Overview

Dataset statistics

Number of variables6
Number of observations9872
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory491.8 KiB
Average record size in memory51.0 B

Variable types

Numeric3
Categorical2
Text1

Dataset

Description대전광역시 동구 관내 복지대상 인구비율 정보로서, 읍면동명, 읍면동코드, 복지구분, 연령(1세단위) 및 인구비율 정보를 포함하고 있습니다.
Author대전광역시 동구
URLhttps://www.data.go.kr/data/15111122/fileData.do

Alerts

법정동코드 is highly overall correlated with 법정읍면동명High correlation
법정읍면동명 is highly overall correlated with 법정동코드High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:12:04.296083
Analysis finished2023-12-12 09:12:06.404208
Duration2.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct9872
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4935.5
Minimum0
Maximum9871
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2023-12-12T18:12:06.496171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile493.55
Q12467.75
median4935.5
Q37403.25
95-th percentile9377.45
Maximum9871
Range9871
Interquartile range (IQR)4935.5

Descriptive statistics

Standard deviation2849.9453
Coefficient of variation (CV)0.577438
Kurtosis-1.2
Mean4935.5
Median Absolute Deviation (MAD)2468
Skewness0
Sum48723256
Variance8122188
MonotonicityStrictly increasing
2023-12-12T18:12:06.660989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
6585 1
 
< 0.1%
6578 1
 
< 0.1%
6579 1
 
< 0.1%
6580 1
 
< 0.1%
6581 1
 
< 0.1%
6582 1
 
< 0.1%
6583 1
 
< 0.1%
6584 1
 
< 0.1%
6586 1
 
< 0.1%
Other values (9862) 9862
99.9%
ValueCountFrequency (%)
0 1
< 0.1%
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%
ValueCountFrequency (%)
9871 1
< 0.1%
9870 1
< 0.1%
9869 1
< 0.1%
9868 1
< 0.1%
9867 1
< 0.1%
9866 1
< 0.1%
9865 1
< 0.1%
9864 1
< 0.1%
9863 1
< 0.1%
9862 1
< 0.1%

법정읍면동명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
가양1동
1103 
가양2동
1065 
판암1동
1047 
판암2동
951 
용전동
551 
Other values (11)
5155 

Length

Max length4
Median length3
Mean length3.3202998
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row효동
2nd row효동
3rd row용전동
4th row용전동
5th row용전동

Common Values

ValueCountFrequency (%)
가양1동 1103
11.2%
가양2동 1065
10.8%
판암1동 1047
10.6%
판암2동 951
 
9.6%
용전동 551
 
5.6%
삼성동 536
 
5.4%
용운동 518
 
5.2%
효동 514
 
5.2%
산내동 507
 
5.1%
홍도동 499
 
5.1%
Other values (6) 2581
26.1%

Length

2023-12-12T18:12:06.811203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가양1동 1103
11.2%
가양2동 1065
10.8%
판암1동 1047
10.6%
판암2동 951
 
9.6%
용전동 551
 
5.6%
삼성동 536
 
5.4%
용운동 518
 
5.2%
효동 514
 
5.2%
산내동 507
 
5.1%
홍도동 499
 
5.1%
Other values (6) 2581
26.1%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0110117 × 109
Minimum3.0110103 × 109
Maximum3.0110149 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2023-12-12T18:12:06.964710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0110103 × 109
5-th percentile3.0110103 × 109
Q13.0110107 × 109
median3.0110114 × 109
Q33.0110117 × 109
95-th percentile3.0110148 × 109
Maximum3.0110149 × 109
Range4600
Interquartile range (IQR)1000

Descriptive statistics

Standard deviation1394.1649
Coefficient of variation (CV)4.6302206 × 10-7
Kurtosis0.76891133
Mean3.0110117 × 109
Median Absolute Deviation (MAD)400
Skewness1.5005154
Sum2.9724708 × 1013
Variance1943695.6
MonotonicityNot monotonic
2023-12-12T18:12:07.084126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3011011400 2168
22.0%
3011010700 1998
20.2%
3011011500 551
 
5.6%
3011011800 536
 
5.4%
3011010900 518
 
5.2%
3011010300 514
 
5.2%
3011014700 507
 
5.1%
3011011700 499
 
5.1%
3011011600 491
 
5.0%
3011011000 490
 
5.0%
Other values (4) 1600
16.2%
ValueCountFrequency (%)
3011010300 514
 
5.2%
3011010700 1998
20.2%
3011010900 518
 
5.2%
3011011000 490
 
5.0%
3011011100 485
 
4.9%
3011011400 2168
22.0%
3011011500 551
 
5.6%
3011011600 491
 
5.0%
3011011700 499
 
5.1%
3011011800 536
 
5.4%
ValueCountFrequency (%)
3011014900 401
 
4.1%
3011014800 461
 
4.7%
3011014700 507
 
5.1%
3011014600 253
 
2.6%
3011011800 536
 
5.4%
3011011700 499
 
5.1%
3011011600 491
 
5.0%
3011011500 551
 
5.6%
3011011400 2168
22.0%
3011011100 485
 
4.9%

복지구분
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
의료급여
1778 
기초수급자
1775 
장애인
1728 
차상위계층
1639 
한부모가족
960 
Other values (5)
1992 

Length

Max length6
Median length5
Mean length4.3855348
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row자활지원
2nd row자활지원
3rd row차상위계층
4th row한부모가족
5th row차상위계층

Common Values

ValueCountFrequency (%)
의료급여 1778
18.0%
기초수급자 1775
18.0%
장애인 1728
17.5%
차상위계층 1639
16.6%
한부모가족 960
9.7%
기초연금 576
 
5.8%
서비스이용권 486
 
4.9%
자활지원 421
 
4.3%
긴급복지 415
 
4.2%
영유아 보육 94
 
1.0%

Length

2023-12-12T18:12:07.249370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:12:07.402372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
의료급여 1778
17.8%
기초수급자 1775
17.8%
장애인 1728
17.3%
차상위계층 1639
16.4%
한부모가족 960
9.6%
기초연금 576
 
5.8%
서비스이용권 486
 
4.9%
자활지원 421
 
4.2%
긴급복지 415
 
4.2%
영유아 94
 
0.9%

연령
Real number (ℝ)

Distinct103
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.634927
Minimum0
Maximum103
Zeros37
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size86.9 KiB
2023-12-12T18:12:07.600574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q126
median50
Q371
95-th percentile90
Maximum103
Range103
Interquartile range (IQR)45

Descriptive statistics

Standard deviation26.582165
Coefficient of variation (CV)0.54656534
Kurtosis-1.1122718
Mean48.634927
Median Absolute Deviation (MAD)22
Skewness-0.0643305
Sum480124
Variance706.61152
MonotonicityNot monotonic
2023-12-12T18:12:07.817471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
65 131
 
1.3%
53 127
 
1.3%
68 127
 
1.3%
66 127
 
1.3%
55 126
 
1.3%
44 125
 
1.3%
47 123
 
1.2%
51 121
 
1.2%
52 121
 
1.2%
43 121
 
1.2%
Other values (93) 8623
87.3%
ValueCountFrequency (%)
0 37
 
0.4%
1 44
0.4%
2 76
0.8%
3 94
1.0%
4 92
0.9%
5 107
1.1%
6 106
1.1%
7 102
1.0%
8 102
1.0%
9 98
1.0%
ValueCountFrequency (%)
103 2
 
< 0.1%
101 1
 
< 0.1%
100 7
 
0.1%
99 10
 
0.1%
98 15
 
0.2%
97 20
 
0.2%
96 24
 
0.2%
95 52
0.5%
94 64
0.6%
93 82
0.8%

비율
Text

Distinct2040
Distinct (%)20.7%
Missing0
Missing (%)0.0%
Memory size77.3 KiB
2023-12-12T18:12:08.273100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.2571921
Min length5

Characters and Unicode

Total characters51899
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique914 ?
Unique (%)9.3%

Sample

1st row0.19%
2nd row0.21%
3rd row0.22%
4th row0.22%
5th row0.22%
ValueCountFrequency (%)
50.00 60
 
0.6%
20.00 54
 
0.5%
33.33 53
 
0.5%
14.29 48
 
0.5%
16.67 44
 
0.4%
7.14 43
 
0.4%
11.11 43
 
0.4%
12.50 43
 
0.4%
5.26 41
 
0.4%
10.00 39
 
0.4%
Other values (2030) 9404
95.3%
2023-12-12T18:12:08.893900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 9872
19.0%
% 9872
19.0%
1 4659
9.0%
0 4348
8.4%
2 3683
 
7.1%
3 3388
 
6.5%
4 2909
 
5.6%
5 2880
 
5.5%
6 2770
 
5.3%
7 2753
 
5.3%
Other values (2) 4765
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32155
62.0%
Other Punctuation 19744
38.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4659
14.5%
0 4348
13.5%
2 3683
11.5%
3 3388
10.5%
4 2909
9.0%
5 2880
9.0%
6 2770
8.6%
7 2753
8.6%
8 2525
7.9%
9 2240
7.0%
Other Punctuation
ValueCountFrequency (%)
. 9872
50.0%
% 9872
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51899
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 9872
19.0%
% 9872
19.0%
1 4659
9.0%
0 4348
8.4%
2 3683
 
7.1%
3 3388
 
6.5%
4 2909
 
5.6%
5 2880
 
5.5%
6 2770
 
5.3%
7 2753
 
5.3%
Other values (2) 4765
9.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51899
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 9872
19.0%
% 9872
19.0%
1 4659
9.0%
0 4348
8.4%
2 3683
 
7.1%
3 3388
 
6.5%
4 2909
 
5.6%
5 2880
 
5.5%
6 2770
 
5.3%
7 2753
 
5.3%
Other values (2) 4765
9.2%

Interactions

2023-12-12T18:12:05.865316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.223660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.538972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.981123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.329722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.642768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:06.085669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.426959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T18:12:05.752551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T18:12:09.007973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번법정읍면동명법정동코드복지구분연령
순번1.0000.2810.2880.7450.623
법정읍면동명0.2811.0001.0000.1870.000
법정동코드0.2881.0001.0000.1540.039
복지구분0.7450.1870.1541.0000.536
연령0.6230.0000.0390.5361.000
2023-12-12T18:12:09.112358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정읍면동명복지구분
법정읍면동명1.0000.074
복지구분0.0741.000
2023-12-12T18:12:09.212579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번법정동코드연령법정읍면동명복지구분
순번1.000-0.0080.3950.1130.315
법정동코드-0.0081.0000.0140.9990.063
연령0.3950.0141.0000.0000.190
법정읍면동명0.1130.9990.0001.0000.074
복지구분0.3150.0630.1900.0741.000

Missing values

2023-12-12T18:12:06.217110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T18:12:06.351762image/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

순번법정읍면동명법정동코드복지구분연령비율
00효동3011010300자활지원490.19%
11효동3011010300자활지원470.21%
22용전동3011011500차상위계층260.22%
33용전동3011011500한부모가족280.22%
44용전동3011011500차상위계층280.22%
55용전동3011011500한부모가족290.22%
66용전동3011011500의료급여290.22%
77효동3011010300자활지원450.22%
88용전동3011011500의료급여270.23%
99용전동3011011500서비스이용권270.23%
순번법정읍면동명법정동코드복지구분연령비율
98629862삼성동3011011800기초연금8797.62%
98639863용운동3011010900영유아 보육397.69%
98649864대동3011011000영유아 보육097.73%
98659865산내동3011014700기초연금8797.83%
98669866홍도동3011011700기초연금8298.18%
98679867성남동3011011600기초연금8298.36%
98689868판암2동3011010700기초연금8698.46%
98699869판암2동3011010700기초연금6898.67%
98709870판암1동3011010700기초연금8298.67%
98719871효동3011010300영유아 보육498.96%