Overview

Dataset statistics

Number of variables13
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory121.3 B

Variable types

Text1
Categorical11
DateTime1

Dataset

Description인천광역시 미추홀구 출산장려금지원현황에 대한 데이터로 관할동별로 월별 출산장려금이 지원된 인원(단위:명) 등을 제공합니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15087304&srcSe=7661IVAWM27C61E190

Alerts

기준일 has constant value ""Constant
2023년5월 is highly overall correlated with 2022년8월 and 8 other fieldsHigh correlation
2022년10월 is highly overall correlated with 2023년4월High correlation
2022년8월 is highly overall correlated with 2022년11월 and 5 other fieldsHigh correlation
2023년2월 is highly overall correlated with 2022년8월 and 6 other fieldsHigh correlation
2023년6월 is highly overall correlated with 2022년9월 and 7 other fieldsHigh correlation
2023년4월 is highly overall correlated with 2022년10월 and 5 other fieldsHigh correlation
2023년1월 is highly overall correlated with 2022년8월 and 6 other fieldsHigh correlation
2022년12월 is highly overall correlated with 2022년8월 and 6 other fieldsHigh correlation
2023년3월 is highly overall correlated with 2022년8월 and 7 other fieldsHigh correlation
2022년11월 is highly overall correlated with 2022년8월 and 7 other fieldsHigh correlation
2022년9월 is highly overall correlated with 2023년2월 and 2 other fieldsHigh correlation
2022년10월 is highly imbalanced (54.4%)Imbalance
행정동 has unique valuesUnique

Reproduction

Analysis started2024-03-18 04:44:08.194787
Analysis finished2024-03-18 04:44:10.626916
Duration2.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T13:44:10.756173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1904762
Min length3

Characters and Unicode

Total characters88
Distinct characters23
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

Unique21 ?
Unique (%)100.0%

Sample

1st row숭의1_3동
2nd row숭의2동
3rd row숭의4동
4th row용현1_4동
5th row용현2동
ValueCountFrequency (%)
숭의1_3동 1
 
4.8%
주안1동 1
 
4.8%
관교동 1
 
4.8%
주안8동 1
 
4.8%
주안7동 1
 
4.8%
주안6동 1
 
4.8%
주안5동 1
 
4.8%
주안4동 1
 
4.8%
주안3동 1
 
4.8%
주안2동 1
 
4.8%
Other values (11) 11
52.4%
2024-03-18T13:44:11.098691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
23.9%
안 8
 
9.1%
주 8
 
9.1%
1 5
 
5.7%
2 5
 
5.7%
3 4
 
4.5%
용 4
 
4.5%
현 4
 
4.5%
숭 3
 
3.4%
의 3
 
3.4%
Other values (13) 23
26.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63
71.6%
Decimal Number 22
 
25.0%
Connector Punctuation 3
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
33.3%
안 8
 
12.7%
주 8
 
12.7%
용 4
 
6.3%
현 4
 
6.3%
숭 3
 
4.8%
의 3
 
4.8%
학 3
 
4.8%
익 2
 
3.2%
도 2
 
3.2%
Other values (4) 5
 
7.9%
Decimal Number
ValueCountFrequency (%)
1 5
22.7%
2 5
22.7%
3 4
18.2%
4 3
13.6%
5 2
 
9.1%
6 1
 
4.5%
7 1
 
4.5%
8 1
 
4.5%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63
71.6%
Common 25
 
28.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
33.3%
안 8
 
12.7%
주 8
 
12.7%
용 4
 
6.3%
현 4
 
6.3%
숭 3
 
4.8%
의 3
 
4.8%
학 3
 
4.8%
익 2
 
3.2%
도 2
 
3.2%
Other values (4) 5
 
7.9%
Common
ValueCountFrequency (%)
1 5
20.0%
2 5
20.0%
3 4
16.0%
4 3
12.0%
_ 3
12.0%
5 2
 
8.0%
6 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63
71.6%
ASCII 25
 
28.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
33.3%
안 8
 
12.7%
주 8
 
12.7%
용 4
 
6.3%
현 4
 
6.3%
숭 3
 
4.8%
의 3
 
4.8%
학 3
 
4.8%
익 2
 
3.2%
도 2
 
3.2%
Other values (4) 5
 
7.9%
ASCII
ValueCountFrequency (%)
1 5
20.0%
2 5
20.0%
3 4
16.0%
4 3
12.0%
_ 3
12.0%
5 2
 
8.0%
6 1
 
4.0%
7 1
 
4.0%
8 1
 
4.0%

2022년8월
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
11 
1
7 
3
2 
2
 
1

Length

Max length4
Median length4
Mean length2.5714286
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 11
52.4%
1 7
33.3%
3 2
 
9.5%
2 1
 
4.8%

Length

2024-03-18T13:44:11.290936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:11.412228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 11
52.4%
1 7
33.3%
3 2
 
9.5%
2 1
 
4.8%

2022년9월
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
12 
1
6 
3
2 
2
 
1

Length

Max length4
Median length4
Mean length2.7142857
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 12
57.1%
1 6
28.6%
3 2
 
9.5%
2 1
 
4.8%

Length

2024-03-18T13:44:11.528124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:11.674625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
57.1%
1 6
28.6%
3 2
 
9.5%
2 1
 
4.8%

2022년10월
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
18 
1
2 
2
 
1

Length

Max length4
Median length4
Mean length3.5714286
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
85.7%
1 2
 
9.5%
2 1
 
4.8%

Length

2024-03-18T13:44:11.829148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:12.063139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
85.7%
1 2
 
9.5%
2 1
 
4.8%

2022년11월
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
12 
1
8 
2
 
1

Length

Max length4
Median length4
Mean length2.7142857
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 12
57.1%
1 8
38.1%
2 1
 
4.8%

Length

2024-03-18T13:44:12.204569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:12.371465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
57.1%
1 8
38.1%
2 1
 
4.8%

2022년12월
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
12 
1
5 
2
3 
3
 
1

Length

Max length4
Median length4
Mean length2.7142857
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row1
2nd row2
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 12
57.1%
1 5
23.8%
2 3
 
14.3%
3 1
 
4.8%

Length

2024-03-18T13:44:12.484819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:12.608604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
57.1%
1 5
23.8%
2 3
 
14.3%
3 1
 
4.8%

2023년1월
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
16 
1
4 
2
 
1

Length

Max length4
Median length4
Mean length3.2857143
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row1
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 16
76.2%
1 4
 
19.0%
2 1
 
4.8%

Length

2024-03-18T13:44:12.707194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:12.800348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 16
76.2%
1 4
 
19.0%
2 1
 
4.8%

2023년2월
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
12 
1
4 
2
3 
3
2 

Length

Max length4
Median length4
Mean length2.7142857
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row2

Common Values

ValueCountFrequency (%)
<NA> 12
57.1%
1 4
 
19.0%
2 3
 
14.3%
3 2
 
9.5%

Length

2024-03-18T13:44:12.948124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:13.073388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
57.1%
1 4
 
19.0%
2 3
 
14.3%
3 2
 
9.5%

2023년3월
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
15 
1
5 
4
 
1

Length

Max length4
Median length4
Mean length3.1428571
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 15
71.4%
1 5
 
23.8%
4 1
 
4.8%

Length

2024-03-18T13:44:13.184461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:13.286554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 15
71.4%
1 5
 
23.8%
4 1
 
4.8%

2023년4월
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
1
11 
<NA>
7 
2
2 
3
 
1

Length

Max length4
Median length1
Mean length2
Min length1

Unique

Unique1 ?
Unique (%)4.8%

Sample

1st row<NA>
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 11
52.4%
<NA> 7
33.3%
2 2
 
9.5%
3 1
 
4.8%

Length

2024-03-18T13:44:13.415133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:13.510032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 11
52.4%
na 7
33.3%
2 2
 
9.5%
3 1
 
4.8%

2023년5월
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
14 
1
7 

Length

Max length4
Median length4
Mean length3
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 14
66.7%
1 7
33.3%

Length

2024-03-18T13:44:13.603329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:13.693933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 14
66.7%
1 7
33.3%

2023년6월
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
13 
1
4 
2
2 
5
 
1
3
 
1

Length

Max length4
Median length4
Mean length2.8571429
Min length1

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row1
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 13
61.9%
1 4
 
19.0%
2 2
 
9.5%
5 1
 
4.8%
3 1
 
4.8%

Length

2024-03-18T13:44:13.781568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T13:44:13.878994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 13
61.9%
1 4
 
19.0%
2 2
 
9.5%
5 1
 
4.8%
3 1
 
4.8%

기준일
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2023-08-07 00:00:00
Maximum2023-08-07 00:00:00
2024-03-18T13:44:13.982920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T13:44:14.053838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2024-03-18T13:44:14.119675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동2022년8월2022년9월2022년10월2022년11월2022년12월2023년1월2023년2월2023년3월2023년4월2023년6월
행정동1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2022년8월1.0001.0000.858NaN1.0001.000NaN1.000NaN0.0000.000
2022년9월1.0000.8581.000NaN0.0000.6220.0000.9260.0000.2871.000
2022년10월1.000NaNNaN1.000NaNNaNNaNNaNNaNNaN0.000
2022년11월1.0001.0000.000NaN1.0001.000NaNNaNNaN1.000NaN
2022년12월1.0001.0000.622NaN1.0001.000NaN1.000NaN0.0001.000
2023년1월1.000NaN0.000NaNNaNNaN1.0000.0000.000NaNNaN
2023년2월1.0001.0000.926NaNNaN1.0000.0001.0001.0000.0001.000
2023년3월1.000NaN0.000NaNNaNNaN0.0001.0001.000NaNNaN
2023년4월1.0000.0000.287NaN1.0000.000NaN0.000NaN1.0001.000
2023년6월1.0000.0001.0000.000NaN1.000NaN1.000NaN1.0001.000
2024-03-18T13:44:14.279962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023년5월2022년10월2022년8월2023년2월2023년6월2023년4월2023년1월2022년12월2023년3월2022년11월2022년9월
2023년5월1.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.000
2022년10월NaN1.000NaNNaN0.0001.000NaNNaNNaNNaNNaN
2022년8월1.000NaN1.0000.8160.0000.0001.0000.7071.0000.8940.468
2023년2월1.000NaN0.8161.0001.0000.0000.0001.0001.0001.0000.577
2023년6월1.0000.0000.0001.0001.0000.8161.0001.0001.0001.0001.000
2023년4월1.0001.0000.0000.0000.8161.0001.0000.0001.0000.8160.358
2023년1월1.000NaN1.0000.0001.0001.0001.0001.0001.0001.0000.000
2022년12월1.000NaN0.7071.0001.0000.0001.0001.0001.0000.8160.000
2023년3월1.000NaN1.0001.0001.0001.0001.0001.0001.0001.0000.000
2022년11월1.000NaN0.8941.0001.0000.8161.0000.8161.0001.0000.000
2022년9월1.000NaN0.4680.5771.0000.3580.0000.0000.0000.0001.000
2024-03-18T13:44:14.402042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2022년8월2022년9월2022년10월2022년11월2022년12월2023년1월2023년2월2023년3월2023년4월2023년5월2023년6월
2022년8월1.0000.468NaN0.8940.7071.0000.8161.0000.0001.0000.000
2022년9월0.4681.0000.0000.0000.0000.0000.5770.0000.3581.0001.000
2022년10월NaN0.0001.000NaNNaN0.000NaNNaN1.0000.0000.000
2022년11월0.8940.000NaN1.0000.8161.0001.0001.0000.8161.0001.000
2022년12월0.7070.000NaN0.8161.0001.0001.0001.0000.0001.0001.000
2023년1월1.0000.0000.0001.0001.0001.0000.0001.0001.0001.0001.000
2023년2월0.8160.577NaN1.0001.0000.0001.0001.0000.0001.0001.000
2023년3월1.0000.000NaN1.0001.0001.0001.0001.0001.0001.0001.000
2023년4월0.0000.3581.0000.8160.0001.0000.0001.0001.0001.0000.816
2023년5월1.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.000
2023년6월0.0001.0000.0001.0001.0001.0001.0001.0000.8161.0001.000

Missing values

2024-03-18T13:44:10.412019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T13:44:10.569814image/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

행정동2022년8월2022년9월2022년10월2022년11월2022년12월2023년1월2023년2월2023년3월2023년4월2023년5월2023년6월기준일
0숭의1_3동<NA><NA><NA>111<NA><NA><NA>1<NA>2023-08-07
1숭의2동<NA>1<NA><NA>2<NA>1<NA>1112023-08-07
2숭의4동1<NA><NA><NA><NA><NA><NA><NA>1<NA><NA>2023-08-07
3용현1_4동<NA><NA>1<NA><NA><NA><NA><NA>1<NA>12023-08-07
4용현2동<NA><NA><NA><NA><NA><NA>2<NA>11<NA>2023-08-07
5용현3동<NA><NA><NA><NA>2<NA><NA><NA><NA><NA><NA>2023-08-07
6용현5동<NA>3<NA>1313<NA>1152023-08-07
7학익1동21<NA>22<NA><NA><NA>21<NA>2023-08-07
8학익2동<NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>2023-08-07
9도화1동13<NA>111<NA>13122023-08-07
행정동2022년8월2022년9월2022년10월2022년11월2022년12월2023년1월2023년2월2023년3월2023년4월2023년5월2023년6월기준일
11주안1동<NA><NA>2<NA>1<NA>21<NA><NA>32023-08-07
12주안2동32<NA>11<NA>2<NA><NA><NA><NA>2023-08-07
13주안3동11<NA>1<NA><NA>1<NA>1<NA><NA>2023-08-07
14주안4동1<NA><NA><NA><NA><NA>112<NA><NA>2023-08-07
15주안5동3<NA>11<NA><NA><NA><NA>1<NA>12023-08-07
16주안6동<NA><NA><NA><NA><NA><NA><NA><NA>1<NA><NA>2023-08-07
17주안7동<NA><NA><NA><NA><NA><NA><NA>1<NA><NA>12023-08-07
18주안8동11<NA><NA>1<NA><NA>11<NA><NA>2023-08-07
19관교동1<NA><NA>1<NA>11<NA><NA><NA>22023-08-07
20문학동<NA>1<NA><NA><NA><NA><NA><NA>1<NA><NA>2023-08-07