Overview

Dataset statistics

Number of variables15
Number of observations6532
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory778.4 KiB
Average record size in memory122.0 B

Variable types

Text4
Categorical8
Boolean1
Numeric2

Dataset

Description의정부시 공원시설물 정보로 관리번호, 공원명, 위치구분, 도로명주소, 지번주소, 시설종류, 시설명, 관리상태, 수리필요, 위치설명, 위도, 경도, 행정동, 관리기관명, 데이터기준일을 확인할 수 있습니다.
Author경기도 의정부시
URLhttps://www.data.go.kr/data/15110062/fileData.do

Alerts

관리기관명 has constant value ""Constant
데이터 기준일 has constant value ""Constant
수리필요 유무 is highly overall correlated with 관리상태High correlation
관리상태 is highly overall correlated with 수리필요 유무High correlation
위치구분 is highly overall correlated with 도로명주소High correlation
도로명주소 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
위도 is highly overall correlated with 도로명주소 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 도로명주소 and 1 other fieldsHigh correlation
행정동 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
도로명주소 is highly imbalanced (52.3%)Imbalance
관리상태 is highly imbalanced (86.7%)Imbalance
수리필요 유무 is highly imbalanced (95.2%)Imbalance

Reproduction

Analysis started2023-12-11 23:59:39.868567
Analysis finished2023-12-11 23:59:42.075688
Duration2.21 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

Distinct6531
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2023-12-12T08:59:42.290768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length16
Mean length16
Min length16

Characters and Unicode

Total characters104512
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6530 ?
Unique (%)> 99.9%

Sample

1st row41150-00001-0001
2nd row41150-00001-0002
3rd row41150-00001-0003
4th row41150-00001-0004
5th row41150-00001-0005
ValueCountFrequency (%)
41150-00035-0034 2
 
< 0.1%
41150-00061-0002 1
 
< 0.1%
41150-00061-0011 1
 
< 0.1%
41150-00061-0010 1
 
< 0.1%
41150-00061-0009 1
 
< 0.1%
41150-00061-0008 1
 
< 0.1%
41150-00061-0007 1
 
< 0.1%
41150-00061-0006 1
 
< 0.1%
41150-00061-0005 1
 
< 0.1%
41150-00061-0004 1
 
< 0.1%
Other values (6521) 6521
99.8%
2023-12-12T08:59:42.732596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 41356
39.6%
1 19006
18.2%
- 13064
 
12.5%
5 8793
 
8.4%
4 8666
 
8.3%
2 3469
 
3.3%
3 2501
 
2.4%
6 2222
 
2.1%
8 2001
 
1.9%
7 1782
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91448
87.5%
Dash Punctuation 13064
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 41356
45.2%
1 19006
20.8%
5 8793
 
9.6%
4 8666
 
9.5%
2 3469
 
3.8%
3 2501
 
2.7%
6 2222
 
2.4%
8 2001
 
2.2%
7 1782
 
1.9%
9 1652
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
- 13064
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 104512
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 41356
39.6%
1 19006
18.2%
- 13064
 
12.5%
5 8793
 
8.4%
4 8666
 
8.3%
2 3469
 
3.3%
3 2501
 
2.4%
6 2222
 
2.1%
8 2001
 
1.9%
7 1782
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 104512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 41356
39.6%
1 19006
18.2%
- 13064
 
12.5%
5 8793
 
8.4%
4 8666
 
8.3%
2 3469
 
3.3%
3 2501
 
2.4%
6 2222
 
2.1%
8 2001
 
1.9%
7 1782
 
1.7%

공원명
Text

Distinct120
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2023-12-12T08:59:42.974467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length7.8118494
Min length5

Characters and Unicode

Total characters51027
Distinct characters167
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

Unique0 ?
Unique (%)0.0%

Sample

1st row직동근린공원
2nd row직동근린공원
3rd row직동근린공원
4th row직동근린공원
5th row직동근린공원
ValueCountFrequency (%)
직동근린공원 994
 
15.2%
추동근린공원 669
 
10.2%
옥수당근린공원(수락리버시티공원 209
 
3.2%
중랑천근린공원(시민,양지 174
 
2.7%
고산지구배꽃근린공원 133
 
2.0%
송산사지근린공원 127
 
1.9%
캠프라과디아체육공원 99
 
1.5%
고산지구왕바우근린공원 91
 
1.4%
초록누리근린공원 90
 
1.4%
군마근린공원 88
 
1.3%
Other values (110) 3858
59.1%
2023-12-12T08:59:43.327699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 6797
 
13.3%
원 6769
 
13.3%
린 5338
 
10.5%
근 3487
 
6.8%
동 1863
 
3.7%
어 1841
 
3.6%
이 1788
 
3.5%
직 994
 
1.9%
화 885
 
1.7%
문 846
 
1.7%
Other values (157) 20419
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49380
96.8%
Decimal Number 557
 
1.1%
Open Punctuation 458
 
0.9%
Close Punctuation 458
 
0.9%
Other Punctuation 174
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 6797
 
13.8%
원 6769
 
13.7%
린 5338
 
10.8%
근 3487
 
7.1%
동 1863
 
3.8%
어 1841
 
3.7%
이 1788
 
3.6%
직 994
 
2.0%
화 885
 
1.8%
문 846
 
1.7%
Other values (150) 18772
38.0%
Decimal Number
ValueCountFrequency (%)
2 306
54.9%
1 193
34.6%
4 51
 
9.2%
3 7
 
1.3%
Open Punctuation
ValueCountFrequency (%)
( 458
100.0%
Close Punctuation
ValueCountFrequency (%)
) 458
100.0%
Other Punctuation
ValueCountFrequency (%)
, 174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49380
96.8%
Common 1647
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 6797
 
13.8%
원 6769
 
13.7%
린 5338
 
10.8%
근 3487
 
7.1%
동 1863
 
3.8%
어 1841
 
3.7%
이 1788
 
3.6%
직 994
 
2.0%
화 885
 
1.8%
문 846
 
1.7%
Other values (150) 18772
38.0%
Common
ValueCountFrequency (%)
( 458
27.8%
) 458
27.8%
2 306
18.6%
1 193
11.7%
, 174
 
10.6%
4 51
 
3.1%
3 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49380
96.8%
ASCII 1647
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 6797
 
13.8%
원 6769
 
13.7%
린 5338
 
10.8%
근 3487
 
7.1%
동 1863
 
3.8%
어 1841
 
3.7%
이 1788
 
3.6%
직 994
 
2.0%
화 885
 
1.8%
문 846
 
1.7%
Other values (150) 18772
38.0%
ASCII
ValueCountFrequency (%)
( 458
27.8%
) 458
27.8%
2 306
18.6%
1 193
11.7%
, 174
 
10.6%
4 51
 
3.1%
3 7
 
0.4%

위치구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
근린공원
3487 
어린이공원
1763 
문화공원
673 
소공원
372 
체육공원
 
169

Length

Max length5
Median length4
Mean length4.2129516
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
근린공원 3487
53.4%
어린이공원 1763
27.0%
문화공원 673
 
10.3%
소공원 372
 
5.7%
체육공원 169
 
2.6%
수변공원 68
 
1.0%

Length

2023-12-12T08:59:43.475962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:59:43.612004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
근린공원 3487
53.4%
어린이공원 1763
27.0%
문화공원 673
 
10.3%
소공원 372
 
5.7%
체육공원 169
 
2.6%
수변공원 68
 
1.0%

도로명주소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct33
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
<NA>
4050 
경기도 의정부시 호국로1162번길 73
994 
경기도 의정부시 민락로296
 
127
경기도 의정부시 용현로143
 
111
경기도 의정부시 서광로232
 
91
Other values (28)
1159 

Length

Max length22
Median length4
Mean length9.4234538
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 의정부시 호국로1162번길 73
2nd row경기도 의정부시 호국로1162번길 73
3rd row경기도 의정부시 호국로1162번길 73
4th row경기도 의정부시 호국로1162번길 73
5th row경기도 의정부시 호국로1162번길 73

Common Values

ValueCountFrequency (%)
<NA> 4050
62.0%
경기도 의정부시 호국로1162번길 73 994
 
15.2%
경기도 의정부시 민락로296 127
 
1.9%
경기도 의정부시 용현로143 111
 
1.7%
경기도 의정부시 서광로232 91
 
1.4%
경기도 의정부시 녹양로134 79
 
1.2%
경기도 의정부시 신흥로207번길 51 78
 
1.2%
경기도 의정부시 회룡로175 76
 
1.2%
경기도 의정부시 용민로99 73
 
1.1%
경기도 의정부시 민락로299 70
 
1.1%
Other values (23) 783
 
12.0%

Length

2023-12-12T08:59:43.749624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 4050
31.4%
경기도 2482
19.3%
의정부시 2482
19.3%
호국로1162번길 994
 
7.7%
73 994
 
7.7%
민락로296 127
 
1.0%
용현로143 111
 
0.9%
서광로232 91
 
0.7%
녹양로134 79
 
0.6%
신흥로207번길 78
 
0.6%
Other values (37) 1399
 
10.9%

지번주소
Text

Distinct127
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2023-12-12T08:59:44.107005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length17.350735
Min length16

Characters and Unicode

Total characters113335
Distinct characters41
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

Unique2 ?
Unique (%)< 0.1%

Sample

1st row경기도 의정부시 의정부동 348
2nd row경기도 의정부시 의정부동 348
3rd row경기도 의정부시 의정부동 348
4th row경기도 의정부시 의정부동 348
5th row경기도 의정부시 의정부동 348
ValueCountFrequency (%)
경기도 6532
25.0%
의정부시 6532
25.0%
의정부동 1929
 
7.4%
신곡동 1306
 
5.0%
348 1030
 
3.9%
민락동 959
 
3.7%
산25-1 669
 
2.6%
고산동 367
 
1.4%
금오동 310
 
1.2%
녹양동 309
 
1.2%
Other values (130) 6185
23.7%
2023-12-12T08:59:44.630641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19596
17.3%
의 8461
 
7.5%
정 8461
 
7.5%
부 8461
 
7.5%
경 6532
 
5.8%
도 6532
 
5.8%
시 6532
 
5.8%
동 6532
 
5.8%
기 6532
 
5.8%
- 3352
 
3.0%
Other values (31) 32344
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 67934
59.9%
Decimal Number 22453
 
19.8%
Space Separator 19596
 
17.3%
Dash Punctuation 3352
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 8461
12.5%
정 8461
12.5%
부 8461
12.5%
경 6532
9.6%
도 6532
9.6%
시 6532
9.6%
동 6532
9.6%
기 6532
9.6%
곡 1306
 
1.9%
신 1306
 
1.9%
Other values (19) 7279
10.7%
Decimal Number
ValueCountFrequency (%)
2 2869
12.8%
8 2864
12.8%
4 2816
12.5%
5 2661
11.9%
1 2581
11.5%
3 2405
10.7%
6 2070
9.2%
7 1889
8.4%
9 1472
6.6%
0 826
 
3.7%
Space Separator
ValueCountFrequency (%)
19596
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3352
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 67934
59.9%
Common 45401
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 8461
12.5%
정 8461
12.5%
부 8461
12.5%
경 6532
9.6%
도 6532
9.6%
시 6532
9.6%
동 6532
9.6%
기 6532
9.6%
곡 1306
 
1.9%
신 1306
 
1.9%
Other values (19) 7279
10.7%
Common
ValueCountFrequency (%)
19596
43.2%
- 3352
 
7.4%
2 2869
 
6.3%
8 2864
 
6.3%
4 2816
 
6.2%
5 2661
 
5.9%
1 2581
 
5.7%
3 2405
 
5.3%
6 2070
 
4.6%
7 1889
 
4.2%
Other values (2) 2298
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 67934
59.9%
ASCII 45401
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19596
43.2%
- 3352
 
7.4%
2 2869
 
6.3%
8 2864
 
6.3%
4 2816
 
6.2%
5 2661
 
5.9%
1 2581
 
5.7%
3 2405
 
5.3%
6 2070
 
4.6%
7 1889
 
4.2%
Other values (2) 2298
 
5.1%
Hangul
ValueCountFrequency (%)
의 8461
12.5%
정 8461
12.5%
부 8461
12.5%
경 6532
9.6%
도 6532
9.6%
시 6532
9.6%
동 6532
9.6%
기 6532
9.6%
곡 1306
 
1.9%
신 1306
 
1.9%
Other values (19) 7279
10.7%

시설종류
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
공원관리시설
2844 
편익시설
1789 
운동시설
838 
휴양시설
448 
유희시설
379 

Length

Max length6
Median length4
Mean length4.7991427
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공원관리시설 2844
43.5%
편익시설 1789
27.4%
운동시설 838
 
12.8%
휴양시설 448
 
6.9%
유희시설 379
 
5.8%
기타 234
 
3.6%

Length

2023-12-12T08:59:44.827978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:59:44.991597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공원관리시설 2844
43.5%
편익시설 1789
27.4%
운동시설 838
 
12.8%
휴양시설 448
 
6.9%
유희시설 379
 
5.8%
기타 234
 
3.6%

시설명
Text

Distinct72
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2023-12-12T08:59:45.235574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length3
Mean length4.8897734
Min length2

Characters and Unicode

Total characters31940
Distinct characters161
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.1%

Sample

1st row방향안내판
2nd row금지행위안내판
3rd row기타안내판
4th row방향안내판
5th row기타안내판
ValueCountFrequency (%)
공원등 1943
26.4%
등의자 1180
16.0%
평의자 313
 
4.3%
금지행위안내판 298
 
4.0%
퍼걸러_의자형 292
 
4.0%
의자_기타 287
 
3.9%
cctv 231
 
3.1%
기타안내판 228
 
3.1%
방향안내판 149
 
2.0%
흔들말 124
 
1.7%
Other values (78) 2314
31.4%
2023-12-12T08:59:45.634571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
등 3151
 
9.9%
자 2138
 
6.7%
의 2099
 
6.6%
공 2025
 
6.3%
원 1948
 
6.1%
기 1494
 
4.7%
내 933
 
2.9%
판 878
 
2.7%
안 878
 
2.7%
, 836
 
2.6%
Other values (151) 15560
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28612
89.6%
Uppercase Letter 936
 
2.9%
Other Punctuation 836
 
2.6%
Space Separator 827
 
2.6%
Connector Punctuation 688
 
2.2%
Open Punctuation 14
 
< 0.1%
Close Punctuation 14
 
< 0.1%
Math Symbol 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
등 3151
 
11.0%
자 2138
 
7.5%
의 2099
 
7.3%
공 2025
 
7.1%
원 1948
 
6.8%
기 1494
 
5.2%
내 933
 
3.3%
판 878
 
3.1%
안 878
 
3.1%
타 607
 
2.1%
Other values (142) 12461
43.6%
Uppercase Letter
ValueCountFrequency (%)
C 468
50.0%
T 234
25.0%
V 234
25.0%
Other Punctuation
ValueCountFrequency (%)
, 836
100.0%
Space Separator
ValueCountFrequency (%)
827
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 688
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Math Symbol
ValueCountFrequency (%)
+ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28612
89.6%
Common 2392
 
7.5%
Latin 936
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
등 3151
 
11.0%
자 2138
 
7.5%
의 2099
 
7.3%
공 2025
 
7.1%
원 1948
 
6.8%
기 1494
 
5.2%
내 933
 
3.3%
판 878
 
3.1%
안 878
 
3.1%
타 607
 
2.1%
Other values (142) 12461
43.6%
Common
ValueCountFrequency (%)
, 836
34.9%
827
34.6%
_ 688
28.8%
( 14
 
0.6%
) 14
 
0.6%
+ 13
 
0.5%
Latin
ValueCountFrequency (%)
C 468
50.0%
T 234
25.0%
V 234
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28612
89.6%
ASCII 3328
 
10.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
등 3151
 
11.0%
자 2138
 
7.5%
의 2099
 
7.3%
공 2025
 
7.1%
원 1948
 
6.8%
기 1494
 
5.2%
내 933
 
3.3%
판 878
 
3.1%
안 878
 
3.1%
타 607
 
2.1%
Other values (142) 12461
43.6%
ASCII
ValueCountFrequency (%)
, 836
25.1%
827
24.8%
_ 688
20.7%
C 468
14.1%
T 234
 
7.0%
V 234
 
7.0%
( 14
 
0.4%
) 14
 
0.4%
+ 13
 
0.4%

관리상태
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
양호
6341 
노후
 
156
파손
 
35

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양호 6341
97.1%
노후 156
 
2.4%
파손 35
 
0.5%

Length

2023-12-12T08:59:45.810958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:59:45.943903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양호 6341
97.1%
노후 156
 
2.4%
파손 35
 
0.5%

수리필요 유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
False
6497 
True
 
35
ValueCountFrequency (%)
False 6497
99.5%
True 35
 
0.5%
2023-12-12T08:59:46.058066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

위치설명
Categorical

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
1시방향
792 
5시방향
741 
6시방향
657 
3시방향
605 
12시방향
601 
Other values (7)
3136 

Length

Max length5
Median length4
Mean length4.2244336
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12시방향
2nd row12시방향
3rd row12시방향
4th row12시방향
5th row12시방향

Common Values

ValueCountFrequency (%)
1시방향 792
12.1%
5시방향 741
11.3%
6시방향 657
10.1%
3시방향 605
9.3%
12시방향 601
9.2%
7시방향 569
8.7%
11시방향 551
8.4%
2시방향 549
8.4%
9시방향 471
7.2%
4시방향 432
6.6%
Other values (2) 564
8.6%

Length

2023-12-12T08:59:46.193925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1시방향 792
12.1%
5시방향 741
11.3%
6시방향 657
10.1%
3시방향 605
9.3%
12시방향 601
9.2%
7시방향 569
8.7%
11시방향 551
8.4%
2시방향 549
8.4%
9시방향 471
7.2%
4시방향 432
6.6%
Other values (2) 564
8.6%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct6319
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.739416
Minimum37.686937
Maximum37.770699
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.5 KiB
2023-12-12T08:59:46.356438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.686937
5-th percentile37.713882
Q137.734034
median37.741589
Q337.746793
95-th percentile37.757571
Maximum37.770699
Range0.0837618
Interquartile range (IQR)0.01275915

Descriptive statistics

Standard deviation0.013959448
Coefficient of variation (CV)0.00036989042
Kurtosis4.1110987
Mean37.739416
Median Absolute Deviation (MAD)0.0062978
Skewness-1.6104199
Sum246513.86
Variance0.0001948662
MonotonicityNot monotonic
2023-12-12T08:59:46.844278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.7449088 3
 
< 0.1%
37.7458336 3
 
< 0.1%
37.7465691 3
 
< 0.1%
37.7377886 3
 
< 0.1%
37.7463621 3
 
< 0.1%
37.7382702 3
 
< 0.1%
37.7437967 3
 
< 0.1%
37.7391664 3
 
< 0.1%
37.7498643 3
 
< 0.1%
37.7438691 3
 
< 0.1%
Other values (6309) 6502
99.5%
ValueCountFrequency (%)
37.6869367 1
< 0.1%
37.6869514 1
< 0.1%
37.6869693 1
< 0.1%
37.6869989 1
< 0.1%
37.6870121 1
< 0.1%
37.6870172 1
< 0.1%
37.68702 1
< 0.1%
37.6870442 1
< 0.1%
37.687075 1
< 0.1%
37.6871176 1
< 0.1%
ValueCountFrequency (%)
37.7706985 1
< 0.1%
37.7706474 1
< 0.1%
37.7705594 1
< 0.1%
37.7705336 1
< 0.1%
37.7704387 1
< 0.1%
37.7704303 1
< 0.1%
37.7703425 2
< 0.1%
37.7703025 1
< 0.1%
37.7702831 1
< 0.1%
37.7700982 1
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct6371
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.0649
Minimum127.02944
Maximum127.12223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size57.5 KiB
2023-12-12T08:59:47.014810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02944
5-th percentile127.0327
Q1127.03959
median127.05848
Q3127.08618
95-th percentile127.11725
Maximum127.12223
Range0.0927941
Interquartile range (IQR)0.046584275

Descriptive statistics

Standard deviation0.027297033
Coefficient of variation (CV)0.00021482749
Kurtosis-0.91309638
Mean127.0649
Median Absolute Deviation (MAD)0.0203891
Skewness0.56889964
Sum829987.9
Variance0.00074512802
MonotonicityNot monotonic
2023-12-12T08:59:47.163644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1201393 4
 
0.1%
127.1177173 3
 
< 0.1%
127.0341355 3
 
< 0.1%
127.0356392 3
 
< 0.1%
127.1178262 3
 
< 0.1%
127.1196325 3
 
< 0.1%
127.0322285 3
 
< 0.1%
127.072171 3
 
< 0.1%
127.1129019 3
 
< 0.1%
127.1129508 3
 
< 0.1%
Other values (6361) 6501
99.5%
ValueCountFrequency (%)
127.0294405 1
< 0.1%
127.0294517 1
< 0.1%
127.0294573 1
< 0.1%
127.0294668 1
< 0.1%
127.0295896 1
< 0.1%
127.0296944 1
< 0.1%
127.0297118 1
< 0.1%
127.0297132 1
< 0.1%
127.0297648 1
< 0.1%
127.0297673 1
< 0.1%
ValueCountFrequency (%)
127.1222346 1
< 0.1%
127.1221326 1
< 0.1%
127.1217423 1
< 0.1%
127.1213428 1
< 0.1%
127.1212664 1
< 0.1%
127.1211759 1
< 0.1%
127.1211646 1
< 0.1%
127.1211128 1
< 0.1%
127.121073 1
< 0.1%
127.1210653 1
< 0.1%

행정동
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
의정부동
1233 
신곡동
839 
송산3동
697 
송산1동
646 
호원동
551 
Other values (10)
2566 

Length

Max length5
Median length4
Mean length3.6350276
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row의정부2동
2nd row의정부2동
3rd row의정부2동
4th row의정부2동
5th row의정부2동

Common Values

ValueCountFrequency (%)
의정부동 1233
18.9%
신곡동 839
12.8%
송산3동 697
10.7%
송산1동 646
9.9%
호원동 551
8.4%
송산2동 441
 
6.8%
의정부2동 378
 
5.8%
신곡2동 375
 
5.7%
녹양동 309
 
4.7%
장암동 294
 
4.5%
Other values (5) 769
11.8%

Length

2023-12-12T08:59:47.319299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
의정부동 1233
18.9%
신곡동 839
12.8%
송산3동 697
10.7%
송산1동 646
9.9%
호원동 551
8.4%
송산2동 441
 
6.8%
의정부2동 378
 
5.8%
신곡2동 375
 
5.7%
녹양동 309
 
4.7%
장암동 294
 
4.5%
Other values (5) 769
11.8%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
경기도 의정부시
6532 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 의정부시
2nd row경기도 의정부시
3rd row경기도 의정부시
4th row경기도 의정부시
5th row경기도 의정부시

Common Values

ValueCountFrequency (%)
경기도 의정부시 6532
100.0%

Length

2023-12-12T08:59:47.486461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:59:47.603012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 6532
50.0%
의정부시 6532
50.0%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size51.2 KiB
2022-11-11
6532 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-11-11
2nd row2022-11-11
3rd row2022-11-11
4th row2022-11-11
5th row2022-11-11

Common Values

ValueCountFrequency (%)
2022-11-11 6532
100.0%

Length

2023-12-12T08:59:47.751655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:59:47.864397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-11-11 6532
100.0%

Interactions

2023-12-12T08:59:41.461170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:59:41.224708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:59:41.566365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:59:41.352313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:59:47.925546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위치구분도로명주소시설종류시설명관리상태수리필요 유무위치설명위도경도행정동
위치구분1.0000.9930.3350.4150.0820.0390.2720.4240.5220.708
도로명주소0.9931.0000.4280.6150.3150.0770.6610.9620.9810.983
시설종류0.3350.4281.0001.0000.1920.0220.1700.1290.1430.181
시설명0.4150.6151.0001.0000.3330.1770.2510.2710.3180.398
관리상태0.0820.3150.1920.3331.0001.0000.0930.1920.0780.278
수리필요 유무0.0390.0770.0220.1771.0001.0000.0310.0350.0000.051
위치설명0.2720.6610.1700.2510.0930.0311.0000.3900.3520.487
위도0.4240.9620.1290.2710.1920.0350.3901.0000.7210.878
경도0.5220.9810.1430.3180.0780.0000.3520.7211.0000.879
행정동0.7080.9830.1810.3980.2780.0510.4870.8780.8791.000
2023-12-12T08:59:48.063341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수리필요 유무시설종류위치설명행정동관리상태위치구분도로명주소
수리필요 유무1.0000.0160.0240.0461.0000.0280.061
시설종류0.0161.0000.0670.0850.0810.1270.203
위치설명0.0240.0671.0000.2000.0410.1100.275
행정동0.0460.0850.2001.0000.1310.4250.878
관리상태1.0000.0810.0410.1311.0000.0340.166
위치구분0.0280.1270.1100.4250.0341.0000.962
도로명주소0.0610.2030.2750.8780.1660.9621.000
2023-12-12T08:59:48.182741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도위치구분도로명주소시설종류관리상태수리필요 유무위치설명행정동
위도1.0000.3420.2390.8160.0680.1160.0270.1750.570
경도0.3421.0000.3070.8670.0750.0460.0000.1550.571
위치구분0.2390.3071.0000.9620.1270.0340.0280.1100.425
도로명주소0.8160.8670.9621.0000.2030.1660.0610.2750.878
시설종류0.0680.0750.1270.2031.0000.0810.0160.0670.085
관리상태0.1160.0460.0340.1660.0811.0001.0000.0410.131
수리필요 유무0.0270.0000.0280.0610.0161.0001.0000.0240.046
위치설명0.1750.1550.1100.2750.0670.0410.0241.0000.200
행정동0.5700.5710.4250.8780.0850.1310.0460.2001.000

Missing values

2023-12-12T08:59:41.714986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:59:41.967152image/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

관리번호공원명위치구분도로명주소지번주소시설종류시설명관리상태수리필요 유무위치설명위도경도행정동관리기관명데이터 기준일
041150-00001-0001직동근린공원근린공원경기도 의정부시 호국로1162번길 73경기도 의정부시 의정부동 348공원관리시설방향안내판양호N12시방향37.734356127.033081의정부2동경기도 의정부시2022-11-11
141150-00001-0002직동근린공원근린공원경기도 의정부시 호국로1162번길 73경기도 의정부시 의정부동 348공원관리시설금지행위안내판양호N12시방향37.734373127.033077의정부2동경기도 의정부시2022-11-11
241150-00001-0003직동근린공원근린공원경기도 의정부시 호국로1162번길 73경기도 의정부시 의정부동 348공원관리시설기타안내판양호N12시방향37.73438127.03309의정부2동경기도 의정부시2022-11-11
341150-00001-0004직동근린공원근린공원경기도 의정부시 호국로1162번길 73경기도 의정부시 의정부동 348공원관리시설방향안내판양호N12시방향37.734392127.033079의정부2동경기도 의정부시2022-11-11
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