Overview

Dataset statistics

Number of variables6
Number of observations55
Missing cells71
Missing cells (%)21.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory50.4 B

Variable types

Categorical4
Text2

Dataset

Description관내 공간정보시스템 내 행정구역에 대한 데이터로 행정읍면동, 법정읍면동, 법정동리, 관리기관명 등의 항목을 제공합니다.
Author경기도 양주시
URLhttps://www.data.go.kr/data/15040720/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
관리기관명 has constant value ""Constant
행정읍면동명 is highly overall correlated with 법정읍면동명High correlation
법정읍면동명 is highly overall correlated with 행정읍면동명High correlation
비고 has 53 (96.4%) missing valuesMissing
법정동리 has 18 (32.7%) missing valuesMissing

Reproduction

Analysis started2023-12-12 11:27:32.012139
Analysis finished2023-12-12 11:27:33.169682
Duration1.16 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정읍면동명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
남면
10 
백석읍
7 
광적면
7 
장흥면
7 
은현면
6 
Other values (6)
18 

Length

Max length4
Median length3
Mean length3.1454545
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남면 10
18.2%
백석읍 7
12.7%
광적면 7
12.7%
장흥면 7
12.7%
은현면 6
10.9%
양주1동 5
9.1%
양주2동 4
 
7.3%
회천4동 3
 
5.5%
회천1동 2
 
3.6%
회천2동 2
 
3.6%

Length

2023-12-12T20:27:33.288491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남면 10
18.2%
백석읍 7
12.7%
광적면 7
12.7%
장흥면 7
12.7%
은현면 6
10.9%
양주1동 5
9.1%
양주2동 4
 
7.3%
회천4동 3
 
5.5%
회천1동 2
 
3.6%
회천2동 2
 
3.6%

법정읍면동명
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size572.0 B
남면
10 
광적면
7 
장흥면
7 
백석읍
7 
은현면
6 
Other values (17)
18 

Length

Max length3
Median length3
Mean length2.8181818
Min length2

Unique

Unique16 ?
Unique (%)29.1%

Sample

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

Common Values

ValueCountFrequency (%)
남면 10
18.2%
광적면 7
12.7%
장흥면 7
12.7%
백석읍 7
12.7%
은현면 6
10.9%
덕정동 2
 
3.6%
삼숭동 1
 
1.8%
유양동 1
 
1.8%
어둔동 1
 
1.8%
남방동 1
 
1.8%
Other values (12) 12
21.8%

Length

2023-12-12T20:27:33.521832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
남면 10
18.2%
장흥면 7
12.7%
백석읍 7
12.7%
광적면 7
12.7%
은현면 6
10.9%
덕정동 2
 
3.6%
만송동 1
 
1.8%
고읍동 1
 
1.8%
율정동 1
 
1.8%
회암동 1
 
1.8%
Other values (12) 12
21.8%

비고
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing53
Missing (%)96.4%
Memory size572.0 B
2023-12-12T20:27:33.805336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length74
Median length72.5
Mean length72.5
Min length71

Characters and Unicode

Total characters145
Distinct characters15
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row208-4∼14, 210, 210-1∼4, 211-2∼6, 235, 235-1∼9, 236-1∼3, 256, 256-1, 258 제외
2nd row208-4∼14, 210, 210-1∼4, 211-2∼6, 235, 235-1∼9, 236-1∼3, 256, 256-1, 258
ValueCountFrequency (%)
208-4∼14 2
9.5%
210 2
9.5%
210-1∼4 2
9.5%
211-2∼6 2
9.5%
235 2
9.5%
235-1∼9 2
9.5%
236-1∼3 2
9.5%
256 2
9.5%
256-1 2
9.5%
258 2
9.5%
2023-12-12T20:27:34.334537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 22
15.2%
19
13.1%
1 18
12.4%
, 18
12.4%
- 12
8.3%
∼ 10
6.9%
5 10
6.9%
6 8
 
5.5%
3 8
 
5.5%
0 6
 
4.1%
Other values (5) 14
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
57.9%
Space Separator 19
 
13.1%
Other Punctuation 18
 
12.4%
Dash Punctuation 12
 
8.3%
Math Symbol 10
 
6.9%
Other Letter 2
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 22
26.2%
1 18
21.4%
5 10
11.9%
6 8
 
9.5%
3 8
 
9.5%
0 6
 
7.1%
4 6
 
7.1%
8 4
 
4.8%
9 2
 
2.4%
Other Letter
ValueCountFrequency (%)
제 1
50.0%
외 1
50.0%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Math Symbol
ValueCountFrequency (%)
∼ 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 143
98.6%
Hangul 2
 
1.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 22
15.4%
19
13.3%
1 18
12.6%
, 18
12.6%
- 12
8.4%
∼ 10
7.0%
5 10
7.0%
6 8
 
5.6%
3 8
 
5.6%
0 6
 
4.2%
Other values (3) 12
8.4%
Hangul
ValueCountFrequency (%)
제 1
50.0%
외 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 133
91.7%
Math Operators 10
 
6.9%
Hangul 2
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 22
16.5%
19
14.3%
1 18
13.5%
, 18
13.5%
- 12
9.0%
5 10
7.5%
6 8
 
6.0%
3 8
 
6.0%
0 6
 
4.5%
4 6
 
4.5%
Other values (2) 6
 
4.5%
Math Operators
ValueCountFrequency (%)
∼ 10
100.0%
Hangul
ValueCountFrequency (%)
제 1
50.0%
외 1
50.0%

법정동리
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing18
Missing (%)32.7%
Memory size572.0 B
2023-12-12T20:27:34.704861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters111
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique37 ?
Unique (%)100.0%

Sample

1st row방성리
2nd row오산리
3rd row복지리
4th row가업리
5th row홍죽리
ValueCountFrequency (%)
선암리 1
 
2.7%
입암리 1
 
2.7%
한산리 1
 
2.7%
황방리 1
 
2.7%
가납리 1
 
2.7%
광석리 1
 
2.7%
우고리 1
 
2.7%
비암리 1
 
2.7%
효촌리 1
 
2.7%
석우리 1
 
2.7%
Other values (27) 27
73.0%
2023-12-12T20:27:35.255061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 37
33.3%
암 8
 
7.2%
곡 4
 
3.6%
산 4
 
3.6%
석 3
 
2.7%
하 3
 
2.7%
신 3
 
2.7%
우 2
 
1.8%
현 2
 
1.8%
삼 2
 
1.8%
Other values (39) 43
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 111
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 37
33.3%
암 8
 
7.2%
곡 4
 
3.6%
산 4
 
3.6%
석 3
 
2.7%
하 3
 
2.7%
신 3
 
2.7%
우 2
 
1.8%
현 2
 
1.8%
삼 2
 
1.8%
Other values (39) 43
38.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 111
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 37
33.3%
암 8
 
7.2%
곡 4
 
3.6%
산 4
 
3.6%
석 3
 
2.7%
하 3
 
2.7%
신 3
 
2.7%
우 2
 
1.8%
현 2
 
1.8%
삼 2
 
1.8%
Other values (39) 43
38.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 111
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 37
33.3%
암 8
 
7.2%
곡 4
 
3.6%
산 4
 
3.6%
석 3
 
2.7%
하 3
 
2.7%
신 3
 
2.7%
우 2
 
1.8%
현 2
 
1.8%
삼 2
 
1.8%
Other values (39) 43
38.7%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
2022-08-11
55 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-11
2nd row2022-08-11
3rd row2022-08-11
4th row2022-08-11
5th row2022-08-11

Common Values

ValueCountFrequency (%)
2022-08-11 55
100.0%

Length

2023-12-12T20:27:35.484996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:27:35.664247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-11 55
100.0%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size572.0 B
양주시 정보통신과
55 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row양주시 정보통신과
2nd row양주시 정보통신과
3rd row양주시 정보통신과
4th row양주시 정보통신과
5th row양주시 정보통신과

Common Values

ValueCountFrequency (%)
양주시 정보통신과 55
100.0%

Length

2023-12-12T20:27:35.842562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:27:36.021659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양주시 55
50.0%
정보통신과 55
50.0%

Correlations

2023-12-12T20:27:36.119803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정읍면동명법정읍면동명비고법정동리
행정읍면동명1.0001.0000.0001.000
법정읍면동명1.0001.000NaN1.000
비고0.000NaN1.000NaN
법정동리1.0001.000NaN1.000
2023-12-12T20:27:36.288082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정읍면동명행정읍면동명
법정읍면동명1.0000.830
행정읍면동명0.8301.000
2023-12-12T20:27:36.436263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정읍면동명법정읍면동명
행정읍면동명1.0000.830
법정읍면동명0.8301.000

Missing values

2023-12-12T20:27:32.321020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:27:32.931752image/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.
2023-12-12T20:27:33.075393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

행정읍면동명법정읍면동명비고법정동리데이터기준일자관리기관명
0백석읍백석읍<NA>방성리2022-08-11양주시 정보통신과
1백석읍백석읍<NA>오산리2022-08-11양주시 정보통신과
2백석읍백석읍<NA>복지리2022-08-11양주시 정보통신과
3백석읍백석읍<NA>가업리2022-08-11양주시 정보통신과
4백석읍백석읍<NA>홍죽리2022-08-11양주시 정보통신과
5백석읍백석읍<NA>연곡리2022-08-11양주시 정보통신과
6백석읍백석읍<NA>기산리2022-08-11양주시 정보통신과
7은현면은현면<NA>용암리2022-08-11양주시 정보통신과
8은현면은현면<NA>선암리2022-08-11양주시 정보통신과
9은현면은현면<NA>운암리2022-08-11양주시 정보통신과
행정읍면동명법정읍면동명비고법정동리데이터기준일자관리기관명
45양주2동고읍동<NA><NA>2022-08-11양주시 정보통신과
46회천1동덕정동208-4∼14, 210, 210-1∼4, 211-2∼6, 235, 235-1∼9, 236-1∼3, 256, 256-1, 258 제외<NA>2022-08-11양주시 정보통신과
47회천1동봉양동<NA><NA>2022-08-11양주시 정보통신과
48회천2동덕계동<NA><NA>2022-08-11양주시 정보통신과
49회천2동회정동<NA><NA>2022-08-11양주시 정보통신과
50회천3동덕정동208-4∼14, 210, 210-1∼4, 211-2∼6, 235, 235-1∼9, 236-1∼3, 256, 256-1, 258<NA>2022-08-11양주시 정보통신과
51회천3동고암동<NA><NA>2022-08-11양주시 정보통신과
52회천4동회암동<NA><NA>2022-08-11양주시 정보통신과
53회천4동율정동<NA><NA>2022-08-11양주시 정보통신과
54회천4동옥정동<NA><NA>2022-08-11양주시 정보통신과