros (%)19.9%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:09.335693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q322
95-th percentile78
Maximum2279
Range2279
Interquartile range (IQR)21

Descriptive statistics

Standard deviation62.44035
Coefficient of variation (CV)2.9000526
Kurtosis401.76592
Mean21.530765
Median Absolute Deviation (MAD)6
Skewness15.311671
Sum152567
Variance3898.7973
MonotonicityNot monotonic
2024-05-10T21:07:09.813056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1416
19.9%
1 784
 
11.0%
2 435
 
6.1%
3 315
 
4.4%
4 230
 
3.2%
6 200
 
2.8%
5 179
 
2.5%
7 177
 
2.5%
8 155
 
2.2%
10 143
 
2.0%
Other values (241) 3052
42.9%
ValueCountFrequency (%)
0 1416
19.9%
1 784
11.0%
2 435
 
6.1%
3 315
 
4.4%
4 230
 
3.2%
5 179
 
2.5%
6 200
 
2.8%
7 177
 
2.5%
8 155
 
2.2%
9 131
 
1.8%
ValueCountFrequency (%)
2279 1
< 0.1%
1865 1
< 0.1%
1123 1
< 0.1%
1031 1
< 0.1%
864 1
< 0.1%
786 1
< 0.1%
759 1
< 0.1%
758 1
< 0.1%
755 1
< 0.1%
694 1
< 0.1%

심한장애인수(여성)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct194
Distinct (%)2.7%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean14.151849
Minimum0
Maximum1109
Zeros1962
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:10.253099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q316
95-th percentile50
Maximum1109
Range1109
Interquartile range (IQR)16

Descriptive statistics

Standard deviation39.645947
Coefficient of variation (CV)2.8014677
Kurtosis251.14747
Mean14.151849
Median Absolute Deviation (MAD)4
Skewness12.679347
Sum100280
Variance1571.8011
MonotonicityNot monotonic
2024-05-10T21:07:10.685766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1962
27.6%
1 879
 
12.3%
2 420
 
5.9%
3 272
 
3.8%
4 209
 
2.9%
6 181
 
2.5%
7 163
 
2.3%
8 160
 
2.2%
5 156
 
2.2%
10 156
 
2.2%
Other values (184) 2528
35.5%
ValueCountFrequency (%)
0 1962
27.6%
1 879
12.3%
2 420
 
5.9%
3 272
 
3.8%
4 209
 
2.9%
5 156
 
2.2%
6 181
 
2.5%
7 163
 
2.3%
8 160
 
2.2%
9 152
 
2.1%
ValueCountFrequency (%)
1109 1
< 0.1%
1093 1
< 0.1%
872 1
< 0.1%
718 1
< 0.1%
655 1
< 0.1%
598 1
< 0.1%
575 1
< 0.1%
574 1
< 0.1%
469 1
< 0.1%
463 1
< 0.1%

심하지않은장애인수(합계)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct572
Distinct (%)8.1%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean61.362546
Minimum0
Maximum13230
Zeros2134
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:11.114137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q333
95-th percentile336.75
Maximum13230
Range13230
Interquartile range (IQR)33

Descriptive statistics

Standard deviation237.81417
Coefficient of variation (CV)3.875559
Kurtosis1369.2213
Mean61.362546
Median Absolute Deviation (MAD)4
Skewness27.57962
Sum434815
Variance56555.578
MonotonicityNot monotonic
2024-05-10T21:07:11.582939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2134
30.0%
1 680
 
9.5%
2 396
 
5.6%
3 304
 
4.3%
4 231
 
3.2%
5 202
 
2.8%
6 167
 
2.3%
7 158
 
2.2%
8 124
 
1.7%
9 100
 
1.4%
Other values (562) 2590
36.4%
ValueCountFrequency (%)
0 2134
30.0%
1 680
 
9.5%
2 396
 
5.6%
3 304
 
4.3%
4 231
 
3.2%
5 202
 
2.8%
6 167
 
2.3%
7 158
 
2.2%
8 124
 
1.7%
9 100
 
1.4%
ValueCountFrequency (%)
13230 1
< 0.1%
4981 1
< 0.1%
3248 1
< 0.1%
2927 1
< 0.1%
2420 1
< 0.1%
2214 1
< 0.1%
2199 1
< 0.1%
2157 1
< 0.1%
2146 1
< 0.1%
1988 1
< 0.1%

심하지않은장애인수(남성)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct422
Distinct (%)6.0%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean36.322467
Minimum0
Maximum8114
Zeros2470
Zeros (%)34.7%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:11.983545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320
95-th percentile197.75
Maximum8114
Range8114
Interquartile range (IQR)20

Descriptive statistics

Standard deviation142.80405
Coefficient of variation (CV)3.9315626
Kurtosis1478.8421
Mean36.322467
Median Absolute Deviation (MAD)2
Skewness28.830435
Sum257381
Variance20392.997
MonotonicityNot monotonic
2024-05-10T21:07:12.462475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2470
34.7%
1 703
 
9.9%
2 430
 
6.0%
3 345
 
4.8%
4 252
 
3.5%
5 193
 
2.7%
6 177
 
2.5%
7 113
 
1.6%
8 105
 
1.5%
9 83
 
1.2%
Other values (412) 2215
31.1%
ValueCountFrequency (%)
0 2470
34.7%
1 703
 
9.9%
2 430
 
6.0%
3 345
 
4.8%
4 252
 
3.5%
5 193
 
2.7%
6 177
 
2.5%
7 113
 
1.6%
8 105
 
1.5%
9 83
 
1.2%
ValueCountFrequency (%)
8114 1
< 0.1%
2719 1
< 0.1%
1877 1
< 0.1%
1821 1
< 0.1%
1505 1
< 0.1%
1368 1
< 0.1%
1340 1
< 0.1%
1268 1
< 0.1%
1224 1
< 0.1%
1163 1
< 0.1%

심하지않은장애인수(여성)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct335
Distinct (%)4.7%
Missing35
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean25.038809
Minimum0
Maximum5116
Zeros2905
Zeros (%)40.8%
Negative0
Negative (%)0.0%
Memory size62.7 KiB
2024-05-10T21:07:12.906527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q313
95-th percentile141
Maximum5116
Range5116
Interquartile range (IQR)13

Descriptive statistics

Standard deviation95.576916
Coefficient of variation (CV)3.8171511
Kurtosis1195.3522
Mean25.038809
Median Absolute Deviation (MAD)1
Skewness25.561144
Sum177425
Variance9134.9468
MonotonicityNot monotonic
2024-05-10T21:07:13.370770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2905
40.8%
1 850
 
11.9%
2 434
 
6.1%
3 293
 
4.1%
4 179
 
2.5%
5 154
 
2.2%
6 105
 
1.5%
7 100
 
1.4%
9 66
 
0.9%
8 62
 
0.9%
Other values (325) 1938
27.2%
ValueCountFrequency (%)
0 2905
40.8%
1 850
 
11.9%
2 434
 
6.1%
3 293
 
4.1%
4 179
 
2.5%
5 154
 
2.2%
6 105
 
1.5%
7 100
 
1.4%
8 62
 
0.9%
9 66
 
0.9%
ValueCountFrequency (%)
5116 1
< 0.1%
2262 1
< 0.1%
1371 1
< 0.1%
1106 1
< 0.1%
990 1
< 0.1%
915 1
< 0.1%
889 1
< 0.1%
859 1
< 0.1%
830 1
< 0.1%
825 1
< 0.1%

Interactions

2024-05-10T21:06:58.228425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:38.181692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:40.623881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:42.946484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:45.251792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:47.877503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:50.906474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:53.375957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:55.732537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:58.501997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:38.432731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:40.904290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:43.283530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:45.522839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:48.205987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:51.172942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:53.644644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:56.030099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:58.768315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:38.698694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:41.167148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:43.509553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:45.818590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:48.502086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:51.434085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:53.916533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:56.267692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:59.026996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:38.954441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:41.395224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:43.749793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:46.087775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:48.804680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:51.713867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:54.182491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:56.543175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:59.313548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:39.247414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:41.665727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:44.047449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:46.332484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:49.094252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:51.988889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:54.429640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:56.839073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:59.645666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:39.530529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:41.914030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:44.274843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:46.624489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:49.497480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:52.239314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:54.656616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:57.109657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:59.914001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:39.804212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:42.129266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:44.501537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:46.972221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:49.808679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:52.487058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:54.920281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:57.380445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:07:00.176653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:40.053944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:42.365146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:44.737224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:47.271939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:50.116622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:52.760231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:55.163027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:57.654342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:07:00.464256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:40.342273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:42.657376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:44.987347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:47.597679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:50.419844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:53.034479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:55.446283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:06:57.948476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:07:13.763874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명구명장애유형등록장애인수(합계)등록장애인수(남성)등록장애인수(여성)심한장애인수(합계)심한장애인수(남성)심한장애인수(여성)심하지않은장애인수(합계)심하지않은장애인수(남성)심하지않은장애인수(여성)
시군명1.0001.0000.3240.4530.4320.4150.4650.4360.4980.4050.4040.403
구명1.0001.0000.2360.1540.1370.1250.1530.1440.1530.1320.1130.142
장애유형0.3240.2361.0000.4250.3420.5200.6000.5650.7150.3390.3260.344
등록장애인수(합계)0.4530.1540.4251.0000.9960.9430.8630.8410.8560.9900.9890.989
등록장애인수(남성)0.4320.1370.3420.9961.0000.9120.8410.7990.8070.9950.9950.994
등록장애인수(여성)0.4150.1250.5200.9430.9121.0000.8590.8540.8660.9260.9220.920
심한장애인수(합계)0.4650.1530.6000.8630.8410.8591.0000.9620.9420.8290.8200.821
심한장애인수(남성)0.4360.1440.5650.8410.7990.8540.9621.0000.8920.8080.8000.813
심한장애인수(여성)0.4980.1530.7150.8560.8070.8660.9420.8921.0000.7820.7830.776
심하지않은장애인수(합계)0.4050.1320.3390.9900.9950.9260.8290.8080.7821.0001.0001.000
심하지않은장애인수(남성)0.4040.1130.3260.9890.9950.9220.8200.8000.7831.0001.0000.999
심하지않은장애인수(여성)0.4030.1420.3440.9890.9940.9200.8210.8130.7761.0000.9991.000
2024-05-10T21:07:14.135213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명구명장애유형
시군명1.0000.9980.093
구명0.9981.0000.077
장애유형0.0930.0771.000
2024-05-10T21:07:14.406918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록장애인수(합계)등록장애인수(남성)등록장애인수(여성)심한장애인수(합계)심한장애인수(남성)심한장애인수(여성)심하지않은장애인수(합계)심하지않은장애인수(남성)심하지않은장애인수(여성)시군명구명장애유형
등록장애인수(합계)1.0000.9890.9600.8870.8670.8790.6450.6560.6820.2130.0810.232
등록장애인수(남성)0.9891.0000.9150.8810.8780.8460.6300.6560.6480.2010.0720.181
등록장애인수(여성)0.9600.9151.0000.8510.8020.9010.6500.6360.7210.1970.0590.234
심한장애인수(합계)0.8870.8810.8511.0000.9830.9540.3230.3390.3890.2040.0780.302
심한장애인수(남성)0.8670.8780.8020.9831.0000.8950.2990.3150.3660.1960.0730.293
심한장애인수(여성)0.8790.8460.9010.9540.8951.0000.3780.3890.4330.2110.0740.321
심하지않은장애인수(합계)0.6450.6300.6500.3230.2990.3781.0000.9820.9530.2050.0710.180
심하지않은장애인수(남성)0.6560.6560.6360.3390.3150.3890.9821.0000.9030.2040.0610.173
심하지않은장애인수(여성)0.6820.6480.7210.3890.3660.4330.9530.9031.0000.2030.0770.183
시군명0.2130.2010.1970.2040.1960.2110.2050.2040.2031.0000.9980.093
구명0.0810.0720.0590.0780.0730.0740.0710.0610.0770.9981.0000.077
장애유형0.2320.1810.2340.3020.2930.3210.1800.1730.1830.0930.0771.000

Missing values

2024-05-10T21:07:00.863792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:07:01.589014image/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.
2024-05-10T21:07:02.122934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명구명읍면동명장애유형등록장애인수(합계)등록장애인수(남성)등록장애인수(여성)심한장애인수(합계)심한장애인수(남성)심한장애인수(여성)심하지않은장애인수(합계)심하지않은장애인수(남성)심하지않은장애인수(여성)
0가평군<NA>가평읍소계1334780554415253162919527392
1가평군<NA>가평읍장루.요루1055312743
2가평군<NA>가평읍안면110110000
3가평군<NA>가평읍13941101284
4가평군<NA>가평읍호흡기211211000
5가평군<NA>가평읍심장101101000
6가평군<NA>가평읍신장5029213822161275
7가평군<NA>가평읍정신341618341618000
8가평군<NA>가평읍자폐성1414014140000
9가평군<NA>가평읍뇌병변945143532627412516
시군명구명읍면동명장애유형등록장애인수(합계)등록장애인수(남성)등록장애인수(여성)심한장애인수(합계)심한장애인수(남성)심한장애인수(여성)심하지않은장애인수(합계)심하지않은장애인수(남성)심하지않은장애인수(여성)
7111화성시<NA>화산동정신361620361620000
7112화성시<NA>화산동신장4925243718191275
7113화성시<NA>화산동심장321211110
7114화성시<NA>화산동호흡기431431000
7115화성시<NA>화산동752000752
7116화성시<NA>화산동장루.요루871000871
7117화성시<NA>화산동뇌전증422101321
7118화성시<NA>화산동소계1295808487453278175842530312
7119화성시<NA>화산동지체6163912251157837501313188
7120화성시<NA>화산동언어181265321394

Duplicate rows

Most frequently occurring

시군명구명읍면동명장애유형등록장애인수(합계)등록장애인수(남성)등록장애인수(여성)심한장애인수(합계)심한장애인수(남성)심한장애인수(여성)심하지않은장애인수(합계)심하지않은장애인수(남성)심하지않은장애인수(여성)# duplicates
0가평군<NA>청평면심장1011010002
1가평군<NA>청평면안면1101100002
2성남시분당구운중동5500005502
3성남시분당구운중동장루.요루7610007612
4안양시동안구갈산동1100001102
5안양시동안구갈산동장루.요루2110002112
6안양시동안구갈산동호흡기1011010002