Overview

Dataset statistics

Number of variables3
Number of observations109
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.0 KiB
Average record size in memory28.2 B

Variable types

Numeric3

Dataset

Description대전광역시 장애인 연령별 등록현황에 대한 데이터로 연령(1세 단위), 성별(남성 및 여성) 등의 항목을 제공합니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15062786/fileData.do

Alerts

남성 is highly overall correlated with 여성High correlation
여성 is highly overall correlated with 남성High correlation
연령 has unique valuesUnique
남성 has 6 (5.5%) zerosZeros

Reproduction

Analysis started2023-12-12 21:59:32.943556
Analysis finished2023-12-12 21:59:33.954466
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연령
Real number (ℝ)

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.119266
Minimum0
Maximum119
Zeros1
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T06:59:34.036319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.4
Q127
median54
Q381
95-th percentile102.6
Maximum119
Range119
Interquartile range (IQR)54

Descriptive statistics

Standard deviation31.831944
Coefficient of variation (CV)0.58818138
Kurtosis-1.1515171
Mean54.119266
Median Absolute Deviation (MAD)27
Skewness0.02792864
Sum5899
Variance1013.2727
MonotonicityStrictly increasing
2023-12-13T06:59:34.248065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
0.9%
69 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
Other values (99) 99
90.8%
ValueCountFrequency (%)
0 1
0.9%
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
ValueCountFrequency (%)
119 1
0.9%
109 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%

남성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct94
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean385.73394
Minimum0
Maximum1282
Zeros6
Zeros (%)5.5%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T06:59:34.405097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.4
Q1115
median235
Q3675
95-th percentile1069.4
Maximum1282
Range1282
Interquartile range (IQR)560

Descriptive statistics

Standard deviation353.28439
Coefficient of variation (CV)0.91587582
Kurtosis-0.58820719
Mean385.73394
Median Absolute Deviation (MAD)219
Skewness0.78036023
Sum42045
Variance124809.86
MonotonicityNot monotonic
2023-12-13T06:59:34.579238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 6
 
5.5%
121 3
 
2.8%
5 2
 
1.8%
211 2
 
1.8%
115 2
 
1.8%
128 2
 
1.8%
143 2
 
1.8%
837 2
 
1.8%
1 2
 
1.8%
9 2
 
1.8%
Other values (84) 84
77.1%
ValueCountFrequency (%)
0 6
5.5%
1 2
 
1.8%
2 1
 
0.9%
3 1
 
0.9%
5 2
 
1.8%
9 2
 
1.8%
13 1
 
0.9%
16 1
 
0.9%
28 1
 
0.9%
29 1
 
0.9%
ValueCountFrequency (%)
1282 1
0.9%
1258 1
0.9%
1112 1
0.9%
1110 1
0.9%
1101 1
0.9%
1081 1
0.9%
1052 1
0.9%
984 1
0.9%
970 1
0.9%
964 1
0.9%

여성
Real number (ℝ)

HIGH CORRELATION 

Distinct94
Distinct (%)86.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean274.41284
Minimum0
Maximum867
Zeros1
Zeros (%)0.9%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T06:59:34.731234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.4
Q171
median151
Q3511
95-th percentile711.4
Maximum867
Range867
Interquartile range (IQR)440

Descriptive statistics

Standard deviation253.27358
Coefficient of variation (CV)0.92296545
Kurtosis-0.99085875
Mean274.41284
Median Absolute Deviation (MAD)127
Skewness0.70705693
Sum29911
Variance64147.504
MonotonicityNot monotonic
2023-12-13T06:59:34.867856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 3
 
2.8%
107 3
 
2.8%
72 2
 
1.8%
121 2
 
1.8%
208 2
 
1.8%
203 2
 
1.8%
71 2
 
1.8%
6 2
 
1.8%
587 2
 
1.8%
51 2
 
1.8%
Other values (84) 87
79.8%
ValueCountFrequency (%)
0 1
 
0.9%
1 3
2.8%
2 2
1.8%
3 1
 
0.9%
6 2
1.8%
8 1
 
0.9%
15 1
 
0.9%
16 1
 
0.9%
17 1
 
0.9%
20 1
 
0.9%
ValueCountFrequency (%)
867 1
0.9%
754 1
0.9%
750 1
0.9%
724 1
0.9%
717 1
0.9%
713 1
0.9%
709 1
0.9%
707 1
0.9%
704 1
0.9%
697 1
0.9%

Interactions

2023-12-13T06:59:33.586526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.022862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.342542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.665993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.167192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.436829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.751929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.260191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:59:33.511149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:59:34.956497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령남성여성
연령1.0000.8870.925
남성0.8871.0000.909
여성0.9250.9091.000
2023-12-13T06:59:35.337955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령남성여성
연령1.0000.0470.275
남성0.0471.0000.888
여성0.2750.8881.000

Missing values

2023-12-13T06:59:33.852749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:59:33.926768image/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

연령남성여성
0001
1156
22915
332817
444124
558434
6611859
7712156
8812151
9914372
연령남성여성
9999520
100100216
10110108
10210233
10310316
10410402
10510502
10610601
10710910
10811901