Overview

Dataset statistics

Number of variables8
Number of observations35
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory67.8 B

Variable types

Categorical5
Text1
DateTime2

Dataset

Description경기도 낚시 금지 및 제한 구역 지정 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=S4AMKUVUAEN1ZB341AUV32174529&infSeq=1

Alerts

지정종료일자 has constant value ""Constant
지정권자 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 지정권자High correlation
구분 is highly imbalanced (68.4%)Imbalance
지정사유 is highly imbalanced (81.3%)Imbalance

Reproduction

Analysis started2024-03-12 23:52:42.642520
Analysis finished2024-03-12 23:52:43.043431
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
금지구역
33 
제한구역
 
2

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금지구역 33
94.3%
제한구역 2
 
5.7%

Length

2024-03-13T08:52:43.095721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:52:43.180675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금지구역 33
94.3%
제한구역 2
 
5.7%

시군명
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
파주시
8 
수원시
5 
성남시
4 
화성시
4 
의왕시
3 
Other values (7)
11 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)11.4%

Sample

1st row군포시
2nd row군포시
3rd row성남시
4th row성남시
5th row성남시

Common Values

ValueCountFrequency (%)
파주시 8
22.9%
수원시 5
14.3%
성남시 4
11.4%
화성시 4
11.4%
의왕시 3
 
8.6%
포천시 3
 
8.6%
군포시 2
 
5.7%
용인시 2
 
5.7%
평택시 1
 
2.9%
김포시 1
 
2.9%
Other values (2) 2
 
5.7%

Length

2024-03-13T08:52:43.275712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파주시 8
22.9%
수원시 5
14.3%
성남시 4
11.4%
화성시 4
11.4%
의왕시 3
 
8.6%
포천시 3
 
8.6%
군포시 2
 
5.7%
용인시 2
 
5.7%
평택시 1
 
2.9%
김포시 1
 
2.9%
Other values (2) 2
 
5.7%

명칭
Text

Distinct33
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-03-13T08:52:43.439032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length5
Mean length5.3428571
Min length3

Characters and Unicode

Total characters187
Distinct characters65
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

Unique31 ?
Unique (%)88.6%

Sample

1st row반월저수지
2nd row갈치저수지
3rd row대왕저수지
4th row운중저수지
5th row서현저수지
ValueCountFrequency (%)
남양호 2
 
5.3%
낙생저수지 2
 
5.3%
물왕호수 1
 
2.6%
산정저수지 1
 
2.6%
기산저수지 1
 
2.6%
서랑저수지 1
 
2.6%
백운호수 1
 
2.6%
고모저수지 1
 
2.6%
서호저수지 1
 
2.6%
축만제 1
 
2.6%
Other values (26) 26
68.4%
2024-03-13T08:52:43.716652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 32
17.1%
지 29
15.5%
저 28
 
15.0%
호 7
 
3.7%
왕 4
 
2.1%
리 4
 
2.1%
남 3
 
1.6%
3
 
1.6%
서 3
 
1.6%
대 3
 
1.6%
Other values (55) 71
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
96.3%
Space Separator 3
 
1.6%
Close Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 32
17.8%
지 29
16.1%
저 28
15.6%
호 7
 
3.9%
왕 4
 
2.2%
리 4
 
2.2%
남 3
 
1.7%
서 3
 
1.7%
대 3
 
1.7%
양 3
 
1.7%
Other values (52) 64
35.6%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
96.3%
Common 7
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 32
17.8%
지 29
16.1%
저 28
15.6%
호 7
 
3.9%
왕 4
 
2.2%
리 4
 
2.2%
남 3
 
1.7%
서 3
 
1.7%
대 3
 
1.7%
양 3
 
1.7%
Other values (52) 64
35.6%
Common
ValueCountFrequency (%)
3
42.9%
) 2
28.6%
( 2
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
96.3%
ASCII 7
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 32
17.8%
지 29
16.1%
저 28
15.6%
호 7
 
3.9%
왕 4
 
2.2%
리 4
 
2.2%
남 3
 
1.7%
서 3
 
1.7%
대 3
 
1.7%
양 3
 
1.7%
Other values (52) 64
35.6%
ASCII
ValueCountFrequency (%)
3
42.9%
) 2
28.6%
( 2
28.6%

지정일자
Date

Distinct22
Distinct (%)62.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2001-11-30 00:00:00
Maximum2022-06-07 00:00:00
2024-03-13T08:52:43.810053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:52:43.912072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)

지정권자
Categorical

HIGH CORRELATION 

Distinct12
Distinct (%)34.3%
Missing0
Missing (%)0.0%
Memory size412.0 B
파주시장
8 
수원시장
5 
성남시장
4 
화성시장
4 
의왕시장
3 
Other values (7)
11 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique4 ?
Unique (%)11.4%

Sample

1st row군포시장
2nd row군포시장
3rd row성남시장
4th row성남시장
5th row성남시장

Common Values

ValueCountFrequency (%)
파주시장 8
22.9%
수원시장 5
14.3%
성남시장 4
11.4%
화성시장 4
11.4%
의왕시장 3
 
8.6%
포천시장 3
 
8.6%
군포시장 2
 
5.7%
용인시장 2
 
5.7%
평택시장 1
 
2.9%
김포시장 1
 
2.9%
Other values (2) 2
 
5.7%

Length

2024-03-13T08:52:44.008123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파주시장 8
22.9%
수원시장 5
14.3%
성남시장 4
11.4%
화성시장 4
11.4%
의왕시장 3
 
8.6%
포천시장 3
 
8.6%
군포시장 2
 
5.7%
용인시장 2
 
5.7%
평택시장 1
 
2.9%
김포시장 1
 
2.9%
Other values (2) 2
 
5.7%

지정시작일자
Date

Distinct21
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
Minimum2001-11-30 00:00:00
Maximum2022-06-07 00:00:00
2024-03-13T08:52:44.087739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:52:44.176038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

지정종료일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2059-12-31
35 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2059-12-31
2nd row2059-12-31
3rd row2059-12-31
4th row2059-12-31
5th row2059-12-31

Common Values

ValueCountFrequency (%)
2059-12-31 35
100.0%

Length

2024-03-13T08:52:44.284974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:52:44.364142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2059-12-31 35
100.0%

지정사유
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
농업용
34 
하천유지관리
 
1

Length

Max length6
Median length3
Mean length3.0857143
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
농업용 34
97.1%
하천유지관리 1
 
2.9%

Length

2024-03-13T08:52:44.478830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:52:44.569466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
농업용 34
97.1%
하천유지관리 1
 
2.9%

Correlations

2024-03-13T08:52:44.623121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군명명칭지정일자지정권자지정시작일자지정사유
구분1.0000.0001.0001.0000.0001.0000.000
시군명0.0001.0000.0000.9881.0000.9900.000
명칭1.0000.0001.0000.9840.0000.9781.000
지정일자1.0000.9880.9841.0000.9881.0000.000
지정권자0.0001.0000.0000.9881.0000.9900.000
지정시작일자1.0000.9900.9781.0000.9901.0000.000
지정사유0.0000.0001.0000.0000.0000.0001.000
2024-03-13T08:52:44.717902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정사유지정권자시군명구분
지정사유1.0000.0000.0000.000
지정권자0.0001.0001.0000.000
시군명0.0001.0001.0000.000
구분0.0000.0000.0001.000
2024-03-13T08:52:44.801160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군명지정권자지정사유
구분1.0000.0000.0000.000
시군명0.0001.0001.0000.000
지정권자0.0001.0001.0000.000
지정사유0.0000.0000.0001.000

Missing values

2024-03-13T08:52:42.915870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:52:43.008386image/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

구분시군명명칭지정일자지정권자지정시작일자지정종료일자지정사유
0금지구역군포시반월저수지2011-11-21군포시장2011-11-212059-12-31농업용
1금지구역군포시갈치저수지2011-11-21군포시장2011-11-212059-12-31농업용
2금지구역성남시대왕저수지2003-07-07성남시장2003-07-072059-12-31농업용
3금지구역성남시운중저수지2007-02-20성남시장2007-02-202059-12-31농업용
4금지구역성남시서현저수지2007-02-20성남시장2007-02-202059-12-31농업용
5금지구역성남시낙생저수지2014-01-01성남시장2014-01-012059-12-31농업용
6금지구역용인시기흥저수지2010-08-25용인시장2010-08-252059-12-31농업용
7금지구역용인시낙생저수지2014-01-01용인시장2014-01-012059-12-31농업용
8금지구역파주시공릉저수지2017-02-01파주시장2017-02-012059-12-31농업용
9금지구역파주시애룡저수지2017-02-01파주시장2017-02-012059-12-31농업용
구분시군명명칭지정일자지정권자지정시작일자지정종료일자지정사유
25금지구역수원시원천저수지2005-06-15수원시장2005-06-152059-12-31농업용
26금지구역수원시서호저수지 (축만제)2005-06-16수원시장2005-06-152059-12-31농업용
27금지구역수원시신대저수지2008-12-03수원시장2008-12-032059-12-31농업용
28금지구역포천시고모저수지2017-02-01포천시장2017-02-012059-12-31농업용
29금지구역오산시서랑저수지2017-11-01오산시장2017-11-012059-12-31농업용
30금지구역포천시기산저수지2021-03-02포천시장2021-03-022059-12-31농업용
31금지구역포천시산정저수지2021-03-02포천시장2021-03-022059-12-31농업용
32금지구역시흥시물왕호수2022-06-07시흥시장2022-06-072059-12-31농업용
33제한구역파주시발랑저수지2011-05-06파주시장2011-05-062059-12-31농업용
34제한구역파주시마지저수지2008-12-01파주시장2008-12-012059-12-31농업용