Overview

Dataset statistics

Number of variables6
Number of observations1941
Missing cells0
Missing cells (%)0.0%
Duplicate rows1
Duplicate rows (%)0.1%
Total size in memory93.0 KiB
Average record size in memory49.1 B

Variable types

Categorical3
Text2
Numeric1

Dataset

Description경상북도 내 시군구별 녹지에 대한 데이터로 분류별(완충녹지, 경관녹지) 녹지의 시설명, 위치, 결정면적 등의 자료가 있습니다.
Author경상북도
URLhttps://www.data.go.kr/data/15112544/fileData.do

Alerts

대분류 has constant value ""Constant
Dataset has 1 (0.1%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-14 13:17:23.920303
Analysis finished2024-03-14 13:17:25.271997
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

Distinct22
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
구미시
365 
포항시
278 
경산시
219 
경주시
173 
안동시
142 
Other values (17)
764 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
구미시 365
18.8%
포항시 278
14.3%
경산시 219
11.3%
경주시 173
8.9%
안동시 142
 
7.3%
김천시 108
 
5.6%
고령군 83
 
4.3%
칠곡군 74
 
3.8%
예천군 73
 
3.8%
영주시 67
 
3.5%
Other values (12) 359
18.5%

Length

2024-03-14T22:17:25.469405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
구미시 365
18.8%
포항시 278
14.3%
경산시 219
11.3%
경주시 173
8.9%
안동시 142
 
7.3%
김천시 108
 
5.6%
고령군 83
 
4.3%
칠곡군 74
 
3.8%
예천군 73
 
3.8%
영주시 67
 
3.5%
Other values (12) 359
18.5%

대분류
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
녹지
1941 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
녹지 1941
100.0%

Length

2024-03-14T22:17:25.826355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:17:26.132502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
녹지 1941
100.0%

중분류
Categorical

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
완충녹지
1288 
경관녹지
637 
연결녹지
 
16

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 1288
66.4%
경관녹지 637
32.8%
연결녹지 16
 
0.8%

Length

2024-03-14T22:17:26.444865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:17:26.762870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
완충녹지 1288
66.4%
경관녹지 637
32.8%
연결녹지 16
 
0.8%

시설명
Text

Distinct1322
Distinct (%)68.1%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2024-03-14T22:17:27.684528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length18
Mean length8.0814013
Min length2

Characters and Unicode

Total characters15686
Distinct characters202
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1184 ?
Unique (%)61.0%

Sample

1st row그린10호 녹지
2nd row그린11호 녹지
3rd row그린1호 녹지
4th row그린2호 녹지
5th row그린3호 녹지
ValueCountFrequency (%)
녹지 322
 
13.1%
완충녹지 113
 
4.6%
지구단위 52
 
2.1%
사동2택지지구내 49
 
2.0%
경관녹지 42
 
1.7%
일반산업단지내 31
 
1.3%
철도변 25
 
1.0%
공업지역변 22
 
0.9%
주왕산 16
 
0.7%
백천지구내 15
 
0.6%
Other values (1288) 1773
72.1%
2024-03-14T22:17:29.057100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 2356
 
15.0%
녹 1834
 
11.7%
900
 
5.7%
1 723
 
4.6%
완 634
 
4.0%
충 631
 
4.0%
경 458
 
2.9%
관 440
 
2.8%
2 432
 
2.8%
( 390
 
2.5%
Other values (192) 6888
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11148
71.1%
Decimal Number 2651
 
16.9%
Space Separator 900
 
5.7%
Open Punctuation 390
 
2.5%
Close Punctuation 390
 
2.5%
Dash Punctuation 185
 
1.2%
Other Punctuation 22
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2356
21.1%
녹 1834
16.5%
완 634
 
5.7%
충 631
 
5.7%
경 458
 
4.1%
관 440
 
3.9%
단 290
 
2.6%
산 248
 
2.2%
변 240
 
2.2%
구 210
 
1.9%
Other values (177) 3807
34.1%
Decimal Number
ValueCountFrequency (%)
1 723
27.3%
2 432
16.3%
3 306
11.5%
4 251
 
9.5%
5 225
 
8.5%
6 169
 
6.4%
7 152
 
5.7%
9 135
 
5.1%
8 129
 
4.9%
0 129
 
4.9%
Space Separator
ValueCountFrequency (%)
900
100.0%
Open Punctuation
ValueCountFrequency (%)
( 390
100.0%
Close Punctuation
ValueCountFrequency (%)
) 390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 185
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11148
71.1%
Common 4538
28.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2356
21.1%
녹 1834
16.5%
완 634
 
5.7%
충 631
 
5.7%
경 458
 
4.1%
관 440
 
3.9%
단 290
 
2.6%
산 248
 
2.2%
변 240
 
2.2%
구 210
 
1.9%
Other values (177) 3807
34.1%
Common
ValueCountFrequency (%)
900
19.8%
1 723
15.9%
2 432
9.5%
( 390
8.6%
) 390
8.6%
3 306
 
6.7%
4 251
 
5.5%
5 225
 
5.0%
- 185
 
4.1%
6 169
 
3.7%
Other values (5) 567
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11148
71.1%
ASCII 4538
28.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 2356
21.1%
녹 1834
16.5%
완 634
 
5.7%
충 631
 
5.7%
경 458
 
4.1%
관 440
 
3.9%
단 290
 
2.6%
산 248
 
2.2%
변 240
 
2.2%
구 210
 
1.9%
Other values (177) 3807
34.1%
ASCII
ValueCountFrequency (%)
900
19.8%
1 723
15.9%
2 432
9.5%
( 390
8.6%
) 390
8.6%
3 306
 
6.7%
4 251
 
5.5%
5 225
 
5.0%
- 185
 
4.1%
6 169
 
3.7%
Other values (5) 567
12.5%

위치
Text

Distinct1841
Distinct (%)94.8%
Missing0
Missing (%)0.0%
Memory size15.3 KiB
2024-03-14T22:17:30.083462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length13.427099
Min length3

Characters and Unicode

Total characters26062
Distinct characters265
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1758 ?
Unique (%)90.6%

Sample

1st row연일읍 우복리 산54
2nd row연일읍 우복리 106-3
3rd row연일읍 우복리 산19
4th row연일읍 우복리 283
5th row연일읍 우복리 142-8
ValueCountFrequency (%)
일원 774
 
13.4%
해평면 79
 
1.4%
풍천면 77
 
1.3%
산동면 63
 
1.1%
56
 
1.0%
도양리 48
 
0.8%
사동 41
 
0.7%
다산면 41
 
0.7%
진량읍 38
 
0.7%
도중리 33
 
0.6%
Other values (2291) 4539
78.4%
2024-03-14T22:17:31.788408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4036
 
15.5%
1 1368
 
5.2%
리 1304
 
5.0%
- 1173
 
4.5%
원 988
 
3.8%
일 982
 
3.8%
2 866
 
3.3%
3 790
 
3.0%
동 780
 
3.0%
산 694
 
2.7%
Other values (255) 13081
50.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13638
52.3%
Decimal Number 6765
26.0%
Space Separator 4036
 
15.5%
Dash Punctuation 1173
 
4.5%
Open Punctuation 124
 
0.5%
Close Punctuation 123
 
0.5%
Other Punctuation 107
 
0.4%
Math Symbol 88
 
0.3%
Uppercase Letter 5
 
< 0.1%
Other Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 1304
 
9.6%
원 988
 
7.2%
일 982
 
7.2%
동 780
 
5.7%
산 694
 
5.1%
면 650
 
4.8%
지 585
 
4.3%
번 397
 
2.9%
읍 279
 
2.0%
대 253
 
1.9%
Other values (232) 6726
49.3%
Decimal Number
ValueCountFrequency (%)
1 1368
20.2%
2 866
12.8%
3 790
11.7%
4 639
9.4%
6 617
9.1%
5 572
8.5%
8 540
 
8.0%
7 523
 
7.7%
9 427
 
6.3%
0 423
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
C 1
 
20.0%
I 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
, 106
99.1%
· 1
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 83
94.3%
∼ 5
 
5.7%
Other Number
ValueCountFrequency (%)
① 2
66.7%
② 1
33.3%
Space Separator
ValueCountFrequency (%)
4036
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1173
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13637
52.3%
Common 12419
47.7%
Latin 5
 
< 0.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 1304
 
9.6%
원 988
 
7.2%
일 982
 
7.2%
동 780
 
5.7%
산 694
 
5.1%
면 650
 
4.8%
지 585
 
4.3%
번 397
 
2.9%
읍 279
 
2.0%
대 253
 
1.9%
Other values (231) 6725
49.3%
Common
ValueCountFrequency (%)
4036
32.5%
1 1368
 
11.0%
- 1173
 
9.4%
2 866
 
7.0%
3 790
 
6.4%
4 639
 
5.1%
6 617
 
5.0%
5 572
 
4.6%
8 540
 
4.3%
7 523
 
4.2%
Other values (10) 1295
 
10.4%
Latin
ValueCountFrequency (%)
B 3
60.0%
C 1
 
20.0%
I 1
 
20.0%
Han
ValueCountFrequency (%)
平 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13637
52.3%
ASCII 12415
47.6%
Math Operators 5
 
< 0.1%
Enclosed Alphanum 3
 
< 0.1%
CJK 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4036
32.5%
1 1368
 
11.0%
- 1173
 
9.4%
2 866
 
7.0%
3 790
 
6.4%
4 639
 
5.1%
6 617
 
5.0%
5 572
 
4.6%
8 540
 
4.3%
7 523
 
4.2%
Other values (9) 1291
 
10.4%
Hangul
ValueCountFrequency (%)
리 1304
 
9.6%
원 988
 
7.2%
일 982
 
7.2%
동 780
 
5.7%
산 694
 
5.1%
면 650
 
4.8%
지 585
 
4.3%
번 397
 
2.9%
읍 279
 
2.0%
대 253
 
1.9%
Other values (231) 6725
49.3%
Math Operators
ValueCountFrequency (%)
∼ 5
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
① 2
66.7%
② 1
33.3%
CJK
ValueCountFrequency (%)
平 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

결정면적
Real number (ℝ)

Distinct1689
Distinct (%)87.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7439.0433
Minimum7
Maximum215310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.2 KiB
2024-03-14T22:17:32.204082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile180
Q1875
median2299
Q36853
95-th percentile32562
Maximum215310
Range215303
Interquartile range (IQR)5978

Descriptive statistics

Standard deviation15823.453
Coefficient of variation (CV)2.1270818
Kurtosis49.149683
Mean7439.0433
Median Absolute Deviation (MAD)1811
Skewness5.873447
Sum14439183
Variance2.5038168 × 108
MonotonicityNot monotonic
2024-03-14T22:17:32.625893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
860 5
 
0.3%
686 4
 
0.2%
650 4
 
0.2%
248 4
 
0.2%
820 4
 
0.2%
795 4
 
0.2%
720 4
 
0.2%
250 4
 
0.2%
553 3
 
0.2%
520 3
 
0.2%
Other values (1679) 1902
98.0%
ValueCountFrequency (%)
7 1
 
0.1%
10 1
 
0.1%
13 1
 
0.1%
15 1
 
0.1%
22 1
 
0.1%
25 1
 
0.1%
30 1
 
0.1%
38 1
 
0.1%
40 3
0.2%
42 1
 
0.1%
ValueCountFrequency (%)
215310 1
0.1%
190472 1
0.1%
170397 1
0.1%
157784 1
0.1%
150129 1
0.1%
143854 1
0.1%
122169 1
0.1%
120887 1
0.1%
116900 1
0.1%
109940 1
0.1%

Interactions

2024-03-14T22:17:24.450932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T22:17:32.886905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구중분류결정면적
시군구1.0000.5090.000
중분류0.5091.0000.000
결정면적0.0000.0001.000
2024-03-14T22:17:33.127199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구중분류
시군구1.0000.308
중분류0.3081.000
2024-03-14T22:17:33.358370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
결정면적시군구중분류
결정면적1.0000.0000.000
시군구0.0001.0000.308
중분류0.0000.3081.000

Missing values

2024-03-14T22:17:24.783541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:17:25.134978image/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

시군구대분류중분류시설명위치결정면적
0포항시녹지완충녹지그린10호 녹지연일읍 우복리 산5421207
1포항시녹지완충녹지그린11호 녹지연일읍 우복리 106-32994
2포항시녹지완충녹지그린1호 녹지연일읍 우복리 산1923897
3포항시녹지완충녹지그린2호 녹지연일읍 우복리 283880
4포항시녹지완충녹지그린3호 녹지연일읍 우복리 142-81156
5포항시녹지완충녹지그린4호 녹지연일읍 우복리 460961
6포항시녹지완충녹지그린5호 녹지연일읍 우복리 산4246868
7포항시녹지완충녹지그린6호 녹지연일읍 우복리 4409010
8포항시녹지완충녹지그린7호 녹지연일읍 우복리 3601300
9포항시녹지완충녹지그린8호 녹지연일읍 우복리 3242485
시군구대분류중분류시설명위치결정면적
1931울릉군녹지경관녹지경관녹지5남양리 산22 일원(남양지구)5696
1932울릉군녹지경관녹지경관녹지5천부리 666전 일원(천부지구)1398
1933울릉군녹지경관녹지경관녹지5현포리 537-4전 일원(현포지구)161
1934울릉군녹지경관녹지경관녹지6태하리 561-1전 일원(태하지구)335
1935울릉군녹지경관녹지경관녹지6남서리 548219
1936울릉군녹지경관녹지경관녹지7태하리 695천 일원(태하지구)834
1937울릉군녹지경관녹지경관녹지7현포리 553-6전 일원(현포지구)4838
1938울릉군녹지경관녹지경관녹지8남서리 66전 일원(남서남양지구)453
1939울릉군녹지경관녹지경관녹지9남서리 91임 일원(남서남양지구)5069
1940울릉군녹지경관녹지경관녹지9현포리 494전 일원(현포지구)2197

Duplicate rows

Most frequently occurring

시군구대분류중분류시설명위치결정면적# duplicates
0경주시녹지경관녹지숲머리1 경관녹지보문동 40-27 ~ 보문동 25-1351702