Overview

Dataset statistics

Number of variables7
Number of observations178
Missing cells161
Missing cells (%)12.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory10.2 KiB
Average record size in memory58.7 B

Variable types

Numeric2
Categorical2
Text3

Dataset

Description충청북도 청주시 미조성공원에 대한 공원명, 공원위치, 공원면적, 조성면적, 공원구분 등을 나타내는 현황입니다.
URLhttps://www.data.go.kr/data/15066941/fileData.do

Alerts

연번 is highly overall correlated with 공원구분 and 1 other fieldsHigh correlation
면적 is highly overall correlated with 공원구분High correlation
공원구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
조성여부 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
조성면적 has 161 (90.4%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:13:11.939195
Analysis finished2023-12-12 17:13:12.717813
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct178
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.5
Minimum1
Maximum178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T02:13:12.783031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.85
Q145.25
median89.5
Q3133.75
95-th percentile169.15
Maximum178
Range177
Interquartile range (IQR)88.5

Descriptive statistics

Standard deviation51.528309
Coefficient of variation (CV)0.5757353
Kurtosis-1.2
Mean89.5
Median Absolute Deviation (MAD)44.5
Skewness0
Sum15931
Variance2655.1667
MonotonicityStrictly increasing
2023-12-13T02:13:12.913986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
135 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
121 1
 
0.6%
122 1
 
0.6%
Other values (168) 168
94.4%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
178 1
0.6%
177 1
0.6%
176 1
0.6%
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%

공원구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)5.1%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
소공원
58 
근린공원
41 
어린이공원
38 
수변공원
18 
가로공원
10 
Other values (4)
13 

Length

Max length5
Median length4
Mean length3.8876404
Min length3

Unique

Unique2 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
소공원 58
32.6%
근린공원 41
23.0%
어린이공원 38
21.3%
수변공원 18
 
10.1%
가로공원 10
 
5.6%
역사공원 6
 
3.4%
문화공원 5
 
2.8%
묘지공원 1
 
0.6%
생태공원 1
 
0.6%

Length

2023-12-13T02:13:13.036803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:13:13.154236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소공원 58
32.6%
근린공원 41
23.0%
어린이공원 38
21.3%
수변공원 18
 
10.1%
가로공원 10
 
5.6%
역사공원 6
 
3.4%
문화공원 5
 
2.8%
묘지공원 1
 
0.6%
생태공원 1
 
0.6%

공 원 명
Text

Distinct177
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T02:13:13.390711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length9.005618
Min length2

Characters and Unicode

Total characters1603
Distinct characters169
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

Unique176 ?
Unique (%)98.9%

Sample

1st row195호
2nd row197호
3rd row198호
4th row사천공원
5th row수동공원(52호)
ValueCountFrequency (%)
현도일반산업단지계획 8
 
3.5%
소공원(남청주 5
 
2.2%
공급촉진지구 4
 
1.7%
지정 4
 
1.7%
기업형임대주택 4
 
1.7%
테크노폴리스 3
 
1.3%
일반산업단지 3
 
1.3%
지역 3
 
1.3%
소공원(청주지북 2
 
0.9%
가로공원 2
 
0.9%
Other values (188) 191
83.4%
2023-12-13T02:13:13.757165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 130
 
8.1%
원 127
 
7.9%
( 75
 
4.7%
1 75
 
4.7%
) 75
 
4.7%
호 63
 
3.9%
2 56
 
3.5%
53
 
3.3%
지 48
 
3.0%
소 37
 
2.3%
Other values (159) 864
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1064
66.4%
Decimal Number 335
 
20.9%
Open Punctuation 75
 
4.7%
Close Punctuation 75
 
4.7%
Space Separator 53
 
3.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 130
 
12.2%
원 127
 
11.9%
호 63
 
5.9%
지 48
 
4.5%
소 37
 
3.5%
산 30
 
2.8%
주 26
 
2.4%
업 26
 
2.4%
단 23
 
2.2%
청 22
 
2.1%
Other values (145) 532
50.0%
Decimal Number
ValueCountFrequency (%)
1 75
22.4%
2 56
16.7%
5 36
10.7%
4 30
 
9.0%
7 30
 
9.0%
9 24
 
7.2%
3 22
 
6.6%
0 22
 
6.6%
8 21
 
6.3%
6 19
 
5.7%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1064
66.4%
Common 539
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 130
 
12.2%
원 127
 
11.9%
호 63
 
5.9%
지 48
 
4.5%
소 37
 
3.5%
산 30
 
2.8%
주 26
 
2.4%
업 26
 
2.4%
단 23
 
2.2%
청 22
 
2.1%
Other values (145) 532
50.0%
Common
ValueCountFrequency (%)
( 75
13.9%
1 75
13.9%
) 75
13.9%
2 56
10.4%
53
9.8%
5 36
6.7%
4 30
 
5.6%
7 30
 
5.6%
9 24
 
4.5%
3 22
 
4.1%
Other values (4) 63
11.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1064
66.4%
ASCII 539
33.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 130
 
12.2%
원 127
 
11.9%
호 63
 
5.9%
지 48
 
4.5%
소 37
 
3.5%
산 30
 
2.8%
주 26
 
2.4%
업 26
 
2.4%
단 23
 
2.2%
청 22
 
2.1%
Other values (145) 532
50.0%
ASCII
ValueCountFrequency (%)
( 75
13.9%
1 75
13.9%
) 75
13.9%
2 56
10.4%
53
9.8%
5 36
6.7%
4 30
 
5.6%
7 30
 
5.6%
9 24
 
4.5%
3 22
 
4.1%
Other values (4) 63
11.7%

위 치
Text

Distinct165
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2023-12-13T02:13:13.981640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length31
Mean length19.522472
Min length5

Characters and Unicode

Total characters3475
Distinct characters137
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

Unique164 ?
Unique (%)92.1%

Sample

1st row흥덕구 문암동 산21 일원(청주 테크노폴리스 일반산업단지 지역)
2nd row흥덕구 송절동 산35-12일원(청주 테크노폴리스 일반산업단지 지역)
3rd row흥덕구문암동 산35 일원(청주 테크노폴리스 일반산업단지 지역)
4th row청원구 사천동 225-75일원
5th row상당구 수동 81-245일원
ValueCountFrequency (%)
일원 77
 
10.7%
흥덕구 48
 
6.7%
상당구 37
 
5.1%
청원구 29
 
4.0%
서원구 29
 
4.0%
현도면 18
 
2.5%
오송읍 16
 
2.2%
방서동 14
 
1.9%
방서지구 14
 
1.9%
도시개발구역내 14
 
1.9%
Other values (268) 425
58.9%
2023-12-13T02:13:14.388436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
549
 
15.8%
구 199
 
5.7%
원 189
 
5.4%
1 134
 
3.9%
일 133
 
3.8%
- 116
 
3.3%
동 106
 
3.1%
2 104
 
3.0%
리 99
 
2.8%
지 95
 
2.7%
Other values (127) 1751
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2101
60.5%
Decimal Number 605
 
17.4%
Space Separator 549
 
15.8%
Dash Punctuation 116
 
3.3%
Close Punctuation 52
 
1.5%
Open Punctuation 52
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 199
 
9.5%
원 189
 
9.0%
일 133
 
6.3%
동 106
 
5.0%
리 99
 
4.7%
지 95
 
4.5%
산 70
 
3.3%
오 69
 
3.3%
서 58
 
2.8%
덕 50
 
2.4%
Other values (113) 1033
49.2%
Decimal Number
ValueCountFrequency (%)
1 134
22.1%
2 104
17.2%
3 66
10.9%
5 59
9.8%
6 57
9.4%
4 48
 
7.9%
9 40
 
6.6%
8 35
 
5.8%
7 31
 
5.1%
0 31
 
5.1%
Space Separator
ValueCountFrequency (%)
549
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2101
60.5%
Common 1374
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 199
 
9.5%
원 189
 
9.0%
일 133
 
6.3%
동 106
 
5.0%
리 99
 
4.7%
지 95
 
4.5%
산 70
 
3.3%
오 69
 
3.3%
서 58
 
2.8%
덕 50
 
2.4%
Other values (113) 1033
49.2%
Common
ValueCountFrequency (%)
549
40.0%
1 134
 
9.8%
- 116
 
8.4%
2 104
 
7.6%
3 66
 
4.8%
5 59
 
4.3%
6 57
 
4.1%
) 52
 
3.8%
( 52
 
3.8%
4 48
 
3.5%
Other values (4) 137
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2101
60.5%
ASCII 1374
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
549
40.0%
1 134
 
9.8%
- 116
 
8.4%
2 104
 
7.6%
3 66
 
4.8%
5 59
 
4.3%
6 57
 
4.1%
) 52
 
3.8%
( 52
 
3.8%
4 48
 
3.5%
Other values (4) 137
 
10.0%
Hangul
ValueCountFrequency (%)
구 199
 
9.5%
원 189
 
9.0%
일 133
 
6.3%
동 106
 
5.0%
리 99
 
4.7%
지 95
 
4.5%
산 70
 
3.3%
오 69
 
3.3%
서 58
 
2.8%
덕 50
 
2.4%
Other values (113) 1033
49.2%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct172
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71538.87
Minimum247
Maximum4158288.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2023-12-13T02:13:14.524319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum247
5-th percentile585.8
Q11524.25
median2975.5
Q315896.5
95-th percentile198730.65
Maximum4158288.1
Range4158041.1
Interquartile range (IQR)14372.25

Descriptive statistics

Standard deviation388860.1
Coefficient of variation (CV)5.4356478
Kurtosis80.287925
Mean71538.87
Median Absolute Deviation (MAD)2065.5
Skewness8.572679
Sum12733919
Variance1.5121218 × 1011
MonotonicityNot monotonic
2023-12-13T02:13:14.700952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1500.0 4
 
2.2%
2000.0 3
 
1.7%
1530.0 2
 
1.1%
77470.0 1
 
0.6%
662.0 1
 
0.6%
526.0 1
 
0.6%
587.0 1
 
0.6%
6861.0 1
 
0.6%
3808.0 1
 
0.6%
5919.0 1
 
0.6%
Other values (162) 162
91.0%
ValueCountFrequency (%)
247.0 1
0.6%
314.0 1
0.6%
330.0 1
0.6%
365.1 1
0.6%
485.0 1
0.6%
496.0 1
0.6%
526.0 1
0.6%
539.0 1
0.6%
579.0 1
0.6%
587.0 1
0.6%
ValueCountFrequency (%)
4158288.1 1
0.6%
2636456.0 1
0.6%
1407811.8 1
0.6%
957631.0 1
0.6%
389663.2 1
0.6%
278410.0 1
0.6%
239608.2 1
0.6%
209416.0 1
0.6%
203177.0 1
0.6%
197946.0 1
0.6%

조성면적
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing161
Missing (%)90.4%
Memory size1.5 KiB
2023-12-13T02:13:14.844501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.5294118
Min length3

Characters and Unicode

Total characters77
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)88.2%

Sample

1st row6896
2nd row6424
3rd row51192
4th row21962
5th row8986
ValueCountFrequency (%)
2
 
11.8%
6896 1
 
5.9%
6424 1
 
5.9%
51192 1
 
5.9%
21962 1
 
5.9%
8986 1
 
5.9%
10581 1
 
5.9%
12918 1
 
5.9%
5070 1
 
5.9%
423441 1
 
5.9%
Other values (6) 6
35.3%
2023-12-13T02:13:15.433485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.2%
2 10
13.0%
7 8
10.4%
4 7
9.1%
0 7
9.1%
9 6
7.8%
6 5
 
6.5%
8 5
 
6.5%
5 5
 
6.5%
4
 
5.2%
Other values (2) 6
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
92.2%
Space Separator 4
 
5.2%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
19.7%
2 10
14.1%
7 8
11.3%
4 7
9.9%
0 7
9.9%
9 6
8.5%
6 5
 
7.0%
8 5
 
7.0%
5 5
 
7.0%
3 4
 
5.6%
Space Separator
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.2%
2 10
13.0%
7 8
10.4%
4 7
9.1%
0 7
9.1%
9 6
7.8%
6 5
 
6.5%
8 5
 
6.5%
5 5
 
6.5%
4
 
5.2%
Other values (2) 6
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
18.2%
2 10
13.0%
7 8
10.4%
4 7
9.1%
0 7
9.1%
9 6
7.8%
6 5
 
6.5%
8 5
 
6.5%
5 5
 
6.5%
4
 
5.2%
Other values (2) 6
7.8%

조성여부
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
미조성
123 
미조성
41 
부분조성
14 

Length

Max length5
Median length3
Mean length3.5393258
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미조성
2nd row미조성
3rd row미조성
4th row부분조성
5th row부분조성

Common Values

ValueCountFrequency (%)
미조성 123
69.1%
미조성 41
 
23.0%
부분조성 14
 
7.9%

Length

2023-12-13T02:13:15.604821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:13:15.753685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미조성 164
92.1%
부분조성 14
 
7.9%

Interactions

2023-12-13T02:13:12.395508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:12.255368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:12.478312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:13:12.323468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:13:15.845897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번공원구분면적조성면적조성여부
연번1.0000.8600.0000.0000.739
공원구분0.8601.0000.8471.0000.913
면적0.0000.8471.0001.0000.159
조성면적0.0001.0001.0001.0001.000
조성여부0.7390.9130.1591.0001.000
2023-12-13T02:13:15.958371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공원구분조성여부
공원구분1.0000.648
조성여부0.6481.000
2023-12-13T02:13:16.077352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적공원구분조성여부
연번1.000-0.2940.6200.594
면적-0.2941.0000.6890.120
공원구분0.6200.6891.0000.648
조성여부0.5940.1200.6481.000

Missing values

2023-12-13T02:13:12.576240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:13:12.674065image/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

연번공원구분공 원 명위 치면적조성면적조성여부
01근린공원195호흥덕구 문암동 산21 일원(청주 테크노폴리스 일반산업단지 지역)77470.0<NA>미조성
12근린공원197호흥덕구 송절동 산35-12일원(청주 테크노폴리스 일반산업단지 지역)123412.0<NA>미조성
23근린공원198호흥덕구문암동 산35 일원(청주 테크노폴리스 일반산업단지 지역)32077.0<NA>미조성
34근린공원사천공원청원구 사천동 225-75일원31799.06896부분조성
45근린공원수동공원(52호)상당구 수동 81-245일원21816.06424부분조성
56근린공원홍골공원(94호)흥덕구 가경동 산91-7번지 일원(가경노인복지마을 인근)203177.051192부분조성
67근린공원영운공원상당구 영운동 산62번지 일원119072.0<NA>미조성
78근린공원당산공원상당구 대성동 109-4번지 일원68090.021962미조성
89근린공원복대공원흥덕구 복대동 산42-127092.0<NA>미조성
910근린공원월명공원흥덕구 봉명동 산19-5147771.0<NA>미조성
연번공원구분공 원 명위 치면적조성면적조성여부
168169가로공원로드파크 가로공원상당구 용정동 산110-8 일원21072.019477부분조성
169170가로공원공원201흥덕구 오승읍 오송리 167-2 일원(오송역세권)5707.0<NA>미조성
170171가로공원공원202흥덕구 오승읍 오송리 53-3 일원(오송역세권)1928.0<NA>미조성
171172가로공원공원203흥덕구 오승읍 오송리 109-12 일원(오송역세권)1785.0<NA>미조성
172173가로공원공원204흥덕구 오승읍 궁평리 369-2 일원(오송역세권)1262.0<NA>미조성
173174가로공원공원205흥덕구 오승읍 봉산리 42-10 일원(오송역세권)1300.0<NA>미조성
174175가로공원공원206흥덕구 오승읍 궁평리 350-3 일원(오송역세권)1654.0<NA>미조성
175176가로공원공원207흥덕구 오승읍 궁평리 385-6 일원(오송역세권)2690.0<NA>미조성
176177가로공원215호 공원상당구 수동 81-71 일원485.0<NA>미조성
177178생태공원미호천미호천일원2636456.0<NA>미조성