Overview

Dataset statistics

Number of variables13
Number of observations1637
Missing cells0
Missing cells (%)0.0%
Duplicate rows15
Duplicate rows (%)0.9%
Total size in memory174.4 KiB
Average record size in memory109.1 B

Variable types

Categorical7
Text2
DateTime2
Numeric2

Dataset

Description대구광역시_달서구_CCTV_20200316
Author대구광역시 달서구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3047239&dataSetDetailId=30472391b0138e949ab0_202003171552&provdMethod=FILE

Alerts

관리기관명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 15 (0.9%) duplicate rowsDuplicates
관리기관전화번호 is highly overall correlated with 설치목적구분High correlation
설치목적구분 is highly overall correlated with 촬영방면정보 and 1 other fieldsHigh correlation
촬영방면정보 is highly overall correlated with 설치목적구분High correlation
카메라대수 is highly imbalanced (97.9%)Imbalance
카메라화소수 is highly imbalanced (98.1%)Imbalance
보관일수 is highly imbalanced (94.2%)Imbalance
관리기관전화번호 is highly imbalanced (65.0%)Imbalance

Reproduction

Analysis started2024-04-20 19:12:52.232868
Analysis finished2024-04-20 19:12:54.558181
Duration2.33 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
대구광역시 달서구청
1637 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 달서구청
2nd row대구광역시 달서구청
3rd row대구광역시 달서구청
4th row대구광역시 달서구청
5th row대구광역시 달서구청

Common Values

ValueCountFrequency (%)
대구광역시 달서구청 1637
100.0%

Length

2024-04-21T04:12:54.876683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:12:55.044413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 1637
50.0%
달서구청 1637
50.0%

소재지도로명주소
Text

Distinct1569
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2024-04-21T04:12:56.019075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length32
Mean length23.359805
Min length15

Characters and Unicode

Total characters38240
Distinct characters269
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

Unique1514 ?
Unique (%)92.5%

Sample

1st row대구광역시 달서구 두류남길 60(두류동)
2nd row대구광역시 달서구 본리서3길 5(본리동)
3rd row대구광역시 달서구 호산동로36북길 60(호산동)
4th row대구광역시 달서구 월배로68길 48(송현동)
5th row대구광역시 달서구 상화로15길 27(진천동)
ValueCountFrequency (%)
대구광역시 1637
24.1%
달서구 1636
24.1%
앞 92
 
1.4%
월배로 34
 
0.5%
달구벌대로 27
 
0.4%
장기로 22
 
0.3%
상화로 20
 
0.3%
선원남로 19
 
0.3%
코너 18
 
0.3%
월곡로 15
 
0.2%
Other values (1877) 3276
48.2%
2024-04-21T04:12:57.273887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5159
 
13.5%
구 3415
 
8.9%
서 1820
 
4.8%
대 1816
 
4.7%
달 1747
 
4.6%
광 1640
 
4.3%
시 1638
 
4.3%
역 1637
 
4.3%
로 1451
 
3.8%
( 1244
 
3.3%
Other values (259) 16673
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24187
63.3%
Decimal Number 6107
 
16.0%
Space Separator 5159
 
13.5%
Open Punctuation 1244
 
3.3%
Close Punctuation 1243
 
3.3%
Dash Punctuation 274
 
0.7%
Other Punctuation 21
 
0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3415
14.1%
서 1820
 
7.5%
대 1816
 
7.5%
달 1747
 
7.2%
광 1640
 
6.8%
시 1638
 
6.8%
역 1637
 
6.8%
로 1451
 
6.0%
동 1237
 
5.1%
길 1175
 
4.9%
Other values (238) 6611
27.3%
Decimal Number
ValueCountFrequency (%)
1 1217
19.9%
2 865
14.2%
3 801
13.1%
4 601
9.8%
5 596
9.8%
7 451
 
7.4%
6 440
 
7.2%
9 408
 
6.7%
0 372
 
6.1%
8 356
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
S 2
40.0%
C 1
20.0%
D 1
20.0%
G 1
20.0%
Other Punctuation
ValueCountFrequency (%)
? 8
38.1%
. 7
33.3%
, 6
28.6%
Space Separator
ValueCountFrequency (%)
5159
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1244
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 274
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24187
63.3%
Common 14048
36.7%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3415
14.1%
서 1820
 
7.5%
대 1816
 
7.5%
달 1747
 
7.2%
광 1640
 
6.8%
시 1638
 
6.8%
역 1637
 
6.8%
로 1451
 
6.0%
동 1237
 
5.1%
길 1175
 
4.9%
Other values (238) 6611
27.3%
Common
ValueCountFrequency (%)
5159
36.7%
( 1244
 
8.9%
) 1243
 
8.8%
1 1217
 
8.7%
2 865
 
6.2%
3 801
 
5.7%
4 601
 
4.3%
5 596
 
4.2%
7 451
 
3.2%
6 440
 
3.1%
Other values (7) 1431
 
10.2%
Latin
ValueCountFrequency (%)
S 2
40.0%
C 1
20.0%
D 1
20.0%
G 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24187
63.3%
ASCII 14053
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5159
36.7%
( 1244
 
8.9%
) 1243
 
8.8%
1 1217
 
8.7%
2 865
 
6.2%
3 801
 
5.7%
4 601
 
4.3%
5 596
 
4.2%
7 451
 
3.2%
6 440
 
3.1%
Other values (11) 1436
 
10.2%
Hangul
ValueCountFrequency (%)
구 3415
14.1%
서 1820
 
7.5%
대 1816
 
7.5%
달 1747
 
7.2%
광 1640
 
6.8%
시 1638
 
6.8%
역 1637
 
6.8%
로 1451
 
6.0%
동 1237
 
5.1%
길 1175
 
4.9%
Other values (238) 6611
27.3%

소재지지번주소
Text

Distinct1537
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
2024-04-21T04:12:57.904880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length24
Mean length19.150886
Min length16

Characters and Unicode

Total characters31350
Distinct characters72
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

Unique1450 ?
Unique (%)88.6%

Sample

1st row대구광역시 달서구 두류동 804-141
2nd row대구광역시 달서구 본리동 1210-1
3rd row대구광역시 달서구 호산동 357-41
4th row대구광역시 달서구 송현동 798-321
5th row대구광역시 달서구 진천동 460
ValueCountFrequency (%)
대구광역시 1637
25.0%
달서구 1635
25.0%
송현동 198
 
3.0%
상인동 169
 
2.6%
두류동 137
 
2.1%
용산동 129
 
2.0%
감삼동 106
 
1.6%
진천동 104
 
1.6%
성당동 103
 
1.6%
이곡동 97
 
1.5%
Other values (1512) 2228
34.1%
2024-04-21T04:12:58.737131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4906
15.6%
구 3274
 
10.4%
대 1701
 
5.4%
1 1650
 
5.3%
동 1640
 
5.2%
광 1637
 
5.2%
역 1637
 
5.2%
시 1637
 
5.2%
서 1637
 
5.2%
달 1636
 
5.2%
Other values (62) 9995
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18014
57.5%
Decimal Number 7108
 
22.7%
Space Separator 4906
 
15.6%
Dash Punctuation 1298
 
4.1%
Open Punctuation 12
 
< 0.1%
Close Punctuation 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 3274
18.2%
대 1701
9.4%
동 1640
9.1%
광 1637
9.1%
역 1637
9.1%
시 1637
9.1%
서 1637
9.1%
달 1636
9.1%
현 200
 
1.1%
송 200
 
1.1%
Other values (48) 2815
15.6%
Decimal Number
ValueCountFrequency (%)
1 1650
23.2%
2 853
12.0%
3 683
9.6%
4 656
 
9.2%
5 648
 
9.1%
9 559
 
7.9%
8 530
 
7.5%
6 524
 
7.4%
0 512
 
7.2%
7 493
 
6.9%
Space Separator
ValueCountFrequency (%)
4906
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1298
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18014
57.5%
Common 13336
42.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 3274
18.2%
대 1701
9.4%
동 1640
9.1%
광 1637
9.1%
역 1637
9.1%
시 1637
9.1%
서 1637
9.1%
달 1636
9.1%
현 200
 
1.1%
송 200
 
1.1%
Other values (48) 2815
15.6%
Common
ValueCountFrequency (%)
4906
36.8%
1 1650
 
12.4%
- 1298
 
9.7%
2 853
 
6.4%
3 683
 
5.1%
4 656
 
4.9%
5 648
 
4.9%
9 559
 
4.2%
8 530
 
4.0%
6 524
 
3.9%
Other values (4) 1029
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18014
57.5%
ASCII 13336
42.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4906
36.8%
1 1650
 
12.4%
- 1298
 
9.7%
2 853
 
6.4%
3 683
 
5.1%
4 656
 
4.9%
5 648
 
4.9%
9 559
 
4.2%
8 530
 
4.0%
6 524
 
3.9%
Other values (4) 1029
 
7.7%
Hangul
ValueCountFrequency (%)
구 3274
18.2%
대 1701
9.4%
동 1640
9.1%
광 1637
9.1%
역 1637
9.1%
시 1637
9.1%
서 1637
9.1%
달 1636
9.1%
현 200
 
1.1%
송 200
 
1.1%
Other values (48) 2815
15.6%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
생활방범
896 
어린이보호
471 
쓰레기단속
150 
교통단속
100 
기타
 
12
Other values (2)
 
8

Length

Max length5
Median length4
Mean length4.367135
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 896
54.7%
어린이보호 471
28.8%
쓰레기단속 150
 
9.2%
교통단속 100
 
6.1%
기타 12
 
0.7%
재난재해 4
 
0.2%
시설물관리 4
 
0.2%

Length

2024-04-21T04:12:58.965641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:12:59.175179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 896
54.7%
어린이보호 471
28.8%
쓰레기단속 150
 
9.2%
교통단속 100
 
6.1%
기타 12
 
0.7%
재난재해 4
 
0.2%
시설물관리 4
 
0.2%

카메라대수
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
1
1632 
3
 
3
2
 
2

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 1632
99.7%
3 3
 
0.2%
2 2
 
0.1%

Length

2024-04-21T04:12:59.396118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:12:59.572923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1632
99.7%
3 3
 
0.2%
2 2
 
0.1%

카메라화소수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
200
1634 
41
 
3

Length

Max length3
Median length3
Mean length2.9981674
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row200
2nd row200
3rd row200
4th row200
5th row200

Common Values

ValueCountFrequency (%)
200 1634
99.8%
41 3
 
0.2%

Length

2024-04-21T04:12:59.766030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:12:59.945024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 1634
99.8%
41 3
 
0.2%

촬영방면정보
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
회전
1208 
고정
429 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row회전
2nd row회전
3rd row회전
4th row고정
5th row회전

Common Values

ValueCountFrequency (%)
회전 1208
73.8%
고정 429
 
26.2%

Length

2024-04-21T04:13:00.234242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:13:00.553667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
회전 1208
73.8%
고정 429
 
26.2%

보관일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
30
1626 
10
 
11

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 1626
99.3%
10 11
 
0.7%

Length

2024-04-21T04:13:00.903949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:13:01.219657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 1626
99.3%
10 11
 
0.7%

설치년월
Date

Distinct72
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
Minimum2005-02-01 00:00:00
Maximum2019-12-01 00:00:00
2024-04-21T04:13:01.547683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:13:01.958202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

관리기관전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
053-667-3900
1379 
053-667-2747
150 
053-667-3048
 
100
053-667-3784
 
4
053-667-2824
 
4

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row053-667-3900
2nd row053-667-3900
3rd row053-667-3900
4th row053-667-3900
5th row053-667-3900

Common Values

ValueCountFrequency (%)
053-667-3900 1379
84.2%
053-667-2747 150
 
9.2%
053-667-3048 100
 
6.1%
053-667-3784 4
 
0.2%
053-667-2824 4
 
0.2%

Length

2024-04-21T04:13:02.351949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T04:13:02.682946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
053-667-3900 1379
84.2%
053-667-2747 150
 
9.2%
053-667-3048 100
 
6.1%
053-667-3784 4
 
0.2%
053-667-2824 4
 
0.2%

위도
Real number (ℝ)

Distinct1538
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.837256
Minimum35.792955
Maximum35.865108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2024-04-21T04:13:03.059589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.792955
5-th percentile35.80746
Q135.821746
median35.840419
Q335.853633
95-th percentile35.859519
Maximum35.865108
Range0.072152846
Interquartile range (IQR)0.031887017

Descriptive statistics

Standard deviation0.017935629
Coefficient of variation (CV)0.00050047438
Kurtosis-1.177852
Mean35.837256
Median Absolute Deviation (MAD)0.01459555
Skewness-0.39707501
Sum58665.589
Variance0.00032168678
MonotonicityNot monotonic
2024-04-21T04:13:03.511246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.84945213 5
 
0.3%
35.8574952977 4
 
0.2%
35.8245525581 3
 
0.2%
35.83592968 3
 
0.2%
35.8500241905 3
 
0.2%
35.8559693978 3
 
0.2%
35.8577881201 3
 
0.2%
35.80702352 3
 
0.2%
35.8383963832 3
 
0.2%
35.86169597 3
 
0.2%
Other values (1528) 1604
98.0%
ValueCountFrequency (%)
35.79295489 1
0.1%
35.79395808 1
0.1%
35.7953987963 1
0.1%
35.7957065444 1
0.1%
35.79613214 1
0.1%
35.7961778512 1
0.1%
35.7966440434 1
0.1%
35.7972128202 1
0.1%
35.7979006933 1
0.1%
35.7980125943 2
0.1%
ValueCountFrequency (%)
35.8651077361 1
0.1%
35.86479823 1
0.1%
35.8634169257 1
0.1%
35.8626906 2
0.1%
35.86256547 1
0.1%
35.86236995 1
0.1%
35.86224035 1
0.1%
35.8621145754 1
0.1%
35.86192424 1
0.1%
35.86186602 1
0.1%

경도
Real number (ℝ)

Distinct1538
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.53343
Minimum128.4734
Maximum128.57413
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.5 KiB
2024-04-21T04:13:03.944210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.4734
5-th percentile128.49419
Q1128.52236
median128.53513
Q3128.5484
95-th percentile128.56421
Maximum128.57413
Range0.1007249
Interquartile range (IQR)0.0260411

Descriptive statistics

Standard deviation0.020429331
Coefficient of variation (CV)0.00015894177
Kurtosis0.1220194
Mean128.53343
Median Absolute Deviation (MAD)0.0129498
Skewness-0.55445679
Sum210409.22
Variance0.00041735755
MonotonicityNot monotonic
2024-04-21T04:13:04.369639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5274033 5
 
0.3%
128.5122727754 4
 
0.2%
128.5367433 3
 
0.2%
128.5199997124 3
 
0.2%
128.4926282 3
 
0.2%
128.4788712767 3
 
0.2%
128.513222344 3
 
0.2%
128.5091625693 3
 
0.2%
128.500708094 3
 
0.2%
128.5165576899 3
 
0.2%
Other values (1528) 1604
98.0%
ValueCountFrequency (%)
128.4734032 1
0.1%
128.4736813 2
0.1%
128.4748738866 1
0.1%
128.4748804 1
0.1%
128.4760092 1
0.1%
128.4762944 1
0.1%
128.4772540367 1
0.1%
128.4772753 1
0.1%
128.4773065 1
0.1%
128.4775582 1
0.1%
ValueCountFrequency (%)
128.5741281 1
0.1%
128.5741098 1
0.1%
128.5739672 1
0.1%
128.5738702 1
0.1%
128.5737503 1
0.1%
128.5737412 1
0.1%
128.5736258 1
0.1%
128.5735174 1
0.1%
128.5734407 1
0.1%
128.5734052 1
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size12.9 KiB
Minimum2020-03-16 00:00:00
Maximum2020-03-16 00:00:00
2024-04-21T04:13:04.706776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:13:05.002705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T04:12:53.742525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:12:53.405215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:12:53.910323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T04:12:53.581906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T04:13:05.218473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도
설치목적구분1.0000.0000.1470.5680.2360.9841.0000.2370.200
카메라대수0.0001.0000.0000.0000.0000.0000.0000.0000.112
카메라화소수0.1470.0001.0000.0000.0000.7540.1310.0000.000
촬영방면정보0.5680.0000.0001.0000.1980.9880.4110.0950.064
보관일수0.2360.0000.0000.1981.0000.6110.2080.0470.000
설치년월0.9840.0000.7540.9880.6111.0000.9750.4920.566
관리기관전화번호1.0000.0000.1310.4110.2080.9751.0000.2550.130
위도0.2370.0000.0000.0950.0470.4920.2551.0000.627
경도0.2000.1120.0000.0640.0000.5660.1300.6271.000
2024-04-21T04:13:05.523657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
촬영방면정보카메라대수보관일수관리기관전화번호카메라화소수설치목적구분
촬영방면정보1.0000.0000.1270.4990.0000.610
카메라대수0.0001.0000.0000.0000.0000.000
보관일수0.1270.0001.0000.2540.0000.252
관리기관전화번호0.4990.0000.2541.0000.1610.999
카메라화소수0.0000.0000.0000.1611.0000.157
설치목적구분0.6100.0000.2520.9990.1571.000
2024-04-21T04:13:05.807711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치목적구분카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호
위도1.000-0.1160.1220.0000.0000.0730.0360.109
경도-0.1161.0000.1020.0650.0000.0490.0000.054
설치목적구분0.1220.1021.0000.0000.1570.6100.2520.999
카메라대수0.0000.0650.0001.0000.0000.0000.0000.000
카메라화소수0.0000.0000.1570.0001.0000.0000.0000.161
촬영방면정보0.0730.0490.6100.0000.0001.0000.1270.499
보관일수0.0360.0000.2520.0000.0000.1271.0000.254
관리기관전화번호0.1090.0540.9990.0000.1610.4990.2541.000

Missing values

2024-04-21T04:12:54.126917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T04:12:54.434449image/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

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자
0대구광역시 달서구청대구광역시 달서구 두류남길 60(두류동)대구광역시 달서구 두류동 804-141생활방범1200회전302015-08053-667-390035.857264128.5712672020-03-16
1대구광역시 달서구청대구광역시 달서구 본리서3길 5(본리동)대구광역시 달서구 본리동 1210-1생활방범1200회전302015-08053-667-390035.839517128.5299172020-03-16
2대구광역시 달서구청대구광역시 달서구 호산동로36북길 60(호산동)대구광역시 달서구 호산동 357-41생활방범1200회전302015-08053-667-390035.851404128.4879592020-03-16
3대구광역시 달서구청대구광역시 달서구 월배로68길 48(송현동)대구광역시 달서구 송현동 798-321생활방범1200고정302012-07053-667-390035.824135128.5492152020-03-16
4대구광역시 달서구청대구광역시 달서구 상화로15길 27(진천동)대구광역시 달서구 진천동 460생활방범1200회전302015-08053-667-390035.809239128.5223562020-03-16
5대구광역시 달서구청대구광역시 달서구 월배로32길 58(상인동)대구광역시 달서구 상인동 344-15생활방범1200고정302012-07053-667-390035.814339128.5329582020-03-16
6대구광역시 달서구청대구광역시 달서구 당산로45길 17(감삼동)대구광역시 달서구 감삼동 31-5생활방범1200회전302015-08053-667-390035.856136128.5464252020-03-16
7대구광역시 달서구청대구광역시 달서구 죽전4길 95(감삼동)대구광역시 달서구 감삼동 32-34생활방범1200회전302015-08053-667-390035.855564128.5453692020-03-16
8대구광역시 달서구청대구광역시 달서구 달구벌대로323길 68(감삼동)대구광역시 달서구 감삼동 35-1생활방범1200회전302015-08053-667-390035.855371128.5421022020-03-16
9대구광역시 달서구청대구광역시 달서구 달구벌대로323길 55(감삼동)대구광역시 달서구 감삼동 37-25생활방범1200회전302015-08053-667-390035.854922128.5418882020-03-16
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자
1627대구광역시 달서구청대구광역시 달서구 와룡로2길84(본동) 홍은하이츠 앞대구광역시 달서구 본동 793쓰레기단속1200고정102018-11053-667-274735.83593128.5401092020-03-16
1628대구광역시 달서구청대구광역시 달서구 진천로3길 49대구광역시 달서구 진천동 384쓰레기단속1200고정102018-12053-667-274735.809867128.5234012020-03-16
1629대구광역시 달서구청대구광역시 달서구 상화로 406대구광역시 달서구 상인동 1593재난재해1200회전302018-08053-667-378435.807896128.5582322020-03-16
1630대구광역시 달서구청대구광역시 달서구 수밭길 2-15대구광역시 달서구 도원동 1395재난재해1200회전302018-08053-667-378435.797213128.5478362020-03-16
1631대구광역시 달서구청대구광역시 달서구 화암로 342대구광역시 달서구 대곡동 314재난재해1200회전302019-06053-667-378435.8007128.5200052020-03-16
1632대구광역시 달서구청대구광역시 달서구 선원로 60대구광역시 달서구 신당동 1749-1재난재해1200회전302019-06053-667-378435.858966128.4988342020-03-16
1633대구광역시 달서구청대구광역시 달서구 상화로 371 남편대구광역시 달서구 상인동 1563-8시설물관리1200고정302013-05053-667-282435.808529128.5538982020-03-16
1634대구광역시 달서구청대구광역시 달서구 월곡로26길 45 남편대구광역시 달서구 상인동 1584-15시설물관리1200고정302013-05053-667-282435.808408128.5508222020-03-16
1635대구광역시 달서구청대구광역시 달서구 월곡로 112 북편대구광역시 달서구 상인동 1587-4시설물관리1200고정302013-05053-667-282435.807957128.5509732020-03-16
1636대구광역시 달서구청대구광역시 달서구 상화로 370 북편대구광역시 달서구 상인동 1591-6시설물관리1200고정302013-05053-667-282435.808006128.5539722020-03-16

Duplicate rows

Most frequently occurring

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자# duplicates
0대구광역시 달서구청대구광역시 달서구 달구벌대로 1396대구광역시 달서구 장기동 105-7(동양전업사)기타1200고정302011-06053-667-390035.850088128.522020-03-163
1대구광역시 달서구청대구광역시 달서구 달구벌대로 1467대구광역시 달서구 용산동 230-11(홈플러스)기타1200고정302011-06053-667-390035.849452128.5274032020-03-163
2대구광역시 달서구청대구광역시 달서구 달서대로 696대구광역시 달서구 신당동 680(에스오일주유소)기타1200고정302011-06053-667-390035.861696128.4926282020-03-163
3대구광역시 달서구청대구광역시 달서구 상화로 88-11(진천동)대구광역시 달서구 대곡동 1031-1어린이보호1200고정302010-12053-667-390035.806429128.5239312020-03-162
4대구광역시 달서구청대구광역시 달서구 상화로9길 6대구광역시 달서구 진천동 809-73생활방범1200고정302018-07053-667-390035.808358128.5196292020-03-162
5대구광역시 달서구청대구광역시 달서구 선원로 283대구광역시 달서구 용산동 396-5어린이보호1200고정302018-12053-667-390035.858998128.5237172020-03-162
6대구광역시 달서구청대구광역시 달서구 선원로 284대구광역시 달서구 용산동 395(유림카센터)기타1200고정302011-06053-667-390035.858553128.5235582020-03-162
7대구광역시 달서구청대구광역시 달서구 선원로23길 68대구광역시 달서구 이곡동 산18-3어린이보호1200회전302016-06053-667-390035.862691128.5048592020-03-162
8대구광역시 달서구청대구광역시 달서구 선원로33길 106(이곡동)대구광역시 달서구 이곡동 1345-11어린이보호1200고정302010-12053-667-390035.861046128.514262020-03-162
9대구광역시 달서구청대구광역시 달서구 앞산순환로 206(송현동)대구광역시 달서구 송현동 694생활방범1200회전302015-08053-667-390035.821977128.5539372020-03-162