Overview

Dataset statistics

Number of variables8
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory75.5 B

Variable types

Text1
Categorical1
Numeric6

Dataset

Description인천광역시 서구의 동별 뇌병변 장애인 현황에 관한 데이터입니다. 관내 동별 장애인 수, 장애정도별 장애인 수에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15120978/fileData.do

Alerts

장애유형 has constant value ""Constant
등록장애인수_남성 is highly overall correlated with 등록장애인수_여성 and 4 other fieldsHigh correlation
등록장애인수_여성 is highly overall correlated with 등록장애인수_남성 and 4 other fieldsHigh correlation
심한 장애_남성 is highly overall correlated with 등록장애인수_남성 and 4 other fieldsHigh correlation
심한 장애_여성 is highly overall correlated with 등록장애인수_남성 and 4 other fieldsHigh correlation
심하지 않은 장애_남성 is highly overall correlated with 등록장애인수_남성 and 4 other fieldsHigh correlation
심하지 않은 장애_여성 is highly overall correlated with 등록장애인수_남성 and 4 other fieldsHigh correlation
읍면동 has unique valuesUnique
등록장애인수_여성 has 1 (4.2%) zerosZeros
심한 장애_여성 has 1 (4.2%) zerosZeros
심하지 않은 장애_남성 has 1 (4.2%) zerosZeros
심하지 않은 장애_여성 has 1 (4.2%) zerosZeros

Reproduction

Analysis started2023-12-12 00:50:27.576898
Analysis finished2023-12-12 00:50:32.285724
Duration4.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T09:50:32.416245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9166667
Min length3

Characters and Unicode

Total characters94
Distinct characters36
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row검암경서동
2nd row연희동
3rd row청라1동
4th row청라2동
5th row청라3동
ValueCountFrequency (%)
검암경서동 1
 
4.2%
연희동 1
 
4.2%
마전동 1
 
4.2%
오류왕길동 1
 
4.2%
당하동 1
 
4.2%
원당동 1
 
4.2%
불로대곡동 1
 
4.2%
검단동 1
 
4.2%
검단4동 1
 
4.2%
가좌4동 1
 
4.2%
Other values (14) 14
58.3%
2023-12-12T09:50:32.763886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
25.5%
가 7
 
7.4%
좌 4
 
4.3%
라 4
 
4.3%
1 4
 
4.3%
2 4
 
4.3%
3 4
 
4.3%
검 3
 
3.2%
남 3
 
3.2%
청 3
 
3.2%
Other values (26) 34
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80
85.1%
Decimal Number 14
 
14.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
30.0%
가 7
 
8.8%
좌 4
 
5.0%
라 4
 
5.0%
검 3
 
3.8%
남 3
 
3.8%
청 3
 
3.8%
정 3
 
3.8%
석 3
 
3.8%
당 2
 
2.5%
Other values (22) 24
30.0%
Decimal Number
ValueCountFrequency (%)
1 4
28.6%
2 4
28.6%
3 4
28.6%
4 2
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80
85.1%
Common 14
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
30.0%
가 7
 
8.8%
좌 4
 
5.0%
라 4
 
5.0%
검 3
 
3.8%
남 3
 
3.8%
청 3
 
3.8%
정 3
 
3.8%
석 3
 
3.8%
당 2
 
2.5%
Other values (22) 24
30.0%
Common
ValueCountFrequency (%)
1 4
28.6%
2 4
28.6%
3 4
28.6%
4 2
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80
85.1%
ASCII 14
 
14.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
30.0%
가 7
 
8.8%
좌 4
 
5.0%
라 4
 
5.0%
검 3
 
3.8%
남 3
 
3.8%
청 3
 
3.8%
정 3
 
3.8%
석 3
 
3.8%
당 2
 
2.5%
Other values (22) 24
30.0%
ASCII
ValueCountFrequency (%)
1 4
28.6%
2 4
28.6%
3 4
28.6%
4 2
14.3%

장애유형
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
뇌병변
24 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
뇌병변 24
100.0%

Length

2023-12-12T09:50:32.922863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:50:33.010186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
뇌병변 24
100.0%

등록장애인수_남성
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.333333
Minimum1
Maximum135
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T09:50:33.101202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.6
Q137.5
median45
Q373.5
95-th percentile96.8
Maximum135
Range134
Interquartile range (IQR)36

Descriptive statistics

Standard deviation29.270354
Coefficient of variation (CV)0.55930613
Kurtosis1.5241296
Mean52.333333
Median Absolute Deviation (MAD)15
Skewness0.96845735
Sum1256
Variance856.75362
MonotonicityNot monotonic
2023-12-12T09:50:33.247284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
45 2
 
8.3%
90 1
 
4.2%
135 1
 
4.2%
73 1
 
4.2%
39 1
 
4.2%
55 1
 
4.2%
42 1
 
4.2%
54 1
 
4.2%
76 1
 
4.2%
1 1
 
4.2%
Other values (13) 13
54.2%
ValueCountFrequency (%)
1 1
4.2%
19 1
4.2%
23 1
4.2%
24 1
4.2%
27 1
4.2%
33 1
4.2%
39 1
4.2%
40 1
4.2%
41 1
4.2%
42 1
4.2%
ValueCountFrequency (%)
135 1
4.2%
98 1
4.2%
90 1
4.2%
78 1
4.2%
76 1
4.2%
75 1
4.2%
73 1
4.2%
55 1
4.2%
54 1
4.2%
51 1
4.2%

등록장애인수_여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.833333
Minimum0
Maximum94
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T09:50:33.381707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.6
Q130
median38
Q349.75
95-th percentile73.55
Maximum94
Range94
Interquartile range (IQR)19.75

Descriptive statistics

Standard deviation21.249382
Coefficient of variation (CV)0.52039303
Kurtosis0.68376047
Mean40.833333
Median Absolute Deviation (MAD)10
Skewness0.50792371
Sum980
Variance451.53623
MonotonicityNot monotonic
2023-12-12T09:50:33.511455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
41 2
 
8.3%
30 2
 
8.3%
55 2
 
8.3%
48 2
 
8.3%
74 1
 
4.2%
35 1
 
4.2%
46 1
 
4.2%
32 1
 
4.2%
39 1
 
4.2%
71 1
 
4.2%
Other values (10) 10
41.7%
ValueCountFrequency (%)
0 1
4.2%
11 1
4.2%
15 1
4.2%
17 1
4.2%
27 1
4.2%
30 2
8.3%
32 1
4.2%
33 1
4.2%
35 1
4.2%
36 1
4.2%
ValueCountFrequency (%)
94 1
4.2%
74 1
4.2%
71 1
4.2%
65 1
4.2%
55 2
8.3%
48 2
8.3%
46 1
4.2%
41 2
8.3%
39 1
4.2%
37 1
4.2%

심한 장애_남성
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T09:50:33.665946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q118.5
median24
Q340
95-th percentile49.85
Maximum77
Range76
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation16.539807
Coefficient of variation (CV)0.59070739
Kurtosis2.0114497
Mean28
Median Absolute Deviation (MAD)8.5
Skewness1.1394177
Sum672
Variance273.56522
MonotonicityNot monotonic
2023-12-12T09:50:33.964857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
23 2
 
8.3%
19 2
 
8.3%
28 2
 
8.3%
14 2
 
8.3%
10 2
 
8.3%
40 2
 
8.3%
24 2
 
8.3%
27 2
 
8.3%
50 1
 
4.2%
41 1
 
4.2%
Other values (6) 6
25.0%
ValueCountFrequency (%)
1 1
4.2%
10 2
8.3%
14 2
8.3%
17 1
4.2%
19 2
8.3%
21 1
4.2%
23 2
8.3%
24 2
8.3%
27 2
8.3%
28 2
8.3%
ValueCountFrequency (%)
77 1
4.2%
50 1
4.2%
49 1
4.2%
46 1
4.2%
41 1
4.2%
40 2
8.3%
28 2
8.3%
27 2
8.3%
24 2
8.3%
23 2
8.3%

심한 장애_여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)91.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.708333
Minimum0
Maximum52
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T09:50:34.122902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.15
Q115.75
median24
Q333.5
95-th percentile47.25
Maximum52
Range52
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation12.936229
Coefficient of variation (CV)0.52355732
Kurtosis-0.22228935
Mean24.708333
Median Absolute Deviation (MAD)9
Skewness0.32263076
Sum593
Variance167.34601
MonotonicityNot monotonic
2023-12-12T09:50:34.282250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
20 2
 
8.3%
26 2
 
8.3%
43 1
 
4.2%
25 1
 
4.2%
35 1
 
4.2%
31 1
 
4.2%
17 1
 
4.2%
21 1
 
4.2%
23 1
 
4.2%
48 1
 
4.2%
Other values (12) 12
50.0%
ValueCountFrequency (%)
0 1
4.2%
8 1
4.2%
9 1
4.2%
12 1
4.2%
13 1
4.2%
15 1
4.2%
16 1
4.2%
17 1
4.2%
20 2
8.3%
21 1
4.2%
ValueCountFrequency (%)
52 1
4.2%
48 1
4.2%
43 1
4.2%
37 1
4.2%
36 1
4.2%
35 1
4.2%
33 1
4.2%
31 1
4.2%
27 1
4.2%
26 2
8.3%

심하지 않은 장애_남성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct21
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.333333
Minimum0
Maximum58
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T09:50:34.409089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q116
median23
Q330.5
95-th percentile47.65
Maximum58
Range58
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation13.206279
Coefficient of variation (CV)0.54272378
Kurtosis0.82695333
Mean24.333333
Median Absolute Deviation (MAD)7
Skewness0.7010219
Sum584
Variance174.4058
MonotonicityNot monotonic
2023-12-12T09:50:34.570569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
23 2
 
8.3%
9 2
 
8.3%
16 2
 
8.3%
40 1
 
4.2%
24 1
 
4.2%
32 1
 
4.2%
28 1
 
4.2%
21 1
 
4.2%
26 1
 
4.2%
30 1
 
4.2%
Other values (11) 11
45.8%
ValueCountFrequency (%)
0 1
4.2%
9 2
8.3%
10 1
4.2%
14 1
4.2%
16 2
8.3%
17 1
4.2%
19 1
4.2%
21 1
4.2%
22 1
4.2%
23 2
8.3%
ValueCountFrequency (%)
58 1
4.2%
49 1
4.2%
40 1
4.2%
38 1
4.2%
35 1
4.2%
32 1
4.2%
30 1
4.2%
28 1
4.2%
26 1
4.2%
25 1
4.2%

심하지 않은 장애_여성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.125
Minimum0
Maximum42
Zeros1
Zeros (%)4.2%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T09:50:34.737604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.45
Q110
median15
Q321.25
95-th percentile30.55
Maximum42
Range42
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation9.8215048
Coefficient of variation (CV)0.60908557
Kurtosis0.6891402
Mean16.125
Median Absolute Deviation (MAD)5.5
Skewness0.71125945
Sum387
Variance96.461957
MonotonicityNot monotonic
2023-12-12T09:50:34.884237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
10 3
 
12.5%
11 2
 
8.3%
15 2
 
8.3%
28 2
 
8.3%
20 2
 
8.3%
22 1
 
4.2%
9 1
 
4.2%
16 1
 
4.2%
23 1
 
4.2%
0 1
 
4.2%
Other values (8) 8
33.3%
ValueCountFrequency (%)
0 1
 
4.2%
2 1
 
4.2%
5 1
 
4.2%
7 1
 
4.2%
9 1
 
4.2%
10 3
12.5%
11 2
8.3%
12 1
 
4.2%
15 2
8.3%
16 1
 
4.2%
ValueCountFrequency (%)
42 1
4.2%
31 1
4.2%
28 2
8.3%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 2
8.3%
19 1
4.2%
16 1
4.2%
15 2
8.3%

Interactions

2023-12-12T09:50:31.108858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:27.838259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.442153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.170338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.862199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.471157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:31.251265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:27.937773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.575418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.313476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.986659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.577429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:31.369474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.022288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.704256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.432746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.096686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.669407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:31.489025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.127572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.823650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.545180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.186282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.770094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:31.631721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.220916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.942646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.634094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.276887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.886168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:31.850289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:28.349682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.065216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:29.752071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:30.378135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:50:31.003121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:50:34.984829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동등록장애인수_남성등록장애인수_여성심한 장애_남성심한 장애_여성심하지 않은 장애_남성심하지 않은 장애_여성
읍면동1.0001.0001.0001.0001.0001.0001.000
등록장애인수_남성1.0001.0000.9140.9700.8010.9660.923
등록장애인수_여성1.0000.9141.0000.8270.8500.8880.914
심한 장애_남성1.0000.9700.8271.0000.7680.9000.809
심한 장애_여성1.0000.8010.8500.7681.0000.4860.660
심하지 않은 장애_남성1.0000.9660.8880.9000.4861.0000.842
심하지 않은 장애_여성1.0000.9230.9140.8090.6600.8421.000
2023-12-12T09:50:35.477500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록장애인수_남성등록장애인수_여성심한 장애_남성심한 장애_여성심하지 않은 장애_남성심하지 않은 장애_여성
등록장애인수_남성1.0000.8880.9650.8450.9630.763
등록장애인수_여성0.8881.0000.9030.9280.8330.866
심한 장애_남성0.9650.9031.0000.9000.8840.745
심한 장애_여성0.8450.9280.9001.0000.7760.669
심하지 않은 장애_남성0.9630.8330.8840.7761.0000.724
심하지 않은 장애_여성0.7630.8660.7450.6690.7241.000

Missing values

2023-12-12T09:50:32.025340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:50:32.219920image/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

읍면동장애유형등록장애인수_남성등록장애인수_여성심한 장애_남성심한 장애_여성심하지 않은 장애_남성심하지 않은 장애_여성
0검암경서동뇌병변907450434031
1연희동뇌병변1359477525842
2청라1동뇌병변332719151412
3청라2동뇌병변516528372328
4청라3동뇌병변243014201010
5가정1동뇌병변985549364919
6가정2동뇌병변191110992
7가정3동뇌병변2715108177
8석남1동뇌병변784840273821
9석남2동뇌병변403721261911
읍면동장애유형등록장애인수_남성등록장애인수_여성심한 장애_남성심한 장애_여성심하지 않은 장애_남성심하지 않은 장애_여성
14가좌3동뇌병변454823202228
15가좌4동뇌병변2317141295
16검단4동뇌병변101000
17검단동뇌병변767146483023
18불로대곡동뇌병변543928232616
19원당동뇌병변42301921239
20당하동뇌병변453224172115
21오류왕길동뇌병변554127312810
22마전동뇌병변394123261615
23아라동뇌병변734641353211