Overview

Dataset statistics

Number of variables13
Number of observations1654
Missing cells4831
Missing cells (%)22.5%
Duplicate rows99
Duplicate rows (%)6.0%
Total size in memory179.4 KiB
Average record size in memory111.1 B

Variable types

Categorical6
Text2
Unsupported2
Numeric2
DateTime1

Alerts

카메라대수 has constant value ""Constant
보관일수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 99 (6.0%) duplicate rowsDuplicates
관리기관전화번호 is highly overall correlated with 관리기관명 and 1 other fieldsHigh correlation
관리기관명 is highly overall correlated with 설치목적구분 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
설치목적구분 is highly overall correlated with 관리기관명 and 1 other fieldsHigh correlation
관리기관명 is highly imbalanced (65.7%)Imbalance
카메라화소수 is highly imbalanced (54.6%)Imbalance
관리기관전화번호 is highly imbalanced (66.1%)Imbalance
소재지도로명주소 has 332 (20.1%) missing valuesMissing
소재지지번주소 has 1191 (72.0%) missing valuesMissing
촬영방면정보 has 1654 (100.0%) missing valuesMissing
설치년월 has 1654 (100.0%) missing valuesMissing
촬영방면정보 is an unsupported type, check if it needs cleaning or further analysisUnsupported
설치년월 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-19 05:53:15.974681
Analysis finished2024-04-19 05:53:17.321479
Duration1.35 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct32
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
대구광역시 북구청 정보통신과
1155 
대구광역시 북구청 교통과
233 
대구광역시 북구청 자원순환과
 
109
대구광역시 북구청 총무과
 
33
대구광역시 북구청 보건과
 
25
Other values (27)
 
99

Length

Max length21
Median length15
Mean length14.738815
Min length13

Unique

Unique5 ?
Unique (%)0.3%

Sample

1st row대구광역시 북구청 교통과
2nd row대구광역시 북구청 교통과
3rd row대구광역시 북구청 교통과
4th row대구광역시 북구청 교통과
5th row대구광역시 북구청 교통과

Common Values

ValueCountFrequency (%)
대구광역시 북구청 정보통신과 1155
69.8%
대구광역시 북구청 교통과 233
 
14.1%
대구광역시 북구청 자원순환과 109
 
6.6%
대구광역시 북구청 총무과 33
 
2.0%
대구광역시 북구청 보건과 25
 
1.5%
대구광역시 북구청 공원녹지과 19
 
1.1%
대구광역시 북구청 산격1동 12
 
0.7%
대구광역시 북구청 민원여권과 8
 
0.5%
대구광역시 북구청 문화체육과 8
 
0.5%
대구광역시 북구청 재무과 5
 
0.3%
Other values (22) 47
 
2.8%

Length

2024-04-19T14:53:17.398991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대구광역시 1654
33.1%
북구청 1612
32.3%
정보통신과 1155
23.1%
교통과 233
 
4.7%
자원순환과 109
 
2.2%
북구 42
 
0.8%
행정복지센터 35
 
0.7%
총무과 33
 
0.7%
보건과 25
 
0.5%
공원녹지과 19
 
0.4%
Other values (26) 80
 
1.6%

소재지도로명주소
Text

MISSING 

Distinct1070
Distinct (%)80.9%
Missing332
Missing (%)20.1%
Memory size13.1 KiB
2024-04-19T14:53:17.651551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length23.639939
Min length14

Characters and Unicode

Total characters31252
Distinct characters303
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique981 ?
Unique (%)74.2%

Sample

1st row대구광역시 북구 칠곡중앙대로 59, 웨딩아일랜드
2nd row대구광역시 북구 동북로 234, KB은행
3rd row대구광역시 북구 동북로 234, KB은행
4th row대구광역시 북구 동북로 234, KB은행
5th row대구광역시 북구 동북로 270, 시티병원
ValueCountFrequency (%)
대구광역시 1322
23.4%
북구 1322
23.4%
옥산로 41
 
0.7%
65 35
 
0.6%
북구청 33
 
0.6%
청사내외 29
 
0.5%
일원 20
 
0.4%
14 19
 
0.3%
앞 19
 
0.3%
경진로남1길 19
 
0.3%
Other values (1421) 2781
49.3%
2024-04-19T14:53:18.401702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4318
 
13.8%
구 2833
 
9.1%
대 1641
 
5.3%
북 1504
 
4.8%
시 1397
 
4.5%
광 1323
 
4.2%
역 1322
 
4.2%
로 1294
 
4.1%
1 1143
 
3.7%
길 853
 
2.7%
Other values (293) 13624
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20358
65.1%
Decimal Number 4857
 
15.5%
Space Separator 4318
 
13.8%
Open Punctuation 527
 
1.7%
Close Punctuation 525
 
1.7%
Other Punctuation 328
 
1.0%
Dash Punctuation 321
 
1.0%
Uppercase Letter 15
 
< 0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2833
 
13.9%
대 1641
 
8.1%
북 1504
 
7.4%
시 1397
 
6.9%
광 1323
 
6.5%
역 1322
 
6.5%
로 1294
 
6.4%
길 853
 
4.2%
동 381
 
1.9%
원 380
 
1.9%
Other values (269) 7430
36.5%
Decimal Number
ValueCountFrequency (%)
1 1143
23.5%
2 807
16.6%
3 577
11.9%
4 456
 
9.4%
6 380
 
7.8%
5 372
 
7.7%
7 303
 
6.2%
0 285
 
5.9%
8 267
 
5.5%
9 267
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
I 3
20.0%
N 3
20.0%
G 3
20.0%
B 3
20.0%
K 3
20.0%
Lowercase Letter
ValueCountFrequency (%)
p 1
33.3%
t 1
33.3%
a 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 327
99.7%
@ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
4318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 527
100.0%
Close Punctuation
ValueCountFrequency (%)
) 525
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20358
65.1%
Common 10876
34.8%
Latin 18
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2833
 
13.9%
대 1641
 
8.1%
북 1504
 
7.4%
시 1397
 
6.9%
광 1323
 
6.5%
역 1322
 
6.5%
로 1294
 
6.4%
길 853
 
4.2%
동 381
 
1.9%
원 380
 
1.9%
Other values (269) 7430
36.5%
Common
ValueCountFrequency (%)
4318
39.7%
1 1143
 
10.5%
2 807
 
7.4%
3 577
 
5.3%
( 527
 
4.8%
) 525
 
4.8%
4 456
 
4.2%
6 380
 
3.5%
5 372
 
3.4%
, 327
 
3.0%
Other values (6) 1444
 
13.3%
Latin
ValueCountFrequency (%)
I 3
16.7%
N 3
16.7%
G 3
16.7%
B 3
16.7%
K 3
16.7%
p 1
 
5.6%
t 1
 
5.6%
a 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20358
65.1%
ASCII 10894
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4318
39.6%
1 1143
 
10.5%
2 807
 
7.4%
3 577
 
5.3%
( 527
 
4.8%
) 525
 
4.8%
4 456
 
4.2%
6 380
 
3.5%
5 372
 
3.4%
, 327
 
3.0%
Other values (14) 1462
 
13.4%
Hangul
ValueCountFrequency (%)
구 2833
 
13.9%
대 1641
 
8.1%
북 1504
 
7.4%
시 1397
 
6.9%
광 1323
 
6.5%
역 1322
 
6.5%
로 1294
 
6.4%
길 853
 
4.2%
동 381
 
1.9%
원 380
 
1.9%
Other values (269) 7430
36.5%

소재지지번주소
Text

MISSING 

Distinct399
Distinct (%)86.2%
Missing1191
Missing (%)72.0%
Memory size13.1 KiB
2024-04-19T14:53:18.631972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length33
Mean length23.710583
Min length13

Characters and Unicode

Total characters10978
Distinct characters220
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

Unique371 ?
Unique (%)80.1%

Sample

1st row대구광역시 북구 관음동 474-4
2nd row대구광역시 북구 관음동 474-4
3rd row대구광역시 북구 관음동 474-4
4th row대구광역시 북구 칠성동2가 302-94, 칠성공영주차장(구. 남일상회)
5th row대구광역시 북구 칠성동2가 302-94, 칠성공영주차장(구. 남일상회)
ValueCountFrequency (%)
대구광역시 463
23.0%
북구 461
22.9%
산격동 53
 
2.6%
일원 34
 
1.7%
관음동 32
 
1.6%
태전동 32
 
1.6%
침산동 24
 
1.2%
복현동 23
 
1.1%
읍내동 19
 
0.9%
대현동 19
 
0.9%
Other values (560) 850
42.3%
2024-04-19T14:53:18.984051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1547
 
14.1%
구 990
 
9.0%
동 557
 
5.1%
대 515
 
4.7%
북 479
 
4.4%
시 475
 
4.3%
1 469
 
4.3%
역 466
 
4.2%
광 463
 
4.2%
- 282
 
2.6%
Other values (210) 4735
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6664
60.7%
Decimal Number 1995
 
18.2%
Space Separator 1547
 
14.1%
Dash Punctuation 282
 
2.6%
Other Punctuation 180
 
1.6%
Close Punctuation 155
 
1.4%
Open Punctuation 155
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 990
14.9%
동 557
 
8.4%
대 515
 
7.7%
북 479
 
7.2%
시 475
 
7.1%
역 466
 
7.0%
광 463
 
6.9%
원 262
 
3.9%
공 197
 
3.0%
산 136
 
2.0%
Other values (194) 2124
31.9%
Decimal Number
ValueCountFrequency (%)
1 469
23.5%
3 235
11.8%
2 221
11.1%
7 185
 
9.3%
9 167
 
8.4%
8 157
 
7.9%
5 148
 
7.4%
4 148
 
7.4%
6 147
 
7.4%
0 118
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 177
98.3%
. 3
 
1.7%
Space Separator
ValueCountFrequency (%)
1547
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 282
100.0%
Close Punctuation
ValueCountFrequency (%)
) 155
100.0%
Open Punctuation
ValueCountFrequency (%)
( 155
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6664
60.7%
Common 4314
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 990
14.9%
동 557
 
8.4%
대 515
 
7.7%
북 479
 
7.2%
시 475
 
7.1%
역 466
 
7.0%
광 463
 
6.9%
원 262
 
3.9%
공 197
 
3.0%
산 136
 
2.0%
Other values (194) 2124
31.9%
Common
ValueCountFrequency (%)
1547
35.9%
1 469
 
10.9%
- 282
 
6.5%
3 235
 
5.4%
2 221
 
5.1%
7 185
 
4.3%
, 177
 
4.1%
9 167
 
3.9%
8 157
 
3.6%
) 155
 
3.6%
Other values (6) 719
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6664
60.7%
ASCII 4314
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1547
35.9%
1 469
 
10.9%
- 282
 
6.5%
3 235
 
5.4%
2 221
 
5.1%
7 185
 
4.3%
, 177
 
4.1%
9 167
 
3.9%
8 157
 
3.6%
) 155
 
3.6%
Other values (6) 719
16.7%
Hangul
ValueCountFrequency (%)
구 990
14.9%
동 557
 
8.4%
대 515
 
7.7%
북 479
 
7.2%
시 475
 
7.1%
역 466
 
7.0%
광 463
 
6.9%
원 262
 
3.9%
공 197
 
3.0%
산 136
 
2.0%
Other values (194) 2124
31.9%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
생활방범
517 
어린이보호
452 
시설물관리
319 
교통단속
155 
쓰레기단속
109 
Other values (4)
102 

Length

Max length5
Median length5
Mean length4.5320435
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
생활방범 517
31.3%
어린이보호 452
27.3%
시설물관리 319
19.3%
교통단속 155
 
9.4%
쓰레기단속 109
 
6.6%
청사방호 71
 
4.3%
재난재해 18
 
1.1%
생활안전 11
 
0.7%
차량방범 2
 
0.1%

Length

2024-04-19T14:53:19.114759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:53:19.230260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
생활방범 517
31.3%
어린이보호 452
27.3%
시설물관리 319
19.3%
교통단속 155
 
9.4%
쓰레기단속 109
 
6.6%
청사방호 71
 
4.3%
재난재해 18
 
1.1%
생활안전 11
 
0.7%
차량방범 2
 
0.1%

카메라대수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
1
1654 

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 1654
100.0%

Length

2024-04-19T14:53:19.370494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:53:19.461579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1654
100.0%

카메라화소수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
200
1262 
500
183 
41
149 
130
 
46
80
 
8

Length

Max length4
Median length3
Mean length2.9087062
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41
2nd row41
3rd row41
4th row41
5th row41

Common Values

ValueCountFrequency (%)
200 1262
76.3%
500 183
 
11.1%
41 149
 
9.0%
130 46
 
2.8%
80 8
 
0.5%
<NA> 6
 
0.4%

Length

2024-04-19T14:53:19.568047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:53:19.720589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 1262
76.3%
500 183
 
11.1%
41 149
 
9.0%
130 46
 
2.8%
80 8
 
0.5%
na 6
 
0.4%

촬영방면정보
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1654
Missing (%)100.0%
Memory size14.7 KiB

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
30
1654 

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 1654
100.0%

Length

2024-04-19T14:53:19.833861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T14:53:19.939831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 1654
100.0%

설치년월
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1654
Missing (%)100.0%
Memory size14.7 KiB

관리기관전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct32
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
053-665-4481
1164 
053-665-3171
226 
053-665-2581
 
109
053-665-2214
 
33
053-665-3205
 
27
Other values (27)
 
95

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique6 ?
Unique (%)0.4%

Sample

1st row053-665-3171
2nd row053-665-3171
3rd row053-665-3171
4th row053-665-3171
5th row053-665-3171

Common Values

ValueCountFrequency (%)
053-665-4481 1164
70.4%
053-665-3171 226
 
13.7%
053-665-2581 109
 
6.6%
053-665-2214 33
 
2.0%
053-665-3205 27
 
1.6%
053-665-3021 15
 
0.9%
053-665-3543 12
 
0.7%
053-665-2850 10
 
0.6%
053-665-2794 8
 
0.5%
053-665-4583 5
 
0.3%
Other values (22) 45
 
2.7%

Length

2024-04-19T14:53:20.039191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
053-665-4481 1164
70.4%
053-665-3171 226
 
13.7%
053-665-2581 109
 
6.6%
053-665-2214 33
 
2.0%
053-665-3205 27
 
1.6%
053-665-3021 15
 
0.9%
053-665-3543 12
 
0.7%
053-665-2850 10
 
0.6%
053-665-2794 8
 
0.5%
053-665-3740 5
 
0.3%
Other values (22) 45
 
2.7%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct1100
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.909788
Minimum35.874163
Maximum35.969877
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.7 KiB
2024-04-19T14:53:20.173359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.874163
5-th percentile35.878656
Q135.892189
median35.900393
Q335.931306
95-th percentile35.947795
Maximum35.969877
Range0.0957137
Interquartile range (IQR)0.039117

Descriptive statistics

Standard deviation0.023177977
Coefficient of variation (CV)0.00064545013
Kurtosis-1.1351455
Mean35.909788
Median Absolute Deviation (MAD)0.016049
Skewness0.40890448
Sum59394.789
Variance0.00053721863
MonotonicityNot monotonic
2024-04-19T14:53:20.346312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.885724 33
 
2.0%
35.89336926 19
 
1.1%
35.885726 19
 
1.1%
35.941047 14
 
0.8%
35.898004 13
 
0.8%
35.8918778809 13
 
0.8%
35.894397 13
 
0.8%
35.9386329 13
 
0.8%
35.900393 12
 
0.7%
35.892327 12
 
0.7%
Other values (1090) 1493
90.3%
ValueCountFrequency (%)
35.874163 1
0.1%
35.874177 1
0.1%
35.874213 1
0.1%
35.874297 1
0.1%
35.874341 1
0.1%
35.874366 1
0.1%
35.874392 1
0.1%
35.874602 1
0.1%
35.8746823 1
0.1%
35.874705 1
0.1%
ValueCountFrequency (%)
35.9698767 1
 
0.1%
35.965783 1
 
0.1%
35.965597 7
0.4%
35.964367 1
 
0.1%
35.963457 1
 
0.1%
35.9630775 1
 
0.1%
35.9611435 1
 
0.1%
35.960916 2
 
0.1%
35.959031 1
 
0.1%
35.957602 1
 
0.1%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct1101
Distinct (%)66.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58088
Minimum128.50916
Maximum128.74714
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size14.7 KiB
2024-04-19T14:53:20.516778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.50916
5-th percentile128.54303
Q1128.55615
median128.5832
Q3128.60359
95-th percentile128.61931
Maximum128.74714
Range0.2379746
Interquartile range (IQR)0.04744525

Descriptive statistics

Standard deviation0.027021808
Coefficient of variation (CV)0.00021015416
Kurtosis-0.30233113
Mean128.58088
Median Absolute Deviation (MAD)0.0232745
Skewness-0.071202774
Sum212672.78
Variance0.00073017809
MonotonicityNot monotonic
2024-04-19T14:53:20.677538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.5829108 41
 
2.5%
128.6173144 19
 
1.1%
128.544679 14
 
0.8%
128.610616 14
 
0.8%
128.588902 13
 
0.8%
128.605412 13
 
0.8%
128.5655633 13
 
0.8%
128.614681 12
 
0.7%
128.596977 12
 
0.7%
128.582811 11
 
0.7%
Other values (1091) 1492
90.2%
ValueCountFrequency (%)
128.509163 2
0.1%
128.510173 2
0.1%
128.513246 1
0.1%
128.5133 2
0.1%
128.51358 1
0.1%
128.513604 2
0.1%
128.5142402982 2
0.1%
128.5152503 2
0.1%
128.516777 2
0.1%
128.519263 1
0.1%
ValueCountFrequency (%)
128.7471376 1
0.1%
128.6303002 1
0.1%
128.629495 2
0.1%
128.6288427 1
0.1%
128.628826 1
0.1%
128.628695 1
0.1%
128.627979 1
0.1%
128.627102 1
0.1%
128.626623 1
0.1%
128.6261917 2
0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.1 KiB
Minimum2020-01-08 00:00:00
Maximum2020-01-08 00:00:00
2024-04-19T14:53:20.782136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:53:20.865814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-19T14:53:16.754910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:53:16.581234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:53:16.843248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-19T14:53:16.663544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-19T14:53:20.940979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명설치목적구분카메라화소수관리기관전화번호위도경도
관리기관명1.0000.8910.6881.0000.5220.378
설치목적구분0.8911.0000.5840.8830.2870.222
카메라화소수0.6880.5841.0000.6930.1890.176
관리기관전화번호1.0000.8830.6931.0000.5840.376
위도0.5220.2870.1890.5841.0000.620
경도0.3780.2220.1760.3760.6201.000
2024-04-19T14:53:21.039268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카메라화소수관리기관전화번호관리기관명설치목적구분
카메라화소수1.0000.4120.4070.387
관리기관전화번호0.4121.0000.9500.578
관리기관명0.4070.9501.0000.595
설치목적구분0.3870.5780.5951.000
2024-04-19T14:53:21.130980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도관리기관명설치목적구분카메라화소수관리기관전화번호
위도1.000-0.5570.2110.1340.0790.247
경도-0.5571.0000.1640.1210.1150.163
관리기관명0.2110.1641.0000.5950.4070.950
설치목적구분0.1340.1210.5951.0000.3870.578
카메라화소수0.0790.1150.4070.3871.0000.412
관리기관전화번호0.2470.1630.9500.5780.4121.000

Missing values

2024-04-19T14:53:16.977687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T14:53:17.137119image/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.
2024-04-19T14:53:17.258830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자
0대구광역시 북구청 교통과대구광역시 북구 칠곡중앙대로 59, 웨딩아일랜드<NA>교통단속141<NA>30<NA>053-665-317135.901386128.5465452020-01-08
1대구광역시 북구청 교통과대구광역시 북구 동북로 234, KB은행<NA>교통단속141<NA>30<NA>053-665-317135.895785128.6168232020-01-08
2대구광역시 북구청 교통과대구광역시 북구 동북로 234, KB은행<NA>교통단속141<NA>30<NA>053-665-317135.895785128.6168232020-01-08
3대구광역시 북구청 교통과대구광역시 북구 동북로 234, KB은행<NA>교통단속141<NA>30<NA>053-665-317135.895785128.6168232020-01-08
4대구광역시 북구청 교통과대구광역시 북구 동북로 270, 시티병원<NA>교통단속141<NA>30<NA>053-665-317135.893505128.6195762020-01-08
5대구광역시 북구청 교통과대구광역시 북구 동북로 270, 시티병원<NA>교통단속141<NA>30<NA>053-665-317135.893505128.6195762020-01-08
6대구광역시 북구청 교통과대구광역시 북구 동북로 270, 시티병원<NA>교통단속141<NA>30<NA>053-665-317135.893505128.6195762020-01-08
7대구광역시 북구청 교통과대구광역시 북구 대현로20길 30, 대현동 동대구시장<NA>교통단속141<NA>30<NA>053-665-317135.881144128.6089142020-01-08
8대구광역시 북구청 교통과대구광역시 북구 칠성시장로 133-3, 매일천막<NA>교통단속141<NA>30<NA>053-665-317135.885445128.6002992020-01-08
9대구광역시 북구청 교통과대구광역시 북구 칠성시장로 133-3, 매일천막<NA>교통단속141<NA>30<NA>053-665-317135.885445128.6002992020-01-08
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수촬영방면정보보관일수설치년월관리기관전화번호위도경도데이터기준일자
1644대구광역시 북구청 정보통신과대구광역시 북구 대현로3길 17-4<NA>생활안전1500<NA>30<NA>053-665-448135.887521128.6020132020-01-08
1645대구광역시 북구청 정보통신과대구광역시 북구 대현로13길 23-1<NA>생활안전1500<NA>30<NA>053-665-448135.885933128.6049062020-01-08
1646대구광역시 북구청 정보통신과대구광역시 북구 칠성남로35길 15<NA>생활안전1<NA><NA>30<NA>053-665-448135.877538128.5995712020-01-08
1647대구광역시 북구청 정보통신과<NA>대구광역시 북구 복현동 89-3생활안전1<NA><NA>30<NA>053-665-448135.8999128.6185642020-01-08
1648대구광역시 북구청 정보통신과<NA>대구광역시 북구 동천동 896-6생활안전1<NA><NA>30<NA>053-665-448135.942905128.5610042020-01-08
1649대구광역시 북구청 정보통신과대구광역시 북구 대천로17길 3-19<NA>생활안전1<NA><NA>30<NA>053-665-448135.937472128.5551992020-01-08
1650대구광역시 북구청 정보통신과대구광역시 북구 도남길 263-1<NA>생활안전1<NA><NA>30<NA>053-665-448135.969877128.5867592020-01-08
1651대구광역시 북구청 정보통신과대구광역시 북구 동호길 72-16<NA>생활안전1<NA><NA>30<NA>053-665-448135.963077128.5548152020-01-08
1652대구광역시 북구 침산1동 행정복지센터대구광역시 북구 오봉로22길 42-2<NA>청사방호1200<NA>30<NA>053-665-344535.895706128.5829612020-01-08
1653대구광역시 북구 국우동 행정복지센터대구광역시 북구 구리로 188(국우동) 국우동 행정복지센터 1층내부 민원실<NA>청사방호1200<NA>30<NA>053-665-388535.946826128.5745682020-01-08

Duplicate rows

Most frequently occurring

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라대수카메라화소수보관일수관리기관전화번호위도경도데이터기준일자# duplicates
98대구광역시 북구청 총무과대구광역시 북구 옥산로 65, 북구청 청사내외<NA>시설물관리120030053-665-221435.885724128.5829112020-01-0829
14대구광역시 북구청 교통과대구광역시 북구 경진로남1길 40(복현장미공원 공영주차장)<NA>시설물관리120030053-665-317135.893369128.6173142020-01-0818
16대구광역시 북구청 교통과대구광역시 북구 관음중앙로 80, 관음공영주차장<NA>시설물관리14130053-665-317135.941047128.5446792020-01-0814
27대구광역시 북구청 교통과대구광역시 북구 동북로36길 14, 산격공영주차장<NA>시설물관리14130053-665-317135.898004128.6106162020-01-0813
33대구광역시 북구청 교통과대구광역시 북구 산격로 42, 산격3공영주차장<NA>시설물관리14130053-665-317135.894397128.6054122020-01-0813
59대구광역시 북구청 보건과대구광역시 북구 구암서로30(구암동)<NA>청사방호120030053-665-320535.938633128.5655632020-01-0813
52대구광역시 북구청 교통과<NA>대구광역시 북구 산격동 1393시설물관리14130053-665-317135.892327128.6146812020-01-0812
62대구광역시 북구청 산격1동대구광역시 북구 연암로 36길 6(산격동)<NA>시설물관리120030053-665-354335.900393128.5969772020-01-0812
60대구광역시 북구청 보건과대구광역시 북구 성북로 49(침산동)<NA>청사방호120030053-665-320535.891878128.5889022020-01-0811
49대구광역시 북구청 교통과<NA>대구광역시 북구 관음동 185(관음제2공영주차장)시설물관리14130053-665-317135.885726128.5828112020-01-088