Overview

Dataset statistics

Number of variables6
Number of observations983
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory49.1 KiB
Average record size in memory51.1 B

Variable types

Numeric2
Categorical3
Text1

Dataset

Description광주광역시 광산구에 위치해있는 장애인복지관의 이용자 현황 정보를 (성별, 출생년도, 동, 이용연도, 데이터기준일자 등) 제공합니다.
URLhttps://www.data.go.kr/data/15048526/fileData.do

Alerts

이용연도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:39:06.855756
Analysis finished2023-12-12 04:39:07.874729
Duration1.02 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct983
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean492
Minimum1
Maximum983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2023-12-12T13:39:07.987672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50.1
Q1246.5
median492
Q3737.5
95-th percentile933.9
Maximum983
Range982
Interquartile range (IQR)491

Descriptive statistics

Standard deviation283.91196
Coefficient of variation (CV)0.57705683
Kurtosis-1.2
Mean492
Median Absolute Deviation (MAD)246
Skewness0
Sum483636
Variance80606
MonotonicityStrictly increasing
2023-12-12T13:39:08.171285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
647 1
 
0.1%
649 1
 
0.1%
650 1
 
0.1%
651 1
 
0.1%
652 1
 
0.1%
653 1
 
0.1%
654 1
 
0.1%
655 1
 
0.1%
656 1
 
0.1%
Other values (973) 973
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
983 1
0.1%
982 1
0.1%
981 1
0.1%
980 1
0.1%
979 1
0.1%
978 1
0.1%
977 1
0.1%
976 1
0.1%
975 1
0.1%
974 1
0.1%

성별
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
남
512 
여
471 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남 512
52.1%
여 471
47.9%

Length

2023-12-12T13:39:08.364750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:39:08.521741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 512
52.1%
여 471
47.9%

출생연도
Real number (ℝ)

Distinct88
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1982.2665
Minimum1212
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.8 KiB
2023-12-12T13:39:08.689672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1212
5-th percentile1954
Q11970
median1986
Q31998
95-th percentile2006
Maximum2022
Range810
Interquartile range (IQR)28

Descriptive statistics

Standard deviation31.676222
Coefficient of variation (CV)0.0159798
Kurtosis358.99518
Mean1982.2665
Median Absolute Deviation (MAD)14
Skewness-15.290112
Sum1948568
Variance1003.3831
MonotonicityNot monotonic
2023-12-12T13:39:08.901182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2003 34
 
3.5%
1998 33
 
3.4%
1993 31
 
3.2%
2001 31
 
3.2%
1995 30
 
3.1%
1999 29
 
3.0%
2004 27
 
2.7%
2000 26
 
2.6%
1992 26
 
2.6%
1996 26
 
2.6%
Other values (78) 690
70.2%
ValueCountFrequency (%)
1212 1
 
0.1%
1766 1
 
0.1%
1798 1
 
0.1%
1878 1
 
0.1%
1903 1
 
0.1%
1931 1
 
0.1%
1935 1
 
0.1%
1936 1
 
0.1%
1937 1
 
0.1%
1939 4
0.4%
ValueCountFrequency (%)
2022 1
 
0.1%
2017 1
 
0.1%
2016 2
 
0.2%
2015 5
0.5%
2014 1
 
0.1%
2013 1
 
0.1%
2012 1
 
0.1%
2011 1
 
0.1%
2010 5
0.5%
2009 10
1.0%

동
Text

Distinct146
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2023-12-12T13:39:09.199366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.9989827
Min length2

Characters and Unicode

Total characters2948
Distinct characters120
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)7.0%

Sample

1st row우산동
2nd row도산동
3rd row봉선동
4th row함평군
5th row월곡동
ValueCountFrequency (%)
우산동 151
 
15.3%
월곡동 62
 
6.3%
신가동 62
 
6.3%
운남동 60
 
6.1%
산정동 39
 
4.0%
소촌동 37
 
3.8%
송정동 36
 
3.7%
신창동 28
 
2.8%
장덕동 27
 
2.7%
봉선동 25
 
2.5%
Other values (136) 457
46.4%
2023-12-12T13:39:09.732244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 900
30.5%
산 270
 
9.2%
우 151
 
5.1%
월 107
 
3.6%
신 106
 
3.6%
정 99
 
3.4%
남 79
 
2.7%
운 76
 
2.6%
곡 67
 
2.3%
가 62
 
2.1%
Other values (110) 1031
35.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2944
99.9%
Decimal Number 3
 
0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 900
30.6%
산 270
 
9.2%
우 151
 
5.1%
월 107
 
3.6%
신 106
 
3.6%
정 99
 
3.4%
남 79
 
2.7%
운 76
 
2.6%
곡 67
 
2.3%
가 62
 
2.1%
Other values (107) 1027
34.9%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
3 1
33.3%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2944
99.9%
Common 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 900
30.6%
산 270
 
9.2%
우 151
 
5.1%
월 107
 
3.6%
신 106
 
3.6%
정 99
 
3.4%
남 79
 
2.7%
운 76
 
2.6%
곡 67
 
2.3%
가 62
 
2.1%
Other values (107) 1027
34.9%
Common
ValueCountFrequency (%)
1 2
50.0%
1
25.0%
3 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2944
99.9%
ASCII 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 900
30.6%
산 270
 
9.2%
우 151
 
5.1%
월 107
 
3.6%
신 106
 
3.6%
정 99
 
3.4%
남 79
 
2.7%
운 76
 
2.6%
곡 67
 
2.3%
가 62
 
2.1%
Other values (107) 1027
34.9%
ASCII
ValueCountFrequency (%)
1 2
50.0%
1
25.0%
3 1
25.0%

이용연도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2022
983 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 983
100.0%

Length

2023-12-12T13:39:09.881931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:39:09.991746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 983
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.8 KiB
2022-12-31
983 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-31
2nd row2022-12-31
3rd row2022-12-31
4th row2022-12-31
5th row2022-12-31

Common Values

ValueCountFrequency (%)
2022-12-31 983
100.0%

Length

2023-12-12T13:39:10.400615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:39:10.528007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-31 983
100.0%

Interactions

2023-12-12T13:39:07.356571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:07.087708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:07.492458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:39:07.206155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:39:10.609883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번성별출생연도
연번1.0000.1940.000
성별0.1941.0000.000
출생연도0.0000.0001.000
2023-12-12T13:39:10.723865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번출생연도성별
연번1.000-0.0290.148
출생연도-0.0291.0000.000
성별0.1480.0001.000

Missing values

2023-12-12T13:39:07.675696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:39:07.830192image/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

연번성별출생연도동이용연도데이터기준일자
01여1982우산동20222022-12-31
12여1965도산동20222022-12-31
23여1983봉선동20222022-12-31
34여1968함평군20222022-12-31
45여2002월곡동20222022-12-31
56남1982월계동20222022-12-31
67여2004봉선동20222022-12-31
78남1980신가동20222022-12-31
89여1980삼도동20222022-12-31
910여2003삼거동20222022-12-31
연번성별출생연도동이용연도데이터기준일자
973974여1972덕림동20222022-12-31
974975남1995운암동20222022-12-31
975976남1989운암동20222022-12-31
976977남1955흑석동20222022-12-31
977978남1971진월동20222022-12-31
978979여2009산정동20222022-12-31
979980여1969산정동20222022-12-31
980981여1995우산동20222022-12-31
981982여1995우산동20222022-12-31
982983여1997송정동20222022-12-31