Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 KiB
Average record size in memory53.3 B

Variable types

Numeric1
Categorical4
Text1

Dataset

Description인천광역시 미추홀구의 복합민원 사전심사 청구대상민원에 대한 데이터로 처리부서, 민원사무명, 민원구분, 법정일수, 사전심사처리기간 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://www.data.go.kr/data/15085582/fileData.do

Alerts

연번 is highly overall correlated with 처리부서High correlation
처리부서 is highly overall correlated with 연번High correlation
법정일수 is highly overall correlated with 사전심사처리기간 High correlation
사전심사처리기간 is highly overall correlated with 법정일수 High correlation
연번 has unique valuesUnique
민원사무명 has unique valuesUnique

Reproduction

Analysis started2024-03-15 00:05:52.703450
Analysis finished2024-03-15 00:05:53.856090
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-03-15T09:05:54.051358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2024-03-15T09:05:54.466204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

처리부서
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size368.0 B
경제지원과
7 
건설과
7 
보건행정과
3 
문화예술과
2 
자동차관리과
2 
Other values (8)
9 

Length

Max length6
Median length5
Mean length4.5
Min length3

Unique

Unique7 ?
Unique (%)23.3%

Sample

1st row시민공동체과
2nd row문화예술과
3rd row문화예술과
4th row경제지원과
5th row경제지원과

Common Values

ValueCountFrequency (%)
경제지원과 7
23.3%
건설과 7
23.3%
보건행정과 3
10.0%
문화예술과 2
 
6.7%
자동차관리과 2
 
6.7%
건축과 2
 
6.7%
시민공동체과 1
 
3.3%
여성가족과 1
 
3.3%
자원순환과 1
 
3.3%
도시계획과 1
 
3.3%
Other values (3) 3
10.0%

Length

2024-03-15T09:05:54.882681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경제지원과 7
23.3%
건설과 7
23.3%
보건행정과 3
10.0%
문화예술과 2
 
6.7%
자동차관리과 2
 
6.7%
건축과 2
 
6.7%
시민공동체과 1
 
3.3%
여성가족과 1
 
3.3%
자원순환과 1
 
3.3%
도시계획과 1
 
3.3%
Other values (3) 3
10.0%

민원사무명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-03-15T09:05:55.798417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length12.666667
Min length4

Characters and Unicode

Total characters380
Distinct characters110
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row도서관 등록
2nd row관광사업계획 변경승인- 관광숙박업
3rd row관광편의시설업지정신청
4th row공장설립승인(변경)신청<복합>-동일행정기관
5th row농지전용허가
ValueCountFrequency (%)
등록 2
 
3.7%
국유재산의 2
 
3.7%
신청 2
 
3.7%
허가 2
 
3.7%
골재채취업등록 1
 
1.9%
사용.수익허가(대부 1
 
1.9%
매수 1
 
1.9%
도시계획시설부지매수청구 1
 
1.9%
하천점용허가(토지의점용 1
 
1.9%
지하수개발.이용의 1
 
1.9%
Other values (40) 40
74.1%
2024-03-15T09:05:57.260360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
6.3%
가 17
 
4.5%
허 15
 
3.9%
설 14
 
3.7%
업 12
 
3.2%
신 11
 
2.9%
) 10
 
2.6%
( 10
 
2.6%
관 9
 
2.4%
등 9
 
2.4%
Other values (100) 249
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
86.1%
Space Separator 24
 
6.3%
Close Punctuation 10
 
2.6%
Open Punctuation 10
 
2.6%
Other Punctuation 4
 
1.1%
Dash Punctuation 3
 
0.8%
Math Symbol 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 17
 
5.2%
허 15
 
4.6%
설 14
 
4.3%
업 12
 
3.7%
신 11
 
3.4%
관 9
 
2.8%
등 9
 
2.8%
의 9
 
2.8%
개 8
 
2.4%
경 8
 
2.4%
Other values (92) 215
65.7%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
86.1%
Common 53
 
13.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 17
 
5.2%
허 15
 
4.6%
설 14
 
4.3%
업 12
 
3.7%
신 11
 
3.4%
관 9
 
2.8%
등 9
 
2.8%
의 9
 
2.8%
개 8
 
2.4%
경 8
 
2.4%
Other values (92) 215
65.7%
Common
ValueCountFrequency (%)
24
45.3%
) 10
18.9%
( 10
18.9%
- 3
 
5.7%
, 2
 
3.8%
. 2
 
3.8%
> 1
 
1.9%
< 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
86.1%
ASCII 53
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24
45.3%
) 10
18.9%
( 10
18.9%
- 3
 
5.7%
, 2
 
3.8%
. 2
 
3.8%
> 1
 
1.9%
< 1
 
1.9%
Hangul
ValueCountFrequency (%)
가 17
 
5.2%
허 15
 
4.6%
설 14
 
4.3%
업 12
 
3.7%
신 11
 
3.4%
관 9
 
2.8%
등 9
 
2.8%
의 9
 
2.8%
개 8
 
2.4%
경 8
 
2.4%
Other values (92) 215
65.7%

민원구분
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size368.0 B
단순민원
19 
복합민원
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단순민원
2nd row단순민원
3rd row단순민원
4th row복합민원
5th row단순민원

Common Values

ValueCountFrequency (%)
단순민원 19
63.3%
복합민원 11
36.7%

Length

2024-03-15T09:05:57.485449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T09:05:57.775966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단순민원 19
63.3%
복합민원 11
36.7%

법정일수
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)43.3%
Missing0
Missing (%)0.0%
Memory size368.0 B
10
7 
14
3 
30
3 
20
3 
15
3 
Other values (8)
11 

Length

Max length12
Median length2
Mean length2.4333333
Min length1

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row10
2nd row12
3rd row14
4th row14
5th row10~30

Common Values

ValueCountFrequency (%)
10 7
23.3%
14 3
10.0%
30 3
10.0%
20 3
10.0%
15 3
10.0%
7 2
 
6.7%
5 2
 
6.7%
180 2
 
6.7%
12 1
 
3.3%
10~30 1
 
3.3%
Other values (3) 3
10.0%

Length

2024-03-15T09:05:58.045423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10 7
22.6%
14 3
9.7%
30 3
9.7%
20 3
9.7%
15 3
9.7%
7 2
 
6.5%
5 2
 
6.5%
180 2
 
6.5%
12 1
 
3.2%
10~30 1
 
3.2%
Other values (4) 4
12.9%

사전심사처리기간
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size368.0 B
10
8 
20
4 
7
3 
5
3 
12
2 
Other values (9)
10 

Length

Max length12
Median length2
Mean length2.2666667
Min length1

Unique

Unique8 ?
Unique (%)26.7%

Sample

1st row7
2nd row12
3rd row12
4th row10
5th row9~29

Common Values

ValueCountFrequency (%)
10 8
26.7%
20 4
13.3%
7 3
 
10.0%
5 3
 
10.0%
12 2
 
6.7%
60 2
 
6.7%
9~29 1
 
3.3%
14 1
 
3.3%
25 1
 
3.3%
21 1
 
3.3%
Other values (4) 4
13.3%

Length

2024-03-15T09:05:58.296632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
10 8
25.8%
20 4
12.9%
7 3
 
9.7%
5 3
 
9.7%
12 2
 
6.5%
60 2
 
6.5%
9~29 1
 
3.2%
14 1
 
3.2%
25 1
 
3.2%
21 1
 
3.2%
Other values (5) 5
16.1%

Interactions

2024-03-15T09:05:53.142015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T09:05:58.441751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번처리부서민원사무명민원구분법정일수사전심사처리기간
연번1.0000.9061.0000.7190.8180.810
처리부서0.9061.0001.0000.6520.8050.614
민원사무명1.0001.0001.0001.0001.0001.000
민원구분0.7190.6521.0001.0000.4540.744
법정일수0.8180.8051.0000.4541.0000.920
사전심사처리기간0.8100.6141.0000.7440.9201.000
2024-03-15T09:05:58.624643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사전심사처리기간민원구분법정일수처리부서
사전심사처리기간1.0000.4400.6310.217
민원구분0.4401.0000.3120.470
법정일수0.6310.3121.0000.310
처리부서0.2170.4700.3101.000
2024-03-15T09:05:58.794184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번처리부서민원구분법정일수사전심사처리기간
연번1.0000.6240.4680.4650.427
처리부서0.6241.0000.4700.3100.217
민원구분0.4680.4701.0000.3120.440
법정일수0.4650.3100.3121.0000.631
사전심사처리기간0.4270.2170.4400.6311.000

Missing values

2024-03-15T09:05:53.478029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T09:05:53.774784image/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

연번처리부서민원사무명민원구분법정일수사전심사처리기간
01시민공동체과도서관 등록단순민원107
12문화예술과관광사업계획 변경승인- 관광숙박업단순민원1212
23문화예술과관광편의시설업지정신청단순민원1412
34경제지원과공장설립승인(변경)신청<복합>-동일행정기관복합민원1410
45경제지원과농지전용허가단순민원10~309~29
56경제지원과시장상인회 등록신청단순민원1414
67경제지원과대규모점포 개설등록(변경)신청(복합)복합민원3025
78경제지원과석유판매업(주유소)등록복합민원77
89경제지원과액화석유가스의 충전사업허가복합민원55
910경제지원과고압가스 제조,판매,저장소 설치허가복합민원55
연번처리부서민원사무명민원구분법정일수사전심사처리기간
2021토지정보과개발행위허가(토지분할)복합민원1510
2122공원녹지과산지전용(변경)허가단순민원2520
2223자동차관리과자동차관리사업등록신청단순민원1515
2324자동차관리과건설기계대여업신고단순민원1010
2425건축과건축물 용도변경허가(신고)단순민원3(신고), 7(허가)3(신고), 7(허가)
2526건축과건축허가복합민원7~157~15
2627도시경관과옥외광고물 등 표시 허가복합민원75
2728보건행정과부속의료기관개설변경허가 및 변경신고단순민원1010
2829보건행정과의료기관개설변경허가단순민원1010
2930보건행정과의료기관개설허가복합민원1010