Overview

Dataset statistics

Number of variables7
Number of observations139
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory59.9 B

Variable types

Numeric3
Categorical4

Dataset

Description대구광역시 중구의 행정동 기준으로 장애인 유형 및 정도별 등록현황(연번,시도명, 시군구명, 행정동명,장애유형, 심한 장애, 심하지 않은 장애) 정보를 제공합니다. - 최근 통계 기준 자료입니다. (2022-12-31 집계자료) - 생활지원과 장애인지원팀에서 제공합니다.
Author대구광역시 중구
URLhttps://www.data.go.kr/data/15112233/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
연번 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
심한 장애 has 20 (14.4%) zerosZeros
심하지 않은 장애 has 48 (34.5%) zerosZeros

Reproduction

Analysis started2023-12-12 04:18:55.249845
Analysis finished2023-12-12 04:18:56.704702
Duration1.45 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct139
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70
Minimum1
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:18:56.780435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.9
Q135.5
median70
Q3104.5
95-th percentile132.1
Maximum139
Range138
Interquartile range (IQR)69

Descriptive statistics

Standard deviation40.269923
Coefficient of variation (CV)0.57528461
Kurtosis-1.2
Mean70
Median Absolute Deviation (MAD)35
Skewness0
Sum9730
Variance1621.6667
MonotonicityStrictly increasing
2023-12-12T13:18:56.932911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
97 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
98 1
 
0.7%
89 1
 
0.7%
Other values (129) 129
92.8%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
대구광역시
139 

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 139
100.0%

Length

2023-12-12T13:18:57.088905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:18:57.185231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 139
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
중구
139 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 139
100.0%

Length

2023-12-12T13:18:57.292123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:18:57.412149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 139
100.0%

행정동명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
남산4동
14 
성내3동
13 
대봉1동
13 
성내2동
12 
남산2동
12 
Other values (7)
75 

Length

Max length4
Median length4
Mean length3.7769784
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남산4동 14
10.1%
성내3동 13
9.4%
대봉1동 13
9.4%
성내2동 12
8.6%
남산2동 12
8.6%
남산3동 12
8.6%
대봉2동 12
8.6%
동인동 11
7.9%
남산1동 11
7.9%
삼덕동 10
7.2%
Other values (2) 19
13.7%

Length

2023-12-12T13:18:57.589374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남산4동 14
10.1%
성내3동 13
9.4%
대봉1동 13
9.4%
성내2동 12
8.6%
남산2동 12
8.6%
남산3동 12
8.6%
대봉2동 12
8.6%
동인동 11
7.9%
남산1동 11
7.9%
삼덕동 10
7.2%
Other values (2) 19
13.7%

장애유형
Categorical

Distinct15
Distinct (%)10.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
지체
12 
시각
12 
청각
12 
지적
12 
뇌병변
12 
Other values (10)
79 

Length

Max length5
Median length2
Mean length2.4028777
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지체 12
8.6%
시각 12
8.6%
청각 12
8.6%
지적 12
8.6%
뇌병변 12
8.6%
정신 12
8.6%
신장 12
8.6%
자폐성 11
7.9%
장루+요루 10
 
7.2%
언어 9
 
6.5%
Other values (5) 25
18.0%

Length

2023-12-12T13:18:57.728579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지체 12
8.6%
시각 12
8.6%
청각 12
8.6%
지적 12
8.6%
뇌병변 12
8.6%
정신 12
8.6%
신장 12
8.6%
자폐성 11
7.9%
장루+요루 10
 
7.2%
언어 9
 
6.5%
Other values (5) 25
18.0%

심한 장애
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.100719
Minimum0
Maximum77
Zeros20
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:18:57.873792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q314
95-th percentile26.2
Maximum77
Range77
Interquartile range (IQR)13

Descriptive statistics

Standard deviation12.557286
Coefficient of variation (CV)1.2432071
Kurtosis9.9035127
Mean10.100719
Median Absolute Deviation (MAD)5
Skewness2.7008342
Sum1404
Variance157.68543
MonotonicityNot monotonic
2023-12-12T13:18:58.055292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 20
 
14.4%
1 16
 
11.5%
2 11
 
7.9%
6 8
 
5.8%
10 6
 
4.3%
14 6
 
4.3%
3 6
 
4.3%
9 5
 
3.6%
12 5
 
3.6%
7 5
 
3.6%
Other values (23) 51
36.7%
ValueCountFrequency (%)
0 20
14.4%
1 16
11.5%
2 11
7.9%
3 6
 
4.3%
4 5
 
3.6%
5 4
 
2.9%
6 8
 
5.8%
7 5
 
3.6%
8 3
 
2.2%
9 5
 
3.6%
ValueCountFrequency (%)
77 1
 
0.7%
66 1
 
0.7%
65 1
 
0.7%
44 1
 
0.7%
41 1
 
0.7%
37 1
 
0.7%
28 1
 
0.7%
26 3
2.2%
24 2
1.4%
23 3
2.2%

심하지 않은 장애
Real number (ℝ)

ZEROS 

Distinct48
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.94964
Minimum0
Maximum239
Zeros48
Zeros (%)34.5%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T13:18:58.217906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320.5
95-th percentile82.9
Maximum239
Range239
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation35.817436
Coefficient of variation (CV)1.8901381
Kurtosis11.490051
Mean18.94964
Median Absolute Deviation (MAD)2
Skewness2.9612021
Sum2634
Variance1282.8887
MonotonicityNot monotonic
2023-12-12T13:18:58.371155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 48
34.5%
1 18
 
12.9%
2 8
 
5.8%
4 6
 
4.3%
3 6
 
4.3%
10 3
 
2.2%
12 3
 
2.2%
81 2
 
1.4%
7 2
 
1.4%
45 2
 
1.4%
Other values (38) 41
29.5%
ValueCountFrequency (%)
0 48
34.5%
1 18
 
12.9%
2 8
 
5.8%
3 6
 
4.3%
4 6
 
4.3%
5 2
 
1.4%
7 2
 
1.4%
8 1
 
0.7%
9 1
 
0.7%
10 3
 
2.2%
ValueCountFrequency (%)
239 1
0.7%
150 1
0.7%
127 1
0.7%
120 1
0.7%
113 1
0.7%
109 1
0.7%
100 1
0.7%
81 2
1.4%
76 1
0.7%
71 2
1.4%

Interactions

2023-12-12T13:18:56.123384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:55.504249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:55.807417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:56.229689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:55.623039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:55.917013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:56.355515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:55.722048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:18:56.018327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:18:58.464510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번행정동명장애유형심한 장애심하지 않은 장애
연번1.0000.9610.0000.1560.000
행정동명0.9611.0000.0000.0000.000
장애유형0.0000.0001.0000.5320.598
심한 장애0.1560.0000.5321.0000.909
심하지 않은 장애0.0000.0000.5980.9091.000
2023-12-12T13:18:58.598439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
장애유형행정동명
장애유형1.0000.000
행정동명0.0001.000
2023-12-12T13:18:58.696287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번심한 장애심하지 않은 장애행정동명장애유형
연번1.000-0.086-0.0820.8370.000
심한 장애-0.0861.0000.2750.0000.252
심하지 않은 장애-0.0820.2751.0000.0000.297
행정동명0.8370.0000.0001.0000.000
장애유형0.0000.2520.2970.0001.000

Missing values

2023-12-12T13:18:56.520565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:18:56.652624image/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

연번시도명시군구명행정동명장애유형심한 장애심하지 않은 장애
01대구광역시중구동인동지체44150
12대구광역시중구동인동시각1032
23대구광역시중구동인동청각11100
34대구광역시중구동인동언어05
45대구광역시중구동인동지적240
56대구광역시중구동인동뇌병변3724
67대구광역시중구동인동정신170
78대구광역시중구동인동신장143
89대구광역시중구동인동호흡기30
910대구광역시중구동인동간01
연번시도명시군구명행정동명장애유형심한 장애심하지 않은 장애
129130대구광역시중구대봉2동청각836
130131대구광역시중구대봉2동언어12
131132대구광역시중구대봉2동지적140
132133대구광역시중구대봉2동뇌병변177
133134대구광역시중구대봉2동자폐성40
134135대구광역시중구대봉2동정신100
135136대구광역시중구대봉2동신장45
136137대구광역시중구대봉2동심장01
137138대구광역시중구대봉2동간01
138139대구광역시중구대봉2동장루+요루03