Overview

Dataset statistics

Number of variables15
Number of observations536
Missing cells323
Missing cells (%)4.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory64.0 KiB
Average record size in memory122.2 B

Variable types

Numeric2
Categorical8
Text5

Dataset

Description함안소방서 관내 소방용수 현황으로, 관리번호, 수리위치 및 형식, 주변 대상물, 안심마을 지정여부, 센터와의 거리 등의 데이터를 포함하고 있습니다.
URLhttps://www.data.go.kr/data/15088088/fileData.do

Alerts

관서명 has constant value ""Constant
센터명 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
지역대 is highly overall correlated with 연번 and 4 other fieldsHigh correlation
읍면동 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
안심마을 지정여부 is highly overall correlated with 지역대High correlation
연번 is highly overall correlated with 센터명 and 2 other fieldsHigh correlation
수리형식 is highly overall correlated with 설치년도 and 1 other fieldsHigh correlation
설치년도 is highly overall correlated with 센터명 and 2 other fieldsHigh correlation
유지관리 주체 is highly overall correlated with 수리형식High correlation
안심마을 지정여부 is highly imbalanced (96.5%)Imbalance
수리형식 is highly imbalanced (81.5%)Imbalance
유지관리 주체 is highly imbalanced (93.7%)Imbalance
주변 대상물 has 12 (2.2%) missing valuesMissing
마을명칭 has 311 (58.0%) missing valuesMissing
연번 has unique valuesUnique
관리번호 has unique valuesUnique
센터와 용수와의 거리 has 12 (2.2%) zerosZeros

Reproduction

Analysis started2023-12-12 21:46:13.681912
Analysis finished2023-12-12 21:46:16.099408
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct536
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean268.5
Minimum1
Maximum536
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-13T06:46:16.183977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile27.75
Q1134.75
median268.5
Q3402.25
95-th percentile509.25
Maximum536
Range535
Interquartile range (IQR)267.5

Descriptive statistics

Standard deviation154.87414
Coefficient of variation (CV)0.57681245
Kurtosis-1.2
Mean268.5
Median Absolute Deviation (MAD)134
Skewness0
Sum143916
Variance23986
MonotonicityStrictly increasing
2023-12-13T06:46:16.342406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
354 1
 
0.2%
368 1
 
0.2%
367 1
 
0.2%
366 1
 
0.2%
365 1
 
0.2%
364 1
 
0.2%
363 1
 
0.2%
362 1
 
0.2%
361 1
 
0.2%
Other values (526) 526
98.1%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
536 1
0.2%
535 1
0.2%
534 1
0.2%
533 1
0.2%
532 1
0.2%
531 1
0.2%
530 1
0.2%
529 1
0.2%
528 1
0.2%
527 1
0.2%

관서명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
함안
536 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
함안 536
100.0%

Length

2023-12-13T06:46:16.492956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:16.584070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
함안 536
100.0%

센터명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
가야
192 
군북
175 
칠원
169 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가야 192
35.8%
군북 175
32.6%
칠원 169
31.5%

Length

2023-12-13T06:46:16.682528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:16.802758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가야 192
35.8%
군북 175
32.6%
칠원 169
31.5%

지역대
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
<NA>
375 
칠서
62 
대산
51 
법수
48 

Length

Max length4
Median length4
Mean length3.3992537
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 375
70.0%
칠서 62
 
11.6%
대산 51
 
9.5%
법수 48
 
9.0%

Length

2023-12-13T06:46:16.916869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:17.049720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 375
70.0%
칠서 62
 
11.6%
대산 51
 
9.5%
법수 48
 
9.0%

관리번호
Text

UNIQUE 

Distinct536
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T06:46:17.336502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length7.1716418
Min length6

Characters and Unicode

Total characters3844
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique536 ?
Unique (%)100.0%

Sample

1st row가야-저-1
2nd row가야-저-2
3rd row가야-상-1
4th row가야-상-2
5th row가야-상-3
ValueCountFrequency (%)
가야-저-1 1
 
0.2%
칠서산단-하-12 1
 
0.2%
군북-상-10 1
 
0.2%
군북-상-09 1
 
0.2%
군북-상-08 1
 
0.2%
군북-상-07 1
 
0.2%
군북-상-01 1
 
0.2%
칠서산단-하-28 1
 
0.2%
칠서산단-상-27 1
 
0.2%
칠서산단-하-25 1
 
0.2%
Other values (526) 526
98.1%
2023-12-13T06:46:17.804623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1072
27.9%
상 513
13.3%
산 177
 
4.6%
1 176
 
4.6%
칠 169
 
4.4%
2 165
 
4.3%
3 134
 
3.5%
4 123
 
3.2%
북 122
 
3.2%
단 95
 
2.5%
Other values (21) 1098
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1798
46.8%
Dash Punctuation 1072
27.9%
Decimal Number 974
25.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 513
28.5%
산 177
 
9.8%
칠 169
 
9.4%
북 122
 
6.8%
단 95
 
5.3%
안 90
 
5.0%
함 90
 
5.0%
군 73
 
4.1%
가 69
 
3.8%
야 69
 
3.8%
Other values (10) 331
18.4%
Decimal Number
ValueCountFrequency (%)
1 176
18.1%
2 165
16.9%
3 134
13.8%
4 123
12.6%
5 88
9.0%
6 70
 
7.2%
0 63
 
6.5%
7 58
 
6.0%
8 49
 
5.0%
9 48
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 1072
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2046
53.2%
Hangul 1798
46.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 513
28.5%
산 177
 
9.8%
칠 169
 
9.4%
북 122
 
6.8%
단 95
 
5.3%
안 90
 
5.0%
함 90
 
5.0%
군 73
 
4.1%
가 69
 
3.8%
야 69
 
3.8%
Other values (10) 331
18.4%
Common
ValueCountFrequency (%)
- 1072
52.4%
1 176
 
8.6%
2 165
 
8.1%
3 134
 
6.5%
4 123
 
6.0%
5 88
 
4.3%
6 70
 
3.4%
0 63
 
3.1%
7 58
 
2.8%
8 49
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2046
53.2%
Hangul 1798
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1072
52.4%
1 176
 
8.6%
2 165
 
8.1%
3 134
 
6.5%
4 123
 
6.0%
5 88
 
4.3%
6 70
 
3.4%
0 63
 
3.1%
7 58
 
2.8%
8 49
 
2.4%
Hangul
ValueCountFrequency (%)
상 513
28.5%
산 177
 
9.8%
칠 169
 
9.4%
북 122
 
6.8%
단 95
 
5.3%
안 90
 
5.0%
함 90
 
5.0%
군 73
 
4.1%
가 69
 
3.8%
야 69
 
3.8%
Other values (10) 331
18.4%

주소
Text

Distinct483
Distinct (%)90.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T06:46:18.150167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19
Mean length16.065299
Min length10

Characters and Unicode

Total characters8611
Distinct characters147
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

Unique454 ?
Unique (%)84.7%

Sample

1st row함안군 가야읍 말산로 25
2nd row함안군 가야읍 선왕길 59
3rd row함안군 가야읍 말산로 25
4th row함안군 가야읍 도항2길 57
5th row함안군 가야읍 검암천북길 51
ValueCountFrequency (%)
함안군 534
25.0%
군북면 127
 
6.0%
가야읍 71
 
3.3%
칠서면 62
 
2.9%
칠원읍 58
 
2.7%
대산면 51
 
2.4%
칠북면 49
 
2.3%
법수면 47
 
2.2%
함안면 32
 
1.5%
산인면 31
 
1.5%
Other values (593) 1070
50.2%
2023-12-13T06:46:18.615858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1608
18.7%
군 665
 
7.7%
함 651
 
7.6%
안 633
 
7.4%
면 404
 
4.7%
1 368
 
4.3%
2 284
 
3.3%
길 284
 
3.3%
3 219
 
2.5%
북 214
 
2.5%
Other values (137) 3281
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5049
58.6%
Decimal Number 1795
 
20.8%
Space Separator 1608
 
18.7%
Dash Punctuation 159
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 665
13.2%
함 651
12.9%
안 633
12.5%
면 404
 
8.0%
길 284
 
5.6%
북 214
 
4.2%
로 204
 
4.0%
산 192
 
3.8%
칠 181
 
3.6%
읍 129
 
2.6%
Other values (125) 1492
29.6%
Decimal Number
ValueCountFrequency (%)
1 368
20.5%
2 284
15.8%
3 219
12.2%
5 193
10.8%
4 149
8.3%
9 121
 
6.7%
8 121
 
6.7%
6 120
 
6.7%
7 112
 
6.2%
0 108
 
6.0%
Space Separator
ValueCountFrequency (%)
1608
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 159
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5049
58.6%
Common 3562
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 665
13.2%
함 651
12.9%
안 633
12.5%
면 404
 
8.0%
길 284
 
5.6%
북 214
 
4.2%
로 204
 
4.0%
산 192
 
3.8%
칠 181
 
3.6%
읍 129
 
2.6%
Other values (125) 1492
29.6%
Common
ValueCountFrequency (%)
1608
45.1%
1 368
 
10.3%
2 284
 
8.0%
3 219
 
6.1%
5 193
 
5.4%
- 159
 
4.5%
4 149
 
4.2%
9 121
 
3.4%
8 121
 
3.4%
6 120
 
3.4%
Other values (2) 220
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5049
58.6%
ASCII 3562
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1608
45.1%
1 368
 
10.3%
2 284
 
8.0%
3 219
 
6.1%
5 193
 
5.4%
- 159
 
4.5%
4 149
 
4.2%
9 121
 
3.4%
8 121
 
3.4%
6 120
 
3.4%
Other values (2) 220
 
6.2%
Hangul
ValueCountFrequency (%)
군 665
13.2%
함 651
12.9%
안 633
12.5%
면 404
 
8.0%
길 284
 
5.6%
북 214
 
4.2%
로 204
 
4.0%
산 192
 
3.8%
칠 181
 
3.6%
읍 129
 
2.6%
Other values (125) 1492
29.6%

읍면동
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
군북면
127 
가야읍
71 
칠서면
62 
칠원읍
58 
대산면
51 
Other values (5)
167 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군북면 127
23.7%
가야읍 71
13.2%
칠서면 62
11.6%
칠원읍 58
10.8%
대산면 51
9.5%
칠북면 49
 
9.1%
법수면 48
 
9.0%
함안면 34
 
6.3%
산인면 31
 
5.8%
여항면 5
 
0.9%

Length

2023-12-13T06:46:18.788313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:18.918955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군북면 127
23.7%
가야읍 71
13.2%
칠서면 62
11.6%
칠원읍 58
10.8%
대산면 51
9.5%
칠북면 49
 
9.1%
법수면 48
 
9.0%
함안면 34
 
6.3%
산인면 31
 
5.8%
여항면 5
 
0.9%

주변 대상물
Text

MISSING 

Distinct495
Distinct (%)94.5%
Missing12
Missing (%)2.2%
Memory size4.3 KiB
2023-12-13T06:46:19.201869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length23
Mean length9.4599237
Min length2

Characters and Unicode

Total characters4957
Distinct characters398
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique490 ?
Unique (%)93.5%

Sample

1st row함안군여성센터 앞
2nd row함안소방서 입구
3rd row함안군여성센터 앞
4th row동신아파트 상가 앞
5th row현대자동차 1급정비 전봇대 옆
ValueCountFrequency (%)
앞 185
 
16.2%
입구 40
 
3.5%
옆 37
 
3.2%
영동산업단지 25
 
2.2%
맞은편 22
 
1.9%
정문 16
 
1.4%
없음 15
 
1.3%
출입문 11
 
1.0%
버스정류장 8
 
0.7%
부근 8
 
0.7%
Other values (630) 778
67.9%
2023-12-13T06:46:19.658933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
660
 
13.3%
앞 228
 
4.6%
지 130
 
2.6%
마 97
 
2.0%
) 91
 
1.8%
( 88
 
1.8%
을 87
 
1.8%
산 81
 
1.6%
동 79
 
1.6%
주 75
 
1.5%
Other values (388) 3341
67.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3919
79.1%
Space Separator 660
 
13.3%
Close Punctuation 91
 
1.8%
Open Punctuation 88
 
1.8%
Uppercase Letter 76
 
1.5%
Decimal Number 55
 
1.1%
Other Symbol 53
 
1.1%
Other Punctuation 8
 
0.2%
Lowercase Letter 6
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 228
 
5.8%
지 130
 
3.3%
마 97
 
2.5%
을 87
 
2.2%
산 81
 
2.1%
동 79
 
2.0%
주 75
 
1.9%
회 71
 
1.8%
관 70
 
1.8%
입 65
 
1.7%
Other values (347) 2936
74.9%
Uppercase Letter
ValueCountFrequency (%)
C 9
 
11.8%
S 8
 
10.5%
G 7
 
9.2%
E 6
 
7.9%
I 4
 
5.3%
B 4
 
5.3%
T 4
 
5.3%
N 4
 
5.3%
P 4
 
5.3%
A 3
 
3.9%
Other values (11) 23
30.3%
Decimal Number
ValueCountFrequency (%)
1 19
34.5%
0 8
14.5%
3 6
 
10.9%
2 5
 
9.1%
5 5
 
9.1%
9 4
 
7.3%
7 3
 
5.5%
4 2
 
3.6%
8 2
 
3.6%
6 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 5
62.5%
. 2
 
25.0%
& 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
m 5
83.3%
h 1
 
16.7%
Space Separator
ValueCountFrequency (%)
660
100.0%
Close Punctuation
ValueCountFrequency (%)
) 91
100.0%
Open Punctuation
ValueCountFrequency (%)
( 88
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3972
80.1%
Common 903
 
18.2%
Latin 82
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 228
 
5.7%
지 130
 
3.3%
마 97
 
2.4%
을 87
 
2.2%
산 81
 
2.0%
동 79
 
2.0%
주 75
 
1.9%
회 71
 
1.8%
관 70
 
1.8%
입 65
 
1.6%
Other values (348) 2989
75.3%
Latin
ValueCountFrequency (%)
C 9
 
11.0%
S 8
 
9.8%
G 7
 
8.5%
E 6
 
7.3%
m 5
 
6.1%
I 4
 
4.9%
B 4
 
4.9%
T 4
 
4.9%
N 4
 
4.9%
P 4
 
4.9%
Other values (13) 27
32.9%
Common
ValueCountFrequency (%)
660
73.1%
) 91
 
10.1%
( 88
 
9.7%
1 19
 
2.1%
0 8
 
0.9%
3 6
 
0.7%
, 5
 
0.6%
2 5
 
0.6%
5 5
 
0.6%
9 4
 
0.4%
Other values (7) 12
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3919
79.1%
ASCII 985
 
19.9%
None 53
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
660
67.0%
) 91
 
9.2%
( 88
 
8.9%
1 19
 
1.9%
C 9
 
0.9%
S 8
 
0.8%
0 8
 
0.8%
G 7
 
0.7%
E 6
 
0.6%
3 6
 
0.6%
Other values (30) 83
 
8.4%
Hangul
ValueCountFrequency (%)
앞 228
 
5.8%
지 130
 
3.3%
마 97
 
2.5%
을 87
 
2.2%
산 81
 
2.1%
동 79
 
2.0%
주 75
 
1.9%
회 71
 
1.8%
관 70
 
1.8%
입 65
 
1.7%
Other values (347) 2936
74.9%
None
ValueCountFrequency (%)
㈜ 53
100.0%

리
Text

Distinct85
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T06:46:19.911480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1608
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.4%

Sample

1st row말산리
2nd row도항리
3rd row말산리
4th row도항리
5th row검암리
ValueCountFrequency (%)
사도리 45
 
8.4%
영동리 27
 
5.0%
대치리 27
 
5.0%
월촌리 22
 
4.1%
말산리 21
 
3.9%
계내리 17
 
3.2%
도항리 16
 
3.0%
중암리 15
 
2.8%
장암리 15
 
2.8%
강주리 14
 
2.6%
Other values (75) 317
59.1%
2023-12-13T06:46:20.382574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 536
33.3%
사 71
 
4.4%
도 61
 
3.8%
산 59
 
3.7%
대 52
 
3.2%
촌 42
 
2.6%
암 38
 
2.4%
곡 36
 
2.2%
동 32
 
2.0%
내 31
 
1.9%
Other values (77) 650
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1608
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 536
33.3%
사 71
 
4.4%
도 61
 
3.8%
산 59
 
3.7%
대 52
 
3.2%
촌 42
 
2.6%
암 38
 
2.4%
곡 36
 
2.2%
동 32
 
2.0%
내 31
 
1.9%
Other values (77) 650
40.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1608
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 536
33.3%
사 71
 
4.4%
도 61
 
3.8%
산 59
 
3.7%
대 52
 
3.2%
촌 42
 
2.6%
암 38
 
2.4%
곡 36
 
2.2%
동 32
 
2.0%
내 31
 
1.9%
Other values (77) 650
40.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1608
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 536
33.3%
사 71
 
4.4%
도 61
 
3.8%
산 59
 
3.7%
대 52
 
3.2%
촌 42
 
2.6%
암 38
 
2.4%
곡 36
 
2.2%
동 32
 
2.0%
내 31
 
1.9%
Other values (77) 650
40.4%

마을명칭
Text

MISSING 

Distinct140
Distinct (%)62.2%
Missing311
Missing (%)58.0%
Memory size4.3 KiB
2023-12-13T06:46:20.765991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.1288889
Min length4

Characters and Unicode

Total characters929
Distinct characters134
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique97 ?
Unique (%)43.1%

Sample

1st row상검마을
2nd row묘동마을
3rd row장명동마을
4th row월성마을
5th row춘곡마을
ValueCountFrequency (%)
중암마을 15
 
6.7%
매산마을 7
 
3.1%
용산마을 6
 
2.7%
봉국마을 6
 
2.7%
유계마을 5
 
2.2%
유상마을 5
 
2.2%
예곡마을 4
 
1.8%
석전마을 3
 
1.3%
가곡마을 3
 
1.3%
우계마을 3
 
1.3%
Other values (130) 168
74.7%
2023-12-13T06:46:21.318535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 226
24.3%
을 225
24.2%
산 28
 
3.0%
동 23
 
2.5%
촌 20
 
2.2%
중 19
 
2.0%
곡 19
 
2.0%
암 19
 
2.0%
계 17
 
1.8%
유 13
 
1.4%
Other values (124) 320
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 929
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 226
24.3%
을 225
24.2%
산 28
 
3.0%
동 23
 
2.5%
촌 20
 
2.2%
중 19
 
2.0%
곡 19
 
2.0%
암 19
 
2.0%
계 17
 
1.8%
유 13
 
1.4%
Other values (124) 320
34.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 929
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 226
24.3%
을 225
24.2%
산 28
 
3.0%
동 23
 
2.5%
촌 20
 
2.2%
중 19
 
2.0%
곡 19
 
2.0%
암 19
 
2.0%
계 17
 
1.8%
유 13
 
1.4%
Other values (124) 320
34.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 929
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 226
24.3%
을 225
24.2%
산 28
 
3.0%
동 23
 
2.5%
촌 20
 
2.2%
중 19
 
2.0%
곡 19
 
2.0%
암 19
 
2.0%
계 17
 
1.8%
유 13
 
1.4%
Other values (124) 320
34.4%

안심마을 지정여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
미지정
534 
지정
 
2

Length

Max length3
Median length3
Mean length2.9962687
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
미지정 534
99.6%
지정 2
 
0.4%

Length

2023-12-13T06:46:21.494592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:21.601607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미지정 534
99.6%
지정 2
 
0.4%

수리형식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
지상
513 
일반지하
 
16
저수조
 
7

Length

Max length4
Median length2
Mean length2.0727612
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row저수조
2nd row저수조
3rd row지상
4th row지상
5th row지상

Common Values

ValueCountFrequency (%)
지상 513
95.7%
일반지하 16
 
3.0%
저수조 7
 
1.3%

Length

2023-12-13T06:46:21.708124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:21.842880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지상 513
95.7%
일반지하 16
 
3.0%
저수조 7
 
1.3%

설치년도
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2018
87 
2011
70 
1995
35 
2017
 
25
2013
 
25
Other values (33)
294 

Length

Max length4
Median length4
Mean length3.9962687
Min length2

Unique

Unique8 ?
Unique (%)1.5%

Sample

1st row1987
2nd row1999
3rd row1993
4th row2000
5th row2000

Common Values

ValueCountFrequency (%)
2018 87
16.2%
2011 70
 
13.1%
1995 35
 
6.5%
2017 25
 
4.7%
2013 25
 
4.7%
2009 24
 
4.5%
2010 23
 
4.3%
2008 22
 
4.1%
2015 20
 
3.7%
2004 18
 
3.4%
Other values (28) 187
34.9%

Length

2023-12-13T06:46:21.977588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018 87
16.2%
2011 70
 
13.1%
1995 35
 
6.5%
2017 25
 
4.7%
2013 25
 
4.7%
2009 24
 
4.5%
2010 23
 
4.3%
2008 22
 
4.1%
2015 20
 
3.7%
1991 18
 
3.4%
Other values (28) 187
34.9%

유지관리 주체
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
시군
532 
소방서
 
4

Length

Max length3
Median length2
Mean length2.0074627
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군
2nd row소방서
3rd row시군
4th row시군
5th row시군

Common Values

ValueCountFrequency (%)
시군 532
99.3%
소방서 4
 
0.7%

Length

2023-12-13T06:46:22.128563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:46:22.225904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시군 532
99.3%
소방서 4
 
0.7%

센터와 용수와의 거리
Real number (ℝ)

ZEROS 

Distinct98
Distinct (%)18.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8802239
Minimum0
Maximum13.7
Zeros12
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-13T06:46:22.351371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.6
Q11.9
median3.9
Q35.3
95-th percentile7.925
Maximum13.7
Range13.7
Interquartile range (IQR)3.4

Descriptive statistics

Standard deviation2.4323637
Coefficient of variation (CV)0.62686169
Kurtosis0.98458521
Mean3.8802239
Median Absolute Deviation (MAD)1.7
Skewness0.78786729
Sum2079.8
Variance5.9163932
MonotonicityNot monotonic
2023-12-13T06:46:22.542030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.3 17
 
3.2%
1.9 15
 
2.8%
0.6 14
 
2.6%
4.1 13
 
2.4%
5.4 12
 
2.2%
4.4 12
 
2.2%
0.0 12
 
2.2%
3.2 11
 
2.1%
1.6 11
 
2.1%
5.1 11
 
2.1%
Other values (88) 408
76.1%
ValueCountFrequency (%)
0.0 12
2.2%
0.1 1
 
0.2%
0.3 5
 
0.9%
0.4 4
 
0.7%
0.5 3
 
0.6%
0.6 14
2.6%
0.7 6
1.1%
0.8 2
 
0.4%
0.9 3
 
0.6%
1.0 5
 
0.9%
ValueCountFrequency (%)
13.7 1
0.2%
13.0 1
0.2%
12.9 1
0.2%
12.8 1
0.2%
12.7 1
0.2%
11.2 1
0.2%
10.9 1
0.2%
10.7 1
0.2%
10.4 1
0.2%
9.7 2
0.4%

Interactions

2023-12-13T06:46:15.083796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:46:14.879088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:46:15.185567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:46:14.981583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:46:22.636556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번센터명지역대읍면동리안심마을 지정여부수리형식설치년도유지관리 주체센터와 용수와의 거리
연번1.0000.9431.0000.9770.9800.0000.3440.8320.0800.669
센터명0.9431.0001.0001.0000.9990.0000.3800.7590.0000.392
지역대1.0001.0001.0001.0001.000NaN0.5840.8360.0200.477
읍면동0.9771.0001.0001.0001.0000.1010.4200.8050.0520.835
리0.9800.9991.0001.0001.0000.0000.4300.9370.0000.933
안심마을 지정여부0.0000.000NaN0.1010.0001.0000.0000.0000.0000.066
수리형식0.3440.3800.5840.4200.4300.0001.0000.8680.4940.278
설치년도0.8320.7590.8360.8050.9370.0000.8681.0000.6000.677
유지관리 주체0.0800.0000.0200.0520.0000.0000.4940.6001.0000.104
센터와 용수와의 거리0.6690.3920.4770.8350.9330.0660.2780.6770.1041.000
2023-12-13T06:46:22.760207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
센터명유지관리 주체설치년도지역대읍면동안심마을 지정여부수리형식
센터명1.0000.0000.5161.0000.9930.0000.137
유지관리 주체0.0001.0000.4660.0310.0390.0000.752
설치년도0.5160.4661.0000.6060.4220.0000.658
지역대1.0000.0310.6061.0001.0001.0000.259
읍면동0.9930.0390.4221.0001.0000.0770.277
안심마을 지정여부0.0000.0000.0001.0000.0771.0000.000
수리형식0.1370.7520.6580.2590.2770.0001.000
2023-12-13T06:46:22.866774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번센터와 용수와의 거리센터명지역대읍면동안심마을 지정여부수리형식설치년도유지관리 주체
연번1.000-0.1210.9240.9940.7350.0000.2180.4600.061
센터와 용수와의 거리-0.1211.0000.2540.3400.4030.0500.1720.3000.079
센터명0.9240.2541.0001.0000.9930.0000.1370.5160.000
지역대0.9940.3401.0001.0001.0001.0000.2590.6060.031
읍면동0.7350.4030.9931.0001.0000.0770.2770.4220.039
안심마을 지정여부0.0000.0500.0001.0000.0771.0000.0000.0000.000
수리형식0.2180.1720.1370.2590.2770.0001.0000.6580.752
설치년도0.4600.3000.5160.6060.4220.0000.6581.0000.466
유지관리 주체0.0610.0790.0000.0310.0390.0000.7520.4661.000

Missing values

2023-12-13T06:46:15.630908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:46:15.877798image/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.
2023-12-13T06:46:16.027575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번관서명센터명지역대관리번호주소읍면동주변 대상물리마을명칭안심마을 지정여부수리형식설치년도유지관리 주체센터와 용수와의 거리
01함안가야<NA>가야-저-1함안군 가야읍 말산로 25가야읍함안군여성센터 앞말산리<NA>미지정저수조1987시군1.8
12함안가야<NA>가야-저-2함안군 가야읍 선왕길 59가야읍함안소방서 입구도항리<NA>미지정저수조1999소방서0.0
23함안가야<NA>가야-상-1함안군 가야읍 말산로 25가야읍함안군여성센터 앞말산리<NA>미지정지상1993시군1.8
34함안가야<NA>가야-상-2함안군 가야읍 도항2길 57가야읍동신아파트 상가 앞도항리<NA>미지정지상2000시군0.6
45함안가야<NA>가야-상-3함안군 가야읍 검암천북길 51가야읍현대자동차 1급정비 전봇대 옆검암리<NA>미지정지상2000시군0.6
56함안가야<NA>가야-상-4함안군 가야읍 가야로 46-5가야읍BYC속옷나라 앞말산리<NA>미지정지상2003시군1.3
67함안가야<NA>가야-상-5함안군 가야읍 중앙남길 37가야읍만하정 식당 앞말산리<NA>미지정지상2004시군1.6
78함안가야<NA>가야-상-6함안군 가야읍 함안대로 534가야읍CU함안아라점 앞말산리<NA>미지정지상2004시군1.5
89함안가야<NA>가야-상-7함안군 가야읍 함안대로 539가야읍농협하나로마트 앞(정류소 앞)말산리<NA>미지정지상2004시군1.4
910함안가야<NA>가야-상-8함안군 가야읍 본동길 29가야읍옷수선집 맞은편말산리<NA>미지정지상2004시군1.4
연번관서명센터명지역대관리번호주소읍면동주변 대상물리마을명칭안심마을 지정여부수리형식설치년도유지관리 주체센터와 용수와의 거리
526527함안군북법수법수-상-38함안군 법수면 법수로 465법수면법수지역대 앞(기타지역)우거리윤산마을미지정지상1995시군2.4
527528함안군북법수법수-상-39함안군 법수면 황사길 18법수면황사마을회관앞(주거지역)황사리황사마을미지정지상2018시군3.0
528529함안군북법수법수-상-40함안군 법수면 황사공단로 4법수면광진금속 주변황사리<NA>미지정지상2018시군5.0
529530함안군북법수법수-상-41함안군 법수면 장백로 545법수면태광이엔지 주변강주리<NA>미지정지상2018시군2.7
530531함안군북법수법수-상-42함안군 법수면 주물리 533-6법수면사평마을 입구주물리사평마을미지정지상2018시군3.1
531532함안군북법수법수-상-43함안군 법수면 악양길 6법수면(악양동마을 표지석)윤외리악양동마을미지정지상2018시군5.1
532533함안군북법수법수-상-44함안군 법수면 강주2길 40법수면국계마을회관강주리국계마을미지정지상2019시군3.8
533534함안군북법수법수-상-45함안군 법수면 사정길 78법수면사정마을회관사정리사정마을미지정지상2019시군7.1
534535함안군북법수법수-상-46함안군 황사리 599-1법수면매곡마을 표지석황사리매곡마을미지정지상2020시군4.4
535536함안군북법수법수-상-47함안군 법수면 대법로 223-4법수면악양동회관윤외리악양동마을미지정지상2020시군5.6