Overview

Dataset statistics

Number of variables13
Number of observations40
Missing cells37
Missing cells (%)7.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory111.2 B

Variable types

Numeric4
Text3
Categorical4
Boolean2

Dataset

Description대전광역시 중구에 위치한 안심화장실 정보입니다.This is information on a safe restroom located in Jung-gu, Daejeon.
Author대전광역시 중구
URLhttps://www.data.go.kr/data/15126560/fileData.do

Alerts

비상벨 설치여부 has constant value ""Constant
운영시간 has constant value ""Constant
담당부서 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
불법촬영탐지시스템 설치여부 is highly overall correlated with 담당부서High correlation
연번 is highly overall correlated with 담당부서High correlation
경도 is highly overall correlated with 위도High correlation
위도 is highly overall correlated with 경도High correlation
구분 is highly overall correlated with 형식 and 1 other fieldsHigh correlation
형식 is highly overall correlated with 구분High correlation
형식 is highly imbalanced (61.6%)Imbalance
불법촬영탐지시스템 설치여부 is highly imbalanced (83.1%)Imbalance
기타 has 37 (92.5%) missing valuesMissing
연번 has unique valuesUnique
장소명 has unique valuesUnique
경도 has unique valuesUnique
위도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:18:37.210986
Analysis finished2024-03-14 12:18:43.166101
Duration5.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.5
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T21:18:43.367648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.95
Q110.75
median20.5
Q330.25
95-th percentile38.05
Maximum40
Range39
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation11.690452
Coefficient of variation (CV)0.57026595
Kurtosis-1.2
Mean20.5
Median Absolute Deviation (MAD)10
Skewness0
Sum820
Variance136.66667
MonotonicityStrictly increasing
2024-03-14T21:18:43.633482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
1 1
 
2.5%
22 1
 
2.5%
24 1
 
2.5%
25 1
 
2.5%
26 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 1
 
2.5%
30 1
 
2.5%
31 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
1 1
2.5%
2 1
2.5%
3 1
2.5%
4 1
2.5%
5 1
2.5%
6 1
2.5%
7 1
2.5%
8 1
2.5%
9 1
2.5%
10 1
2.5%
ValueCountFrequency (%)
40 1
2.5%
39 1
2.5%
38 1
2.5%
37 1
2.5%
36 1
2.5%
35 1
2.5%
34 1
2.5%
33 1
2.5%
32 1
2.5%
31 1
2.5%

장소명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-03-14T21:18:44.533502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.625
Min length4

Characters and Unicode

Total characters305
Distinct characters108
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

Unique40 ?
Unique (%)100.0%

Sample

1st row단재신채호선생생가지
2nd row중촌육교 아래
3rd row무수동 농촌전통테마마을
4th row은행동상점가 고객지원센터
5th row대전천변 공중화장실
ValueCountFrequency (%)
아래 2
 
3.8%
뿌리공원 2
 
3.8%
중촌근린공원 2
 
3.8%
단재신채호선생생가지 1
 
1.9%
보문산 1
 
1.9%
경로공원 1
 
1.9%
탑골어린이공원 1
 
1.9%
당대어린이공원 1
 
1.9%
푸른어린이공원 1
 
1.9%
안영2어린이공원 1
 
1.9%
Other values (40) 40
75.5%
2024-03-14T21:18:45.883605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 26
 
8.5%
공 26
 
8.5%
린 18
 
5.9%
이 14
 
4.6%
어 14
 
4.6%
13
 
4.3%
장 12
 
3.9%
대 8
 
2.6%
전 7
 
2.3%
중 6
 
2.0%
Other values (98) 161
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 286
93.8%
Space Separator 13
 
4.3%
Open Punctuation 2
 
0.7%
Close Punctuation 2
 
0.7%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 26
 
9.1%
공 26
 
9.1%
린 18
 
6.3%
이 14
 
4.9%
어 14
 
4.9%
장 12
 
4.2%
대 8
 
2.8%
전 7
 
2.4%
중 6
 
2.1%
근 5
 
1.7%
Other values (93) 150
52.4%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 286
93.8%
Common 19
 
6.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 26
 
9.1%
공 26
 
9.1%
린 18
 
6.3%
이 14
 
4.9%
어 14
 
4.9%
장 12
 
4.2%
대 8
 
2.8%
전 7
 
2.4%
중 6
 
2.1%
근 5
 
1.7%
Other values (93) 150
52.4%
Common
ValueCountFrequency (%)
13
68.4%
( 2
 
10.5%
) 2
 
10.5%
1 1
 
5.3%
2 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 286
93.8%
ASCII 19
 
6.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 26
 
9.1%
공 26
 
9.1%
린 18
 
6.3%
이 14
 
4.9%
어 14
 
4.9%
장 12
 
4.2%
대 8
 
2.8%
전 7
 
2.4%
중 6
 
2.1%
근 5
 
1.7%
Other values (93) 150
52.4%
ASCII
ValueCountFrequency (%)
13
68.4%
( 2
 
10.5%
) 2
 
10.5%
1 1
 
5.3%
2 1
 
5.3%

주소
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
2024-03-14T21:18:46.912655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length10.7
Min length5

Characters and Unicode

Total characters428
Distinct characters53
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

Unique38 ?
Unique (%)95.0%

Sample

1st row단재로229번길 29
2nd row중촌동 143-1
3rd row운남로85번길 32-8
4th row중교로83
5th row대전천서로 439 (은행동)
ValueCountFrequency (%)
23 3
 
3.7%
중촌동 3
 
3.7%
유등천동로 3
 
3.7%
계백로1716번길 2
 
2.4%
문화동 2
 
2.4%
뿌리공원로 2
 
2.4%
대전천서로 2
 
2.4%
은행동 2
 
2.4%
180 2
 
2.4%
용두로28번길 2
 
2.4%
Other values (59) 59
72.0%
2024-03-14T21:18:48.326396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
42
 
9.8%
1 33
 
7.7%
로 32
 
7.5%
2 24
 
5.6%
4 24
 
5.6%
3 22
 
5.1%
번 22
 
5.1%
길 22
 
5.1%
6 16
 
3.7%
동 15
 
3.5%
Other values (43) 176
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 194
45.3%
Decimal Number 174
40.7%
Space Separator 42
 
9.8%
Dash Punctuation 14
 
3.3%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 32
16.5%
번 22
 
11.3%
길 22
 
11.3%
동 15
 
7.7%
문 9
 
4.6%
천 8
 
4.1%
대 6
 
3.1%
산 6
 
3.1%
서 6
 
3.1%
화 6
 
3.1%
Other values (29) 62
32.0%
Decimal Number
ValueCountFrequency (%)
1 33
19.0%
2 24
13.8%
4 24
13.8%
3 22
12.6%
6 16
9.2%
9 13
 
7.5%
7 13
 
7.5%
8 12
 
6.9%
5 11
 
6.3%
0 6
 
3.4%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 234
54.7%
Hangul 194
45.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 32
16.5%
번 22
 
11.3%
길 22
 
11.3%
동 15
 
7.7%
문 9
 
4.6%
천 8
 
4.1%
대 6
 
3.1%
산 6
 
3.1%
서 6
 
3.1%
화 6
 
3.1%
Other values (29) 62
32.0%
Common
ValueCountFrequency (%)
42
17.9%
1 33
14.1%
2 24
10.3%
4 24
10.3%
3 22
9.4%
6 16
 
6.8%
- 14
 
6.0%
9 13
 
5.6%
7 13
 
5.6%
8 12
 
5.1%
Other values (4) 21
9.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 234
54.7%
Hangul 194
45.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
42
17.9%
1 33
14.1%
2 24
10.3%
4 24
10.3%
3 22
9.4%
6 16
 
6.8%
- 14
 
6.0%
9 13
 
5.6%
7 13
 
5.6%
8 12
 
5.1%
Other values (4) 21
9.0%
Hangul
ValueCountFrequency (%)
로 32
16.5%
번 22
 
11.3%
길 22
 
11.3%
동 15
 
7.7%
문 9
 
4.6%
천 8
 
4.1%
대 6
 
3.1%
산 6
 
3.1%
서 6
 
3.1%
화 6
 
3.1%
Other values (29) 62
32.0%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.40449
Minimum127.37902
Maximum127.4298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T21:18:48.736460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.37902
5-th percentile127.38453
Q1127.39395
median127.4044
Q3127.41534
95-th percentile127.42837
Maximum127.4298
Range0.0507811
Interquartile range (IQR)0.02139825

Descriptive statistics

Standard deviation0.013961677
Coefficient of variation (CV)0.00010958544
Kurtosis-0.96079203
Mean127.40449
Median Absolute Deviation (MAD)0.0109715
Skewness0.058170384
Sum5096.1796
Variance0.00019492841
MonotonicityNot monotonic
2024-03-14T21:18:49.179106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
127.4102795 1
 
2.5%
127.383992 1
 
2.5%
127.391252 1
 
2.5%
127.416685 1
 
2.5%
127.379017 1
 
2.5%
127.402967 1
 
2.5%
127.396006 1
 
2.5%
127.394891 1
 
2.5%
127.415439 1
 
2.5%
127.399204 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
127.379017 1
2.5%
127.383992 1
2.5%
127.384559 1
2.5%
127.384577 1
2.5%
127.385399 1
2.5%
127.386453 1
2.5%
127.388387 1
2.5%
127.391069 1
2.5%
127.391252 1
2.5%
127.391493 1
2.5%
ValueCountFrequency (%)
127.4297981 1
2.5%
127.4285332 1
2.5%
127.428357 1
2.5%
127.4240933 1
2.5%
127.421333 1
2.5%
127.4211595 1
2.5%
127.420629 1
2.5%
127.4200678 1
2.5%
127.416685 1
2.5%
127.415439 1
2.5%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.315313
Minimum36.232452
Maximum36.343714
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T21:18:49.580684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.232452
5-th percentile36.284366
Q136.306021
median36.319841
Q336.328224
95-th percentile36.342786
Maximum36.343714
Range0.11126178
Interquartile range (IQR)0.02220239

Descriptive statistics

Standard deviation0.021546511
Coefficient of variation (CV)0.00059331752
Kurtosis4.3557854
Mean36.315313
Median Absolute Deviation (MAD)0.0112517
Skewness-1.6102873
Sum1452.6125
Variance0.00046425215
MonotonicityNot monotonic
2024-03-14T21:18:49.994953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
36.23245222 1
 
2.5%
36.3036 1
 
2.5%
36.308602 1
 
2.5%
36.335239 1
 
2.5%
36.290172 1
 
2.5%
36.331959 1
 
2.5%
36.312626 1
 
2.5%
36.320543 1
 
2.5%
36.338585 1
 
2.5%
36.324478 1
 
2.5%
Other values (30) 30
75.0%
ValueCountFrequency (%)
36.23245222 1
2.5%
36.2782609 1
2.5%
36.284687 1
2.5%
36.285531 1
2.5%
36.287271 1
2.5%
36.290172 1
2.5%
36.299806 1
2.5%
36.3036 1
2.5%
36.304877 1
2.5%
36.305207 1
2.5%
ValueCountFrequency (%)
36.343714 1
2.5%
36.34326089 1
2.5%
36.34276094 1
2.5%
36.339128 1
2.5%
36.338585 1
2.5%
36.335239 1
2.5%
36.331959 1
2.5%
36.3311054 1
2.5%
36.33106288 1
2.5%
36.328618 1
2.5%

구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
공원
23 
체육시설
3 
관광지
3 
저소득
3 
주차장
3 
Other values (3)
5 

Length

Max length4
Median length2
Mean length2.425
Min length2

Unique

Unique1 ?
Unique (%)2.5%

Sample

1st row문화재
2nd row체육시설
3rd row문화재
4th row기타
5th row천변

Common Values

ValueCountFrequency (%)
공원 23
57.5%
체육시설 3
 
7.5%
관광지 3
 
7.5%
저소득 3
 
7.5%
주차장 3
 
7.5%
문화재 2
 
5.0%
기타 2
 
5.0%
천변 1
 
2.5%

Length

2024-03-14T21:18:50.440364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:18:50.814971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공원 23
57.5%
체육시설 3
 
7.5%
관광지 3
 
7.5%
저소득 3
 
7.5%
주차장 3
 
7.5%
문화재 2
 
5.0%
기타 2
 
5.0%
천변 1
 
2.5%

면적
Real number (ℝ)

Distinct31
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.7115
Minimum2.64
Maximum162.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size488.0 B
2024-03-14T21:18:51.192715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.64
5-th percentile3.9605
Q110.815
median20.625
Q339.0825
95-th percentile93.055
Maximum162.02
Range159.38
Interquartile range (IQR)28.2675

Descriptive statistics

Standard deviation33.841497
Coefficient of variation (CV)1.0345443
Kurtosis4.5212906
Mean32.7115
Median Absolute Deviation (MAD)11.325
Skewness2.003821
Sum1308.46
Variance1145.2469
MonotonicityNot monotonic
2024-03-14T21:18:51.614780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
18.0 5
 
12.5%
2.64 2
 
5.0%
31.44 2
 
5.0%
4.03 2
 
5.0%
9.0 2
 
5.0%
21.0 2
 
5.0%
10.29 1
 
2.5%
27.0 1
 
2.5%
12.0 1
 
2.5%
90.0 1
 
2.5%
Other values (21) 21
52.5%
ValueCountFrequency (%)
2.64 2
5.0%
4.03 2
5.0%
4.9 1
2.5%
6.7 1
2.5%
9.0 2
5.0%
9.6 1
2.5%
10.29 1
2.5%
10.99 1
2.5%
12.0 1
2.5%
12.42 1
2.5%
ValueCountFrequency (%)
162.02 1
2.5%
96.95 1
2.5%
92.85 1
2.5%
90.0 1
2.5%
88.44 1
2.5%
75.18 1
2.5%
62.02 1
2.5%
56.7 1
2.5%
41.3 1
2.5%
40.5 1
2.5%

형식
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size448.0 B
수세식
37 
간 이
 
3

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수세식
2nd row간 이
3rd row수세식
4th row수세식
5th row수세식

Common Values

ValueCountFrequency (%)
수세식 37
92.5%
간 이 3
 
7.5%

Length

2024-03-14T21:18:52.027019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:18:52.335110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수세식 37
86.0%
간 3
 
7.0%
이 3
 
7.0%

담당부서
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
공원녹지과
24 
환경과
7 
일자리경제과
3 
문화체육과
 
2
뿌리공원과
 
2
Other values (2)
 
2

Length

Max length6
Median length5
Mean length4.65
Min length3

Unique

Unique2 ?
Unique (%)5.0%

Sample

1st row문화체육과
2nd row문화체육과
3rd row일자리경제과
4th row일자리경제과
5th row일자리경제과

Common Values

ValueCountFrequency (%)
공원녹지과 24
60.0%
환경과 7
 
17.5%
일자리경제과 3
 
7.5%
문화체육과 2
 
5.0%
뿌리공원과 2
 
5.0%
효문화과 1
 
2.5%
교통과 1
 
2.5%

Length

2024-03-14T21:18:52.706992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:18:52.914751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공원녹지과 24
60.0%
환경과 7
 
17.5%
일자리경제과 3
 
7.5%
문화체육과 2
 
5.0%
뿌리공원과 2
 
5.0%
효문화과 1
 
2.5%
교통과 1
 
2.5%

비상벨 설치여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size168.0 B
True
40 
ValueCountFrequency (%)
True 40
100.0%
2024-03-14T21:18:53.105330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

불법촬영탐지시스템 설치여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size168.0 B
True
39 
False
 
1
ValueCountFrequency (%)
True 39
97.5%
False 1
 
2.5%
2024-03-14T21:18:53.259434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

운영시간
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size448.0 B
상시개방
40 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상시개방 40
100.0%

Length

2024-03-14T21:18:53.433629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:18:53.648218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상시개방 40
100.0%

기타
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing37
Missing (%)92.5%
Memory size448.0 B
2024-03-14T21:18:54.288405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length10.666667
Min length7

Characters and Unicode

Total characters32
Distinct characters26
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

Unique3 ?
Unique (%)100.0%

Sample

1st row구. 용정아파트 아래 기와
2nd row태양솜공장 옆
3rd row한마음정육식당 맞은편
ValueCountFrequency (%)
구 1
12.5%
용정아파트 1
12.5%
아래 1
12.5%
기와 1
12.5%
태양솜공장 1
12.5%
옆 1
12.5%
한마음정육식당 1
12.5%
맞은편 1
12.5%
2024-03-14T21:18:55.132573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
15.6%
정 2
 
6.2%
아 2
 
6.2%
구 1
 
3.1%
장 1
 
3.1%
은 1
 
3.1%
맞 1
 
3.1%
당 1
 
3.1%
식 1
 
3.1%
육 1
 
3.1%
Other values (16) 16
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26
81.2%
Space Separator 5
 
15.6%
Other Punctuation 1
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 2
 
7.7%
아 2
 
7.7%
구 1
 
3.8%
장 1
 
3.8%
은 1
 
3.8%
맞 1
 
3.8%
당 1
 
3.8%
식 1
 
3.8%
육 1
 
3.8%
음 1
 
3.8%
Other values (14) 14
53.8%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26
81.2%
Common 6
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 2
 
7.7%
아 2
 
7.7%
구 1
 
3.8%
장 1
 
3.8%
은 1
 
3.8%
맞 1
 
3.8%
당 1
 
3.8%
식 1
 
3.8%
육 1
 
3.8%
음 1
 
3.8%
Other values (14) 14
53.8%
Common
ValueCountFrequency (%)
5
83.3%
. 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26
81.2%
ASCII 6
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5
83.3%
. 1
 
16.7%
Hangul
ValueCountFrequency (%)
정 2
 
7.7%
아 2
 
7.7%
구 1
 
3.8%
장 1
 
3.8%
은 1
 
3.8%
맞 1
 
3.8%
당 1
 
3.8%
식 1
 
3.8%
육 1
 
3.8%
음 1
 
3.8%
Other values (14) 14
53.8%

Interactions

2024-03-14T21:18:41.024038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:37.962770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:39.004985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:40.016635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:41.290475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:38.230508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:39.267389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:40.276665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:41.541380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:38.483096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:39.510778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:40.519773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:42.004348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:38.740047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:39.756768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:18:40.764398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:18:55.296083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번장소명주소경도위도구분면적형식담당부서불법촬영탐지시스템 설치여부기타
연번1.0001.0001.0000.6520.5810.7420.0000.5590.7810.1131.000
장소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.000
경도0.6521.0001.0001.0000.6370.3260.0000.3040.4150.0001.000
위도0.5811.0001.0000.6371.0000.5530.6270.2150.7920.0001.000
구분0.7421.0001.0000.3260.5531.0000.0000.8770.8370.5481.000
면적0.0001.0000.0000.0000.6270.0001.0000.0000.5680.288NaN
형식0.5591.0001.0000.3040.2150.8770.0001.0000.3990.0001.000
담당부서0.7811.0001.0000.4150.7920.8370.5680.3991.0001.000NaN
불법촬영탐지시스템 설치여부0.1131.0001.0000.0000.0000.5480.2880.0001.0001.000NaN
기타1.0001.0001.0001.0001.0001.000NaN1.000NaNNaN1.000
2024-03-14T21:18:55.522593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분담당부서불법촬영탐지시스템 설치여부형식
구분1.0000.6350.3750.641
담당부서0.6351.0000.9320.394
불법촬영탐지시스템 설치여부0.3750.9321.0000.000
형식0.6410.3940.0001.000
2024-03-14T21:18:55.689058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도위도면적구분형식담당부서불법촬영탐지시스템 설치여부
연번1.000-0.473-0.0750.2420.4540.3770.5180.000
경도-0.4731.0000.5370.1210.1330.1940.1990.000
위도-0.0750.5371.000-0.1730.3240.2060.3840.000
면적0.2420.121-0.1731.0000.0000.0000.2180.281
구분0.4540.1330.3240.0001.0000.6410.6350.375
형식0.3770.1940.2060.0000.6411.0000.3940.000
담당부서0.5180.1990.3840.2180.6350.3941.0000.932
불법촬영탐지시스템 설치여부0.0000.0000.0000.2810.3750.0000.9321.000

Missing values

2024-03-14T21:18:42.388609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:18:42.947709image/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

연번장소명주소경도위도구분면적형식담당부서비상벨 설치여부불법촬영탐지시스템 설치여부운영시간기타
01단재신채호선생생가지단재로229번길 29127.4102836.232452문화재40.5수세식문화체육과YY상시개방<NA>
12중촌육교 아래중촌동 143-1127.40754636.343261체육시설4.03간 이문화체육과YY상시개방<NA>
23무수동 농촌전통테마마을운남로85번길 32-8127.40786336.278261문화재62.02수세식일자리경제과YY상시개방<NA>
34은행동상점가 고객지원센터중교로83127.42853336.327146기타96.95수세식일자리경제과YY상시개방<NA>
45대전천변 공중화장실대전천서로 439 (은행동)127.42979836.328093천변21.8수세식일자리경제과YY상시개방<NA>
56으뜸화장실보문산공원로497번길 14127.4211636.312878관광지34.84수세식환경과YY상시개방<NA>
67청소년문화마당선화로119번길 16-3127.42006836.331063관광지9.6수세식환경과YY상시개방<NA>
78남부화장실용두로28번길 21-14127.40925936.327778저소득4.9수세식환경과YY상시개방구. 용정아파트 아래 기와
89서대전초교 뒤용두로28번길 22-6127.4100736.327395저소득10.99수세식환경과YY상시개방<NA>
910서대전육교 아래유천2동 464127.39503936.317795체육시설6.7간 이환경과YY상시개방태양솜공장 옆
연번장소명주소경도위도구분면적형식담당부서비상벨 설치여부불법촬영탐지시스템 설치여부운영시간기타
3031평리어린이공원유천로132번길 64127.39920436.324478공원18.0수세식공원녹지과YY상시개방<NA>
3132강변공원동서대로 1207번길 53127.39476336.328618공원31.44수세식공원녹지과YY상시개방<NA>
3233버드내조폐근린공원유등천동로 420127.38645336.318475공원41.3수세식공원녹지과YY상시개방<NA>
3334중촌근린공원유등천동로 731127.40382136.339128공원162.02수세식공원녹지과YY상시개방<NA>
3435양지근린공원선화서로23번길 63127.41531236.325482공원26.7수세식공원녹지과YY상시개방<NA>
3536효문화마을 주차장 옆뿌리공원로 47 (안영동)127.38457736.284687관광지21.0수세식효문화과YY상시개방<NA>
3637뿌리공원 중앙광장뿌리공원로 79127.38838736.285531주차장88.44수세식뿌리공원과YY상시개방<NA>
3738뿌리공원 교통광장산서로 180127.39106936.287271주차장56.7수세식뿌리공원과YY상시개방<NA>
3839보문산 공영주차장대사동 644-113127.42062936.312074주차장38.61수세식교통과YN상시개방<NA>
3940중촌근린공원 야구장중촌동 258-1127.40498736.343714체육시설21.12수세식공원녹지과YY상시개방<NA>