Overview

Dataset statistics

Number of variables7
Number of observations209
Missing cells4
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.2 KiB
Average record size in memory59.6 B

Variable types

Numeric3
Categorical1
Text2
DateTime1

Dataset

Description인천광역시 남동구 녹지현황에 대한 데이터로 연번, 녹지종류, 녹지명, 녹지위치, 면적, 조성면적 항목을 개방합니다.
URLhttps://www.data.go.kr/data/15067432/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 녹지종류High correlation
면적 is highly overall correlated with 녹지조성면적High correlation
녹지조성면적 is highly overall correlated with 면적High correlation
녹지종류 is highly overall correlated with 연번High correlation
녹지조성면적 has 4 (1.9%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:48:50.280255
Analysis finished2023-12-11 22:48:51.360116
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct209
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean105
Minimum1
Maximum209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T07:48:51.422269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.4
Q153
median105
Q3157
95-th percentile198.6
Maximum209
Range208
Interquartile range (IQR)104

Descriptive statistics

Standard deviation60.477268
Coefficient of variation (CV)0.57597399
Kurtosis-1.2
Mean105
Median Absolute Deviation (MAD)52
Skewness0
Sum21945
Variance3657.5
MonotonicityStrictly increasing
2023-12-12T07:48:51.764627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
158 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
140 1
 
0.5%
141 1
 
0.5%
Other values (199) 199
95.2%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
209 1
0.5%
208 1
0.5%
207 1
0.5%
206 1
0.5%
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%

녹지종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
완충녹지
153 
경관녹지
53 
연결녹지
 
3

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
완충녹지 153
73.2%
경관녹지 53
 
25.4%
연결녹지 3
 
1.4%

Length

2023-12-12T07:48:51.889425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:48:52.005567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완충녹지 153
73.2%
경관녹지 53
 
25.4%
연결녹지 3
 
1.4%

녹지명
Text

Distinct194
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T07:48:52.224756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14
Mean length7.6028708
Min length4

Characters and Unicode

Total characters1589
Distinct characters63
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

Unique179 ?
Unique (%)85.6%

Sample

1st row구월1녹지
2nd row구월2녹지
3rd row구월3녹지
4th row십정녹지
5th row만수1녹지
ValueCountFrequency (%)
소래논현 21
 
8.1%
서창 8
 
3.1%
1녹지 7
 
2.7%
구월보금자리 6
 
2.3%
2녹지 5
 
1.9%
3녹지 4
 
1.6%
지구단위계획 3
 
1.2%
6녹지 3
 
1.2%
소래구역 3
 
1.2%
장수구획 3
 
1.2%
Other values (173) 195
75.6%
2023-12-12T07:48:52.662491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 219
13.8%
녹 207
13.0%
2 134
 
8.4%
논 118
 
7.4%
현 118
 
7.4%
- 99
 
6.2%
1 73
 
4.6%
49
 
3.1%
3 34
 
2.1%
5 31
 
2.0%
Other values (53) 507
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1046
65.8%
Decimal Number 395
 
24.9%
Dash Punctuation 99
 
6.2%
Space Separator 49
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 219
20.9%
녹 207
19.8%
논 118
11.3%
현 118
11.3%
구 28
 
2.7%
창 26
 
2.5%
서 26
 
2.5%
소 25
 
2.4%
래 25
 
2.4%
도 22
 
2.1%
Other values (41) 232
22.2%
Decimal Number
ValueCountFrequency (%)
2 134
33.9%
1 73
18.5%
3 34
 
8.6%
5 31
 
7.8%
4 29
 
7.3%
6 28
 
7.1%
7 25
 
6.3%
8 15
 
3.8%
9 14
 
3.5%
0 12
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1046
65.8%
Common 543
34.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 219
20.9%
녹 207
19.8%
논 118
11.3%
현 118
11.3%
구 28
 
2.7%
창 26
 
2.5%
서 26
 
2.5%
소 25
 
2.4%
래 25
 
2.4%
도 22
 
2.1%
Other values (41) 232
22.2%
Common
ValueCountFrequency (%)
2 134
24.7%
- 99
18.2%
1 73
13.4%
49
 
9.0%
3 34
 
6.3%
5 31
 
5.7%
4 29
 
5.3%
6 28
 
5.2%
7 25
 
4.6%
8 15
 
2.8%
Other values (2) 26
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1046
65.8%
ASCII 543
34.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 219
20.9%
녹 207
19.8%
논 118
11.3%
현 118
11.3%
구 28
 
2.7%
창 26
 
2.5%
서 26
 
2.5%
소 25
 
2.4%
래 25
 
2.4%
도 22
 
2.1%
Other values (41) 232
22.2%
ASCII
ValueCountFrequency (%)
2 134
24.7%
- 99
18.2%
1 73
13.4%
49
 
9.0%
3 34
 
6.3%
5 31
 
5.7%
4 29
 
5.3%
6 28
 
5.2%
7 25
 
4.6%
8 15
 
2.8%
Other values (2) 26
 
4.8%

녹지위치
Text

Distinct207
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T07:48:53.062023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length19.205742
Min length17

Characters and Unicode

Total characters4014
Distinct characters39
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

Unique206 ?
Unique (%)98.6%

Sample

1st row인천광역시 남동구 구월동 1394-12일원
2nd row인천광역시 남동구 구월동 1254-7
3rd row인천광역시 남동구 만수동 909
4th row인천광역시 남동구 간석동762-2
5th row인천광역시 남동구 만수동 33일원
ValueCountFrequency (%)
인천광역시 209
25.1%
남동구 209
25.1%
논현동 124
14.9%
서창동 25
 
3.0%
도림동 17
 
2.0%
구월동 13
 
1.6%
만수동 8
 
1.0%
장수동 7
 
0.8%
간석동 3
 
0.4%
일원 3
 
0.4%
Other values (210) 215
25.8%
2023-12-12T07:48:53.676360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
624
15.5%
동 418
 
10.4%
구 222
 
5.5%
남 211
 
5.3%
인 209
 
5.2%
천 209
 
5.2%
광 209
 
5.2%
역 209
 
5.2%
시 209
 
5.2%
- 181
 
4.5%
Other values (29) 1313
32.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2339
58.3%
Decimal Number 867
 
21.6%
Space Separator 624
 
15.5%
Dash Punctuation 181
 
4.5%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 418
17.9%
구 222
9.5%
남 211
9.0%
인 209
8.9%
천 209
8.9%
광 209
8.9%
역 209
8.9%
시 209
8.9%
논 124
 
5.3%
현 124
 
5.3%
Other values (16) 195
8.3%
Decimal Number
ValueCountFrequency (%)
5 133
15.3%
6 122
14.1%
1 103
11.9%
7 90
10.4%
2 78
9.0%
9 78
9.0%
4 70
8.1%
3 67
7.7%
8 65
7.5%
0 61
7.0%
Space Separator
ValueCountFrequency (%)
624
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 181
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2339
58.3%
Common 1675
41.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 418
17.9%
구 222
9.5%
남 211
9.0%
인 209
8.9%
천 209
8.9%
광 209
8.9%
역 209
8.9%
시 209
8.9%
논 124
 
5.3%
현 124
 
5.3%
Other values (16) 195
8.3%
Common
ValueCountFrequency (%)
624
37.3%
- 181
 
10.8%
5 133
 
7.9%
6 122
 
7.3%
1 103
 
6.1%
7 90
 
5.4%
2 78
 
4.7%
9 78
 
4.7%
4 70
 
4.2%
3 67
 
4.0%
Other values (3) 129
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2339
58.3%
ASCII 1675
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
624
37.3%
- 181
 
10.8%
5 133
 
7.9%
6 122
 
7.3%
1 103
 
6.1%
7 90
 
5.4%
2 78
 
4.7%
9 78
 
4.7%
4 70
 
4.2%
3 67
 
4.0%
Other values (3) 129
 
7.7%
Hangul
ValueCountFrequency (%)
동 418
17.9%
구 222
9.5%
남 211
9.0%
인 209
8.9%
천 209
8.9%
광 209
8.9%
역 209
8.9%
시 209
8.9%
논 124
 
5.3%
현 124
 
5.3%
Other values (16) 195
8.3%

면적
Real number (ℝ)

HIGH CORRELATION 

Distinct208
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3798.1244
Minimum31.3
Maximum74448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T07:48:53.855324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.3
5-th percentile122.7
Q1533.4
median1381.6
Q33141.6
95-th percentile15397.54
Maximum74448
Range74416.7
Interquartile range (IQR)2608.2

Descriptive statistics

Standard deviation8738.6434
Coefficient of variation (CV)2.3007786
Kurtosis40.122367
Mean3798.1244
Median Absolute Deviation (MAD)997.1
Skewness5.7719088
Sum793808
Variance76363888
MonotonicityNot monotonic
2023-12-12T07:48:54.018632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
655.7 2
 
1.0%
4836.4 1
 
0.5%
429.0 1
 
0.5%
3461.0 1
 
0.5%
584.0 1
 
0.5%
8447.0 1
 
0.5%
6278.0 1
 
0.5%
5912.0 1
 
0.5%
5005.0 1
 
0.5%
2471.0 1
 
0.5%
Other values (198) 198
94.7%
ValueCountFrequency (%)
31.3 1
0.5%
34.6 1
0.5%
36.9 1
0.5%
45.2 1
0.5%
60.1 1
0.5%
65.4 1
0.5%
70.1 1
0.5%
83.1 1
0.5%
100.5 1
0.5%
103.0 1
0.5%
ValueCountFrequency (%)
74448.0 1
0.5%
72616.2 1
0.5%
42371.0 1
0.5%
32029.0 1
0.5%
27330.4 1
0.5%
21913.4 1
0.5%
19762.1 1
0.5%
18273.4 1
0.5%
17566.0 1
0.5%
16487.3 1
0.5%

녹지조성면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct204
Distinct (%)99.5%
Missing4
Missing (%)1.9%
Infinite0
Infinite (%)0.0%
Mean3797.2932
Minimum31.3
Maximum74448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2023-12-12T07:48:54.193836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31.3
5-th percentile122.3
Q1533.4
median1381.6
Q33133.9
95-th percentile15417.22
Maximum74448
Range74416.7
Interquartile range (IQR)2600.5

Descriptive statistics

Standard deviation8803.2268
Coefficient of variation (CV)2.31829
Kurtosis39.714382
Mean3797.2932
Median Absolute Deviation (MAD)992.4
Skewness5.7556823
Sum778445.1
Variance77496803
MonotonicityNot monotonic
2023-12-12T07:48:54.328288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
655.7 2
 
1.0%
2502.0 1
 
0.5%
3734.0 1
 
0.5%
3458.0 1
 
0.5%
3461.0 1
 
0.5%
584.0 1
 
0.5%
8447.0 1
 
0.5%
6278.0 1
 
0.5%
5912.0 1
 
0.5%
5005.0 1
 
0.5%
Other values (194) 194
92.8%
(Missing) 4
 
1.9%
ValueCountFrequency (%)
31.3 1
0.5%
34.6 1
0.5%
36.9 1
0.5%
45.2 1
0.5%
60.1 1
0.5%
65.4 1
0.5%
70.1 1
0.5%
83.1 1
0.5%
100.5 1
0.5%
103.0 1
0.5%
ValueCountFrequency (%)
74448.0 1
0.5%
72616.2 1
0.5%
42371.0 1
0.5%
32029.0 1
0.5%
27330.4 1
0.5%
21913.4 1
0.5%
19762.1 1
0.5%
18273.4 1
0.5%
17566.0 1
0.5%
16487.3 1
0.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
Minimum2023-05-19 00:00:00
Maximum2023-05-19 00:00:00
2023-12-12T07:48:54.458709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:54.538913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T07:48:50.936665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:50.471030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:50.682688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:51.009177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:50.532887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:50.753628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:51.103931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:50.608247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:48:50.860684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:48:54.620788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번녹지종류면적녹지조성면적
연번1.0000.7940.0000.000
녹지종류0.7941.0000.0000.000
면적0.0000.0001.0001.000
녹지조성면적0.0000.0001.0001.000
2023-12-12T07:48:54.721058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번면적녹지조성면적녹지종류
연번1.0000.0970.1070.670
면적0.0971.0001.0000.000
녹지조성면적0.1071.0001.0000.000
녹지종류0.6700.0000.0001.000

Missing values

2023-12-12T07:48:51.216712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:48:51.321241image/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

연번녹지종류녹지명녹지위치면적녹지조성면적데이터기준일자
01완충녹지구월1녹지인천광역시 남동구 구월동 1394-12일원4836.44836.42023-05-19
12완충녹지구월2녹지인천광역시 남동구 구월동 1254-7306.2306.22023-05-19
23완충녹지구월3녹지인천광역시 남동구 만수동 909623.8623.82023-05-19
34완충녹지십정녹지인천광역시 남동구 간석동762-23602.03602.02023-05-19
45완충녹지만수1녹지인천광역시 남동구 만수동 33일원13220.813220.82023-05-19
56완충녹지만수2녹지인천광역시 남동구 만수동 1005-83569.33569.32023-05-19
67완충녹지만수3녹지인천광역시 남동구 만수동 1007-4일원1935.31935.32023-05-19
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