Overview

Dataset statistics

Number of variables15
Number of observations114
Missing cells228
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.5 KiB
Average record size in memory130.2 B

Variable types

Categorical6
Text2
Numeric5
Unsupported2

Dataset

Description계룡시 재난안전 목적으로 운영되는 CCTV에 관한 데이터로서, 소재지, 설치일, 영상보관일자, 카메라대수, 위도, 경도, 설치목적, 촬영방면, 카메라화소수, 관리기관번호 등의 공공데이터를 제공합니다.
Author충청남도 계룡시
URLhttps://www.data.go.kr/data/15093901/fileData.do

Alerts

관리기관명 has constant value ""Constant
보관일수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
설치년월 is highly overall correlated with 설치목적구분High correlation
설치목적구분 is highly overall correlated with 설치년월 and 1 other fieldsHigh correlation
촬영방면정보 is highly overall correlated with 설치목적구분High correlation
Unnamed: 13 has 114 (100.0%) missing valuesMissing
Unnamed: 14 has 114 (100.0%) missing valuesMissing
소재지지번주소 has unique valuesUnique
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 05:59:46.883821
Analysis finished2023-12-12 05:59:50.804829
Duration3.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
충청남도 계룡시청
114 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 계룡시청
2nd row충청남도 계룡시청
3rd row충청남도 계룡시청
4th row충청남도 계룡시청
5th row충청남도 계룡시청

Common Values

ValueCountFrequency (%)
충청남도 계룡시청 114
100.0%

Length

2023-12-12T14:59:50.893441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:50.982383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 114
50.0%
계룡시청 114
50.0%

소재지지번주소
Text

UNIQUE 

Distinct114
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T14:59:51.256212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length38
Mean length32.315789
Min length22

Characters and Unicode

Total characters3684
Distinct characters212
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

Unique114 ?
Unique (%)100.0%

Sample

1st row충청남도 계룡시 엄사면 엄사리 572 (숲어린이집)
2nd row충청남도 계룡시 두마면 농소리 778 (계룡고 옥상)
3rd row충청남도 계룡시 엄사면 엄사리 18-4 (엄사근린공원 충령탑)
4th row충청남도 계룡시 신도안면 남선리1049-1 (용남초등학교 담장)
5th row충청남도 계룡시 엄사면 엄사리 142-3 (평리지하도)
ValueCountFrequency (%)
충청남도 114
 
15.6%
계룡시 114
 
15.6%
엄사면 62
 
8.5%
엄사리 41
 
5.6%
금암동 24
 
3.3%
앞 24
 
3.3%
두마면 17
 
2.3%
두계리 11
 
1.5%
신도안면 11
 
1.5%
유동리 8
 
1.1%
Other values (243) 306
41.8%
2023-12-12T14:59:51.672605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
618
 
16.8%
계 145
 
3.9%
도 135
 
3.7%
사 129
 
3.5%
룡 128
 
3.5%
엄 125
 
3.4%
남 122
 
3.3%
시 118
 
3.2%
청 117
 
3.2%
) 117
 
3.2%
Other values (202) 1930
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2314
62.8%
Space Separator 618
 
16.8%
Decimal Number 432
 
11.7%
Close Punctuation 117
 
3.2%
Open Punctuation 117
 
3.2%
Dash Punctuation 81
 
2.2%
Other Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 145
 
6.3%
도 135
 
5.8%
사 129
 
5.6%
룡 128
 
5.5%
엄 125
 
5.4%
남 122
 
5.3%
시 118
 
5.1%
청 117
 
5.1%
충 115
 
5.0%
리 109
 
4.7%
Other values (184) 1071
46.3%
Decimal Number
ValueCountFrequency (%)
1 87
20.1%
2 75
17.4%
4 44
10.2%
7 39
9.0%
5 39
9.0%
8 36
8.3%
6 34
 
7.9%
3 31
 
7.2%
0 27
 
6.2%
9 20
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
@ 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
618
100.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2314
62.8%
Common 1368
37.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 145
 
6.3%
도 135
 
5.8%
사 129
 
5.6%
룡 128
 
5.5%
엄 125
 
5.4%
남 122
 
5.3%
시 118
 
5.1%
청 117
 
5.1%
충 115
 
5.0%
리 109
 
4.7%
Other values (184) 1071
46.3%
Common
ValueCountFrequency (%)
618
45.2%
) 117
 
8.6%
( 117
 
8.6%
1 87
 
6.4%
- 81
 
5.9%
2 75
 
5.5%
4 44
 
3.2%
7 39
 
2.9%
5 39
 
2.9%
8 36
 
2.6%
Other values (6) 115
 
8.4%
Latin
ValueCountFrequency (%)
I 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2314
62.8%
ASCII 1370
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
618
45.1%
) 117
 
8.5%
( 117
 
8.5%
1 87
 
6.4%
- 81
 
5.9%
2 75
 
5.5%
4 44
 
3.2%
7 39
 
2.8%
5 39
 
2.8%
8 36
 
2.6%
Other values (8) 117
 
8.5%
Hangul
ValueCountFrequency (%)
계 145
 
6.3%
도 135
 
5.8%
사 129
 
5.6%
룡 128
 
5.5%
엄 125
 
5.4%
남 122
 
5.3%
시 118
 
5.1%
청 117
 
5.1%
충 115
 
5.0%
리 109
 
4.7%
Other values (184) 1071
46.3%

설치년월
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20210763
Minimum20210116
Maximum20211216
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:59:51.790578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20210116
5-th percentile20210116
Q120210616
median20210716
Q320210991
95-th percentile20211216
Maximum20211216
Range1100
Interquartile range (IQR)375

Descriptive statistics

Standard deviation286.33214
Coefficient of variation (CV)1.416731 × 10-5
Kurtosis0.045835094
Mean20210763
Median Absolute Deviation (MAD)100
Skewness-0.2706041
Sum2.3040269 × 109
Variance81986.092
MonotonicityNot monotonic
2023-12-12T14:59:51.889822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
20210716 28
24.6%
20210616 25
21.9%
20211116 14
12.3%
20211216 12
10.5%
20210816 8
 
7.0%
20210116 8
 
7.0%
20210516 6
 
5.3%
20210916 5
 
4.4%
20210817 3
 
2.6%
20211016 2
 
1.8%
Other values (2) 3
 
2.6%
ValueCountFrequency (%)
20210116 8
 
7.0%
20210316 2
 
1.8%
20210516 6
 
5.3%
20210616 25
21.9%
20210716 28
24.6%
20210816 8
 
7.0%
20210817 3
 
2.6%
20210916 5
 
4.4%
20211016 2
 
1.8%
20211017 1
 
0.9%
ValueCountFrequency (%)
20211216 12
10.5%
20211116 14
12.3%
20211017 1
 
0.9%
20211016 2
 
1.8%
20210916 5
 
4.4%
20210817 3
 
2.6%
20210816 8
 
7.0%
20210716 28
24.6%
20210616 25
21.9%
20210516 6
 
5.3%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
30
114 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row30
3rd row30
4th row30
5th row30

Common Values

ValueCountFrequency (%)
30 114
100.0%

Length

2023-12-12T14:59:52.021794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:52.105998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 114
100.0%

카메라대수
Real number (ℝ)

Distinct10
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4210526
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:59:52.201761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile7.15
Maximum39
Range38
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.072736
Coefficient of variation (CV)2.0952605
Kurtosis30.043727
Mean2.4210526
Median Absolute Deviation (MAD)0
Skewness5.2322818
Sum276
Variance25.73265
MonotonicityNot monotonic
2023-12-12T14:59:52.319327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
1 76
66.7%
2 28
 
24.6%
3 3
 
2.6%
27 1
 
0.9%
14 1
 
0.9%
13 1
 
0.9%
17 1
 
0.9%
39 1
 
0.9%
21 1
 
0.9%
4 1
 
0.9%
ValueCountFrequency (%)
1 76
66.7%
2 28
 
24.6%
3 3
 
2.6%
4 1
 
0.9%
13 1
 
0.9%
14 1
 
0.9%
17 1
 
0.9%
21 1
 
0.9%
27 1
 
0.9%
39 1
 
0.9%
ValueCountFrequency (%)
39 1
 
0.9%
27 1
 
0.9%
21 1
 
0.9%
17 1
 
0.9%
14 1
 
0.9%
13 1
 
0.9%
4 1
 
0.9%
3 3
 
2.6%
2 28
 
24.6%
1 76
66.7%

경도
Real number (ℝ)

Distinct111
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.24517
Minimum127.21276
Maximum127.28015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:59:52.470162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.21276
5-th percentile127.22682
Q1127.23717
median127.2431
Q3127.25143
95-th percentile127.27347
Maximum127.28015
Range0.067391
Interquartile range (IQR)0.014258

Descriptive statistics

Standard deviation0.013450174
Coefficient of variation (CV)0.00010570283
Kurtosis0.37199736
Mean127.24517
Median Absolute Deviation (MAD)0.0064895
Skewness0.61367211
Sum14505.949
Variance0.00018090718
MonotonicityNot monotonic
2023-12-12T14:59:52.612081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.235767 2
 
1.8%
127.238223 2
 
1.8%
127.238217 2
 
1.8%
127.241611 1
 
0.9%
127.237365 1
 
0.9%
127.274445 1
 
0.9%
127.255711 1
 
0.9%
127.258633 1
 
0.9%
127.257849 1
 
0.9%
127.267909 1
 
0.9%
Other values (101) 101
88.6%
ValueCountFrequency (%)
127.212762 1
0.9%
127.215096 1
0.9%
127.221748 1
0.9%
127.223606 1
0.9%
127.224626 1
0.9%
127.225428 1
0.9%
127.227569 1
0.9%
127.227682 1
0.9%
127.228839 1
0.9%
127.229123 1
0.9%
ValueCountFrequency (%)
127.280153 1
0.9%
127.278452 1
0.9%
127.276519 1
0.9%
127.274445 1
0.9%
127.274079 1
0.9%
127.273976 1
0.9%
127.273205 1
0.9%
127.27239 1
0.9%
127.271346 1
0.9%
127.269338 1
0.9%

소재지도로명주소
Text

Distinct113
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T14:59:52.887760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length29.175439
Min length21

Characters and Unicode

Total characters3326
Distinct characters213
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

Unique112 ?
Unique (%)98.2%

Sample

1st row충청남도 계룡시 엄사면 엄사중앙로 (숲어린이집 앞)
2nd row충청남도 계룡시 두마면 서금암로 89 (계룡고 옥상)
3rd row충청남도 계룡시 엄사면 번영로 11 (엄사근린공원 충령탑)
4th row충청남도 계룡시 신도안면 (용남초등학교 담장)
5th row충청남도 계룡시 엄사면 평리길 (평리지하도)
ValueCountFrequency (%)
충청남도 114
17.0%
계룡시 114
17.0%
엄사면 60
 
9.0%
앞 48
 
7.2%
두마면 17
 
2.5%
신도안면 11
 
1.6%
번영3길 9
 
1.3%
정문 8
 
1.2%
팥거리로 6
 
0.9%
계룡대로 6
 
0.9%
Other values (196) 276
41.3%
2023-12-12T14:59:53.332608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
555
 
16.7%
계 147
 
4.4%
도 139
 
4.2%
룡 134
 
4.0%
시 118
 
3.5%
청 117
 
3.5%
( 116
 
3.5%
남 116
 
3.5%
) 116
 
3.5%
충 115
 
3.5%
Other values (203) 1653
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2366
71.1%
Space Separator 555
 
16.7%
Decimal Number 151
 
4.5%
Open Punctuation 116
 
3.5%
Close Punctuation 116
 
3.5%
Dash Punctuation 17
 
0.5%
Other Punctuation 3
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 147
 
6.2%
도 139
 
5.9%
룡 134
 
5.7%
시 118
 
5.0%
청 117
 
4.9%
남 116
 
4.9%
충 115
 
4.9%
사 93
 
3.9%
면 90
 
3.8%
엄 86
 
3.6%
Other values (185) 1211
51.2%
Decimal Number
ValueCountFrequency (%)
1 38
25.2%
2 23
15.2%
3 22
14.6%
4 16
10.6%
5 15
 
9.9%
7 9
 
6.0%
8 9
 
6.0%
0 7
 
4.6%
9 7
 
4.6%
6 5
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
@ 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%
Space Separator
ValueCountFrequency (%)
555
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2366
71.1%
Common 958
28.8%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 147
 
6.2%
도 139
 
5.9%
룡 134
 
5.7%
시 118
 
5.0%
청 117
 
4.9%
남 116
 
4.9%
충 115
 
4.9%
사 93
 
3.9%
면 90
 
3.8%
엄 86
 
3.6%
Other values (185) 1211
51.2%
Common
ValueCountFrequency (%)
555
57.9%
( 116
 
12.1%
) 116
 
12.1%
1 38
 
4.0%
2 23
 
2.4%
3 22
 
2.3%
- 17
 
1.8%
4 16
 
1.7%
5 15
 
1.6%
7 9
 
0.9%
Other values (6) 31
 
3.2%
Latin
ValueCountFrequency (%)
C 1
50.0%
I 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2366
71.1%
ASCII 960
28.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
555
57.8%
( 116
 
12.1%
) 116
 
12.1%
1 38
 
4.0%
2 23
 
2.4%
3 22
 
2.3%
- 17
 
1.8%
4 16
 
1.7%
5 15
 
1.6%
7 9
 
0.9%
Other values (8) 33
 
3.4%
Hangul
ValueCountFrequency (%)
계 147
 
6.2%
도 139
 
5.9%
룡 134
 
5.7%
시 118
 
5.0%
청 117
 
4.9%
남 116
 
4.9%
충 115
 
4.9%
사 93
 
3.9%
면 90
 
3.8%
엄 86
 
3.6%
Other values (185) 1211
51.2%

위도
Real number (ℝ)

Distinct112
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.279865
Minimum36.252945
Maximum36.336523
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:59:53.553445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.252945
5-th percentile36.261268
Q136.270987
median36.279238
Q336.288083
95-th percentile36.29861
Maximum36.336523
Range0.083578
Interquartile range (IQR)0.017096

Descriptive statistics

Standard deviation0.013646819
Coefficient of variation (CV)0.00037615408
Kurtosis2.968809
Mean36.279865
Median Absolute Deviation (MAD)0.0085745
Skewness1.037641
Sum4135.9046
Variance0.00018623568
MonotonicityNot monotonic
2023-12-12T14:59:53.717407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.298393 2
 
1.8%
36.286523 2
 
1.8%
36.284861 1
 
0.9%
36.269857 1
 
0.9%
36.269129 1
 
0.9%
36.274461 1
 
0.9%
36.273708 1
 
0.9%
36.268131 1
 
0.9%
36.285948 1
 
0.9%
36.285614 1
 
0.9%
Other values (102) 102
89.5%
ValueCountFrequency (%)
36.252945 1
0.9%
36.253919 1
0.9%
36.254313 1
0.9%
36.254741 1
0.9%
36.259596 1
0.9%
36.261079 1
0.9%
36.261369 1
0.9%
36.262232 1
0.9%
36.262838 1
0.9%
36.262947 1
0.9%
ValueCountFrequency (%)
36.336523 1
0.9%
36.325088 1
0.9%
36.323675 1
0.9%
36.304517 1
0.9%
36.301741 1
0.9%
36.299013 1
0.9%
36.298393 2
1.8%
36.297998 1
0.9%
36.297661 1
0.9%
36.292194 1
0.9%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
어린이보호
66 
생활방범
29 
재난재해
8 
시설물관리
7 
차량방범
 
3

Length

Max length5
Median length5
Mean length4.6403509
Min length4

Unique

Unique1 ?
Unique (%)0.9%

Sample

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

Common Values

ValueCountFrequency (%)
어린이보호 66
57.9%
생활방범 29
25.4%
재난재해 8
 
7.0%
시설물관리 7
 
6.1%
차량방범 3
 
2.6%
교통단속 1
 
0.9%

Length

2023-12-12T14:59:53.866749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:53.982381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이보호 66
57.9%
생활방범 29
25.4%
재난재해 8
 
7.0%
시설물관리 7
 
6.1%
차량방범 3
 
2.6%
교통단속 1
 
0.9%

촬영방면정보
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)20.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
360도전방향
57 
마을입구방향
17 
360도전방향, 어린이집정문
7 
360도전방향, 유치원정문
7 
건물내,외부
6 
Other values (18)
20 

Length

Max length21
Median length7
Mean length8.6491228
Min length6

Unique

Unique17 ?
Unique (%)14.9%

Sample

1st row360도전방향, 어린이집정문
2nd row360도전방향
3rd row360도전방향
4th row360도전방향
5th row360도전방향

Common Values

ValueCountFrequency (%)
360도전방향 57
50.0%
마을입구방향 17
 
14.9%
360도전방향, 어린이집정문 7
 
6.1%
360도전방향, 유치원정문 7
 
6.1%
건물내,외부 6
 
5.3%
360도전방향, 주차장방향 3
 
2.6%
삼진삼거리방향 1
 
0.9%
360도전방향, 마을입구방향 1
 
0.9%
360도전방향, 마을입구, 횡단보드방향 1
 
0.9%
360도전방향, 횡단보도방향 1
 
0.9%
Other values (13) 13
 
11.4%

Length

2023-12-12T14:59:54.120768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
360도전방향 83
57.6%
마을입구방향 18
 
12.5%
어린이집정문 7
 
4.9%
유치원정문 7
 
4.9%
건물내,외부 6
 
4.2%
주차장방향 3
 
2.1%
엄사초 1
 
0.7%
대전경계방향 1
 
0.7%
공원입구방향 1
 
0.7%
공원방향 1
 
0.7%
Other values (16) 16
 
11.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
20171128
114 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20171128
2nd row20171128
3rd row20171128
4th row20171128
5th row20171128

Common Values

ValueCountFrequency (%)
20171128 114
100.0%

Length

2023-12-12T14:59:54.261064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:54.359332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20171128 114
100.0%

카메라화소수
Real number (ℝ)

Distinct6
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.11404
Minimum41
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T14:59:54.463110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41
5-th percentile41
Q1130
median200
Q3200
95-th percentile200
Maximum300
Range259
Interquartile range (IQR)70

Descriptive statistics

Standard deviation55.641991
Coefficient of variation (CV)0.33097766
Kurtosis0.81438765
Mean168.11404
Median Absolute Deviation (MAD)0
Skewness-1.2877337
Sum19165
Variance3096.0311
MonotonicityNot monotonic
2023-12-12T14:59:54.593145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
200 77
67.5%
130 20
 
17.5%
41 13
 
11.4%
140 2
 
1.8%
300 1
 
0.9%
52 1
 
0.9%
ValueCountFrequency (%)
41 13
 
11.4%
52 1
 
0.9%
130 20
 
17.5%
140 2
 
1.8%
200 77
67.5%
300 1
 
0.9%
ValueCountFrequency (%)
300 1
 
0.9%
200 77
67.5%
140 2
 
1.8%
130 20
 
17.5%
52 1
 
0.9%
41 13
 
11.4%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
042-840-3807
114 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row042-840-3807
2nd row042-840-3807
3rd row042-840-3807
4th row042-840-3807
5th row042-840-3807

Common Values

ValueCountFrequency (%)
042-840-3807 114
100.0%

Length

2023-12-12T14:59:54.754187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:59:55.216064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
042-840-3807 114
100.0%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing114
Missing (%)100.0%
Memory size1.1 KiB

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing114
Missing (%)100.0%
Memory size1.1 KiB

Interactions

2023-12-12T14:59:49.905986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:47.506158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.370747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.902543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.417465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:50.043379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:47.932717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.458341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.006624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.499157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:50.133172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.059947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.589890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.127743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.596755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:50.221310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.196870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.716000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.231184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.683244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:50.301134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.292063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:48.821902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.322554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:59:49.757018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:59:55.299334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년월카메라대수경도위도설치목적구분촬영방면정보카메라화소수
설치년월1.0000.5830.0000.2720.7520.8010.636
카메라대수0.5831.0000.0000.0000.7530.2030.759
경도0.0000.0001.0000.5640.3970.4320.000
위도0.2720.0000.5641.0000.4240.8130.000
설치목적구분0.7520.7530.3970.4241.0000.9630.524
촬영방면정보0.8010.2030.4320.8130.9631.0000.541
카메라화소수0.6360.7590.0000.0000.5240.5411.000
2023-12-12T14:59:55.443416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
촬영방면정보설치목적구분
촬영방면정보1.0000.777
설치목적구분0.7771.000
2023-12-12T14:59:55.540235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년월카메라대수경도위도카메라화소수설치목적구분촬영방면정보
설치년월1.0000.0750.123-0.0200.0420.5350.393
카메라대수0.0751.000-0.0740.0970.0650.3630.075
경도0.123-0.0741.000-0.228-0.0600.2160.158
위도-0.0200.097-0.2281.0000.0090.2220.449
카메라화소수0.0420.065-0.0600.0091.0000.3610.288
설치목적구분0.5350.3630.2160.2220.3611.0000.777
촬영방면정보0.3930.0750.1580.4490.2880.7771.000

Missing values

2023-12-12T14:59:50.441569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:59:50.683650image/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

관리기관명소재지지번주소설치년월보관일수카메라대수경도소재지도로명주소위도설치목적구분촬영방면정보데이터기준일자카메라화소수관리기관전화번호Unnamed: 13Unnamed: 14
0충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 572 (숲어린이집)20211116302127.241611충청남도 계룡시 엄사면 엄사중앙로 (숲어린이집 앞)36.284861어린이보호360도전방향, 어린이집정문20171128200042-840-3807<NA><NA>
1충청남도 계룡시청충청남도 계룡시 두마면 농소리 778 (계룡고 옥상)20210616301127.258561충청남도 계룡시 두마면 서금암로 89 (계룡고 옥상)36.268158어린이보호360도전방향2017112841042-840-3807<NA><NA>
2충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 18-4 (엄사근린공원 충령탑)20210616301127.244252충청남도 계룡시 엄사면 번영로 11 (엄사근린공원 충령탑)36.286955어린이보호360도전방향20171128200042-840-3807<NA><NA>
3충청남도 계룡시청충청남도 계룡시 신도안면 남선리1049-1 (용남초등학교 담장)20210816301127.244683충청남도 계룡시 신도안면 (용남초등학교 담장)36.297998어린이보호360도전방향20171128200042-840-3807<NA><NA>
4충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 142-3 (평리지하도)20210916301127.244328충청남도 계룡시 엄사면 평리길 (평리지하도)36.290327어린이보호360도전방향2017112841042-840-3807<NA><NA>
5충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 187 (소망광장)20210916301127.240824충청남도 계룡시 엄사면 번영2길 (소망광장)36.289969어린이보호360도전방향20171128130042-840-3807<NA><NA>
6충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 181-1 (엄사상점가공영주차장)202111163027127.242917충청남도 계룡시 엄사면 (엄사상점가공영주차장)36.288924시설물관리건물내,외부20171128300042-840-3807<NA><NA>
7충청남도 계룡시청충청남도 계룡시 엄사면 유동리 279-2 (계룡종합운동장주차장)202110163014127.231395충청남도 계룡시 엄사면 계백로 (계룡종합운동장주차장)36.272863시설물관리건물내,외부20171128200042-840-3807<NA><NA>
8충청남도 계룡시청충청남도 계룡시 엄사면 유동리 277 (계룡종합운동장)202106163013127.231239충청남도 계룡시 엄사면 계백로 2967(계룡종합운동장)36.271261시설물관리건물내,외부2017112841042-840-3807<NA><NA>
9충청남도 계룡시청충청남도 계룡시 엄사면 유동리 269-1 (계룡시민체육관)202109163017127.233399충청남도 계룡시 엄사면 계백로 2935(계룡시민체육관)36.269764시설물관리건물내,외부2017112841042-840-3807<NA><NA>
관리기관명소재지지번주소설치년월보관일수카메라대수경도소재지도로명주소위도설치목적구분촬영방면정보데이터기준일자카메라화소수관리기관전화번호Unnamed: 13Unnamed: 14
104충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 279 (엄사1호어린이공원-놀이터)20210616301127.239604충청남도 계룡시 엄사면 번영3길 7(엄사1호어린이공원-놀이터)36.288221어린이보호360도전방향2017112841042-840-3807<NA><NA>
105충청남도 계룡시청충청남도 계룡시 엄사면 엄사리 279 (엄사1호어린이공원-화장실)20210616301127.239929충청남도 계룡시 엄사면 번영3길 7(엄사1호어린이공원-화장실)36.287989어린이보호360도전방향2017112841042-840-3807<NA><NA>
106충청남도 계룡시청충청남도 계룡시 신도안면 용동리 104-1 공원(괴목정공원3)20210816304127.245263충청남도 계룡시 신도안면 용동리 104-1 공원(괴목정공원3)36.323675어린이보호360도전방향, 공원방향20171128200042-840-3807<NA><NA>
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