Overview

Dataset statistics

Number of variables21
Number of observations757
Missing cells750
Missing cells (%)4.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory131.7 KiB
Average record size in memory178.2 B

Variable types

Categorical12
Numeric5
Text4

Dataset

Description대전광역시 서구 관내에 생활방범용으로 설치된 일부 CCTV 정보(행정동, 지구대 정보, 사업연도, 설치 주소, 카메라 수 등)를 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15124385/fileData.do

Alerts

cctv_개소수 has constant value ""Constant
관리번호_시 is highly imbalanced (92.9%)Imbalance
cctv_대수 is highly imbalanced (54.2%)Imbalance
한전주_기타_건물외벽 is highly imbalanced (54.2%)Imbalance
비고 has 750 (99.1%) missing valuesMissing
관리번호_구 has unique valuesUnique

Reproduction

Analysis started2023-12-12 09:54:27.030248
Analysis finished2023-12-12 09:54:27.717717
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동
Categorical

Distinct23
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
가수원동
73 
도마1동
 
49
관저2동
 
49
갈마1동
 
47
탄방동
 
45
Other values (18)
494 

Length

Max length4
Median length4
Mean length3.4821664
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row갈마1동
2nd row갈마2동
3rd row관저2동
4th row괴정동
5th row갈마2동

Common Values

ValueCountFrequency (%)
가수원동 73
 
9.6%
도마1동 49
 
6.5%
관저2동 49
 
6.5%
갈마1동 47
 
6.2%
탄방동 45
 
5.9%
정림동 45
 
5.9%
도마2동 44
 
5.8%
월평1동 39
 
5.2%
변동 38
 
5.0%
갈마2동 36
 
4.8%
Other values (13) 292
38.6%

Length

2023-12-12T18:54:27.810095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가수원동 73
 
9.6%
도마1동 49
 
6.5%
관저2동 49
 
6.5%
갈마1동 47
 
6.2%
탄방동 45
 
5.9%
정림동 45
 
5.9%
도마2동 44
 
5.8%
월평1동 39
 
5.2%
변동 38
 
5.0%
갈마2동 36
 
4.8%
Other values (13) 292
38.6%

행정동코드
Real number (ℝ)

Distinct23
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170572 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T18:54:27.934154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.017054 × 109
median3.0170581 × 109
Q33.017059 × 109
95-th percentile3.0170642 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)5000

Descriptive statistics

Standard deviation3639.2534
Coefficient of variation (CV)1.2062262 × 10-6
Kurtosis-0.17939422
Mean3.0170572 × 109
Median Absolute Deviation (MAD)2100
Skewness0.35050663
Sum2.2839123 × 1012
Variance13244165
MonotonicityNot monotonic
2023-12-12T18:54:28.069341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3017059000 73
 
9.6%
3017059700 49
 
6.5%
3017052000 49
 
6.5%
3017058100 47
 
6.2%
3017055500 45
 
5.9%
3017053500 45
 
5.9%
3017053000 44
 
5.8%
3017058600 39
 
5.2%
3017054000 38
 
5.0%
3017058200 36
 
4.8%
Other values (13) 292
38.6%
ValueCountFrequency (%)
3017051000 36
4.8%
3017052000 49
6.5%
3017053000 44
5.8%
3017053500 45
5.9%
3017054000 38
5.0%
3017055000 28
3.7%
3017055500 45
5.9%
3017056000 35
4.6%
3017057000 21
2.8%
3017057500 30
4.0%
ValueCountFrequency (%)
3017066000 18
 
2.4%
3017065000 20
 
2.6%
3017064000 27
 
3.6%
3017063000 8
 
1.1%
3017060000 26
 
3.4%
3017059700 49
6.5%
3017059600 22
 
2.9%
3017059000 73
9.6%
3017058800 17
 
2.2%
3017058700 4
 
0.5%

법정동명
Categorical

Distinct27
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
도마동
93 
갈마동
83 
관저동
71 
월평동
60 
둔산동
53 
Other values (22)
397 

Length

Max length4
Median length3
Mean length2.9696169
Min length2

Unique

Unique4 ?
Unique (%)0.5%

Sample

1st row갈마동
2nd row갈마동
3rd row관저동
4th row괴정동
5th row갈마동

Common Values

ValueCountFrequency (%)
도마동 93
12.3%
갈마동 83
11.0%
관저동 71
 
9.4%
월평동 60
 
7.9%
둔산동 53
 
7.0%
가수원동 47
 
6.2%
탄방동 45
 
5.9%
정림동 40
 
5.3%
변동 38
 
5.0%
복수동 36
 
4.8%
Other values (17) 191
25.2%

Length

2023-12-12T18:54:28.249739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
도마동 93
12.3%
갈마동 83
11.0%
관저동 71
 
9.4%
월평동 60
 
7.9%
둔산동 53
 
7.0%
가수원동 47
 
6.2%
탄방동 45
 
5.9%
정림동 40
 
5.3%
변동 38
 
5.0%
복수동 36
 
4.8%
Other values (17) 191
25.2%

법정동코드
Real number (ℝ)

Distinct27
Distinct (%)3.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.017011 × 109
Minimum3.0170101 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T18:54:28.394312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170101 × 109
5-th percentile3.0170102 × 109
Q13.0170104 × 109
median3.0170111 × 109
Q33.0170114 × 109
95-th percentile3.017012 × 109
Maximum3.0170128 × 109
Range2700
Interquartile range (IQR)1000

Descriptive statistics

Standard deviation615.39375
Coefficient of variation (CV)2.0397465 × 10-7
Kurtosis0.5798335
Mean3.017011 × 109
Median Absolute Deviation (MAD)500
Skewness0.68338032
Sum2.2838773 × 1012
Variance378709.47
MonotonicityNot monotonic
2023-12-12T18:54:28.535518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3017010300 93
12.3%
3017011100 83
11.0%
3017011600 71
 
9.4%
3017011300 60
 
7.9%
3017011200 53
 
7.0%
3017011400 50
 
6.6%
3017010600 45
 
5.9%
3017010400 40
 
5.3%
3017010200 38
 
5.0%
3017010100 36
 
4.8%
Other values (17) 188
24.8%
ValueCountFrequency (%)
3017010100 36
 
4.8%
3017010200 38
5.0%
3017010300 93
12.3%
3017010400 40
5.3%
3017010500 28
 
3.7%
3017010600 45
5.9%
3017010800 35
 
4.6%
3017010900 21
 
2.8%
3017011000 30
 
4.0%
3017011100 83
11.0%
ValueCountFrequency (%)
3017012800 20
2.6%
3017012700 5
 
0.7%
3017012600 2
 
0.3%
3017012500 1
 
0.1%
3017012400 2
 
0.3%
3017012300 1
 
0.1%
3017012200 2
 
0.3%
3017012100 5
 
0.7%
3017012000 3
 
0.4%
3017011900 1
 
0.1%

지구대
Categorical

Distinct9
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
내동
146 
도마
128 
둔산
91 
갈마
86 
구봉
86 
Other values (4)
220 

Length

Max length4
Median length2
Mean length2.2774108
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row갈마
2nd row갈마
3rd row구봉
4th row내동
5th row갈마

Common Values

ValueCountFrequency (%)
내동 146
19.3%
도마 128
16.9%
둔산 91
12.0%
갈마 86
11.4%
구봉 86
11.4%
월평 77
10.2%
가수원 76
10.0%
도안지구 48
 
6.3%
<NA> 19
 
2.5%

Length

2023-12-12T18:54:28.694990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:28.864742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
내동 146
19.3%
도마 128
16.9%
둔산 91
12.0%
갈마 86
11.4%
구봉 86
11.4%
월평 77
10.2%
가수원 76
10.0%
도안지구 48
 
6.3%
na 19
 
2.5%

사업연도
Real number (ℝ)

Distinct17
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.6552
Minimum2005
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T18:54:29.001597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2005
5-th percentile2008
Q12011
median2014
Q32016
95-th percentile2020
Maximum2021
Range16
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.5788569
Coefficient of variation (CV)0.0017772938
Kurtosis-0.81686636
Mean2013.6552
Median Absolute Deviation (MAD)3
Skewness0.074809623
Sum1524337
Variance12.808217
MonotonicityIncreasing
2023-12-12T18:54:29.108588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
2016 161
21.3%
2010 92
12.2%
2011 86
11.4%
2012 70
9.2%
2015 66
8.7%
2009 42
 
5.5%
2019 40
 
5.3%
2013 34
 
4.5%
2017 31
 
4.1%
2014 28
 
3.7%
Other values (7) 107
14.1%
ValueCountFrequency (%)
2005 4
 
0.5%
2006 4
 
0.5%
2007 10
 
1.3%
2008 26
 
3.4%
2009 42
5.5%
2010 92
12.2%
2011 86
11.4%
2012 70
9.2%
2013 34
 
4.5%
2014 28
 
3.7%
ValueCountFrequency (%)
2021 20
 
2.6%
2020 25
 
3.3%
2019 40
 
5.3%
2018 18
 
2.4%
2017 31
 
4.1%
2016 161
21.3%
2015 66
8.7%
2014 28
 
3.7%
2013 34
 
4.5%
2012 70
9.2%

관리번호_시
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
<NA>
745 
2020.12이전
 
5
2020.4이전
 
4
2020.3이전
 
3

Length

Max length9
Median length4
Mean length4.0700132
Min length4

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> 745
98.4%
2020.12이전 5
 
0.7%
2020.4이전 4
 
0.5%
2020.3이전 3
 
0.4%

Length

2023-12-12T18:54:29.228157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:29.319351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 745
98.4%
2020.12이전 5
 
0.7%
2020.4이전 4
 
0.5%
2020.3이전 3
 
0.4%

관리번호_구
Text

UNIQUE 

Distinct757
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T18:54:29.557362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.365918
Min length4

Characters and Unicode

Total characters7847
Distinct characters14
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

Unique757 ?
Unique (%)100.0%

Sample

1st row1-2005-1
2nd row2-2005-2
3rd row3-2005-3
4th row4-2005-4
5th row5-2006-1
ValueCountFrequency (%)
차번 19
 
2.4%
1-2005-1 1
 
0.1%
422-2015-34 1
 
0.1%
424-2015-36 1
 
0.1%
425-2015-37 1
 
0.1%
426-2015-38 1
 
0.1%
427-2015-39 1
 
0.1%
428-2015-40 1
 
0.1%
429-2015-41 1
 
0.1%
430-2015-42 1
 
0.1%
Other values (748) 748
96.4%
2023-12-12T18:54:30.004436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1476
18.8%
2 1318
16.8%
1 1263
16.1%
0 1143
14.6%
5 466
 
5.9%
3 445
 
5.7%
6 440
 
5.6%
4 401
 
5.1%
7 293
 
3.7%
9 288
 
3.7%
Other values (4) 314
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6314
80.5%
Dash Punctuation 1476
 
18.8%
Other Letter 38
 
0.5%
Space Separator 19
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1318
20.9%
1 1263
20.0%
0 1143
18.1%
5 466
 
7.4%
3 445
 
7.0%
6 440
 
7.0%
4 401
 
6.4%
7 293
 
4.6%
9 288
 
4.6%
8 257
 
4.1%
Other Letter
ValueCountFrequency (%)
차 19
50.0%
번 19
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1476
100.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7809
99.5%
Hangul 38
 
0.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1476
18.9%
2 1318
16.9%
1 1263
16.2%
0 1143
14.6%
5 466
 
6.0%
3 445
 
5.7%
6 440
 
5.6%
4 401
 
5.1%
7 293
 
3.8%
9 288
 
3.7%
Other values (2) 276
 
3.5%
Hangul
ValueCountFrequency (%)
차 19
50.0%
번 19
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7809
99.5%
Hangul 38
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1476
18.9%
2 1318
16.9%
1 1263
16.2%
0 1143
14.6%
5 466
 
6.0%
3 445
 
5.7%
6 440
 
5.6%
4 401
 
5.1%
7 293
 
3.8%
9 288
 
3.7%
Other values (2) 276
 
3.5%
Hangul
ValueCountFrequency (%)
차 19
50.0%
번 19
50.0%

구분유형코드
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
58
483 
59
255 
60
 
19

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row58
2nd row58
3rd row58
4th row58
5th row58

Common Values

ValueCountFrequency (%)
58 483
63.8%
59 255
33.7%
60 19
 
2.5%

Length

2023-12-12T18:54:30.204056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:30.350082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
58 483
63.8%
59 255
33.7%
60 19
 
2.5%

구분_유형별
Categorical

Distinct3
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
방범용
483 
어린이보호
255 
차량번호인식
 
19

Length

Max length6
Median length3
Mean length3.7490092
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
방범용 483
63.8%
어린이보호 255
33.7%
차량번호인식 19
 
2.5%

Length

2023-12-12T18:54:30.477051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:30.587278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
방범용 483
63.8%
어린이보호 255
33.7%
차량번호인식 19
 
2.5%

구분_장소별
Categorical

Distinct7
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
우범지역
479 
도시공원
105 
초등학교
81 
보육시설
 
47
유치원
 
25
Other values (2)
 
20

Length

Max length4
Median length4
Mean length3.9669749
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
우범지역 479
63.3%
도시공원 105
 
13.9%
초등학교 81
 
10.7%
보육시설 47
 
6.2%
유치원 25
 
3.3%
주요도로 19
 
2.5%
특수학교 1
 
0.1%

Length

2023-12-12T18:54:30.717432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:30.872088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우범지역 479
63.3%
도시공원 105
 
13.9%
초등학교 81
 
10.7%
보육시설 47
 
6.2%
유치원 25
 
3.3%
주요도로 19
 
2.5%
특수학교 1
 
0.1%

설치년월일
Categorical

Distinct50
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2010-12
65 
2011-09
60 
2016-06
59 
2012-06
56 
2015-08
48 
Other values (45)
469 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique8 ?
Unique (%)1.1%

Sample

1st row2006-02
2nd row2006-02
3rd row2006-02
4th row2006-02
5th row2007-01

Common Values

ValueCountFrequency (%)
2010-12 65
 
8.6%
2011-09 60
 
7.9%
2016-06 59
 
7.8%
2012-06 56
 
7.4%
2015-08 48
 
6.3%
2015-09 42
 
5.5%
2016-11 41
 
5.4%
2009-05 32
 
4.2%
2010-07 27
 
3.6%
2017-08 26
 
3.4%
Other values (40) 301
39.8%

Length

2023-12-12T18:54:31.037877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2010-12 65
 
8.6%
2011-09 60
 
7.9%
2016-06 59
 
7.8%
2012-06 56
 
7.4%
2015-08 48
 
6.3%
2015-09 42
 
5.5%
2016-11 41
 
5.4%
2009-05 32
 
4.2%
2010-07 27
 
3.6%
2017-08 26
 
3.4%
Other values (40) 301
39.8%

설치위치_주소
Text

Distinct744
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T18:54:31.405549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length22.40819
Min length6

Characters and Unicode

Total characters16963
Distinct characters149
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique732 ?
Unique (%)96.7%

Sample

1st row신갈마로 209번길 65(갈마1동)(갈마1동 301-1)
2nd row계룡로 416번길 28(갈마동)(갈마동 344-21)
3rd row관저중로 94번길(관저동)(관저동 1016)
4th row도솔로 388번길 8(괴정동)(괴정동 423-21)
5th row괴정로 11번길 73(갈마동)(갈마2동 1416)
ValueCountFrequency (%)
도솔로 16
 
0.7%
계룡로 14
 
0.6%
가수원동 14
 
0.6%
13
 
0.6%
도안동 13
 
0.6%
신갈마로 11
 
0.5%
유등로 10
 
0.4%
탄방로 10
 
0.4%
문정로 9
 
0.4%
관저2동 9
 
0.4%
Other values (1687) 2122
94.7%
2023-12-12T18:54:31.900719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1487
 
8.8%
동 1371
 
8.1%
1 1298
 
7.7%
) 1260
 
7.4%
( 1259
 
7.4%
2 843
 
5.0%
3 620
 
3.7%
로 528
 
3.1%
- 494
 
2.9%
4 481
 
2.8%
Other values (139) 7322
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6778
40.0%
Decimal Number 5674
33.4%
Space Separator 1487
 
8.8%
Close Punctuation 1260
 
7.4%
Open Punctuation 1259
 
7.4%
Dash Punctuation 494
 
2.9%
Other Punctuation 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1371
20.2%
로 528
 
7.8%
길 425
 
6.3%
마 409
 
6.0%
번 338
 
5.0%
도 305
 
4.5%
갈 212
 
3.1%
정 206
 
3.0%
수 172
 
2.5%
평 149
 
2.2%
Other values (121) 2663
39.3%
Decimal Number
ValueCountFrequency (%)
1 1298
22.9%
2 843
14.9%
3 620
10.9%
4 481
 
8.5%
5 466
 
8.2%
6 435
 
7.7%
8 411
 
7.2%
0 388
 
6.8%
7 375
 
6.6%
9 357
 
6.3%
Other Punctuation
ValueCountFrequency (%)
/ 5
45.5%
@ 4
36.4%
, 1
 
9.1%
? 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1487
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1260
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1259
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10185
60.0%
Hangul 6778
40.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1371
20.2%
로 528
 
7.8%
길 425
 
6.3%
마 409
 
6.0%
번 338
 
5.0%
도 305
 
4.5%
갈 212
 
3.1%
정 206
 
3.0%
수 172
 
2.5%
평 149
 
2.2%
Other values (121) 2663
39.3%
Common
ValueCountFrequency (%)
1487
14.6%
1 1298
12.7%
) 1260
12.4%
( 1259
12.4%
2 843
8.3%
3 620
6.1%
- 494
 
4.9%
4 481
 
4.7%
5 466
 
4.6%
6 435
 
4.3%
Other values (8) 1542
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10185
60.0%
Hangul 6778
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1487
14.6%
1 1298
12.7%
) 1260
12.4%
( 1259
12.4%
2 843
8.3%
3 620
6.1%
- 494
 
4.9%
4 481
 
4.7%
5 466
 
4.6%
6 435
 
4.3%
Other values (8) 1542
15.1%
Hangul
ValueCountFrequency (%)
동 1371
20.2%
로 528
 
7.8%
길 425
 
6.3%
마 409
 
6.0%
번 338
 
5.0%
도 305
 
4.5%
갈 212
 
3.1%
정 206
 
3.0%
수 172
 
2.5%
평 149
 
2.2%
Other values (121) 2663
39.3%

설치위치_상세현황
Text

Distinct733
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
2023-12-12T18:54:32.198447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length7.1030383
Min length3

Characters and Unicode

Total characters5377
Distinct characters446
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

Unique714 ?
Unique (%)94.3%

Sample

1st row그린빌라 인근
2nd row물댄동산 인근
3rd row국민은행 앞
4th row롯데백화점 주차장
5th row둔원중 정문
ValueCountFrequency (%)
앞 58
 
5.8%
인근 16
 
1.6%
옆 13
 
1.3%
정문 12
 
1.2%
주택가 11
 
1.1%
후문 9
 
0.9%
맞은편 8
 
0.8%
입구 7
 
0.7%
골목 6
 
0.6%
뒤 6
 
0.6%
Other values (773) 861
85.5%
2023-12-12T18:54:32.719806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
256
 
4.8%
원 237
 
4.4%
공 165
 
3.1%
이 164
 
3.1%
린 162
 
3.0%
교 156
 
2.9%
앞 149
 
2.8%
어 135
 
2.5%
초 117
 
2.2%
정 84
 
1.6%
Other values (436) 3752
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4835
89.9%
Space Separator 256
 
4.8%
Decimal Number 115
 
2.1%
Other Punctuation 57
 
1.1%
Close Punctuation 41
 
0.8%
Open Punctuation 41
 
0.8%
Uppercase Letter 25
 
0.5%
Lowercase Letter 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 237
 
4.9%
공 165
 
3.4%
이 164
 
3.4%
린 162
 
3.4%
교 156
 
3.2%
앞 149
 
3.1%
어 135
 
2.8%
초 117
 
2.4%
정 84
 
1.7%
문 75
 
1.6%
Other values (400) 3391
70.1%
Uppercase Letter
ValueCountFrequency (%)
G 4
16.0%
C 3
12.0%
S 3
12.0%
N 2
8.0%
E 2
8.0%
I 2
8.0%
L 2
8.0%
U 1
 
4.0%
Y 1
 
4.0%
M 1
 
4.0%
Other values (4) 4
16.0%
Decimal Number
ValueCountFrequency (%)
1 38
33.0%
0 23
20.0%
2 15
 
13.0%
3 13
 
11.3%
5 10
 
8.7%
4 7
 
6.1%
9 6
 
5.2%
7 1
 
0.9%
8 1
 
0.9%
6 1
 
0.9%
Other Punctuation
ValueCountFrequency (%)
/ 22
38.6%
, 16
28.1%
@ 15
26.3%
? 2
 
3.5%
* 1
 
1.8%
＠ 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
m 5
71.4%
k 1
 
14.3%
t 1
 
14.3%
Space Separator
ValueCountFrequency (%)
256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4835
89.9%
Common 510
 
9.5%
Latin 32
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 237
 
4.9%
공 165
 
3.4%
이 164
 
3.4%
린 162
 
3.4%
교 156
 
3.2%
앞 149
 
3.1%
어 135
 
2.8%
초 117
 
2.4%
정 84
 
1.7%
문 75
 
1.6%
Other values (400) 3391
70.1%
Common
ValueCountFrequency (%)
256
50.2%
) 41
 
8.0%
( 41
 
8.0%
1 38
 
7.5%
0 23
 
4.5%
/ 22
 
4.3%
, 16
 
3.1%
2 15
 
2.9%
@ 15
 
2.9%
3 13
 
2.5%
Other values (9) 30
 
5.9%
Latin
ValueCountFrequency (%)
m 5
15.6%
G 4
12.5%
C 3
9.4%
S 3
9.4%
N 2
 
6.2%
E 2
 
6.2%
I 2
 
6.2%
L 2
 
6.2%
U 1
 
3.1%
k 1
 
3.1%
Other values (7) 7
21.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4835
89.9%
ASCII 541
 
10.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
256
47.3%
) 41
 
7.6%
( 41
 
7.6%
1 38
 
7.0%
0 23
 
4.3%
/ 22
 
4.1%
, 16
 
3.0%
2 15
 
2.8%
@ 15
 
2.8%
3 13
 
2.4%
Other values (25) 61
 
11.3%
Hangul
ValueCountFrequency (%)
원 237
 
4.9%
공 165
 
3.4%
이 164
 
3.4%
린 162
 
3.4%
교 156
 
3.2%
앞 149
 
3.1%
어 135
 
2.8%
초 117
 
2.4%
정 84
 
1.7%
문 75
 
1.6%
Other values (400) 3391
70.1%
None
ValueCountFrequency (%)
＠ 1
100.0%

위도
Real number (ℝ)

Distinct750
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.326317
Minimum36.220798
Maximum36.371049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T18:54:32.912663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.220798
5-th percentile36.293908
Q136.307389
median36.329803
Q336.346256
95-th percentile36.359777
Maximum36.371049
Range0.150251
Interquartile range (IQR)0.038867

Descriptive statistics

Standard deviation0.025702472
Coefficient of variation (CV)0.00070754413
Kurtosis1.5896248
Mean36.326317
Median Absolute Deviation (MAD)0.019284
Skewness-0.93938604
Sum27499.022
Variance0.00066061708
MonotonicityNot monotonic
2023-12-12T18:54:33.083749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.349939 2
 
0.3%
36.295853 2
 
0.3%
36.339383 2
 
0.3%
36.299936 2
 
0.3%
36.354697 2
 
0.3%
36.318522 2
 
0.3%
36.3495 2
 
0.3%
36.357888 1
 
0.1%
36.355672 1
 
0.1%
36.305814 1
 
0.1%
Other values (740) 740
97.8%
ValueCountFrequency (%)
36.220798 1
0.1%
36.2219841 1
0.1%
36.226232 1
0.1%
36.227322 1
0.1%
36.231794 1
0.1%
36.235367 1
0.1%
36.236433 1
0.1%
36.237481 1
0.1%
36.238606 1
0.1%
36.238622 1
0.1%
ValueCountFrequency (%)
36.371049 1
0.1%
36.370739 1
0.1%
36.369736 1
0.1%
36.369412 1
0.1%
36.368147 1
0.1%
36.367689 1
0.1%
36.367378 1
0.1%
36.367359 1
0.1%
36.367233 1
0.1%
36.366514 1
0.1%

경도
Real number (ℝ)

Distinct747
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.36913
Minimum127.28567
Maximum127.4019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.8 KiB
2023-12-12T18:54:33.263090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.28567
5-th percentile127.33413
Q1127.36036
median127.37271
Q3127.38082
95-th percentile127.39654
Maximum127.4019
Range0.116226
Interquartile range (IQR)0.020464

Descriptive statistics

Standard deviation0.019142292
Coefficient of variation (CV)0.00015028988
Kurtosis0.79283409
Mean127.36913
Median Absolute Deviation (MAD)0.009472
Skewness-0.84525174
Sum96418.435
Variance0.00036642736
MonotonicityNot monotonic
2023-12-12T18:54:33.485080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.401897 2
 
0.3%
127.376719 2
 
0.3%
127.372303 2
 
0.3%
127.378103 2
 
0.3%
127.373269 2
 
0.3%
127.368764 2
 
0.3%
127.378675 2
 
0.3%
127.371253 2
 
0.3%
127.365958 2
 
0.3%
127.394928 2
 
0.3%
Other values (737) 737
97.4%
ValueCountFrequency (%)
127.285671 1
0.1%
127.293885 1
0.1%
127.3015425 1
0.1%
127.307286 1
0.1%
127.309543 1
0.1%
127.309812 1
0.1%
127.313865 1
0.1%
127.315595 1
0.1%
127.315694 1
0.1%
127.317439 1
0.1%
ValueCountFrequency (%)
127.401897 2
0.3%
127.401767 1
0.1%
127.401588 1
0.1%
127.401376 1
0.1%
127.401331 1
0.1%
127.401297 1
0.1%
127.4012657 1
0.1%
127.401156 1
0.1%
127.400736 1
0.1%
127.400617 1
0.1%

cctv_개소수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
1
757 

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 (%)
1 757
100.0%

Length

2023-12-12T18:54:33.653978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:33.768317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 757
100.0%

cctv_대수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
1
684 
0
73 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 684
90.4%
0 73
 
9.6%

Length

2023-12-12T18:54:33.896528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:34.014222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 684
90.4%
0 73
 
9.6%

한전주_기타_건물외벽
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
0
684 
1
73 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 684
90.4%
1 73
 
9.6%

Length

2023-12-12T18:54:34.130454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:34.280409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 684
90.4%
1 73
 
9.6%

카메라대수
Categorical

Distinct4
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size6.0 KiB
1
349 
2
328 
3
73 
4
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row3
5th row2

Common Values

ValueCountFrequency (%)
1 349
46.1%
2 328
43.3%
3 73
 
9.6%
4 7
 
0.9%

Length

2023-12-12T18:54:34.446998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T18:54:34.566162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 349
46.1%
2 328
43.3%
3 73
 
9.6%
4 7
 
0.9%

비고
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing750
Missing (%)99.1%
Memory size6.0 KiB
2023-12-12T18:54:34.729691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length12
Mean length14.142857
Min length8

Characters and Unicode

Total characters99
Distinct characters44
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

Unique7 ?
Unique (%)100.0%

Sample

1st row숭어리샘 철거 장비 설치(531-2016-22)
2nd row1대(2차로 감시)
3rd row어린이안전 주품목
4th row도시디자인 신규 주품목
5th row재난안전 주품목
ValueCountFrequency (%)
주품목 3
14.3%
방범용 2
 
9.5%
신규설치 2
 
9.5%
주품 2
 
9.5%
숭어리샘 1
 
4.8%
철거 1
 
4.8%
장비 1
 
4.8%
설치(531-2016-22 1
 
4.8%
1대(2차로 1
 
4.8%
감시 1
 
4.8%
Other values (6) 6
28.6%
2023-12-12T18:54:35.117361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14
 
14.1%
2 8
 
8.1%
주 5
 
5.1%
품 5
 
5.1%
1 4
 
4.0%
0 4
 
4.0%
목 3
 
3.0%
규 3
 
3.0%
설 3
 
3.0%
치 3
 
3.0%
Other values (34) 47
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60
60.6%
Decimal Number 19
 
19.2%
Space Separator 14
 
14.1%
Dash Punctuation 2
 
2.0%
Close Punctuation 2
 
2.0%
Open Punctuation 2
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 5
 
8.3%
품 5
 
8.3%
목 3
 
5.0%
규 3
 
5.0%
설 3
 
5.0%
치 3
 
5.0%
신 3
 
5.0%
시 2
 
3.3%
어 2
 
3.3%
용 2
 
3.3%
Other values (24) 29
48.3%
Decimal Number
ValueCountFrequency (%)
2 8
42.1%
1 4
21.1%
0 4
21.1%
6 1
 
5.3%
3 1
 
5.3%
5 1
 
5.3%
Space Separator
ValueCountFrequency (%)
14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60
60.6%
Common 39
39.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 5
 
8.3%
품 5
 
8.3%
목 3
 
5.0%
규 3
 
5.0%
설 3
 
5.0%
치 3
 
5.0%
신 3
 
5.0%
시 2
 
3.3%
어 2
 
3.3%
용 2
 
3.3%
Other values (24) 29
48.3%
Common
ValueCountFrequency (%)
14
35.9%
2 8
20.5%
1 4
 
10.3%
0 4
 
10.3%
- 2
 
5.1%
) 2
 
5.1%
( 2
 
5.1%
6 1
 
2.6%
3 1
 
2.6%
5 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60
60.6%
ASCII 39
39.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14
35.9%
2 8
20.5%
1 4
 
10.3%
0 4
 
10.3%
- 2
 
5.1%
) 2
 
5.1%
( 2
 
5.1%
6 1
 
2.6%
3 1
 
2.6%
5 1
 
2.6%
Hangul
ValueCountFrequency (%)
주 5
 
8.3%
품 5
 
8.3%
목 3
 
5.0%
규 3
 
5.0%
설 3
 
5.0%
치 3
 
5.0%
신 3
 
5.0%
시 2
 
3.3%
어 2
 
3.3%
용 2
 
3.3%
Other values (24) 29
48.3%

Sample

행정동행정동코드법정동명법정동코드지구대사업연도관리번호_시관리번호_구구분유형코드구분_유형별구분_장소별설치년월일설치위치_주소설치위치_상세현황위도경도cctv_개소수cctv_대수한전주_기타_건물외벽카메라대수비고
0갈마1동3017058100갈마동3017011100갈마2005<NA>1-2005-158방범용우범지역2006-02신갈마로 209번길 65(갈마1동)(갈마1동 301-1)그린빌라 인근36.352222127.3646381012<NA>
1갈마2동3017058200갈마동3017011100갈마2005<NA>2-2005-258방범용우범지역2006-02계룡로 416번길 28(갈마동)(갈마동 344-21)물댄동산 인근36.348999127.3734431101<NA>
2관저2동3017059700관저동3017011600구봉2005<NA>3-2005-358방범용우범지역2006-02관저중로 94번길(관저동)(관저동 1016)국민은행 앞36.300556127.3353441102<NA>
3괴정동3017056000괴정동3017010800내동2005<NA>4-2005-458방범용우범지역2006-02도솔로 388번길 8(괴정동)(괴정동 423-21)롯데백화점 주차장36.339914127.3891061103<NA>
4갈마2동3017058200갈마동3017011100갈마2006<NA>5-2006-158방범용우범지역2007-01괴정로 11번길 73(갈마동)(갈마2동 1416)둔원중 정문36.341744127.3771171102<NA>
5도마2동3017053000도마동3017010300도마2006<NA>6-2006-258방범용우범지역2007-01도솔4길 25(도마동)(도마2동 120-29)배재대 먹자골목36.316778127.3723281102<NA>
6용문동3017055000용문동3017010500내동2006<NA>7-2006-358방범용우범지역2007-01도솔로 511번길 51(용문동)(용문동 215-21)제일택시 뒤편36.342031127.4011561102<NA>
7월평1동3017058600월평동3017011300월평2006<NA>8-2006-458방범용우범지역2007-01월평중로 13번길 53(월평동)(월평1동 1041)월평동성당옆36.355647127.3610081102<NA>
8갈마2동3017058200갈마동3017011100갈마2007<NA>10-2007-258방범용우범지역2007-08갈마중로 28(갈마동)(갈마2동 345-1)동산@놀이터 인근36.354072127.3700751101<NA>
9괴정동3017056000괴정동3017010800내동2007<NA>11-2007-358방범용우범지역2007-08괴정로 115번길 30(괴정동)(괴정동 50-1)백운어린이공원옆36.347594127.3722811102<NA>
행정동행정동코드법정동명법정동코드지구대사업연도관리번호_시관리번호_구구분유형코드구분_유형별구분_장소별설치년월일설치위치_주소설치위치_상세현황위도경도cctv_개소수cctv_대수한전주_기타_건물외벽카메라대수비고
747내동3017057500내동3017011000내동2021<NA>729-2021-1058방범용우범지역2021-06동서대로 1013-4(내동 23-15)쌈지공원 골목36.31211127.374731102<NA>
748도마2동3017053000도마동3017010300도마2021<NA>730-2021-1158방범용우범지역2021-06제비내 9길 37(도마2동 164-10)대신주택 옆 골목36.301072127.3773851012<NA>
749복수동3017051000복수동3017010100도마2021<NA>731-2021-1258방범용우범지역2021-06복수동로 40-33(복수동 457)신계중학교 정문앞36.352618127.3710291102<NA>
750갈마1동3017058100갈마동3017011100갈마2021<NA>732-2021-1358방범용우범지역2021-06계룡로 379-16(갈마1동 269-24)대진영빌라 앞36.356071127.3666071012<NA>
751월평1동3017058600월평동3017011300월평2021<NA>733-2021-1458방범용우범지역2021-06월평로 88(월평1동 677)월평중 옆 번화가 도로36.371049127.3930241102<NA>
752만년동3017065000만년동3017012800월평2021<NA>734-2021-1558방범용우범지역2021-06만년동 397수상스포츠체험장 입구36.299463127.3417421103<NA>
753관저2동3017059700관저동3017011600구봉2021<NA>735-2021-1658방범용우범지역2021-06관저로 175(관저2동 1409)느리울근린공원 앞36.239976127.3138651102<NA>
754기성동3017060000평촌동3017012100구봉2021<NA>736-2021-1758방범용우범지역2021-06돌마루길 188-1(평촌동 318-20)돌마루길 주택가36.307134127.3665921013<NA>
755정림동3017053500정림동3017010400가수원2021<NA>737-2021-1858방범용우범지역2021-06정림로 70번길 30(정림동 123-4)공영빌라 앞36.306498127.3477951012<NA>
756가수원동3017059000가수원동3017011400가수원2021<NA>738-2021-1958방범용우범지역2021-06원도안로 25번길 24(가수원동 862)공주칼국수 뒷길36.299249127.3559261102<NA>