Overview

Dataset statistics

Number of variables8
Number of observations23
Missing cells5
Missing cells (%)2.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory75.7 B

Variable types

Text1
Categorical3
Numeric4

Dataset

Description인천광역시 서구의 동별 장루요루 장애인 현황에 관한 데이터입니다. 관내 동별 장애인 수, 장애정도별 장애인 수에 대한 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15120987/fileData.do

Alerts

장애유형 is highly overall correlated with 등록장애인수_남성 and 5 other fieldsHigh correlation
심한 장애_여성 is highly overall correlated with 등록장애인수_여성 and 2 other fieldsHigh correlation
심한 장애_남성 is highly overall correlated with 장애유형High correlation
등록장애인수_남성 is highly overall correlated with 심하지 않은 장애_남성 and 1 other fieldsHigh correlation
등록장애인수_여성 is highly overall correlated with 심하지 않은 장애_여성 and 2 other fieldsHigh correlation
심하지 않은 장애_남성 is highly overall correlated with 등록장애인수_남성 and 1 other fieldsHigh correlation
심하지 않은 장애_여성 is highly overall correlated with 등록장애인수_여성 and 2 other fieldsHigh correlation
장애유형 is highly imbalanced (74.2%)Imbalance
읍면동 has 1 (4.3%) missing valuesMissing
등록장애인수_남성 has 1 (4.3%) missing valuesMissing
등록장애인수_여성 has 1 (4.3%) missing valuesMissing
심하지 않은 장애_남성 has 1 (4.3%) missing valuesMissing
심하지 않은 장애_여성 has 1 (4.3%) missing valuesMissing
등록장애인수_여성 has 3 (13.0%) zerosZeros
심하지 않은 장애_여성 has 3 (13.0%) zerosZeros

Reproduction

Analysis started2023-12-12 10:57:20.933893
Analysis finished2023-12-12 10:57:24.813401
Duration3.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Text

MISSING 

Distinct22
Distinct (%)100.0%
Missing1
Missing (%)4.3%
Memory size316.0 B
2023-12-12T19:57:25.022895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9090909
Min length3

Characters and Unicode

Total characters86
Distinct characters35
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

Unique22 ?
Unique (%)100.0%

Sample

1st row검암경서동
2nd row연희동
3rd row청라1동
4th row청라2동
5th row청라3동
ValueCountFrequency (%)
검암경서동 1
 
4.5%
연희동 1
 
4.5%
마전동 1
 
4.5%
오류왕길동 1
 
4.5%
당하동 1
 
4.5%
원당동 1
 
4.5%
불로대곡동 1
 
4.5%
검단동 1
 
4.5%
가좌3동 1
 
4.5%
가좌2동 1
 
4.5%
Other values (12) 12
54.5%
2023-12-12T19:57:25.763490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
25.6%
가 6
 
7.0%
3 4
 
4.7%
라 4
 
4.7%
1 4
 
4.7%
2 4
 
4.7%
정 3
 
3.5%
좌 3
 
3.5%
남 3
 
3.5%
청 3
 
3.5%
Other values (25) 30
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
86.0%
Decimal Number 12
 
14.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
29.7%
가 6
 
8.1%
라 4
 
5.4%
정 3
 
4.1%
좌 3
 
4.1%
남 3
 
4.1%
청 3
 
4.1%
석 3
 
4.1%
당 2
 
2.7%
원 2
 
2.7%
Other values (22) 23
31.1%
Decimal Number
ValueCountFrequency (%)
3 4
33.3%
1 4
33.3%
2 4
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
86.0%
Common 12
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
29.7%
가 6
 
8.1%
라 4
 
5.4%
정 3
 
4.1%
좌 3
 
4.1%
남 3
 
4.1%
청 3
 
4.1%
석 3
 
4.1%
당 2
 
2.7%
원 2
 
2.7%
Other values (22) 23
31.1%
Common
ValueCountFrequency (%)
3 4
33.3%
1 4
33.3%
2 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
86.0%
ASCII 12
 
14.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
29.7%
가 6
 
8.1%
라 4
 
5.4%
정 3
 
4.1%
좌 3
 
4.1%
남 3
 
4.1%
청 3
 
4.1%
석 3
 
4.1%
당 2
 
2.7%
원 2
 
2.7%
Other values (22) 23
31.1%
ASCII
ValueCountFrequency (%)
3 4
33.3%
1 4
33.3%
2 4
33.3%

장애유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
장루.요루
22 
<NA>
 
1

Length

Max length5
Median length5
Mean length4.9565217
Min length4

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row장루.요루
2nd row장루.요루
3rd row장루.요루
4th row장루.요루
5th row장루.요루

Common Values

ValueCountFrequency (%)
장루.요루 22
95.7%
<NA> 1
 
4.3%

Length

2023-12-12T19:57:26.040819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:57:26.224849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
장루.요루 22
95.7%
na 1
 
4.3%

등록장애인수_남성
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct9
Distinct (%)40.9%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean4.3636364
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:57:26.376581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.05
Q12
median3.5
Q36.75
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation2.5550222
Coefficient of variation (CV)0.58552592
Kurtosis-1.2247136
Mean4.3636364
Median Absolute Deviation (MAD)1.5
Skewness0.41889725
Sum96
Variance6.5281385
MonotonicityNot monotonic
2023-12-12T19:57:26.617359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
2 5
21.7%
3 4
17.4%
8 3
13.0%
5 3
13.0%
7 2
 
8.7%
1 2
 
8.7%
6 1
 
4.3%
4 1
 
4.3%
9 1
 
4.3%
(Missing) 1
 
4.3%
ValueCountFrequency (%)
1 2
 
8.7%
2 5
21.7%
3 4
17.4%
4 1
 
4.3%
5 3
13.0%
6 1
 
4.3%
7 2
 
8.7%
8 3
13.0%
9 1
 
4.3%
ValueCountFrequency (%)
9 1
 
4.3%
8 3
13.0%
7 2
 
8.7%
6 1
 
4.3%
5 3
13.0%
4 1
 
4.3%
3 4
17.4%
2 5
21.7%
1 2
 
8.7%

등록장애인수_여성
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)27.3%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean2.6818182
Minimum0
Maximum7
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:57:26.847720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2.5
Q33
95-th percentile6.9
Maximum7
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.0560333
Coefficient of variation (CV)0.76665647
Kurtosis-0.039156859
Mean2.6818182
Median Absolute Deviation (MAD)1.5
Skewness0.72589931
Sum59
Variance4.2272727
MonotonicityNot monotonic
2023-12-12T19:57:27.062292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 6
26.1%
1 4
17.4%
2 4
17.4%
5 3
13.0%
0 3
13.0%
7 2
 
8.7%
(Missing) 1
 
4.3%
ValueCountFrequency (%)
0 3
13.0%
1 4
17.4%
2 4
17.4%
3 6
26.1%
5 3
13.0%
7 2
 
8.7%
ValueCountFrequency (%)
7 2
 
8.7%
5 3
13.0%
3 6
26.1%
2 4
17.4%
1 4
17.4%
0 3
13.0%

심한 장애_남성
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
13 
1
7 
2
2 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1304348
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 13
56.5%
1 7
30.4%
2 2
 
8.7%
<NA> 1
 
4.3%

Length

2023-12-12T19:57:27.329967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:57:27.533643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 13
56.5%
1 7
30.4%
2 2
 
8.7%
na 1
 
4.3%

심한 장애_여성
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
19 
1
3 
<NA>
 
1

Length

Max length4
Median length1
Mean length1.1304348
Min length1

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 19
82.6%
1 3
 
13.0%
<NA> 1
 
4.3%

Length

2023-12-12T19:57:28.249099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:57:28.447953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 19
82.6%
1 3
 
13.0%
na 1
 
4.3%

심하지 않은 장애_남성
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct8
Distinct (%)36.4%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean3.8636364
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:57:28.612990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3.5
Q35
95-th percentile7.95
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.2529442
Coefficient of variation (CV)0.58311497
Kurtosis-0.85166605
Mean3.8636364
Median Absolute Deviation (MAD)1.5
Skewness0.51605536
Sum85
Variance5.0757576
MonotonicityNot monotonic
2023-12-12T19:57:28.805928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 5
21.7%
4 3
13.0%
5 3
13.0%
3 3
13.0%
1 3
13.0%
8 2
 
8.7%
7 2
 
8.7%
6 1
 
4.3%
(Missing) 1
 
4.3%
ValueCountFrequency (%)
1 3
13.0%
2 5
21.7%
3 3
13.0%
4 3
13.0%
5 3
13.0%
6 1
 
4.3%
7 2
 
8.7%
8 2
 
8.7%
ValueCountFrequency (%)
8 2
 
8.7%
7 2
 
8.7%
6 1
 
4.3%
5 3
13.0%
4 3
13.0%
3 3
13.0%
2 5
21.7%
1 3
13.0%

심하지 않은 장애_여성
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct6
Distinct (%)27.3%
Missing1
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean2.5454545
Minimum0
Maximum6
Zeros3
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-12T19:57:28.995366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5.95
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8702501
Coefficient of variation (CV)0.73474112
Kurtosis-0.66664469
Mean2.5454545
Median Absolute Deviation (MAD)1
Skewness0.49829201
Sum56
Variance3.4978355
MonotonicityNot monotonic
2023-12-12T19:57:29.187247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 5
21.7%
2 5
21.7%
1 4
17.4%
5 3
13.0%
0 3
13.0%
6 2
 
8.7%
(Missing) 1
 
4.3%
ValueCountFrequency (%)
0 3
13.0%
1 4
17.4%
2 5
21.7%
3 5
21.7%
5 3
13.0%
6 2
 
8.7%
ValueCountFrequency (%)
6 2
 
8.7%
5 3
13.0%
3 5
21.7%
2 5
21.7%
1 4
17.4%
0 3
13.0%

Interactions

2023-12-12T19:57:23.470152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:21.472378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.158350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.809647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:23.656310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:21.646615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.332328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.958339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:23.825221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:21.832236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.494902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:23.107281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:24.001471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.002082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:22.662399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:57:23.279479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:57:29.337748image/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_남성1.0001.0000.0000.7930.3750.8560.000
등록장애인수_여성1.0000.0001.0000.0000.9300.5260.999
심한 장애_남성1.0000.7930.0001.0000.0240.3800.000
심한 장애_여성1.0000.3750.9300.0241.0000.5460.936
심하지 않은 장애_남성1.0000.8560.5260.3800.5461.0000.552
심하지 않은 장애_여성1.0000.0000.9990.0000.9360.5521.000
2023-12-12T19:57:29.559882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장애유형심한 장애_여성심한 장애_남성
장애유형1.0001.0001.000
심한 장애_여성1.0001.0000.000
심한 장애_남성1.0000.0001.000
2023-12-12T19:57:29.754183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록장애인수_남성등록장애인수_여성심하지 않은 장애_남성심하지 않은 장애_여성장애유형심한 장애_남성심한 장애_여성
등록장애인수_남성1.0000.1560.9730.1701.0000.3950.275
등록장애인수_여성0.1561.0000.0920.9871.0000.0000.680
심하지 않은 장애_남성0.9730.0921.0000.1271.0000.1870.325
심하지 않은 장애_여성0.1700.9870.1271.0001.0000.0000.690
장애유형1.0001.0001.0001.0001.0001.0001.000
심한 장애_남성0.3950.0000.1870.0001.0001.0000.000
심한 장애_여성0.2750.6800.3250.6901.0000.0001.000

Missing values

2023-12-12T19:57:24.184781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:57:24.413597image/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.
2023-12-12T19:57:24.652535image/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

읍면동장애유형등록장애인수_남성등록장애인수_여성심한 장애_남성심한 장애_여성심하지 않은 장애_남성심하지 않은 장애_여성
0검암경서동장루.요루850085
1연희동장루.요루531043
2청라1동장루.요루701060
3청라2동장루.요루611051
4청라3동장루.요루230023
5가정1동장루.요루820082
6가정2동장루.요루300030
7가정3동장루.요루120012
8석남1동장루.요루350035
9석남2동장루.요루330033
읍면동장애유형등록장애인수_남성등록장애인수_여성심한 장애_남성심한 장애_여성심하지 않은 장애_남성심하지 않은 장애_여성
13가좌2동장루.요루110011
14가좌3동장루.요루831073
15검단동장루.요루571146
16불로대곡동장루.요루712051
17원당동장루.요루200020
18당하동장루.요루932073
19오류왕길동장루.요루220022
20마전동장루.요루210021
21아라동장루.요루251015
22<NA><NA><NA><NA><NA><NA><NA><NA>