Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells14
Missing cells (%)10.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory47.9 B

Variable types

Numeric3
Text2

Dataset

Description경기도 고양시_쌈지공원 현황에 대한 데이터로 쌈지공원의 구분, 조성년도, 소재지, 면적, 조성내역 등의 항목을 제공합니다.
Author경기도 고양시
URLhttps://www.data.go.kr/data/15055268/fileData.do

Alerts

연번 is highly overall correlated with 조성년도High correlation
조성년도 is highly overall correlated with 연번High correlation
조성년도 has 14 (51.9%) missing valuesMissing
연번 has unique valuesUnique
사업명 has unique valuesUnique
소재지 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:58:06.037810
Analysis finished2023-12-12 12:58:07.321913
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T21:58:07.387733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.3
Q17.5
median14
Q320.5
95-th percentile25.7
Maximum27
Range26
Interquartile range (IQR)13

Descriptive statistics

Standard deviation7.9372539
Coefficient of variation (CV)0.56694671
Kurtosis-1.2
Mean14
Median Absolute Deviation (MAD)7
Skewness0
Sum378
Variance63
MonotonicityStrictly increasing
2023-12-12T21:58:07.527350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 1
 
3.7%
2 1
 
3.7%
27 1
 
3.7%
26 1
 
3.7%
25 1
 
3.7%
24 1
 
3.7%
23 1
 
3.7%
22 1
 
3.7%
21 1
 
3.7%
20 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
2 1
3.7%
3 1
3.7%
4 1
3.7%
5 1
3.7%
6 1
3.7%
7 1
3.7%
8 1
3.7%
9 1
3.7%
10 1
3.7%
ValueCountFrequency (%)
27 1
3.7%
26 1
3.7%
25 1
3.7%
24 1
3.7%
23 1
3.7%
22 1
3.7%
21 1
3.7%
20 1
3.7%
19 1
3.7%
18 1
3.7%

사업명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T21:58:07.758097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length16.777778
Min length8

Characters and Unicode

Total characters453
Distinct characters94
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

Unique27 ?
Unique (%)100.0%

Sample

1st row고양동 쌈지공원
2nd row내유동 쌈지공원
3rd row행주내동 쌈지공원
4th row행신역 주변 쌈지공원
5th row관산동 공릉천변 쌈지공원
ValueCountFrequency (%)
쌈지공원 23
25.6%
조성사업 12
 
13.3%
마을정원 4
 
4.4%
일원 3
 
3.3%
고양동 2
 
2.2%
내유동 2
 
2.2%
관산동 2
 
2.2%
대화동 2
 
2.2%
행주동 2
 
2.2%
인근 1
 
1.1%
Other values (37) 37
41.1%
2023-12-12T21:58:08.154258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
13.9%
원 35
 
7.7%
공 27
 
6.0%
지 25
 
5.5%
쌈 23
 
5.1%
사 22
 
4.9%
성 20
 
4.4%
동 20
 
4.4%
업 20
 
4.4%
조 19
 
4.2%
Other values (84) 179
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
81.2%
Space Separator 63
 
13.9%
Open Punctuation 8
 
1.8%
Close Punctuation 8
 
1.8%
Decimal Number 6
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 35
 
9.5%
공 27
 
7.3%
지 25
 
6.8%
쌈 23
 
6.2%
사 22
 
6.0%
성 20
 
5.4%
동 20
 
5.4%
업 20
 
5.4%
조 19
 
5.2%
정 7
 
1.9%
Other values (77) 150
40.8%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
0 1
 
16.7%
3 1
 
16.7%
8 1
 
16.7%
Space Separator
ValueCountFrequency (%)
63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
81.2%
Common 85
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 35
 
9.5%
공 27
 
7.3%
지 25
 
6.8%
쌈 23
 
6.2%
사 22
 
6.0%
성 20
 
5.4%
동 20
 
5.4%
업 20
 
5.4%
조 19
 
5.2%
정 7
 
1.9%
Other values (77) 150
40.8%
Common
ValueCountFrequency (%)
63
74.1%
( 8
 
9.4%
) 8
 
9.4%
1 3
 
3.5%
0 1
 
1.2%
3 1
 
1.2%
8 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
81.2%
ASCII 85
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
74.1%
( 8
 
9.4%
) 8
 
9.4%
1 3
 
3.5%
0 1
 
1.2%
3 1
 
1.2%
8 1
 
1.2%
Hangul
ValueCountFrequency (%)
원 35
 
9.5%
공 27
 
7.3%
지 25
 
6.8%
쌈 23
 
6.2%
사 22
 
6.0%
성 20
 
5.4%
동 20
 
5.4%
업 20
 
5.4%
조 19
 
5.2%
정 7
 
1.9%
Other values (77) 150
40.8%

조성년도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct13
Distinct (%)100.0%
Missing14
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean2015.6154
Minimum2009
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T21:58:08.283455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2009.6
Q12012
median2016
Q32019
95-th percentile2021.4
Maximum2022
Range13
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.3308671
Coefficient of variation (CV)0.0021486575
Kurtosis-1.3326643
Mean2015.6154
Median Absolute Deviation (MAD)4
Skewness-0.090391725
Sum26203
Variance18.75641
MonotonicityStrictly increasing
2023-12-12T21:58:08.390987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2009 1
 
3.7%
2010 1
 
3.7%
2011 1
 
3.7%
2012 1
 
3.7%
2013 1
 
3.7%
2015 1
 
3.7%
2016 1
 
3.7%
2017 1
 
3.7%
2018 1
 
3.7%
2019 1
 
3.7%
Other values (3) 3
 
11.1%
(Missing) 14
51.9%
ValueCountFrequency (%)
2009 1
3.7%
2010 1
3.7%
2011 1
3.7%
2012 1
3.7%
2013 1
3.7%
2015 1
3.7%
2016 1
3.7%
2017 1
3.7%
2018 1
3.7%
2019 1
3.7%
ValueCountFrequency (%)
2022 1
3.7%
2021 1
3.7%
2020 1
3.7%
2019 1
3.7%
2018 1
3.7%
2017 1
3.7%
2016 1
3.7%
2015 1
3.7%
2013 1
3.7%
2012 1
3.7%

소재지
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2023-12-12T21:58:08.602682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length22.185185
Min length18

Characters and Unicode

Total characters599
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row고양시 덕양구 벽제관로 31(고양동 235-1번지)
2nd row고양시 덕양구 통일로 1258(내유동 966번지)
3rd row고양시 덕양구 행주내동 645번지
4th row고양시 덕양구 행신동 810번지 외 2필지
5th row고양시 덕양구 관산동 172-3번지 외 1필지
ValueCountFrequency (%)
고양시 27
20.9%
덕양구 21
16.3%
일원 11
 
8.5%
일산서구 5
 
3.9%
외 4
 
3.1%
내유동 3
 
2.3%
1필지 3
 
2.3%
대자동 2
 
1.6%
행신동 2
 
1.6%
행주내동 2
 
1.6%
Other values (49) 49
38.0%
2023-12-12T21:58:08.972471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
17.0%
양 49
 
8.2%
지 30
 
5.0%
고 28
 
4.7%
구 28
 
4.7%
1 27
 
4.5%
동 27
 
4.5%
시 27
 
4.5%
번 26
 
4.3%
2 22
 
3.7%
Other values (46) 233
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
58.6%
Decimal Number 123
 
20.5%
Space Separator 102
 
17.0%
Dash Punctuation 15
 
2.5%
Close Punctuation 4
 
0.7%
Open Punctuation 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 49
14.0%
지 30
 
8.5%
고 28
 
8.0%
구 28
 
8.0%
동 27
 
7.7%
시 27
 
7.7%
번 26
 
7.4%
덕 21
 
6.0%
일 19
 
5.4%
산 12
 
3.4%
Other values (32) 84
23.9%
Decimal Number
ValueCountFrequency (%)
1 27
22.0%
2 22
17.9%
3 11
8.9%
5 10
 
8.1%
7 10
 
8.1%
8 10
 
8.1%
9 9
 
7.3%
6 9
 
7.3%
0 8
 
6.5%
4 7
 
5.7%
Space Separator
ValueCountFrequency (%)
102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
58.6%
Common 248
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 49
14.0%
지 30
 
8.5%
고 28
 
8.0%
구 28
 
8.0%
동 27
 
7.7%
시 27
 
7.7%
번 26
 
7.4%
덕 21
 
6.0%
일 19
 
5.4%
산 12
 
3.4%
Other values (32) 84
23.9%
Common
ValueCountFrequency (%)
102
41.1%
1 27
 
10.9%
2 22
 
8.9%
- 15
 
6.0%
3 11
 
4.4%
5 10
 
4.0%
7 10
 
4.0%
8 10
 
4.0%
9 9
 
3.6%
6 9
 
3.6%
Other values (4) 23
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
58.6%
ASCII 248
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
41.1%
1 27
 
10.9%
2 22
 
8.9%
- 15
 
6.0%
3 11
 
4.4%
5 10
 
4.0%
7 10
 
4.0%
8 10
 
4.0%
9 9
 
3.6%
6 9
 
3.6%
Other values (4) 23
 
9.3%
Hangul
ValueCountFrequency (%)
양 49
14.0%
지 30
 
8.5%
고 28
 
8.0%
구 28
 
8.0%
동 27
 
7.7%
시 27
 
7.7%
번 26
 
7.4%
덕 21
 
6.0%
일 19
 
5.4%
산 12
 
3.4%
Other values (32) 84
23.9%

면적(제곱미터)
Real number (ℝ)

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1338.9259
Minimum24
Maximum10000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2023-12-12T21:58:09.138615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile102
Q1240.5
median500
Q31420
95-th percentile4850
Maximum10000
Range9976
Interquartile range (IQR)1179.5

Descriptive statistics

Standard deviation2161.1372
Coefficient of variation (CV)1.6140827
Kurtosis9.8205648
Mean1338.9259
Median Absolute Deviation (MAD)340
Skewness2.9487556
Sum36151
Variance4670514
MonotonicityNot monotonic
2023-12-12T21:58:09.259326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
500 2
 
7.4%
160 2
 
7.4%
150 1
 
3.7%
10000 1
 
3.7%
1000 1
 
3.7%
320 1
 
3.7%
250 1
 
3.7%
241 1
 
3.7%
1500 1
 
3.7%
1800 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
24 1
3.7%
90 1
3.7%
130 1
3.7%
150 1
3.7%
160 2
7.4%
240 1
3.7%
241 1
3.7%
250 1
3.7%
300 1
3.7%
320 1
3.7%
ValueCountFrequency (%)
10000 1
3.7%
5000 1
3.7%
4500 1
3.7%
3212 1
3.7%
1800 1
3.7%
1784 1
3.7%
1500 1
3.7%
1340 1
3.7%
1000 1
3.7%
800 1
3.7%

Interactions

2023-12-12T21:58:06.855561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.291143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.585982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.947160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.396683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.669293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:07.062648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.506372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:58:06.764786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:58:09.347148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업명조성년도소재지면적(제곱미터)
연번1.0001.0001.0001.0000.598
사업명1.0001.0001.0001.0001.000
조성년도1.0001.0001.0001.0000.743
소재지1.0001.0001.0001.0001.000
면적(제곱미터)0.5981.0000.7431.0001.000
2023-12-12T21:58:09.445435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번조성년도면적(제곱미터)
연번1.0001.000-0.015
조성년도1.0001.0000.159
면적(제곱미터)-0.0150.1591.000

Missing values

2023-12-12T21:58:07.175894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:58:07.284922image/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

연번사업명조성년도소재지면적(제곱미터)
01고양동 쌈지공원2009고양시 덕양구 벽제관로 31(고양동 235-1번지)500
12내유동 쌈지공원2010고양시 덕양구 통일로 1258(내유동 966번지)150
23행주내동 쌈지공원2011고양시 덕양구 행주내동 645번지300
34행신역 주변 쌈지공원2012고양시 덕양구 행신동 810번지 외 2필지5000
45관산동 공릉천변 쌈지공원<NA>고양시 덕양구 관산동 172-3번지 외 1필지800
56대화동 킨텍스사거리 쌈지공원2013고양시 일산서구 중앙로 1601(대화동 2320번지)1784
67시정연수원 군철책 철거부지 쌈지공원<NA>고양시 덕양구 행주산성로 93-38(행주외동)3212
78내유동 버스정류장 쌈지공원 조성사업2015고양시 덕양구 내유동 1019-25번지130
89행주동 쌈지공원 조성사업<NA>고양시 덕양구 능곡로 45번길 15240
910보호수주변 쌈지공원 조성사업2016고양시 일산서구 구산동 413-26번지585
연번사업명조성년도소재지면적(제곱미터)
1718도내동 창릉천 주민휴식공원 조성사업<NA>고양시 덕양구 도내동 892-1번지 일원1800
1819관산동 고골교차로 쌈지공원 조성사업2020고양시 덕양구 내유동 산154-2번지 일원1500
1920원릉역 인근 유휴공간 쌈지공원 조성사업<NA>고양시 덕양구 주교동 26-2번지241
2021마을정원 조성사업(동산동 쌈지공원)<NA>고양시 덕양구 동산동 374번지 일원160
2122마을정원 조성사업(효자동 쌈지공원)2021고양시 덕양구 지축동 798번지 일원250
2223마을정원 조성사업(현천동 쌈지공원)<NA>고양시 덕양구 현천동 784번지 일원320
2324고양동 쌈지공원 조성사업(빈정1교 일원)2022고양시 덕양구 대자동 1177번지 일원1000
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