Overview

Dataset statistics

Number of variables15
Number of observations204
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory123.6 B

Variable types

Numeric3
Categorical6
Text4
DateTime2

Dataset

Description대구광역시_민방위비상급수시설현황_20200528
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3072493&dataSetDetailId=30724931c582f28bf6c8_201905171706&provdMethod=FILE

Alerts

시도 has constant value ""Constant
연번 is highly overall correlated with 구,군High correlation
급수능력(톤/일) is highly overall correlated with 사용가능인원(명) High correlation
사용가능인원(명) is highly overall correlated with 급수능력(톤/일) and 1 other fieldsHigh correlation
구,군 is highly overall correlated with 연번High correlation
시설종류 is highly overall correlated with 개방유무High correlation
용도 is highly overall correlated with 사용가능인원(명) and 1 other fieldsHigh correlation
개방유무 is highly overall correlated with 시설종류 and 2 other fieldsHigh correlation
시설유형 is highly overall correlated with 개방유무High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-19 06:49:06.029337
Analysis finished2024-04-19 06:49:07.797186
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.5
Minimum1
Maximum204
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T15:49:07.868121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.15
Q151.75
median102.5
Q3153.25
95-th percentile193.85
Maximum204
Range203
Interquartile range (IQR)101.5

Descriptive statistics

Standard deviation59.033889
Coefficient of variation (CV)0.57594038
Kurtosis-1.2
Mean102.5
Median Absolute Deviation (MAD)51
Skewness0
Sum20910
Variance3485
MonotonicityStrictly increasing
2024-04-19T15:49:08.000712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
142 1
 
0.5%
132 1
 
0.5%
133 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%
Other values (194) 194
95.1%
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 (%)
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
대구
204 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대구 204
100.0%

Length

2024-04-19T15:49:08.126891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:08.207821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구 204
100.0%

구,군
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
달서구
46 
북구
43 
수성구
28 
동구
22 
달성군
22 
Other values (3)
43 

Length

Max length3
Median length2
Mean length2.4705882
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
달서구 46
22.5%
북구 43
21.1%
수성구 28
13.7%
동구 22
10.8%
달성군 22
10.8%
서구 17
 
8.3%
중구 15
 
7.4%
남구 11
 
5.4%

Length

2024-04-19T15:49:08.304495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:08.417423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
달서구 46
22.5%
북구 43
21.1%
수성구 28
13.7%
동구 22
10.8%
달성군 22
10.8%
서구 17
 
8.3%
중구 15
 
7.4%
남구 11
 
5.4%
Distinct99
Distinct (%)48.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T15:49:08.667470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.5686275
Min length2

Characters and Unicode

Total characters728
Distinct characters90
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

Unique44 ?
Unique (%)21.6%

Sample

1st row동인동
2nd row동인동
3rd row동인동
4th row성내1동
5th row성내1동
ValueCountFrequency (%)
다사읍 8
 
3.9%
장기동 6
 
2.9%
화원읍 5
 
2.5%
이곡1동 5
 
2.5%
산격동 5
 
2.5%
구암동 5
 
2.5%
태전동 5
 
2.5%
읍내동 4
 
2.0%
복현동 4
 
2.0%
용산1동 4
 
2.0%
Other values (89) 153
75.0%
2024-04-19T15:49:09.070436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
191
26.2%
1 37
 
5.1%
29
 
4.0%
2 27
 
3.7%
23
 
3.2%
3 20
 
2.7%
19
 
2.6%
14
 
1.9%
14
 
1.9%
4 12
 
1.6%
Other values (80) 342
47.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 619
85.0%
Decimal Number 107
 
14.7%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
191
30.9%
29
 
4.7%
23
 
3.7%
19
 
3.1%
14
 
2.3%
14
 
2.3%
12
 
1.9%
11
 
1.8%
10
 
1.6%
9
 
1.5%
Other values (71) 287
46.4%
Decimal Number
ValueCountFrequency (%)
1 37
34.6%
2 27
25.2%
3 20
18.7%
4 12
 
11.2%
5 6
 
5.6%
6 4
 
3.7%
9 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 619
85.0%
Common 109
 
15.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
191
30.9%
29
 
4.7%
23
 
3.7%
19
 
3.1%
14
 
2.3%
14
 
2.3%
12
 
1.9%
11
 
1.8%
10
 
1.6%
9
 
1.5%
Other values (71) 287
46.4%
Common
ValueCountFrequency (%)
1 37
33.9%
2 27
24.8%
3 20
18.3%
4 12
 
11.0%
5 6
 
5.5%
6 4
 
3.7%
9 1
 
0.9%
, 1
 
0.9%
. 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 619
85.0%
ASCII 109
 
15.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
191
30.9%
29
 
4.7%
23
 
3.7%
19
 
3.1%
14
 
2.3%
14
 
2.3%
12
 
1.9%
11
 
1.8%
10
 
1.6%
9
 
1.5%
Other values (71) 287
46.4%
ASCII
ValueCountFrequency (%)
1 37
33.9%
2 27
24.8%
3 20
18.3%
4 12
 
11.0%
5 6
 
5.5%
6 4
 
3.7%
9 1
 
0.9%
, 1
 
0.9%
. 1
 
0.9%

시설종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
공공용
124 
정부지원
58 
지자체
22 

Length

Max length4
Median length3
Mean length3.2843137
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row정부지원
2nd row정부지원
3rd row정부지원
4th row정부지원
5th row공공용

Common Values

ValueCountFrequency (%)
공공용 124
60.8%
정부지원 58
28.4%
지자체 22
 
10.8%

Length

2024-04-19T15:49:09.197614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:09.304716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공공용 124
60.8%
정부지원 58
28.4%
지자체 22
 
10.8%

용도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
생활용수
149 
음용수
55 

Length

Max length4
Median length4
Mean length3.7303922
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row생활용수
2nd row생활용수
3rd row생활용수
4th row음용수
5th row생활용수

Common Values

ValueCountFrequency (%)
생활용수 149
73.0%
음용수 55
 
27.0%

Length

2024-04-19T15:49:09.433619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:09.528843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활용수 149
73.0%
음용수 55
 
27.0%

개방유무
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
미개방
167 
개방
37 

Length

Max length3
Median length3
Mean length2.8186275
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row미개방
2nd row미개방
3rd row미개방
4th row개방
5th row미개방

Common Values

ValueCountFrequency (%)
미개방 167
81.9%
개방 37
 
18.1%

Length

2024-04-19T15:49:09.895795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:09.984827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
미개방 167
81.9%
개방 37
 
18.1%
Distinct202
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T15:49:10.200412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length14
Mean length8.4068627
Min length3

Characters and Unicode

Total characters1715
Distinct characters266
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)98.0%

Sample

1st row동인아파트비상급수시설
2nd row78태평아파트비상급수시설
3rd row국채보상기념공원비상급수시설
4th row제일중학교비상급수시설
5th row대구백화점비상급수시설
ValueCountFrequency (%)
비상급수시설 24
 
9.9%
목욕탕 4
 
1.6%
계명대학교 2
 
0.8%
2
 
0.8%
장수탕 2
 
0.8%
청소년수련관 2
 
0.8%
국립대구박물관 1
 
0.4%
청소년어린이공원 1
 
0.4%
보건환경연구원 1
 
0.4%
동아스포츠센터 1
 
0.4%
Other values (203) 203
83.5%
2024-04-19T15:49:10.578678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
81
 
4.7%
74
 
4.3%
70
 
4.1%
67
 
3.9%
66
 
3.8%
66
 
3.8%
41
 
2.4%
39
 
2.3%
38
 
2.2%
34
 
2.0%
Other values (256) 1139
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1588
92.6%
Decimal Number 41
 
2.4%
Space Separator 39
 
2.3%
Close Punctuation 16
 
0.9%
Open Punctuation 16
 
0.9%
Other Symbol 8
 
0.5%
Uppercase Letter 5
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
81
 
5.1%
74
 
4.7%
70
 
4.4%
67
 
4.2%
66
 
4.2%
66
 
4.2%
41
 
2.6%
38
 
2.4%
34
 
2.1%
27
 
1.7%
Other values (239) 1024
64.5%
Decimal Number
ValueCountFrequency (%)
2 17
41.5%
1 13
31.7%
3 3
 
7.3%
5 3
 
7.3%
0 2
 
4.9%
8 1
 
2.4%
7 1
 
2.4%
4 1
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
K 2
40.0%
T 1
20.0%
P 1
20.0%
A 1
20.0%
Space Separator
ValueCountFrequency (%)
39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Other Symbol
ValueCountFrequency (%)
8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1596
93.1%
Common 114
 
6.6%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
81
 
5.1%
74
 
4.6%
70
 
4.4%
67
 
4.2%
66
 
4.1%
66
 
4.1%
41
 
2.6%
38
 
2.4%
34
 
2.1%
27
 
1.7%
Other values (240) 1032
64.7%
Common
ValueCountFrequency (%)
39
34.2%
2 17
14.9%
) 16
14.0%
( 16
14.0%
1 13
 
11.4%
3 3
 
2.6%
5 3
 
2.6%
- 2
 
1.8%
0 2
 
1.8%
8 1
 
0.9%
Other values (2) 2
 
1.8%
Latin
ValueCountFrequency (%)
K 2
40.0%
T 1
20.0%
P 1
20.0%
A 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1588
92.6%
ASCII 119
 
6.9%
None 8
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
81
 
5.1%
74
 
4.7%
70
 
4.4%
67
 
4.2%
66
 
4.2%
66
 
4.2%
41
 
2.6%
38
 
2.4%
34
 
2.1%
27
 
1.7%
Other values (239) 1024
64.5%
ASCII
ValueCountFrequency (%)
39
32.8%
2 17
14.3%
) 16
13.4%
( 16
13.4%
1 13
 
10.9%
3 3
 
2.5%
5 3
 
2.5%
K 2
 
1.7%
- 2
 
1.7%
0 2
 
1.7%
Other values (6) 6
 
5.0%
None
ValueCountFrequency (%)
8
100.0%

시설유형
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
상업시설
71 
주거시설
42 
공원
29 
기타
17 
교육시설
13 
Other values (5)
32 

Length

Max length4
Median length4
Mean length3.5196078
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row주거시설
2nd row주거시설
3rd row공원
4th row교육시설
5th row상업시설

Common Values

ValueCountFrequency (%)
상업시설 71
34.8%
주거시설 42
20.6%
공원 29
14.2%
기타 17
 
8.3%
교육시설 13
 
6.4%
체육시설 13
 
6.4%
복지시설 7
 
3.4%
관공서 6
 
2.9%
공공기관 5
 
2.5%
숙박시설 1
 
0.5%

Length

2024-04-19T15:49:10.719709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T15:49:10.842282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업시설 71
34.8%
주거시설 42
20.6%
공원 29
14.2%
기타 17
 
8.3%
교육시설 13
 
6.4%
체육시설 13
 
6.4%
복지시설 7
 
3.4%
관공서 6
 
2.9%
공공기관 5
 
2.5%
숙박시설 1
 
0.5%
Distinct189
Distinct (%)93.6%
Missing2
Missing (%)1.0%
Memory size1.7 KiB
2024-04-19T15:49:11.177441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length19.232673
Min length6

Characters and Unicode

Total characters3885
Distinct characters168
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

Unique177 ?
Unique (%)87.6%

Sample

1st row대구광역시 중구 국채보상로149길 50(동인동3가)
2nd row대구광역시 중구 태평로 225(동인동1가)
3rd row대구광역시 중구 공평로10길 25(동인동2가)
4th row대구광역시 중구 명륜로23길 16(봉산동)
5th row대구광역시 중구 동성로 30(동성로2가)
ValueCountFrequency (%)
대구광역시 150
 
18.8%
북구 41
 
5.1%
수성구 28
 
3.5%
달성군 22
 
2.8%
동구 21
 
2.6%
서구 17
 
2.1%
중구 13
 
1.6%
남구 11
 
1.4%
달구벌대로 9
 
1.1%
다사읍 7
 
0.9%
Other values (349) 480
60.1%
2024-04-19T15:49:11.686223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
607
 
15.6%
307
 
7.9%
196
 
5.0%
190
 
4.9%
166
 
4.3%
159
 
4.1%
155
 
4.0%
153
 
3.9%
1 132
 
3.4%
) 119
 
3.1%
Other values (158) 1701
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2382
61.3%
Decimal Number 639
 
16.4%
Space Separator 607
 
15.6%
Close Punctuation 119
 
3.1%
Open Punctuation 119
 
3.1%
Dash Punctuation 19
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
307
 
12.9%
196
 
8.2%
190
 
8.0%
166
 
7.0%
159
 
6.7%
155
 
6.5%
153
 
6.4%
75
 
3.1%
72
 
3.0%
52
 
2.2%
Other values (144) 857
36.0%
Decimal Number
ValueCountFrequency (%)
1 132
20.7%
2 97
15.2%
5 74
11.6%
3 60
9.4%
0 58
9.1%
4 55
8.6%
6 50
 
7.8%
9 44
 
6.9%
7 37
 
5.8%
8 32
 
5.0%
Space Separator
ValueCountFrequency (%)
607
100.0%
Close Punctuation
ValueCountFrequency (%)
) 119
100.0%
Open Punctuation
ValueCountFrequency (%)
( 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2382
61.3%
Common 1503
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
307
 
12.9%
196
 
8.2%
190
 
8.0%
166
 
7.0%
159
 
6.7%
155
 
6.5%
153
 
6.4%
75
 
3.1%
72
 
3.0%
52
 
2.2%
Other values (144) 857
36.0%
Common
ValueCountFrequency (%)
607
40.4%
1 132
 
8.8%
) 119
 
7.9%
( 119
 
7.9%
2 97
 
6.5%
5 74
 
4.9%
3 60
 
4.0%
0 58
 
3.9%
4 55
 
3.7%
6 50
 
3.3%
Other values (4) 132
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2382
61.3%
ASCII 1503
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
607
40.4%
1 132
 
8.8%
) 119
 
7.9%
( 119
 
7.9%
2 97
 
6.5%
5 74
 
4.9%
3 60
 
4.0%
0 58
 
3.9%
4 55
 
3.7%
6 50
 
3.3%
Other values (4) 132
 
8.8%
Hangul
ValueCountFrequency (%)
307
 
12.9%
196
 
8.2%
190
 
8.0%
166
 
7.0%
159
 
6.7%
155
 
6.5%
153
 
6.4%
75
 
3.1%
72
 
3.0%
52
 
2.2%
Other values (144) 857
36.0%
Distinct189
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-19T15:49:12.031306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length22
Mean length14.161765
Min length5

Characters and Unicode

Total characters2889
Distinct characters110
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

Unique175 ?
Unique (%)85.8%

Sample

1st row대구광역시 중구 동인동3가 228
2nd row대구광역시 중구 동인동1가 116
3rd row대구광역시 중구 동인동2가 78
4th row대구광역시 중구 봉산동 230-1
5th row대구광역시 중구 동성로2가 174
ValueCountFrequency (%)
대구광역시 104
 
16.3%
수성구 28
 
4.4%
동구 22
 
3.4%
달성군 22
 
3.4%
서구 17
 
2.7%
중구 15
 
2.3%
다사읍 7
 
1.1%
이곡동 7
 
1.1%
용산동 7
 
1.1%
범어동 6
 
0.9%
Other values (291) 404
63.2%
2024-04-19T15:49:12.491430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
436
 
15.1%
210
 
7.3%
1 198
 
6.9%
193
 
6.7%
- 121
 
4.2%
120
 
4.2%
105
 
3.6%
104
 
3.6%
104
 
3.6%
2 100
 
3.5%
Other values (100) 1198
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1497
51.8%
Decimal Number 835
28.9%
Space Separator 436
 
15.1%
Dash Punctuation 121
 
4.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
210
14.0%
193
 
12.9%
120
 
8.0%
105
 
7.0%
104
 
6.9%
104
 
6.9%
62
 
4.1%
34
 
2.3%
33
 
2.2%
29
 
1.9%
Other values (88) 503
33.6%
Decimal Number
ValueCountFrequency (%)
1 198
23.7%
2 100
12.0%
3 85
10.2%
4 77
 
9.2%
5 69
 
8.3%
0 67
 
8.0%
7 67
 
8.0%
8 63
 
7.5%
6 61
 
7.3%
9 48
 
5.7%
Space Separator
ValueCountFrequency (%)
436
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 121
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1497
51.8%
Common 1392
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
210
14.0%
193
 
12.9%
120
 
8.0%
105
 
7.0%
104
 
6.9%
104
 
6.9%
62
 
4.1%
34
 
2.3%
33
 
2.2%
29
 
1.9%
Other values (88) 503
33.6%
Common
ValueCountFrequency (%)
436
31.3%
1 198
14.2%
- 121
 
8.7%
2 100
 
7.2%
3 85
 
6.1%
4 77
 
5.5%
5 69
 
5.0%
0 67
 
4.8%
7 67
 
4.8%
8 63
 
4.5%
Other values (2) 109
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1497
51.8%
ASCII 1392
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
436
31.3%
1 198
14.2%
- 121
 
8.7%
2 100
 
7.2%
3 85
 
6.1%
4 77
 
5.5%
5 69
 
5.0%
0 67
 
4.8%
7 67
 
4.8%
8 63
 
4.5%
Other values (2) 109
 
7.8%
Hangul
ValueCountFrequency (%)
210
14.0%
193
 
12.9%
120
 
8.0%
105
 
7.0%
104
 
6.9%
104
 
6.9%
62
 
4.1%
34
 
2.3%
33
 
2.2%
29
 
1.9%
Other values (88) 503
33.6%

급수능력(톤/일)
Real number (ℝ)

HIGH CORRELATION 

Distinct91
Distinct (%)44.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean330.23529
Minimum20
Maximum1500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T15:49:12.637186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile80.6
Q1191.5
median288
Q3400
95-th percentile700
Maximum1500
Range1480
Interquartile range (IQR)208.5

Descriptive statistics

Standard deviation231.36309
Coefficient of variation (CV)0.70060074
Kurtosis5.418862
Mean330.23529
Median Absolute Deviation (MAD)112
Skewness1.9049064
Sum67368
Variance53528.88
MonotonicityNot monotonic
2024-04-19T15:49:12.783413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200 17
 
8.3%
300 16
 
7.8%
250 10
 
4.9%
150 8
 
3.9%
400 8
 
3.9%
500 8
 
3.9%
700 7
 
3.4%
100 5
 
2.5%
210 5
 
2.5%
320 4
 
2.0%
Other values (81) 116
56.9%
ValueCountFrequency (%)
20 1
0.5%
40 1
0.5%
45 1
0.5%
50 1
0.5%
60 1
0.5%
63 2
1.0%
70 1
0.5%
75 2
1.0%
80 1
0.5%
84 1
0.5%
ValueCountFrequency (%)
1500 1
 
0.5%
1350 1
 
0.5%
1200 1
 
0.5%
1122 1
 
0.5%
1000 1
 
0.5%
906 1
 
0.5%
900 1
 
0.5%
800 1
 
0.5%
706 1
 
0.5%
700 7
3.4%

사용가능인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct107
Distinct (%)52.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26002.75
Minimum1250
Maximum166666
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-19T15:49:12.932965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1250
5-th percentile5306.25
Q112500
median19500
Q333437.25
95-th percentile65832.75
Maximum166666
Range165416
Interquartile range (IQR)20937.25

Descriptive statistics

Standard deviation22225.901
Coefficient of variation (CV)0.85475193
Kurtosis12.252579
Mean26002.75
Median Absolute Deviation (MAD)10562.5
Skewness2.7462728
Sum5304561
Variance4.9399067 × 108
MonotonicityNot monotonic
2024-04-19T15:49:13.059227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12500 12
 
5.9%
15625 9
 
4.4%
33333 9
 
4.4%
9375 7
 
3.4%
18750 7
 
3.4%
44444 6
 
2.9%
22222 5
 
2.5%
6250 5
 
2.5%
43750 5
 
2.5%
13125 5
 
2.5%
Other values (97) 134
65.7%
ValueCountFrequency (%)
1250 1
 
0.5%
2500 1
 
0.5%
2812 1
 
0.5%
3125 1
 
0.5%
3937 2
1.0%
4375 1
 
0.5%
4687 2
1.0%
5000 1
 
0.5%
5250 1
 
0.5%
5625 4
2.0%
ValueCountFrequency (%)
166666 1
0.5%
150000 1
0.5%
111111 1
0.5%
77777 2
1.0%
75000 1
0.5%
71111 2
1.0%
70125 1
0.5%
66666 2
1.0%
61111 1
0.5%
60222 1
0.5%
Distinct162
Distinct (%)79.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1968-12-04 00:00:00
Maximum2019-02-19 00:00:00
2024-04-19T15:49:13.182243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:13.307960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct141
Distinct (%)69.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum1978-12-26 00:00:00
Maximum2019-05-23 00:00:00
2024-04-19T15:49:13.444186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:13.584956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-04-19T15:49:07.218494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:06.694769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:06.969656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:07.305378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:06.782942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:07.053141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:07.388452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:06.877015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T15:49:07.137829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T15:49:13.698898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구,군읍,면,동시설종류용도개방유무시설유형급수능력(톤/일)사용가능인원(명)
연번1.0000.9310.9740.5180.3650.4700.5350.3470.063
구,군0.9311.0001.0000.2670.0000.2900.4220.2780.000
읍,면,동0.9741.0001.0000.5180.5420.5510.8180.8200.805
시설종류0.5180.2670.5181.0000.2830.3130.6290.3050.434
용도0.3650.0000.5420.2831.0000.9290.6010.3930.693
개방유무0.4700.2900.5510.3130.9291.0000.7520.2250.479
시설유형0.5350.4220.8180.6290.6010.7521.0000.4330.276
급수능력(톤/일)0.3470.2780.8200.3050.3930.2250.4331.0000.936
사용가능인원(명)0.0630.0000.8050.4340.6930.4790.2760.9361.000
2024-04-19T15:49:13.815739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설유형개방유무시설종류구,군용도
시설유형1.0000.5790.4660.2150.456
개방유무0.5791.0000.5030.2140.759
시설종류0.4660.5031.0000.1730.457
구,군0.2150.2140.1731.0000.000
용도0.4560.7590.4570.0001.000
2024-04-19T15:49:13.920957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번급수능력(톤/일)사용가능인원(명)구,군시설종류용도개방유무시설유형
연번1.000-0.210-0.1670.7930.3560.2740.3540.189
급수능력(톤/일)-0.2101.0000.9340.1340.1880.2950.1690.145
사용가능인원(명)-0.1670.9341.0000.0000.3040.5220.3560.135
구,군0.7930.1340.0001.0000.1730.0000.2140.215
시설종류0.3560.1880.3040.1731.0000.4570.5030.466
용도0.2740.2950.5220.0000.4571.0000.7590.456
개방유무0.3540.1690.3560.2140.5030.7591.0000.579
시설유형0.1890.1450.1350.2150.4660.4560.5791.000

Missing values

2024-04-19T15:49:07.548077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T15:49:07.727062image/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

연번시도구,군읍,면,동시설종류용도개방유무급수시설명시설유형도로명 주소지번주소급수능력(톤/일)사용가능인원(명)시설 건축연도지정/운영시작
01대구중구동인동정부지원생활용수미개방동인아파트비상급수시설주거시설대구광역시 중구 국채보상로149길 50(동인동3가)대구광역시 중구 동인동3가 228314196251982-01-011982-06-09
12대구중구동인동정부지원생활용수미개방78태평아파트비상급수시설주거시설대구광역시 중구 태평로 225(동인동1가)대구광역시 중구 동인동1가 116374233751978-01-011992-05-31
23대구중구동인동정부지원생활용수미개방국채보상기념공원비상급수시설공원대구광역시 중구 공평로10길 25(동인동2가)대구광역시 중구 동인동2가 78906566251999-12-211980-12-20
34대구중구성내1동정부지원음용수개방제일중학교비상급수시설교육시설대구광역시 중구 명륜로23길 16(봉산동)대구광역시 중구 봉산동 230-1390433331997-04-201997-12-02
45대구중구성내1동공공용생활용수미개방대구백화점비상급수시설상업시설대구광역시 중구 동성로 30(동성로2가)대구광역시 중구 동성로2가 174280175001969-12-261978-12-26
56대구중구성내1동공공용생활용수미개방궁전사우나비상급수시설상업시설대구광역시 중구 국채보상로123길 5(문화동)대구광역시 중구 문화동 12-18200125001983-01-011992-05-31
67대구중구성내2동정부지원생활용수미개방경상감영공원비상급수시설공원대구광역시 중구 경상감영길 99(포정동)대구광역시 중구 포정동 21500312501982-01-011982-10-10
78대구중구성내2동지자체생활용수미개방대구콘서트하우스비상급수시설상업시설대구광역시 중구 태평로 141(태평로2가)대구광역시 중구 태평로2가 1350218751983-10-051983-10-05
89대구중구성내2동공공용생활용수미개방동아쇼핑비상급수시설상업시설대구광역시 중구 달구벌대로 2085(덕산동)대구광역시 중구 덕산동 53-3175109371984-01-011992-05-31
910대구중구성내3동공공용생활용수미개방시민사우나비상급수시설상업시설대구광역시 중구 달성공원로 2(대신동)대구광역시 중구 대신동 179-4160100001984-05-012018-09-20
연번시도구,군읍,면,동시설종류용도개방유무급수시설명시설유형도로명 주소지번주소급수능력(톤/일)사용가능인원(명)시설 건축연도지정/운영시작
194195대구달성군다사읍공공용생활용수미개방㈜ 선샤안스포츠2체육시설대구광역시시 달성군 다사읍 대실역북로2길 8-6대구광역시 달성군 다사읍 매곡리 1549-2번지13081252013-01-072017-12-06
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