Overview

Dataset statistics

Number of variables14
Number of observations3927
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows138
Duplicate rows (%)3.5%
Total size in memory445.0 KiB
Average record size in memory116.0 B

Variable types

Categorical3
Text4
Numeric4
Unsupported1
DateTime2

Dataset

Description전라북도_CCTV_20170630_최종수정본
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=201902

Alerts

출처 has constant value ""Constant
Dataset has 138 (3.5%) duplicate rowsDuplicates
경도 is highly overall correlated with 관리기관명High correlation
위도 is highly overall correlated with 관리기관명High correlation
관리기관명 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
카메라화소수 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 23:45:21.233587
Analysis finished2024-03-13 23:45:24.208068
Duration2.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
전라북도 전주시청
910 
전라북도 군산시청
571 
전라북도 익산시청
469 
전라북도 무주군청
404 
전라북도 완주군청
263 
Other values (10)
1310 

Length

Max length10
Median length9
Mean length9.0050929
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전라북도 고창군청
2nd row전라북도 고창군청
3rd row전라북도 고창군청
4th row전라북도 고창군청
5th row전라북도 고창군청

Common Values

ValueCountFrequency (%)
전라북도 전주시청 910
23.2%
전라북도 군산시청 571
14.5%
전라북도 익산시청 469
11.9%
전라북도 무주군청 404
10.3%
전라북도 완주군청 263
 
6.7%
전라북도 정읍시청 259
 
6.6%
전라북도 김제시청 230
 
5.9%
전라북도 고창군청 209
 
5.3%
전라북도 남원시청 136
 
3.5%
전라북도 부안군청 119
 
3.0%
Other values (5) 357
 
9.1%

Length

2024-03-14T08:45:24.265120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전라북도 3927
50.0%
전주시청 910
 
11.6%
군산시청 571
 
7.3%
익산시청 469
 
6.0%
무주군청 404
 
5.1%
완주군청 263
 
3.3%
정읍시청 259
 
3.3%
김제시청 230
 
2.9%
고창군청 209
 
2.7%
부안군청 139
 
1.8%
Other values (5) 473
 
6.0%

소재지주소
Text

Distinct3361
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2024-03-14T08:45:24.681998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length20.195824
Min length14

Characters and Unicode

Total characters79309
Distinct characters344
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

Unique2978 ?
Unique (%)75.8%

Sample

1st row전라북도 고창군 성송면 암치리 232-7
2nd row전라북도 고창군 고창읍 교촌리 88-4
3rd row전라북도 고창군 고창읍 교촌리 산12
4th row전라북도 고창군 고창읍 월곡리 574-3
5th row전라북도 고창군 고창읍 월곡14길 3
ValueCountFrequency (%)
전라북도 3927
 
21.2%
전주시 908
 
4.9%
군산시 571
 
3.1%
완산구 481
 
2.6%
익산시 470
 
2.5%
덕진구 428
 
2.3%
무주군 404
 
2.2%
완주군 265
 
1.4%
정읍시 260
 
1.4%
김제시 228
 
1.2%
Other values (4086) 10552
57.1%
2024-03-14T08:45:25.122317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15011
18.9%
전 4894
 
6.2%
북 4003
 
5.0%
도 4000
 
5.0%
라 3935
 
5.0%
1 3031
 
3.8%
시 2608
 
3.3%
산 2144
 
2.7%
군 1954
 
2.5%
2 1925
 
2.4%
Other values (334) 35804
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48704
61.4%
Space Separator 15011
 
18.9%
Decimal Number 13686
 
17.3%
Dash Punctuation 1878
 
2.4%
Open Punctuation 10
 
< 0.1%
Close Punctuation 10
 
< 0.1%
Other Punctuation 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 4894
 
10.0%
북 4003
 
8.2%
도 4000
 
8.2%
라 3935
 
8.1%
시 2608
 
5.4%
산 2144
 
4.4%
군 1954
 
4.0%
주 1782
 
3.7%
리 1328
 
2.7%
면 1260
 
2.6%
Other values (316) 20796
42.7%
Decimal Number
ValueCountFrequency (%)
1 3031
22.1%
2 1925
14.1%
3 1604
11.7%
4 1226
9.0%
5 1203
 
8.8%
6 1059
 
7.7%
7 990
 
7.2%
9 924
 
6.8%
8 903
 
6.6%
0 821
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 4
40.0%
. 4
40.0%
? 1
 
10.0%
/ 1
 
10.0%
Space Separator
ValueCountFrequency (%)
15011
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1878
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48704
61.4%
Common 30605
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 4894
 
10.0%
북 4003
 
8.2%
도 4000
 
8.2%
라 3935
 
8.1%
시 2608
 
5.4%
산 2144
 
4.4%
군 1954
 
4.0%
주 1782
 
3.7%
리 1328
 
2.7%
면 1260
 
2.6%
Other values (316) 20796
42.7%
Common
ValueCountFrequency (%)
15011
49.0%
1 3031
 
9.9%
2 1925
 
6.3%
- 1878
 
6.1%
3 1604
 
5.2%
4 1226
 
4.0%
5 1203
 
3.9%
6 1059
 
3.5%
7 990
 
3.2%
9 924
 
3.0%
Other values (8) 1754
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48704
61.4%
ASCII 30605
38.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15011
49.0%
1 3031
 
9.9%
2 1925
 
6.3%
- 1878
 
6.1%
3 1604
 
5.2%
4 1226
 
4.0%
5 1203
 
3.9%
6 1059
 
3.5%
7 990
 
3.2%
9 924
 
3.0%
Other values (8) 1754
 
5.7%
Hangul
ValueCountFrequency (%)
전 4894
 
10.0%
북 4003
 
8.2%
도 4000
 
8.2%
라 3935
 
8.1%
시 2608
 
5.4%
산 2144
 
4.4%
군 1954
 
4.0%
주 1782
 
3.7%
리 1328
 
2.7%
면 1260
 
2.6%
Other values (316) 20796
42.7%

소재지지번주소
Text

Distinct3346
Distinct (%)85.2%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2024-03-14T08:45:25.436814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length35
Mean length21.107716
Min length14

Characters and Unicode

Total characters82890
Distinct characters283
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

Unique2953 ?
Unique (%)75.2%

Sample

1st row전라북도 고창군 성송면 암치리 산92-4
2nd row전라북도 고창군 고창읍 교촌리 88-4
3rd row전라북도 고창군 고창읍 교촌리 산12
4th row전라북도 고창군 고창읍 월곡리 574-3
5th row전라북도 고창군 고창읍 월곡리 587
ValueCountFrequency (%)
전라북도 3934
 
21.1%
전주시 908
 
4.9%
군산시 571
 
3.1%
완산구 480
 
2.6%
익산시 470
 
2.5%
덕진구 428
 
2.3%
무주군 404
 
2.2%
완주군 265
 
1.4%
정읍시 260
 
1.4%
김제시 228
 
1.2%
Other values (4008) 10684
57.3%
2024-03-14T08:45:25.851853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15086
18.2%
전 4880
 
5.9%
도 4036
 
4.9%
북 4030
 
4.9%
라 3939
 
4.8%
1 3372
 
4.1%
- 2837
 
3.4%
시 2606
 
3.1%
동 2284
 
2.8%
산 2215
 
2.7%
Other values (273) 37605
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48761
58.8%
Decimal Number 16161
 
19.5%
Space Separator 15086
 
18.2%
Dash Punctuation 2837
 
3.4%
Close Punctuation 15
 
< 0.1%
Open Punctuation 15
 
< 0.1%
Other Punctuation 11
 
< 0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 4880
 
10.0%
도 4036
 
8.3%
북 4030
 
8.3%
라 3939
 
8.1%
시 2606
 
5.3%
동 2284
 
4.7%
산 2215
 
4.5%
군 1955
 
4.0%
리 1834
 
3.8%
주 1768
 
3.6%
Other values (252) 19214
39.4%
Decimal Number
ValueCountFrequency (%)
1 3372
20.9%
2 2163
13.4%
3 1784
11.0%
5 1485
9.2%
4 1402
8.7%
6 1387
8.6%
7 1285
 
8.0%
8 1226
 
7.6%
9 1093
 
6.8%
0 964
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
25.0%
C 1
25.0%
A 1
25.0%
Y 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 9
81.8%
· 1
 
9.1%
/ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
15086
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2837
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48761
58.8%
Common 34125
41.2%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 4880
 
10.0%
도 4036
 
8.3%
북 4030
 
8.3%
라 3939
 
8.1%
시 2606
 
5.3%
동 2284
 
4.7%
산 2215
 
4.5%
군 1955
 
4.0%
리 1834
 
3.8%
주 1768
 
3.6%
Other values (252) 19214
39.4%
Common
ValueCountFrequency (%)
15086
44.2%
1 3372
 
9.9%
- 2837
 
8.3%
2 2163
 
6.3%
3 1784
 
5.2%
5 1485
 
4.4%
4 1402
 
4.1%
6 1387
 
4.1%
7 1285
 
3.8%
8 1226
 
3.6%
Other values (7) 2098
 
6.1%
Latin
ValueCountFrequency (%)
M 1
25.0%
C 1
25.0%
A 1
25.0%
Y 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48761
58.8%
ASCII 34128
41.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15086
44.2%
1 3372
 
9.9%
- 2837
 
8.3%
2 2163
 
6.3%
3 1784
 
5.2%
5 1485
 
4.4%
4 1402
 
4.1%
6 1387
 
4.1%
7 1285
 
3.8%
8 1226
 
3.6%
Other values (10) 2101
 
6.2%
Hangul
ValueCountFrequency (%)
전 4880
 
10.0%
도 4036
 
8.3%
북 4030
 
8.3%
라 3939
 
8.1%
시 2606
 
5.3%
동 2284
 
4.7%
산 2215
 
4.5%
군 1955
 
4.0%
리 1834
 
3.8%
주 1768
 
3.6%
Other values (252) 19214
39.4%
None
ValueCountFrequency (%)
· 1
100.0%

설치목적구분
Categorical

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
생활방범
1652 
어린이보호
1392 
차량방범
263 
시설물관리
 
151
재난재해
 
148
Other values (7)
321 

Length

Max length6
Median length4
Mean length4.3791698
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row생활방범
2nd row어린이보호
3rd row재난재해
4th row생활방범
5th row기타

Common Values

ValueCountFrequency (%)
생활방범 1652
42.1%
어린이보호 1392
35.4%
차량방범 263
 
6.7%
시설물관리 151
 
3.8%
재난재해 148
 
3.8%
교통단속 121
 
3.1%
기타 84
 
2.1%
교통정보수집 48
 
1.2%
쓰레기단속 37
 
0.9%
다목적 25
 
0.6%
Other values (2) 6
 
0.2%

Length

2024-03-14T08:45:25.990310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
생활방범 1652
42.1%
어린이보호 1392
35.4%
차량방범 264
 
6.7%
재난재해 153
 
3.9%
시설물관리 151
 
3.8%
교통단속 121
 
3.1%
기타 84
 
2.1%
교통정보수집 48
 
1.2%
쓰레기단속 37
 
0.9%
다목적 25
 
0.6%

카메라대수
Real number (ℝ)

Distinct24
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1973517
Minimum1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-03-14T08:45:26.087230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum65
Range64
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.1320429
Coefficient of variation (CV)0.97027841
Kurtosis319.47918
Mean2.1973517
Median Absolute Deviation (MAD)1
Skewness13.548204
Sum8629
Variance4.5456068
MonotonicityNot monotonic
2024-03-14T08:45:26.217466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
2 1842
46.9%
1 1158
29.5%
3 657
 
16.7%
4 158
 
4.0%
6 21
 
0.5%
5 17
 
0.4%
8 14
 
0.4%
10 10
 
0.3%
12 8
 
0.2%
15 6
 
0.2%
Other values (14) 36
 
0.9%
ValueCountFrequency (%)
1 1158
29.5%
2 1842
46.9%
3 657
 
16.7%
4 158
 
4.0%
5 17
 
0.4%
6 21
 
0.5%
7 4
 
0.1%
8 14
 
0.4%
9 6
 
0.2%
10 10
 
0.3%
ValueCountFrequency (%)
65 1
 
< 0.1%
57 1
 
< 0.1%
25 1
 
< 0.1%
24 1
 
< 0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%
18 1
 
< 0.1%
17 1
 
< 0.1%
16 5
0.1%
15 6
0.2%

카메라화소수
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size30.8 KiB

촬영방면정보
Text

Distinct1017
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2024-03-14T08:45:26.483267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length9.1471861
Min length2

Characters and Unicode

Total characters35921
Distinct characters480
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique937 ?
Unique (%)23.9%

Sample

1st row도로
2nd row360도전방면
3rd row산불감시
4th row도로
5th row360도전방면
ValueCountFrequency (%)
반경100m 1245
16.8%
이내 1015
13.7%
360도 512
 
6.9%
전방면 512
 
6.9%
반경100m이내 469
 
6.3%
방면 384
 
5.2%
360도전방면 317
 
4.3%
마을입구 178
 
2.4%
도로 129
 
1.7%
정문 111
 
1.5%
Other values (1232) 2519
34.1%
2024-03-14T08:45:26.969148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4275
 
11.9%
3479
 
9.7%
1 1772
 
4.9%
경 1753
 
4.9%
반 1718
 
4.8%
m 1715
 
4.8%
내 1658
 
4.6%
이 1636
 
4.6%
방 1347
 
3.7%
면 1344
 
3.7%
Other values (470) 15224
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22224
61.9%
Decimal Number 7920
 
22.0%
Space Separator 3479
 
9.7%
Lowercase Letter 1718
 
4.8%
Other Punctuation 445
 
1.2%
Dash Punctuation 46
 
0.1%
Uppercase Letter 45
 
0.1%
Close Punctuation 21
 
0.1%
Open Punctuation 20
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1753
 
7.9%
반 1718
 
7.7%
내 1658
 
7.5%
이 1636
 
7.4%
방 1347
 
6.1%
면 1344
 
6.0%
도 1065
 
4.8%
전 880
 
4.0%
원 426
 
1.9%
교 332
 
1.5%
Other values (435) 10065
45.3%
Uppercase Letter
ValueCountFrequency (%)
C 14
31.1%
I 10
22.2%
B 4
 
8.9%
K 4
 
8.9%
H 2
 
4.4%
S 2
 
4.4%
G 2
 
4.4%
U 2
 
4.4%
L 1
 
2.2%
T 1
 
2.2%
Other values (3) 3
 
6.7%
Decimal Number
ValueCountFrequency (%)
0 4275
54.0%
1 1772
22.4%
3 858
 
10.8%
6 846
 
10.7%
2 46
 
0.6%
4 44
 
0.6%
7 23
 
0.3%
9 21
 
0.3%
8 21
 
0.3%
5 14
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
m 1715
99.8%
s 1
 
0.1%
k 1
 
0.1%
y 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
= 1
50.0%
> 1
50.0%
Space Separator
ValueCountFrequency (%)
3479
100.0%
Other Punctuation
ValueCountFrequency (%)
, 445
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22225
61.9%
Common 11933
33.2%
Latin 1763
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1753
 
7.9%
반 1718
 
7.7%
내 1658
 
7.5%
이 1636
 
7.4%
방 1347
 
6.1%
면 1344
 
6.0%
도 1065
 
4.8%
전 880
 
4.0%
원 426
 
1.9%
교 332
 
1.5%
Other values (436) 10066
45.3%
Common
ValueCountFrequency (%)
0 4275
35.8%
3479
29.2%
1 1772
14.8%
3 858
 
7.2%
6 846
 
7.1%
, 445
 
3.7%
- 46
 
0.4%
2 46
 
0.4%
4 44
 
0.4%
7 23
 
0.2%
Other values (7) 99
 
0.8%
Latin
ValueCountFrequency (%)
m 1715
97.3%
C 14
 
0.8%
I 10
 
0.6%
B 4
 
0.2%
K 4
 
0.2%
H 2
 
0.1%
S 2
 
0.1%
G 2
 
0.1%
U 2
 
0.1%
L 1
 
0.1%
Other values (7) 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22224
61.9%
ASCII 13696
38.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4275
31.2%
3479
25.4%
1 1772
12.9%
m 1715
12.5%
3 858
 
6.3%
6 846
 
6.2%
, 445
 
3.2%
- 46
 
0.3%
2 46
 
0.3%
4 44
 
0.3%
Other values (24) 170
 
1.2%
Hangul
ValueCountFrequency (%)
경 1753
 
7.9%
반 1718
 
7.7%
내 1658
 
7.5%
이 1636
 
7.4%
방 1347
 
6.1%
면 1344
 
6.0%
도 1065
 
4.8%
전 880
 
4.0%
원 426
 
1.9%
교 332
 
1.5%
Other values (435) 10065
45.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

보관일수
Real number (ℝ)

Distinct104
Distinct (%)2.6%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean31.735354
Minimum0
Maximum132
Zeros24
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-03-14T08:45:27.081820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q130
median30
Q330
95-th percentile30
Maximum132
Range132
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.145043
Coefficient of variation (CV)0.35118697
Kurtosis37.307085
Mean31.735354
Median Absolute Deviation (MAD)0
Skewness5.7036504
Sum124593
Variance124.21198
MonotonicityNot monotonic
2024-03-14T08:45:27.201300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30 3752
95.5%
90 29
 
0.7%
0 24
 
0.6%
60 21
 
0.5%
62 1
 
< 0.1%
45 1
 
< 0.1%
126 1
 
< 0.1%
110 1
 
< 0.1%
101 1
 
< 0.1%
34 1
 
< 0.1%
Other values (94) 94
 
2.4%
ValueCountFrequency (%)
0 24
 
0.6%
30 3752
95.5%
31 1
 
< 0.1%
32 1
 
< 0.1%
33 1
 
< 0.1%
34 1
 
< 0.1%
35 1
 
< 0.1%
36 1
 
< 0.1%
37 1
 
< 0.1%
38 1
 
< 0.1%
ValueCountFrequency (%)
132 1
< 0.1%
131 1
< 0.1%
130 1
< 0.1%
129 1
< 0.1%
128 1
< 0.1%
127 1
< 0.1%
126 1
< 0.1%
125 1
< 0.1%
124 1
< 0.1%
123 1
< 0.1%

설치년월
Date

Distinct120
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum1905-07-01 00:00:00
Maximum2017-12-01 00:00:00
2024-03-14T08:45:27.309689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:27.426127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관전화번호
Text

Distinct218
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
2024-03-14T08:45:27.602892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters47124
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)4.3%

Sample

1st row063-560-2334
2nd row063-560-2334
3rd row063-560-2334
4th row063-560-2334
5th row063-560-2334
ValueCountFrequency (%)
063-281-2072 879
22.4%
063-454-7922 571
14.5%
063-859-5406 469
11.9%
063-320-2162 295
 
7.5%
063-539-6853 259
 
6.6%
036-290-2442 232
 
5.9%
063-540-2913 230
 
5.9%
063-560-2334 209
 
5.3%
063-580-4862 139
 
3.5%
063-320-2365 42
 
1.1%
Other values (208) 602
15.3%
2024-03-14T08:45:27.875860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 7854
16.7%
0 7018
14.9%
2 6892
14.6%
3 5994
12.7%
6 5924
12.6%
5 3130
 
6.6%
4 3010
 
6.4%
8 2086
 
4.4%
9 1881
 
4.0%
1 1698
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39270
83.3%
Dash Punctuation 7854
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7018
17.9%
2 6892
17.6%
3 5994
15.3%
6 5924
15.1%
5 3130
8.0%
4 3010
7.7%
8 2086
 
5.3%
9 1881
 
4.8%
1 1698
 
4.3%
7 1637
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 7854
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47124
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 7854
16.7%
0 7018
14.9%
2 6892
14.6%
3 5994
12.7%
6 5924
12.6%
5 3130
 
6.6%
4 3010
 
6.4%
8 2086
 
4.4%
9 1881
 
4.0%
1 1698
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 7854
16.7%
0 7018
14.9%
2 6892
14.6%
3 5994
12.7%
6 5924
12.6%
5 3130
 
6.6%
4 3010
 
6.4%
8 2086
 
4.4%
9 1881
 
4.0%
1 1698
 
3.6%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct3577
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.05313
Minimum126.2918
Maximum128.12867
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-03-14T08:45:27.992336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.2918
5-th percentile126.57193
Q1126.7604
median127.0716
Q3127.16202
95-th percentile127.69533
Maximum128.12867
Range1.836868
Interquartile range (IQR)0.4016243

Descriptive statistics

Standard deviation0.32858234
Coefficient of variation (CV)0.0025861806
Kurtosis-0.04091566
Mean127.05313
Median Absolute Deviation (MAD)0.1985925
Skewness0.59967646
Sum498937.65
Variance0.10796635
MonotonicityNot monotonic
2024-03-14T08:45:28.105564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.957714 7
 
0.2%
126.5347984 6
 
0.2%
126.983363 6
 
0.2%
126.974937 5
 
0.1%
127.692229 5
 
0.1%
126.959431 5
 
0.1%
127.6413666 5
 
0.1%
127.6469712 5
 
0.1%
127.6724518 4
 
0.1%
127.8403883 4
 
0.1%
Other values (3567) 3875
98.7%
ValueCountFrequency (%)
126.2918 1
< 0.1%
126.2925 1
< 0.1%
126.2928 1
< 0.1%
126.3038 1
< 0.1%
126.415578 2
0.1%
126.420569 1
< 0.1%
126.422272 1
< 0.1%
126.422559 1
< 0.1%
126.4255699 1
< 0.1%
126.429 1
< 0.1%
ValueCountFrequency (%)
128.128668 1
< 0.1%
127.954846 1
< 0.1%
127.9533304 1
< 0.1%
127.9532836 1
< 0.1%
127.9510948 2
0.1%
127.9458676 1
< 0.1%
127.9434952 1
< 0.1%
127.9424404 1
< 0.1%
127.9396216 1
< 0.1%
127.9370368 1
< 0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct3576
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.793755
Minimum35
Maximum36.723268
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size34.6 KiB
2024-03-14T08:45:28.218521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile35.433398
Q135.586097
median35.834947
Q335.959702
95-th percentile36.041032
Maximum36.723268
Range1.723268
Interquartile range (IQR)0.373605

Descriptive statistics

Standard deviation0.21384693
Coefficient of variation (CV)0.00597442
Kurtosis-0.29658107
Mean35.793755
Median Absolute Deviation (MAD)0.1349685
Skewness-0.30055213
Sum140562.08
Variance0.045730508
MonotonicityNot monotonic
2024-03-14T08:45:28.344594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.948335 7
 
0.2%
35.963992 7
 
0.2%
35.48176 6
 
0.2%
35.8706686 5
 
0.1%
35.9964431 5
 
0.1%
35.926245 5
 
0.1%
36.012028 5
 
0.1%
35.945829 4
 
0.1%
35.957903 4
 
0.1%
35.937024 4
 
0.1%
Other values (3566) 3875
98.7%
ValueCountFrequency (%)
35.0 1
< 0.1%
35.071495 1
< 0.1%
35.13038 1
< 0.1%
35.192308 1
< 0.1%
35.2225 1
< 0.1%
35.2342799 1
< 0.1%
35.235037 1
< 0.1%
35.241107 1
< 0.1%
35.28874 1
< 0.1%
35.302751 1
< 0.1%
ValueCountFrequency (%)
36.723268 1
< 0.1%
36.716668 1
< 0.1%
36.7127452 1
< 0.1%
36.6213228 1
< 0.1%
36.5376816 1
< 0.1%
36.5319056 1
< 0.1%
36.531722 1
< 0.1%
36.5172932 1
< 0.1%
36.4530364 2
0.1%
36.3618239 1
< 0.1%

데이터기준일자
Date

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
Minimum2017-06-30 00:00:00
Maximum2017-09-08 00:00:00
2024-03-14T08:45:28.431276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:28.504960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

출처
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.8 KiB
정보총괄과
3927 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정보총괄과 3927
100.0%

Length

2024-03-14T08:45:28.595100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:45:28.676412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정보총괄과 3927
100.0%

Interactions

2024-03-14T08:45:23.352049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.116778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.615652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.973664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:23.431599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.215000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.699699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:23.063370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:23.514480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.367187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.784900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:23.153335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:23.596177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.521220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:22.874429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:45:23.249292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T08:45:28.731703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명설치목적구분카메라대수보관일수경도위도데이터기준일자
관리기관명1.0000.6780.3310.6580.9080.8651.000
설치목적구분0.6781.0000.4210.5050.4310.3530.257
카메라대수0.3310.4211.0000.1050.2360.2410.048
보관일수0.6580.5050.1051.0000.3430.2980.063
경도0.9080.4310.2360.3431.0000.7410.866
위도0.8650.3530.2410.2980.7411.0000.568
데이터기준일자1.0000.2570.0480.0630.8660.5681.000
2024-03-14T08:45:28.836389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명설치목적구분
관리기관명1.0000.324
설치목적구분0.3241.000
2024-03-14T08:45:28.988145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라대수보관일수경도위도관리기관명설치목적구분
카메라대수1.0000.073-0.141-0.1240.1610.178
보관일수0.0731.0000.083-0.1670.3370.241
경도-0.1410.0831.0000.1110.6310.196
위도-0.124-0.1670.1111.0000.5450.156
관리기관명0.1610.3370.6310.5451.0000.324
설치목적구분0.1780.2410.1960.1560.3241.000

Missing values

2024-03-14T08:45:23.708876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T08:45:24.128652image/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

관리기관명소재지주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호경도위도데이터기준일자출처
0전라북도 고창군청전라북도 고창군 성송면 암치리 232-7전라북도 고창군 성송면 암치리 산92-4생활방범2100도로902013-09-01063-560-2334126.65608635.3341112017-06-30정보총괄과
1전라북도 고창군청전라북도 고창군 고창읍 교촌리 88-4전라북도 고창군 고창읍 교촌리 88-4어린이보호3100360도전방면302011-12-01063-560-2334126.70471435.4366122017-06-30정보총괄과
2전라북도 고창군청전라북도 고창군 고창읍 교촌리 산12전라북도 고창군 고창읍 교촌리 산12재난재해1100산불감시302011-06-01063-560-2334126.70585935.441142017-06-30정보총괄과
3전라북도 고창군청전라북도 고창군 고창읍 월곡리 574-3전라북도 고창군 고창읍 월곡리 574-3생활방범3100도로902015-06-01063-560-2334126.71008735.4424422017-06-30정보총괄과
4전라북도 고창군청전라북도 고창군 고창읍 월곡14길 3전라북도 고창군 고창읍 월곡리 587기타3100360도전방면302010-08-01063-560-2334126.71173535.4385872017-06-30정보총괄과
5전라북도 고창군청전라북도 고창군 고창읍 월산리 59-10전라북도 고창군 고창읍 월산리 산9-12생활방범2100도로902016-04-01063-560-2334126.73824635.4206882017-06-30정보총괄과
6전라북도 고창군청전라북도 고창군 고창읍 월산리 59-10전라북도 고창군 고창읍 월산리 산9-12생활방범2100도로902015-06-01063-560-2334126.73829735.4204722017-06-30정보총괄과
7전라북도 고창군청전라북도 고창군 고창읍 읍내리 183-5전라북도 고창군 고창읍 읍내리 183-5시설물관리3200주차장302015-07-01063-560-2334126.70513535.4333662017-06-30정보총괄과
8전라북도 고창군청전라북도 고창군 고창읍 읍내리 195-8전라북도 고창군 고창읍 읍내리 195-8시설물관리2200주차장302015-07-01063-560-2334126.70013535.4353752017-06-30정보총괄과
9전라북도 고창군청전라북도 고창군 고창읍 읍내리 197-14전라북도 고창군 고창읍 읍내리 197-14시설물관리2200주차장302015-07-01063-560-2334126.70042435.4358632017-06-30정보총괄과
관리기관명소재지주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호경도위도데이터기준일자출처
3917전라북도 완주군청전라북도 완주군 삼례읍 원후정2길 4전라북도 완주군 삼례읍 후정리 394-3생활방범2200원후정마을 탑건원룸 앞 사거리302017-05-01036-290-2442127.34478835.5437492017-06-30정보총괄과
3918전라북도 완주군청전라북도 완주군 삼례읍 삼례화산2길4전라북도 완주군 삼례읍 삼례리 1676-7생활방범2200화산마을 안길302017-05-01036-290-2442127.41142835.5454342017-06-30정보총괄과
3919전라북도 완주군청전라북도 완주군 삼례읍 삼례화산1길 12전라북도 완주군 삼례읍 삼례리 1607-12생활방범2200화산마을 빌라 앞302017-05-01036-290-2442127.41545235.5456792017-06-30정보총괄과
3920전라북도 완주군청전라북도 완주군 삼례읍 삼례로416-1전라북도 완주군 삼례읍 후정리 18-10생활방범2200만경동마을 베스트빌 앞302017-05-01036-290-2442127.41630235.5448852017-06-30정보총괄과
3921전라북도 완주군청전라북도 완주군 삼례읍 충혼안길 8전라북도 완주군 삼례읍 삼례리 863-17생활방범2200남서신마을 현대자동차 뒤302017-05-01036-290-2442127.42744435.9542852017-06-30정보총괄과
3922전라북도 완주군청전라북도 완주군 삼례읍 상서만경길 38-1전라북도 완주군 삼례읍 삼례리 1332-37생활방범2200만경동마을 편의점 앞 삼거리302017-05-01036-290-2442127.49001235.5445092017-06-30정보총괄과
3923전라북도 완주군청전라북도 완주군 봉동읍 둔산2로 70전라북도 완주군 봉동읍 둔산리 898-1생활방범3200우동공원 승강장302016-09-01036-290-2442127.72716335.5743172017-06-30정보총괄과
3924전라북도 완주군청전라북도 완주군 봉동읍 원둔산6길 8전라북도 완주군 봉동읍 둔산리 874-10생활방범3200봉서초 정문302010-12-01036-290-2442127.73281935.5745382017-06-30정보총괄과
3925전라북도 완주군청전라북도 완주군 봉동읍 원둔산6길26-8전라북도 완주군 봉동읍 둔산리 875-2생활방범3200둔산어린이보호공원놀이터302015-12-01036-290-2442127.73585435.5767362017-06-30정보총괄과
3926전라북도 완주군청전라북도 완주군 봉동읍 둔산 3로94전라북도 완주군 봉동읍 둔산리 881생활방범2200둔산공원산책로5302013-12-01036-290-2442127.74487935.5774922017-06-30정보총괄과

Duplicate rows

Most frequently occurring

관리기관명소재지주소소재지지번주소설치목적구분카메라대수촬영방면정보보관일수설치년월관리기관전화번호경도위도데이터기준일자출처# duplicates
133전라북도 익산시청전라북도 익산시 인북로32길 1전라북도 익산시 남중동 60생활방범1반경100m이내302015-01-01063-859-5406126.95771435.9483352017-09-08정보총괄과7
11전라북도 무주군청전라북도 무주군 무주읍 당산리 1723전라북도 무주군 무주읍 당산리 1723시설물관리1도로302017-01-01063-320-2352127.64697135.9964432017-06-30정보총괄과5
16전라북도 무주군청전라북도 무주군 무주읍 오산리 222전라북도 무주군 무주읍 오산리 222시설물관리1문화제 진출입로302017-01-01063-320-2542127.69222936.0120282017-06-30정보총괄과5
87전라북도 무주군청전라북도 무주군 안성면 장기리 1929전라북도 무주군 안성면 장기리 1929시설물관리1도로302014-01-01063-320-2352127.64136735.8706692017-06-30정보총괄과5
30전라북도 무주군청전라북도 무주군 무주읍 읍내리 354전라북도 무주군 무주읍 읍내리 354어린이보호1학교정문302015-01-01063-320-2365127.66381236.0106792017-06-30정보총괄과4
97전라북도 무주군청전라북도 무주군 적상면 괴목리 342-1전라북도 무주군 적상면 괴목리 342-1생활방범1마을입구302017-01-01063-320-2162127.71682535.9357812017-06-30정보총괄과4
13전라북도 무주군청전라북도 무주군 무주읍 당산리 897전라북도 무주군 무주읍 당산리 897생활방범1마을입구302017-01-01063-320-2162127.66789136.0043472017-06-30정보총괄과3
17전라북도 무주군청전라북도 무주군 무주읍 오산리 276-1전라북도 무주군 무주읍 오산리 276-1생활방범1마을입구302017-01-01063-320-2162127.84038835.9263662017-06-30정보총괄과3
38전라북도 무주군청전라북도 무주군 무주읍 장백리 268-5전라북도 무주군 무주읍 장백리 268-5생활방범1마을입구302017-01-01063-320-2162127.71213636.0327612017-06-30정보총괄과3
51전라북도 무주군청전라북도 무주군 무풍면 현내리 636-1전라북도 무주군 무풍면 현내리 636-1어린이보호1학교정문302015-01-01063-320-2365127.8471535.9680792017-06-30정보총괄과3