Overview

Dataset statistics

Number of variables7
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory59.9 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description인천광역시 남동구 전화신청가능 민원현황에 대한 데이터로 연번, 분야, 민원목록, 세부항목, 담당부서, 연락처, 데이터기준일자 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089132&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 분야 and 1 other fieldsHigh correlation
분야 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
담당부서 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
세부항목 has unique valuesUnique

Reproduction

Analysis started2024-01-28 07:16:28.568139
Analysis finished2024-01-28 07:16:29.113123
Duration0.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-01-28T16:16:29.169710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2024-01-28T16:16:29.273364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

분야
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
환경
10 
도로
5 
교통
5 
청소
5 
보건
4 
Other values (12)
17 

Length

Max length5
Median length2
Mean length2.2391304
Min length2

Unique

Unique7 ?
Unique (%)15.2%

Sample

1st row건축
2nd row교통
3rd row교통
4th row교통
5th row교통

Common Values

ValueCountFrequency (%)
환경 10
21.7%
도로 5
10.9%
교통 5
10.9%
청소 5
10.9%
보건 4
 
8.7%
재난 2
 
4.3%
세금 2
 
4.3%
농축산 2
 
4.3%
공원,녹지 2
 
4.3%
생활 2
 
4.3%
Other values (7) 7
15.2%

Length

2024-01-28T16:16:29.369488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
환경 10
21.7%
교통 5
10.9%
청소 5
10.9%
도로 5
10.9%
보건 4
 
8.7%
농축산 2
 
4.3%
생활 2
 
4.3%
공원,녹지 2
 
4.3%
세금 2
 
4.3%
재난 2
 
4.3%
Other values (7) 7
15.2%

민원목록
Text

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-01-28T16:16:29.558099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length4.9565217
Min length2

Characters and Unicode

Total characters228
Distinct characters105
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 (%)91.3%

Sample

1st row위법건축물신고
2nd row교통불편 신고
3rd row방치차량
4th row불법주정차
5th row자동차등록
ValueCountFrequency (%)
쓰레기 3
 
5.3%
신고 3
 
5.3%
세금문의 2
 
3.5%
수거 2
 
3.5%
도로청소 1
 
1.8%
무단투기 1
 
1.8%
교통불편 1
 
1.8%
대부업 1
 
1.8%
통신판매업 1
 
1.8%
노상적치물 1
 
1.8%
Other values (41) 41
71.9%
2024-01-28T16:16:29.854849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
4.8%
수 9
 
3.9%
물 7
 
3.1%
신 7
 
3.1%
고 7
 
3.1%
기 6
 
2.6%
불 6
 
2.6%
설 5
 
2.2%
로 5
 
2.2%
시 4
 
1.8%
Other values (95) 161
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
93.0%
Space Separator 11
 
4.8%
Close Punctuation 2
 
0.9%
Open Punctuation 2
 
0.9%
Other Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 9
 
4.2%
물 7
 
3.3%
신 7
 
3.3%
고 7
 
3.3%
기 6
 
2.8%
불 6
 
2.8%
설 5
 
2.4%
로 5
 
2.4%
시 4
 
1.9%
방 4
 
1.9%
Other values (91) 152
71.7%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 212
93.0%
Common 16
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 9
 
4.2%
물 7
 
3.3%
신 7
 
3.3%
고 7
 
3.3%
기 6
 
2.8%
불 6
 
2.8%
설 5
 
2.4%
로 5
 
2.4%
시 4
 
1.9%
방 4
 
1.9%
Other values (91) 152
71.7%
Common
ValueCountFrequency (%)
11
68.8%
) 2
 
12.5%
( 2
 
12.5%
, 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
93.0%
ASCII 16
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
68.8%
) 2
 
12.5%
( 2
 
12.5%
, 1
 
6.2%
Hangul
ValueCountFrequency (%)
수 9
 
4.2%
물 7
 
3.3%
신 7
 
3.3%
고 7
 
3.3%
기 6
 
2.8%
불 6
 
2.8%
설 5
 
2.4%
로 5
 
2.4%
시 4
 
1.9%
방 4
 
1.9%
Other values (91) 152
71.7%

세부항목
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-01-28T16:16:30.051014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length18
Mean length11.978261
Min length3

Characters and Unicode

Total characters551
Distinct characters149
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row위법건축물관련
2nd row교통표지판, 보행자안내표지판, 교통시설물
3rd row방치차량견인
4th row불법주·정차단속요청
5th row자동차등록, 명의이전, 번호판변경 등
ValueCountFrequency (%)
등 13
 
10.4%
신고 5
 
4.0%
공사장 3
 
2.4%
무단투기 2
 
1.6%
무단점용 2
 
1.6%
시설물 1
 
0.8%
교통표지판 1
 
0.8%
처리 1
 
0.8%
쓰레기 1
 
0.8%
재활용 1
 
0.8%
Other values (95) 95
76.0%
2024-01-28T16:16:30.339575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
79
 
14.3%
, 27
 
4.9%
등 19
 
3.4%
고 17
 
3.1%
신 15
 
2.7%
물 11
 
2.0%
수 11
 
2.0%
장 9
 
1.6%
단 9
 
1.6%
설 9
 
1.6%
Other values (139) 345
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 432
78.4%
Space Separator 79
 
14.3%
Other Punctuation 28
 
5.1%
Uppercase Letter 8
 
1.5%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 19
 
4.4%
고 17
 
3.9%
신 15
 
3.5%
물 11
 
2.5%
수 11
 
2.5%
장 9
 
2.1%
단 9
 
2.1%
설 9
 
2.1%
소 8
 
1.9%
업 8
 
1.9%
Other values (131) 316
73.1%
Uppercase Letter
ValueCountFrequency (%)
C 4
50.0%
T 2
25.0%
V 2
25.0%
Other Punctuation
ValueCountFrequency (%)
, 27
96.4%
· 1
 
3.6%
Space Separator
ValueCountFrequency (%)
79
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 432
78.4%
Common 111
 
20.1%
Latin 8
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 19
 
4.4%
고 17
 
3.9%
신 15
 
3.5%
물 11
 
2.5%
수 11
 
2.5%
장 9
 
2.1%
단 9
 
2.1%
설 9
 
2.1%
소 8
 
1.9%
업 8
 
1.9%
Other values (131) 316
73.1%
Common
ValueCountFrequency (%)
79
71.2%
, 27
 
24.3%
) 2
 
1.8%
( 2
 
1.8%
· 1
 
0.9%
Latin
ValueCountFrequency (%)
C 4
50.0%
T 2
25.0%
V 2
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 432
78.4%
ASCII 118
 
21.4%
None 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
79
66.9%
, 27
 
22.9%
C 4
 
3.4%
T 2
 
1.7%
) 2
 
1.7%
( 2
 
1.7%
V 2
 
1.7%
Hangul
ValueCountFrequency (%)
등 19
 
4.4%
고 17
 
3.9%
신 15
 
3.5%
물 11
 
2.5%
수 11
 
2.5%
장 9
 
2.1%
단 9
 
2.1%
설 9
 
2.1%
소 8
 
1.9%
업 8
 
1.9%
Other values (131) 316
73.1%
None
ValueCountFrequency (%)
· 1
100.0%

담당부서
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Memory size500.0 B
환경보전과
9 
동행정복지센터
7 
도로과
3 
안전총괄과
3 
식품위생과
3 
Other values (14)
21 

Length

Max length7
Median length5
Mean length5.1521739
Min length3

Unique

Unique7 ?
Unique (%)15.2%

Sample

1st row건축과
2nd row교통행정과
3rd row자동차관리과
4th row교통행정과
5th row자동차관리과

Common Values

ValueCountFrequency (%)
환경보전과 9
19.6%
동행정복지센터 7
15.2%
도로과 3
 
6.5%
안전총괄과 3
 
6.5%
식품위생과 3
 
6.5%
공원녹지과 2
 
4.3%
교통행정과 2
 
4.3%
농축수산과 2
 
4.3%
도시디자인과 2
 
4.3%
청소행정과 2
 
4.3%
Other values (9) 11
23.9%

Length

2024-01-28T16:16:30.448645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
환경보전과 9
19.6%
동행정복지센터 7
15.2%
도로과 3
 
6.5%
안전총괄과 3
 
6.5%
식품위생과 3
 
6.5%
도시디자인과 2
 
4.3%
생활경제과 2
 
4.3%
자동차관리과 2
 
4.3%
청소행정과 2
 
4.3%
농축수산과 2
 
4.3%
Other values (9) 11
23.9%

연락처
Text

Distinct30
Distinct (%)65.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-01-28T16:16:30.596606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters552
Distinct characters11
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

Unique22 ?
Unique (%)47.8%

Sample

1st row032-453-2760
2nd row032-453-2680
3rd row032-453-2820
4th row032-453-2890
5th row032-453-2930
ValueCountFrequency (%)
032-466-3811 7
 
15.2%
032-453-2750 3
 
6.5%
032-453-2600 3
 
6.5%
032-453-2650 3
 
6.5%
032-453-2340 2
 
4.3%
032-453-2330 2
 
4.3%
032-453-2840 2
 
4.3%
032-453-5195 2
 
4.3%
032-453-2390 1
 
2.2%
032-453-2760 1
 
2.2%
Other values (20) 20
43.5%
2024-01-28T16:16:30.849406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 102
18.5%
- 92
16.7%
0 89
16.1%
2 83
15.0%
5 56
10.1%
4 53
9.6%
6 27
 
4.9%
1 20
 
3.6%
8 16
 
2.9%
7 8
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 460
83.3%
Dash Punctuation 92
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 102
22.2%
0 89
19.3%
2 83
18.0%
5 56
12.2%
4 53
11.5%
6 27
 
5.9%
1 20
 
4.3%
8 16
 
3.5%
7 8
 
1.7%
9 6
 
1.3%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 102
18.5%
- 92
16.7%
0 89
16.1%
2 83
15.0%
5 56
10.1%
4 53
9.6%
6 27
 
4.9%
1 20
 
3.6%
8 16
 
2.9%
7 8
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 102
18.5%
- 92
16.7%
0 89
16.1%
2 83
15.0%
5 56
10.1%
4 53
9.6%
6 27
 
4.9%
1 20
 
3.6%
8 16
 
2.9%
7 8
 
1.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-08-07
46 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-07
2nd row2023-08-07
3rd row2023-08-07
4th row2023-08-07
5th row2023-08-07

Common Values

ValueCountFrequency (%)
2023-08-07 46
100.0%

Length

2024-01-28T16:16:30.949652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T16:16:31.013259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-07 46
100.0%

Interactions

2024-01-28T16:16:28.890020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T16:16:31.057149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분야민원목록세부항목담당부서연락처
연번1.0000.9190.9661.0000.8920.907
분야0.9191.0001.0001.0000.9710.969
민원목록0.9661.0001.0001.0000.8470.000
세부항목1.0001.0001.0001.0001.0001.000
담당부서0.8920.9710.8471.0001.0001.000
연락처0.9070.9690.0001.0001.0001.000
2024-01-28T16:16:31.134265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분야담당부서
분야1.0000.758
담당부서0.7581.000
2024-01-28T16:16:31.194860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번분야담당부서
연번1.0000.6410.507
분야0.6411.0000.758
담당부서0.5070.7581.000

Missing values

2024-01-28T16:16:28.970118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T16:16:29.076712image/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

연번분야민원목록세부항목담당부서연락처데이터기준일자
01건축위법건축물신고위법건축물관련건축과032-453-27602023-08-07
12교통교통불편 신고교통표지판, 보행자안내표지판, 교통시설물교통행정과032-453-26802023-08-07
23교통방치차량방치차량견인자동차관리과032-453-28202023-08-07
34교통불법주정차불법주·정차단속요청교통행정과032-453-28902023-08-07
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