Overview

Dataset statistics

Number of variables10
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory85.4 B

Variable types

Numeric3
Text3
Categorical4

Dataset

Description대전광역시 서구 결식우려아동 급식지원현황입니다.(순번, 소속, 행정동, 행정동코드, 법정동, 법정동코드, 지번주소, 도로명주소, 지원방법, 지원대상자수)
URLhttps://www.data.go.kr/data/15104071/fileData.do

Alerts

법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
법정동 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
순번 is highly overall correlated with 지원대상자수 and 1 other fieldsHigh correlation
행정동코드 is highly overall correlated with 행정동 and 2 other fieldsHigh correlation
지원대상자수 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
지원방법 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
소속 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:06:54.139037
Analysis finished2023-12-12 05:06:56.174017
Duration2.03 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.5
Minimum1
Maximum54
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T14:06:56.309403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.65
Q114.25
median27.5
Q340.75
95-th percentile51.35
Maximum54
Range53
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation15.732133
Coefficient of variation (CV)0.57207755
Kurtosis-1.2
Mean27.5
Median Absolute Deviation (MAD)13.5
Skewness0
Sum1485
Variance247.5
MonotonicityStrictly increasing
2023-12-12T14:06:56.525342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
42 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
38 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
54 1
1.9%
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%

소속
Text

UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T14:06:56.800579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length6.9814815
Min length2

Characters and Unicode

Total characters377
Distinct characters88
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

Unique54 ?
Unique (%)100.0%

Sample

1st row복수동
2nd row도마1동
3rd row도마2동
4th row정림동
5th row변동
ValueCountFrequency (%)
지역아동센터 28
34.1%
복수동 1
 
1.2%
사랑나무 1
 
1.2%
혜성 1
 
1.2%
꿈쟁이 1
 
1.2%
남부지역아동센터 1
 
1.2%
다음세대 1
 
1.2%
도마해바라기 1
 
1.2%
둔산 1
 
1.2%
미래지기 1
 
1.2%
Other values (45) 45
54.9%
2023-12-12T14:06:57.266106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 53
 
14.1%
지 31
 
8.2%
터 30
 
8.0%
아 29
 
7.7%
역 29
 
7.7%
센 29
 
7.7%
28
 
7.4%
1 5
 
1.3%
2 5
 
1.3%
마 5
 
1.3%
Other values (78) 133
35.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 337
89.4%
Space Separator 28
 
7.4%
Decimal Number 12
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
15.7%
지 31
 
9.2%
터 30
 
8.9%
아 29
 
8.6%
역 29
 
8.6%
센 29
 
8.6%
마 5
 
1.5%
둔 5
 
1.5%
산 5
 
1.5%
관 5
 
1.5%
Other values (74) 116
34.4%
Decimal Number
ValueCountFrequency (%)
1 5
41.7%
2 5
41.7%
3 2
 
16.7%
Space Separator
ValueCountFrequency (%)
28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 337
89.4%
Common 40
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
15.7%
지 31
 
9.2%
터 30
 
8.9%
아 29
 
8.6%
역 29
 
8.6%
센 29
 
8.6%
마 5
 
1.5%
둔 5
 
1.5%
산 5
 
1.5%
관 5
 
1.5%
Other values (74) 116
34.4%
Common
ValueCountFrequency (%)
28
70.0%
1 5
 
12.5%
2 5
 
12.5%
3 2
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 337
89.4%
ASCII 40
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 53
15.7%
지 31
 
9.2%
터 30
 
8.9%
아 29
 
8.6%
역 29
 
8.6%
센 29
 
8.6%
마 5
 
1.5%
둔 5
 
1.5%
산 5
 
1.5%
관 5
 
1.5%
Other values (74) 116
34.4%
ASCII
ValueCountFrequency (%)
28
70.0%
1 5
 
12.5%
2 5
 
12.5%
3 2
 
5.0%

행정동
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
가수원동
5 
괴정동
4 
변동
4 
복수동
4 
기성동
 
3
Other values (18)
34 

Length

Max length4
Median length4
Mean length3.3888889
Min length2

Unique

Unique6 ?
Unique (%)11.1%

Sample

1st row복수동
2nd row도마1동
3rd row도마2동
4th row정림동
5th row변동

Common Values

ValueCountFrequency (%)
가수원동 5
 
9.3%
괴정동 4
 
7.4%
변동 4
 
7.4%
복수동 4
 
7.4%
기성동 3
 
5.6%
갈마1동 3
 
5.6%
내동 3
 
5.6%
도마1동 3
 
5.6%
관저2동 3
 
5.6%
월평1동 2
 
3.7%
Other values (13) 20
37.0%

Length

2023-12-12T14:06:57.471895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가수원동 5
 
9.3%
변동 4
 
7.4%
복수동 4
 
7.4%
괴정동 4
 
7.4%
기성동 3
 
5.6%
갈마1동 3
 
5.6%
내동 3
 
5.6%
도마1동 3
 
5.6%
관저2동 3
 
5.6%
탄방동 2
 
3.7%
Other values (13) 20
37.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)42.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170573 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T14:06:57.650254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017051 × 109
Q13.017054 × 109
median3.0170581 × 109
Q33.0170594 × 109
95-th percentile3.0170644 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)5450

Descriptive statistics

Standard deviation3839.7221
Coefficient of variation (CV)1.2726713 × 10-6
Kurtosis-0.19539876
Mean3.0170573 × 109
Median Absolute Deviation (MAD)2100
Skewness0.26926632
Sum1.629211 × 1011
Variance14743466
MonotonicityNot monotonic
2023-12-12T14:06:57.800123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3017059000 5
 
9.3%
3017051000 4
 
7.4%
3017056000 4
 
7.4%
3017060000 4
 
7.4%
3017054000 4
 
7.4%
3017059700 3
 
5.6%
3017058100 3
 
5.6%
3017052000 3
 
5.6%
3017057500 3
 
5.6%
3017066000 2
 
3.7%
Other values (13) 19
35.2%
ValueCountFrequency (%)
3017051000 4
7.4%
3017052000 3
5.6%
3017053000 2
3.7%
3017053500 2
3.7%
3017054000 4
7.4%
3017055000 1
 
1.9%
3017055500 2
3.7%
3017056000 4
7.4%
3017057000 1
 
1.9%
3017057500 3
5.6%
ValueCountFrequency (%)
3017066000 2
 
3.7%
3017065000 1
 
1.9%
3017064000 2
 
3.7%
3017063000 1
 
1.9%
3017060000 4
7.4%
3017059700 3
5.6%
3017059600 1
 
1.9%
3017059000 5
9.3%
3017058800 1
 
1.9%
3017058700 1
 
1.9%

법정동
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Memory size564.0 B
도마동
5 
둔산동
5 
갈마동
5 
복수동
4 
관저동
4 
Other values (14)
31 

Length

Max length7
Median length3
Mean length3.0185185
Min length2

Unique

Unique6 ?
Unique (%)11.1%

Sample

1st row복수동
2nd row도마동
3rd row도마동
4th row정림동
5th row변동

Common Values

ValueCountFrequency (%)
도마동 5
9.3%
둔산동 5
9.3%
갈마동 5
9.3%
복수동 4
 
7.4%
관저동 4
 
7.4%
변동 4
 
7.4%
가수원동 4
 
7.4%
월평동 4
 
7.4%
괴정동 4
 
7.4%
내동 3
 
5.6%
Other values (9) 12
22.2%

Length

2023-12-12T14:06:57.999890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도마동 5
9.3%
둔산동 5
9.3%
갈마동 5
9.3%
복수동 4
 
7.4%
관저동 4
 
7.4%
변동 4
 
7.4%
가수원동 4
 
7.4%
월평동 4
 
7.4%
괴정동 4
 
7.4%
내동 3
 
5.6%
Other values (9) 12
22.2%

법정동코드
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
3017011100
5 
3017011200
5 
3017010300
5 
3017010800
4 
3017011600
4 
Other values (15)
31 

Length

Max length10
Median length10
Mean length9.9444444
Min length7

Unique

Unique8 ?
Unique (%)14.8%

Sample

1st row3017010100
2nd row3017010300
3rd row3017010300
4th row3017010400
5th row3017010200

Common Values

ValueCountFrequency (%)
3017011100 5
9.3%
3017011200 5
9.3%
3017010300 5
9.3%
3017010800 4
 
7.4%
3017011600 4
 
7.4%
3017011400 4
 
7.4%
3017011300 4
 
7.4%
3017010100 4
 
7.4%
3017010200 4
 
7.4%
3017011000 3
 
5.6%
Other values (10) 12
22.2%

Length

2023-12-12T14:06:58.166114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3017011100 5
9.3%
3017010300 5
9.3%
3017011200 5
9.3%
3017010800 4
 
7.4%
3017011600 4
 
7.4%
3017011400 4
 
7.4%
3017011300 4
 
7.4%
3017010100 4
 
7.4%
3017010200 4
 
7.4%
3017011000 3
 
5.6%
Other values (10) 12
22.2%

지번주소
Text

Distinct47
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T14:06:58.768296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length10.222222
Min length6

Characters and Unicode

Total characters552
Distinct characters56
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)77.8%

Sample

1st row대전광역시 서구 복수동
2nd row대전광역시 서구 도마동
3rd row대전광역시 서구 도마동
4th row대전광역시 서구 정림동
5th row대전광역시 서구 변동
ValueCountFrequency (%)
대전광역시 24
17.6%
서구 24
17.6%
둔산동 5
 
3.7%
갈마동 5
 
3.7%
괴정동 4
 
2.9%
복수동 4
 
2.9%
가수원동 4
 
2.9%
변동 4
 
2.9%
도마동 4
 
2.9%
관저동 4
 
2.9%
Other values (46) 54
39.7%
2023-12-12T14:06:59.243900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
14.9%
동 53
 
9.6%
대 24
 
4.3%
광 24
 
4.3%
역 24
 
4.3%
시 24
 
4.3%
서 24
 
4.3%
구 24
 
4.3%
전 24
 
4.3%
2 23
 
4.2%
Other values (46) 226
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 334
60.5%
Decimal Number 116
 
21.0%
Space Separator 82
 
14.9%
Dash Punctuation 20
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 53
15.9%
대 24
 
7.2%
광 24
 
7.2%
역 24
 
7.2%
시 24
 
7.2%
서 24
 
7.2%
구 24
 
7.2%
전 24
 
7.2%
수 9
 
2.7%
마 9
 
2.7%
Other values (34) 95
28.4%
Decimal Number
ValueCountFrequency (%)
2 23
19.8%
1 21
18.1%
3 13
11.2%
7 10
8.6%
5 9
 
7.8%
9 9
 
7.8%
6 9
 
7.8%
8 9
 
7.8%
4 8
 
6.9%
0 5
 
4.3%
Space Separator
ValueCountFrequency (%)
82
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 334
60.5%
Common 218
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 53
15.9%
대 24
 
7.2%
광 24
 
7.2%
역 24
 
7.2%
시 24
 
7.2%
서 24
 
7.2%
구 24
 
7.2%
전 24
 
7.2%
수 9
 
2.7%
마 9
 
2.7%
Other values (34) 95
28.4%
Common
ValueCountFrequency (%)
82
37.6%
2 23
 
10.6%
1 21
 
9.6%
- 20
 
9.2%
3 13
 
6.0%
7 10
 
4.6%
5 9
 
4.1%
9 9
 
4.1%
6 9
 
4.1%
8 9
 
4.1%
Other values (2) 13
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 334
60.5%
ASCII 218
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
37.6%
2 23
 
10.6%
1 21
 
9.6%
- 20
 
9.2%
3 13
 
6.0%
7 10
 
4.6%
5 9
 
4.1%
9 9
 
4.1%
6 9
 
4.1%
8 9
 
4.1%
Other values (2) 13
 
6.0%
Hangul
ValueCountFrequency (%)
동 53
15.9%
대 24
 
7.2%
광 24
 
7.2%
역 24
 
7.2%
시 24
 
7.2%
서 24
 
7.2%
구 24
 
7.2%
전 24
 
7.2%
수 9
 
2.7%
마 9
 
2.7%
Other values (34) 95
28.4%

도로명주소
Text

Distinct47
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Memory size564.0 B
2023-12-12T14:06:59.581139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length24
Mean length14.537037
Min length10

Characters and Unicode

Total characters785
Distinct characters83
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)77.8%

Sample

1st row대전광역시 서구 복수동
2nd row대전광역시 서구 도마동
3rd row대전광역시 서구 도마동
4th row대전광역시 서구 정림동
5th row대전광역시 서구 변동
ValueCountFrequency (%)
서구 53
26.2%
대전 28
 
13.9%
대전광역시 25
 
12.4%
월평동 3
 
1.5%
도마동 3
 
1.5%
둔산동 3
 
1.5%
도솔로 3
 
1.5%
1층 2
 
1.0%
중반5길 2
 
1.0%
47 2
 
1.0%
Other values (73) 78
38.6%
2023-12-12T14:07:00.109045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
18.9%
서 54
 
6.9%
대 53
 
6.8%
구 53
 
6.8%
전 53
 
6.8%
동 28
 
3.6%
광 25
 
3.2%
역 25
 
3.2%
시 25
 
3.2%
로 24
 
3.1%
Other values (73) 297
37.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 507
64.6%
Space Separator 148
 
18.9%
Decimal Number 121
 
15.4%
Dash Punctuation 8
 
1.0%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 54
 
10.7%
대 53
 
10.5%
구 53
 
10.5%
전 53
 
10.5%
동 28
 
5.5%
광 25
 
4.9%
역 25
 
4.9%
시 25
 
4.9%
로 24
 
4.7%
길 15
 
3.0%
Other values (60) 152
30.0%
Decimal Number
ValueCountFrequency (%)
2 24
19.8%
1 23
19.0%
4 16
13.2%
6 12
9.9%
5 10
8.3%
0 9
 
7.4%
3 9
 
7.4%
9 8
 
6.6%
7 7
 
5.8%
8 3
 
2.5%
Space Separator
ValueCountFrequency (%)
148
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 507
64.6%
Common 278
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 54
 
10.7%
대 53
 
10.5%
구 53
 
10.5%
전 53
 
10.5%
동 28
 
5.5%
광 25
 
4.9%
역 25
 
4.9%
시 25
 
4.9%
로 24
 
4.7%
길 15
 
3.0%
Other values (60) 152
30.0%
Common
ValueCountFrequency (%)
148
53.2%
2 24
 
8.6%
1 23
 
8.3%
4 16
 
5.8%
6 12
 
4.3%
5 10
 
3.6%
0 9
 
3.2%
3 9
 
3.2%
9 8
 
2.9%
- 8
 
2.9%
Other values (3) 11
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 507
64.6%
ASCII 278
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
53.2%
2 24
 
8.6%
1 23
 
8.3%
4 16
 
5.8%
6 12
 
4.3%
5 10
 
3.6%
0 9
 
3.2%
3 9
 
3.2%
9 8
 
2.9%
- 8
 
2.9%
Other values (3) 11
 
4.0%
Hangul
ValueCountFrequency (%)
서 54
 
10.7%
대 53
 
10.5%
구 53
 
10.5%
전 53
 
10.5%
동 28
 
5.5%
광 25
 
4.9%
역 25
 
4.9%
시 25
 
4.9%
로 24
 
4.7%
길 15
 
3.0%
Other values (60) 152
30.0%

지원방법
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
단체급식소
30 
아동급식카드
24 

Length

Max length6
Median length5
Mean length5.4444444
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
단체급식소 30
55.6%
아동급식카드 24
44.4%

Length

2023-12-12T14:07:00.284497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:07:00.422610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단체급식소 30
55.6%
아동급식카드 24
44.4%

지원대상자수
Real number (ℝ)

HIGH CORRELATION 

Distinct42
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.018519
Minimum1
Maximum193
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-12T14:07:00.571129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.25
Q119
median31
Q370.75
95-th percentile159.4
Maximum193
Range192
Interquartile range (IQR)51.75

Descriptive statistics

Standard deviation49.685232
Coefficient of variation (CV)0.91978147
Kurtosis0.62852818
Mean54.018519
Median Absolute Deviation (MAD)14
Skewness1.3233831
Sum2917
Variance2468.6223
MonotonicityNot monotonic
2023-12-12T14:07:00.791489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
19 6
 
11.1%
29 3
 
5.6%
34 2
 
3.7%
23 2
 
3.7%
17 2
 
3.7%
25 2
 
3.7%
33 2
 
3.7%
18 1
 
1.9%
28 1
 
1.9%
20 1
 
1.9%
Other values (32) 32
59.3%
ValueCountFrequency (%)
1 1
 
1.9%
5 1
 
1.9%
7 1
 
1.9%
12 1
 
1.9%
13 1
 
1.9%
15 1
 
1.9%
17 2
 
3.7%
18 1
 
1.9%
19 6
11.1%
20 1
 
1.9%
ValueCountFrequency (%)
193 1
1.9%
165 1
1.9%
162 1
1.9%
158 1
1.9%
156 1
1.9%
141 1
1.9%
139 1
1.9%
128 1
1.9%
113 1
1.9%
102 1
1.9%

Interactions

2023-12-12T14:06:55.470191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:54.738468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:55.144298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:55.579479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:54.847185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:55.244764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:55.698535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:54.975893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:06:55.352942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:07:00.943444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번소속행정동행정동코드법정동법정동코드지번주소도로명주소지원방법지원대상자수
순번1.0001.0000.3630.4000.5880.6600.9750.9750.9960.699
소속1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동0.3631.0001.0000.9970.9850.9800.0000.0000.0000.000
행정동코드0.4001.0000.9971.0000.9700.9310.0000.0000.0000.000
법정동0.5881.0000.9850.9701.0001.0001.0001.0000.0000.249
법정동코드0.6601.0000.9800.9311.0001.0001.0001.0000.0000.068
지번주소0.9751.0000.0000.0001.0001.0001.0001.0001.0000.819
도로명주소0.9751.0000.0000.0001.0001.0001.0001.0001.0000.819
지원방법0.9961.0000.0000.0000.0000.0001.0001.0001.0000.943
지원대상자수0.6991.0000.0000.0000.2490.0680.8190.8190.9431.000
2023-12-12T14:07:01.097240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동코드법정동행정동지원방법
법정동코드1.0000.9860.7640.000
법정동0.9861.0000.7960.000
행정동0.7640.7961.0000.000
지원방법0.0000.0000.0001.000
2023-12-12T14:07:01.219003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번행정동코드지원대상자수행정동법정동법정동코드지원방법
순번1.0000.048-0.5950.0720.2210.2200.869
행정동코드0.0481.000-0.2710.8180.6680.6510.000
지원대상자수-0.595-0.2711.0000.0000.0000.0000.733
행정동0.0720.8180.0001.0000.7960.7640.000
법정동0.2210.6680.0000.7961.0000.9860.000
법정동코드0.2200.6510.0000.7640.9861.0000.000
지원방법0.8690.0000.7330.0000.0000.0001.000

Missing values

2023-12-12T14:06:55.853702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:06:56.065254image/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

순번소속행정동행정동코드법정동법정동코드지번주소도로명주소지원방법지원대상자수
01복수동복수동3017051000복수동3017010100대전광역시 서구 복수동대전광역시 서구 복수동아동급식카드76
12도마1동도마1동3017052000도마동3017010300대전광역시 서구 도마동대전광역시 서구 도마동아동급식카드139
23도마2동도마2동3017053000도마동3017010300대전광역시 서구 도마동대전광역시 서구 도마동아동급식카드141
34정림동정림동3017053500정림동3017010400대전광역시 서구 정림동대전광역시 서구 정림동아동급식카드66
45변동변동3017054000변동3017010200대전광역시 서구 변동대전광역시 서구 변동아동급식카드165
56용문동용문동3017055000용문동3017010500대전광역시 서구 용문동대전광역시 서구 용문동아동급식카드71
67탄방동탄방동3017055500탄방동3017010600대전광역시 서구 탄방동대전광역시 서구 탄방동아동급식카드102
78둔산1동둔산1동3017063000둔산동3017011200대전광역시 서구 둔산동대전광역시 서구 둔산동아동급식카드7
89둔산2동둔산2동3017064000둔산동3017011200대전광역시 서구 둔산동대전광역시 서구 둔산동아동급식카드13
910둔산3동둔산3동3017066000둔산동3017011200대전광역시 서구 둔산동대전광역시 서구 둔산동아동급식카드82
순번소속행정동행정동코드법정동법정동코드지번주소도로명주소지원방법지원대상자수
4445세움 지역아동센터기성동3017060000흑석동3017011700흑석동 950대전 서구 벌곡로 660 , 1층단체급식소22
4546소망 지역아동센터가장동3017060000가장동3017010900가장동 29-2대전 서구 유등로431번길 47단체급식소25
4647연세 지역아동센터갈마2동3017058200갈마동3017011100갈마동 347-4 4층대전 서구 갈마중로38번길 20단체급식소17
4748열방 지역아동센터내동3017057500내동3017011000내동 15-43대전 서구 도솔로 240-1단체급식소26
4849정금 지역아동센터괴정동3017056000괴정동3017010800괴정동 11-22대전 서구 괴정로 71단체급식소29
4950정림 지역아동센터정림동3017053500정림동3017012700정림동 639대전 서구 정림서로 162-15 우성아파트2차단체급식소19
5051하늘 지역아동센터기성동3017060000평촌동3017012100평촌동 339-2대전 서구 길마루길 68단체급식소15
5152향기로운 지역아동센터갈마1동3017058100갈마동3017011100갈마동 392-20대전 서구 신갈마로127번길 5-4단체급식소40
5253혜성 지역아동센터월평1동3017058600월평동3017011300월평동 1272대전 서구 계룡로245번길 26-11단체급식소19
5354둔산종합사회복지관둔산3동3017066000둔산동3017011200둔산동 1812대전 서구 둔산로 241 보라아파트 203동단체급식소5