Overview

Dataset statistics

Number of variables8
Number of observations40
Missing cells17
Missing cells (%)5.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory71.3 B

Variable types

Numeric3
Text2
Categorical2
DateTime1

Dataset

Description충청남도 보령시의 불법투기감시 CCTV 현황 데이터로, 생활폐기물 불법 투기 감시를 위한 CCTV 설치 정보(설치장소, 상세 설치 위치, 설치대수, 위도, 경도, 전원공급방식)를 제공합니다.
URLhttps://www.data.go.kr/data/15103980/fileData.do

Alerts

설치대수 has constant value ""Constant
데이터기준일 has constant value ""Constant
전원공급방식 is highly imbalanced (71.4%)Imbalance
상세 설치 위치 has 17 (42.5%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:07:26.062135
Analysis finished2023-12-12 18:07:27.698308
Duration1.64 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

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 size492.0 B
2023-12-13T03:07:27.810181image/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
2023-12-13T03:07:28.042255image/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%

설치장소
Text

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2023-12-13T03:07:28.382080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length20
Min length16

Characters and Unicode

Total characters800
Distinct characters63
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

Unique36 ?
Unique (%)90.0%

Sample

1st row충청남도 보령시 웅천읍 노천리 218-1
2nd row충청남도 보령시 동대동 1956
3rd row충청남도 보령시 동대동 4-4
4th row충청남도 보령시 웅천읍 관당리 888
5th row충청남도 보령시 주교리 337-1
ValueCountFrequency (%)
충청남도 40
22.1%
보령시 40
22.1%
웅천읍 8
 
4.4%
동대동 6
 
3.3%
남포면 5
 
2.8%
대천동 4
 
2.2%
주교리 3
 
1.7%
천북면 3
 
1.7%
양항리 2
 
1.1%
죽정동 2
 
1.1%
Other values (61) 68
37.6%
2023-12-13T03:07:28.881169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
146
18.2%
남 47
 
5.9%
1 46
 
5.8%
청 42
 
5.2%
충 40
 
5.0%
도 40
 
5.0%
보 40
 
5.0%
령 40
 
5.0%
시 40
 
5.0%
동 26
 
3.2%
Other values (53) 293
36.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 466
58.2%
Decimal Number 163
 
20.4%
Space Separator 146
 
18.2%
Dash Punctuation 25
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 47
10.1%
청 42
 
9.0%
충 40
 
8.6%
도 40
 
8.6%
보 40
 
8.6%
령 40
 
8.6%
시 40
 
8.6%
동 26
 
5.6%
리 22
 
4.7%
천 18
 
3.9%
Other values (41) 111
23.8%
Decimal Number
ValueCountFrequency (%)
1 46
28.2%
2 24
14.7%
3 16
 
9.8%
5 16
 
9.8%
8 16
 
9.8%
6 11
 
6.7%
7 11
 
6.7%
9 9
 
5.5%
4 8
 
4.9%
0 6
 
3.7%
Space Separator
ValueCountFrequency (%)
146
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 466
58.2%
Common 334
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 47
10.1%
청 42
 
9.0%
충 40
 
8.6%
도 40
 
8.6%
보 40
 
8.6%
령 40
 
8.6%
시 40
 
8.6%
동 26
 
5.6%
리 22
 
4.7%
천 18
 
3.9%
Other values (41) 111
23.8%
Common
ValueCountFrequency (%)
146
43.7%
1 46
 
13.8%
- 25
 
7.5%
2 24
 
7.2%
3 16
 
4.8%
5 16
 
4.8%
8 16
 
4.8%
6 11
 
3.3%
7 11
 
3.3%
9 9
 
2.7%
Other values (2) 14
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 466
58.2%
ASCII 334
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
146
43.7%
1 46
 
13.8%
- 25
 
7.5%
2 24
 
7.2%
3 16
 
4.8%
5 16
 
4.8%
8 16
 
4.8%
6 11
 
3.3%
7 11
 
3.3%
9 9
 
2.7%
Other values (2) 14
 
4.2%
Hangul
ValueCountFrequency (%)
남 47
10.1%
청 42
 
9.0%
충 40
 
8.6%
도 40
 
8.6%
보 40
 
8.6%
령 40
 
8.6%
시 40
 
8.6%
동 26
 
5.6%
리 22
 
4.7%
천 18
 
3.9%
Other values (41) 111
23.8%

상세 설치 위치
Text

MISSING 

Distinct23
Distinct (%)100.0%
Missing17
Missing (%)42.5%
Memory size452.0 B
2023-12-13T03:07:29.118926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length6.826087
Min length3

Characters and Unicode

Total characters157
Distinct characters79
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

Unique23 ?
Unique (%)100.0%

Sample

1st row신설마트 앞
2nd row한내여중 앞
3rd row보현사 앞
4th row고인돌공원 앞
5th row 녹문입구
ValueCountFrequency (%)
앞 12
26.7%
옆 2
 
4.4%
입구 2
 
4.4%
영농폐비닐집하장 1
 
2.2%
유성1차아파트 1
 
2.2%
103동 1
 
2.2%
하만 1
 
2.2%
삼거리 1
 
2.2%
신설마트 1
 
2.2%
2리 1
 
2.2%
Other values (22) 22
48.9%
2023-12-13T03:07:29.483714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
30
 
19.1%
앞 12
 
7.6%
원 5
 
3.2%
리 4
 
2.5%
구 3
 
1.9%
한 3
 
1.9%
거 3
 
1.9%
입 3
 
1.9%
교 3
 
1.9%
삼 3
 
1.9%
Other values (69) 88
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 121
77.1%
Space Separator 30
 
19.1%
Decimal Number 6
 
3.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
앞 12
 
9.9%
원 5
 
4.1%
리 4
 
3.3%
구 3
 
2.5%
한 3
 
2.5%
거 3
 
2.5%
입 3
 
2.5%
교 3
 
2.5%
삼 3
 
2.5%
대 2
 
1.7%
Other values (64) 80
66.1%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
3 2
33.3%
0 1
16.7%
2 1
16.7%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 121
77.1%
Common 36
 
22.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
앞 12
 
9.9%
원 5
 
4.1%
리 4
 
3.3%
구 3
 
2.5%
한 3
 
2.5%
거 3
 
2.5%
입 3
 
2.5%
교 3
 
2.5%
삼 3
 
2.5%
대 2
 
1.7%
Other values (64) 80
66.1%
Common
ValueCountFrequency (%)
30
83.3%
1 2
 
5.6%
3 2
 
5.6%
0 1
 
2.8%
2 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 121
77.1%
ASCII 36
 
22.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
30
83.3%
1 2
 
5.6%
3 2
 
5.6%
0 1
 
2.8%
2 1
 
2.8%
Hangul
ValueCountFrequency (%)
앞 12
 
9.9%
원 5
 
4.1%
리 4
 
3.3%
구 3
 
2.5%
한 3
 
2.5%
거 3
 
2.5%
입 3
 
2.5%
교 3
 
2.5%
삼 3
 
2.5%
대 2
 
1.7%
Other values (64) 80
66.1%

설치대수
Categorical

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
1
40 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 40
100.0%

Length

2023-12-13T03:07:29.659969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:07:29.774371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 40
100.0%

위도
Real number (ℝ)

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.335917
Minimum36.226249
Maximum36.47218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T03:07:29.901526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.226249
5-th percentile36.23346
Q136.288156
median36.347822
Q336.358228
95-th percentile36.469555
Maximum36.47218
Range0.24593036
Interquartile range (IQR)0.070071882

Descriptive statistics

Standard deviation0.065522065
Coefficient of variation (CV)0.0018032314
Kurtosis-0.085706173
Mean36.335917
Median Absolute Deviation (MAD)0.032435665
Skewness0.22535838
Sum1453.4367
Variance0.004293141
MonotonicityNot monotonic
2023-12-13T03:07:30.092878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
36.22624937 2
 
5.0%
36.35250304 2
 
5.0%
36.35434761 1
 
2.5%
36.35119852 1
 
2.5%
36.23647634 1
 
2.5%
36.25123484 1
 
2.5%
36.47217973 1
 
2.5%
36.27962691 1
 
2.5%
36.245537 1
 
2.5%
36.40394467 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
36.22624937 2
5.0%
36.23383972 1
2.5%
36.23647634 1
2.5%
36.245537 1
2.5%
36.2487355 1
2.5%
36.25123484 1
2.5%
36.27314761 1
2.5%
36.27633739 1
2.5%
36.27962691 1
2.5%
36.29099916 1
2.5%
ValueCountFrequency (%)
36.47217973 1
2.5%
36.47050053 1
2.5%
36.46950543 1
2.5%
36.45431728 1
2.5%
36.40394467 1
2.5%
36.39353189 1
2.5%
36.38203014 1
2.5%
36.38152641 1
2.5%
36.37073922 1
2.5%
36.361457 1
2.5%

경도
Real number (ℝ)

Distinct38
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.57545
Minimum126.48901
Maximum126.62662
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2023-12-13T03:07:30.245882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.48901
5-th percentile126.51079
Q1126.55114
median126.58656
Q3126.59904
95-th percentile126.62025
Maximum126.62662
Range0.137617
Interquartile range (IQR)0.04789935

Descriptive statistics

Standard deviation0.033925186
Coefficient of variation (CV)0.00026802342
Kurtosis-0.18612567
Mean126.57545
Median Absolute Deviation (MAD)0.0202271
Skewness-0.73722529
Sum5063.0182
Variance0.0011509182
MonotonicityNot monotonic
2023-12-13T03:07:30.398543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
126.5858647 2
 
5.0%
126.6067871 2
 
5.0%
126.58319 1
 
2.5%
126.6024468 1
 
2.5%
126.5968723 1
 
2.5%
126.6201002 1
 
2.5%
126.4890076 1
 
2.5%
126.5512386 1
 
2.5%
126.554072 1
 
2.5%
126.5109671 1
 
2.5%
Other values (28) 28
70.0%
ValueCountFrequency (%)
126.4890076 1
2.5%
126.5074268 1
2.5%
126.5109671 1
2.5%
126.524368 1
2.5%
126.5258457 1
2.5%
126.5408615 1
2.5%
126.5441619 1
2.5%
126.5442154 1
2.5%
126.5499601 1
2.5%
126.5508468 1
2.5%
ValueCountFrequency (%)
126.6266246 1
2.5%
126.6230938 1
2.5%
126.6201002 1
2.5%
126.6082723 1
2.5%
126.6067871 2
5.0%
126.6049761 1
2.5%
126.6026546 1
2.5%
126.6024468 1
2.5%
126.6002238 1
2.5%
126.5986454 1
2.5%

전원공급방식
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
태양광
38 
전기설비
 
2

Length

Max length4
Median length3
Mean length3.05
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
태양광 38
95.0%
전기설비 2
 
5.0%

Length

2023-12-13T03:07:30.611562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:07:30.774186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
태양광 38
95.0%
전기설비 2
 
5.0%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
Minimum2023-08-14 00:00:00
Maximum2023-08-14 00:00:00
2023-12-13T03:07:30.895796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:31.000845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T03:07:26.957757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:26.318013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:26.606588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:27.105313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:26.406008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:26.740312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:27.247449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:26.489153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:07:26.830013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:07:31.086567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치장소상세 설치 위치위도경도전원공급방식
연번1.0000.8571.0000.5620.0000.724
설치장소0.8571.0001.0001.0001.0001.000
상세 설치 위치1.0001.0001.0001.0001.0001.000
위도0.5621.0001.0001.0000.5920.000
경도0.0001.0001.0000.5921.0000.000
전원공급방식0.7241.0001.0000.0000.0001.000
2023-12-13T03:07:31.226610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도전원공급방식
연번1.0000.0680.0220.499
위도0.0681.000-0.1410.000
경도0.022-0.1411.0000.000
전원공급방식0.4990.0000.0001.000

Missing values

2023-12-13T03:07:27.445142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:07:27.623223image/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

연번설치장소상세 설치 위치설치대수위도경도전원공급방식데이터기준일
01충청남도 보령시 웅천읍 노천리 218-1<NA>136.226249126.585865태양광2023-08-14
12충청남도 보령시 동대동 1956신설마트 앞136.352503126.606787태양광2023-08-14
23충청남도 보령시 동대동 4-4한내여중 앞136.34954126.623094태양광2023-08-14
34충청남도 보령시 웅천읍 관당리 888보현사 앞136.248736126.540862태양광2023-08-14
45충청남도 보령시 주교리 337-1고인돌공원 앞136.38203126.562048태양광2023-08-14
56충청남도 보령시 대천동 205-14<NA>136.348921126.595144태양광2023-08-14
67충청남도 보령시 주교면은포리 345-1<NA>136.381526126.544162태양광2023-08-14
78충청남도 보령시 주교면 주교리 168<NA>136.393532126.571566태양광2023-08-14
89충청남도 보령시 내항동 297-28녹문입구136.339547126.587255태양광2023-08-14
910충청남도 보령시 웅천읍 대창리 713-8대화한의원 앞136.23384126.600224전기설비2023-08-14
연번설치장소상세 설치 위치설치대수위도경도전원공급방식데이터기준일
3031충청남도 보령시 웅천읍 수부리 923<NA>136.276337126.626625태양광2023-08-14
3132충청남도 보령시 남곡동 1223남곡 사거리136.33429126.569059태양광2023-08-14
3233충청남도 보령시 대천동 197-10우체국 맞은편136.350489126.595683태양광2023-08-14
3334충청남도 보령시 대천동 618-679평생학습관 앞136.346496126.596347태양광2023-08-14
3435충청남도 보령시 남포면 월전리 820죽도 입구136.273148126.544215태양광2023-08-14
3536충청남도 보령시 동대동 711-5죽정교 앞136.355942126.608272태양광2023-08-14
3637충청남도 보령시 천북면 낙동리 1587<NA>136.469505126.54996태양광2023-08-14
3738충청남도 보령시 동대동 1956<NA>136.352503126.606787태양광2023-08-14
3839충청남도 보령시 동대동 742-1<NA>136.351199126.602447태양광2023-08-14
3940충청남도 보령시 대천동 626-1<NA>136.354348126.58319태양광2023-08-14