Overview

Dataset statistics

Number of variables13
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory117.5 B

Variable types

Numeric2
Text1
Categorical10

Dataset

Description대전광역시 서구 사회복지공동모금회 지원현황(행정동코드, 법정동코드, 생계비건수, 생계비지원금, 생계비지원금단위, 의료비 건수 등) 정보를 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15113077/fileData.do

Alerts

생계비지원금단위 has constant value ""Constant
의료비지원금단위 has constant value ""Constant
재해재난비건수 has constant value ""Constant
재해재난비지원금 has constant value ""Constant
재해재난비지원금단위 has constant value ""Constant
데이터기준일자 has constant value ""Constant
의료비지원금 is highly overall correlated with 의료비건수High correlation
생계비지원금 is highly overall correlated with 생계비건수High correlation
의료비건수 is highly overall correlated with 의료비지원금High correlation
생계비건수 is highly overall correlated with 생계비지원금High correlation
순번 is highly overall correlated with 행정동코드High correlation
행정동코드 is highly overall correlated with 순번High correlation
생계비건수 is highly imbalanced (58.5%)Imbalance
생계비지원금 is highly imbalanced (62.9%)Imbalance
순번 has unique valuesUnique
행정동 has unique valuesUnique
행정동코드 has unique valuesUnique

Reproduction

Analysis started2024-04-21 02:16:39.688169
Analysis finished2024-04-21 02:16:42.659818
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.5
Minimum1
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-21T11:16:42.723532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.15
Q16.75
median12.5
Q318.25
95-th percentile22.85
Maximum24
Range23
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation7.0710678
Coefficient of variation (CV)0.56568542
Kurtosis-1.2
Mean12.5
Median Absolute Deviation (MAD)6
Skewness0
Sum300
Variance50
MonotonicityStrictly increasing
2024-04-21T11:16:42.842211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 1
 
4.2%
14 1
 
4.2%
24 1
 
4.2%
23 1
 
4.2%
22 1
 
4.2%
21 1
 
4.2%
20 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
17 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
1 1
4.2%
2 1
4.2%
3 1
4.2%
4 1
4.2%
5 1
4.2%
6 1
4.2%
7 1
4.2%
8 1
4.2%
9 1
4.2%
10 1
4.2%
ValueCountFrequency (%)
24 1
4.2%
23 1
4.2%
22 1
4.2%
21 1
4.2%
20 1
4.2%
19 1
4.2%
18 1
4.2%
17 1
4.2%
16 1
4.2%
15 1
4.2%

행정동
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-21T11:16:43.042499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.4583333
Min length2

Characters and Unicode

Total characters83
Distinct characters32
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

Unique24 ?
Unique (%)100.0%

Sample

1st row복수동
2nd row도마1동
3rd row도마2동
4th row정림동
5th row변동
ValueCountFrequency (%)
복수동 1
 
4.2%
도마1동 1
 
4.2%
기성동 1
 
4.2%
관저2동 1
 
4.2%
관저1동 1
 
4.2%
가수원동 1
 
4.2%
만년동 1
 
4.2%
월평3동 1
 
4.2%
월평2동 1
 
4.2%
월평1동 1
 
4.2%
Other values (14) 14
58.3%
2024-04-21T11:16:43.427150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 24
28.9%
1 5
 
6.0%
2 5
 
6.0%
마 4
 
4.8%
월 3
 
3.6%
둔 3
 
3.6%
도 3
 
3.6%
평 3
 
3.6%
산 3
 
3.6%
가 2
 
2.4%
Other values (22) 28
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71
85.5%
Decimal Number 12
 
14.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 24
33.8%
마 4
 
5.6%
월 3
 
4.2%
둔 3
 
4.2%
도 3
 
4.2%
평 3
 
4.2%
산 3
 
4.2%
가 2
 
2.8%
수 2
 
2.8%
관 2
 
2.8%
Other values (19) 22
31.0%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 71
85.5%
Common 12
 
14.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 24
33.8%
마 4
 
5.6%
월 3
 
4.2%
둔 3
 
4.2%
도 3
 
4.2%
평 3
 
4.2%
산 3
 
4.2%
가 2
 
2.8%
수 2
 
2.8%
관 2
 
2.8%
Other values (19) 22
31.0%
Common
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 71
85.5%
ASCII 12
 
14.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 24
33.8%
마 4
 
5.6%
월 3
 
4.2%
둔 3
 
4.2%
도 3
 
4.2%
평 3
 
4.2%
산 3
 
4.2%
가 2
 
2.8%
수 2
 
2.8%
관 2
 
2.8%
Other values (19) 22
31.0%
ASCII
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%

행정동코드
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.017058 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2024-04-21T11:16:43.550877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.0170522 × 109
Q13.0170554 × 109
median3.0170584 × 109
Q33.0170596 × 109
95-th percentile3.0170648 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)4250

Descriptive statistics

Standard deviation3925.4996
Coefficient of variation (CV)1.3011018 × 10-6
Kurtosis-0.21236716
Mean3.017058 × 109
Median Absolute Deviation (MAD)2000
Skewness0.23857237
Sum7.2409392 × 1010
Variance15409547
MonotonicityNot monotonic
2024-04-21T11:16:43.683892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3017051000 1
 
4.2%
3017058100 1
 
4.2%
3017059300 1
 
4.2%
3017060000 1
 
4.2%
3017059700 1
 
4.2%
3017059600 1
 
4.2%
3017059000 1
 
4.2%
3017065000 1
 
4.2%
3017058800 1
 
4.2%
3017058700 1
 
4.2%
Other values (14) 14
58.3%
ValueCountFrequency (%)
3017051000 1
4.2%
3017052000 1
4.2%
3017053000 1
4.2%
3017053500 1
4.2%
3017054000 1
4.2%
3017055000 1
4.2%
3017055500 1
4.2%
3017056000 1
4.2%
3017057000 1
4.2%
3017057500 1
4.2%
ValueCountFrequency (%)
3017066000 1
4.2%
3017065000 1
4.2%
3017064000 1
4.2%
3017063000 1
4.2%
3017060000 1
4.2%
3017059700 1
4.2%
3017059600 1
4.2%
3017059300 1
4.2%
3017059000 1
4.2%
3017058800 1
4.2%

생계비건수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
21 
1
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

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

Common Values

ValueCountFrequency (%)
0 21
87.5%
1 2
 
8.3%
2 1
 
4.2%

Length

2024-04-21T11:16:43.814537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:43.914822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
87.5%
1 2
 
8.3%
2 1
 
4.2%

생계비지원금
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
21 
1000000
 
1
1400000
 
1
700000
 
1

Length

Max length7
Median length1
Mean length1.7083333
Min length1

Unique

Unique3 ?
Unique (%)12.5%

Sample

1st row0
2nd row1000000
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 21
87.5%
1000000 1
 
4.2%
1400000 1
 
4.2%
700000 1
 
4.2%

Length

2024-04-21T11:16:44.019728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:44.134896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
87.5%
1000000 1
 
4.2%
1400000 1
 
4.2%
700000 1
 
4.2%

생계비지원금단위
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
원
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원 24
100.0%

Length

2024-04-21T11:16:44.246820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:44.339380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원 24
100.0%

의료비건수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
1
10 
0
7 
2
6 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row1
2nd row2
3rd row2
4th row0
5th row1

Common Values

ValueCountFrequency (%)
1 10
41.7%
0 7
29.2%
2 6
25.0%
3 1
 
4.2%

Length

2024-04-21T11:16:44.444290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:44.557350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 10
41.7%
0 7
29.2%
2 6
25.0%
3 1
 
4.2%

의료비지원금
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size324.0 B
2000000
10 
0
7 
4000000
6 
6000000
 
1

Length

Max length7
Median length7
Mean length5.25
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row2000000
2nd row4000000
3rd row4000000
4th row0
5th row2000000

Common Values

ValueCountFrequency (%)
2000000 10
41.7%
0 7
29.2%
4000000 6
25.0%
6000000 1
 
4.2%

Length

2024-04-21T11:16:44.686733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:44.812940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2000000 10
41.7%
0 7
29.2%
4000000 6
25.0%
6000000 1
 
4.2%

의료비지원금단위
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
원
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원 24
100.0%

Length

2024-04-21T11:16:44.923628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:45.005164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원 24
100.0%

재해재난비건수
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 24
100.0%

Length

2024-04-21T11:16:45.096471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:45.190257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
100.0%

재해재난비지원금
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
0
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 24
100.0%

Length

2024-04-21T11:16:45.310001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:45.400288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
100.0%

재해재난비지원금단위
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
원
24 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원 24
100.0%

Length

2024-04-21T11:16:45.515536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:45.618859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
원 24
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size324.0 B
2024-04-01
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-01
2nd row2024-04-01
3rd row2024-04-01
4th row2024-04-01
5th row2024-04-01

Common Values

ValueCountFrequency (%)
2024-04-01 24
100.0%

Length

2024-04-21T11:16:45.744367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T11:16:45.863898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-01 24
100.0%

Interactions

2024-04-21T11:16:42.138620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:16:41.882487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:16:42.232807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:16:42.018490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:16:45.926549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동행정동코드생계비건수생계비지원금의료비건수의료비지원금
순번1.0001.0000.8630.0000.0000.6350.635
행정동1.0001.0001.0001.0001.0001.0001.000
행정동코드0.8631.0001.0000.7730.6800.0000.000
생계비건수0.0001.0000.7731.0001.0000.0000.000
생계비지원금0.0001.0000.6801.0001.0000.0000.000
의료비건수0.6351.0000.0000.0000.0001.0001.000
의료비지원금0.6351.0000.0000.0000.0001.0001.000
2024-04-21T11:16:46.050699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료비지원금생계비지원금의료비건수생계비건수
의료비지원금1.0000.0001.0000.000
생계비지원금0.0001.0000.0000.976
의료비건수1.0000.0001.0000.000
생계비건수0.0000.9760.0001.000
2024-04-21T11:16:46.145096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드생계비건수생계비지원금의료비건수의료비지원금
순번1.0000.6900.0000.0000.3440.344
행정동코드0.6901.0000.1230.0000.0000.000
생계비건수0.0000.1231.0000.9760.0000.000
생계비지원금0.0000.0000.9761.0000.0000.000
의료비건수0.3440.0000.0000.0001.0001.000
의료비지원금0.3440.0000.0000.0001.0001.000

Missing values

2024-04-21T11:16:42.386407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:16:42.577488image/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

순번행정동행정동코드생계비건수생계비지원금생계비지원금단위의료비건수의료비지원금의료비지원금단위재해재난비건수재해재난비지원금재해재난비지원금단위데이터기준일자
01복수동301705100000원12000000원00원2024-04-01
12도마1동301705200011000000원24000000원00원2024-04-01
23도마2동301705300000원24000000원00원2024-04-01
34정림동301705350000원00원00원2024-04-01
45변동301705400000원12000000원00원2024-04-01
56용문동301705500000원24000000원00원2024-04-01
67탄방동301705550000원12000000원00원2024-04-01
78둔산1동301706300000원00원00원2024-04-01
89둔산2동301706400000원12000000원00원2024-04-01
910둔산3동301706600000원12000000원00원2024-04-01
순번행정동행정동코드생계비건수생계비지원금생계비지원금단위의료비건수의료비지원금의료비지원금단위재해재난비건수재해재난비지원금재해재난비지원금단위데이터기준일자
1415갈마2동301705820000원12000000원00원2024-04-01
1516월평1동301705860000원24000000원00원2024-04-01
1617월평2동301705870000원24000000원00원2024-04-01
1718월평3동301705880000원00원00원2024-04-01
1819만년동301706500000원00원00원2024-04-01
1920가수원동301705900000원12000000원00원2024-04-01
2021관저1동301705960000원12000000원00원2024-04-01
2122관저2동30170597001700000원12000000원00원2024-04-01
2223기성동301706000000원00원00원2024-04-01
2324도안동301705930000원12000000원00원2024-04-01