Overview

Dataset statistics

Number of variables15
Number of observations2159
Missing cells4323
Missing cells (%)13.3%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory265.8 KiB
Average record size in memory126.1 B

Variable types

Categorical7
Text4
Unsupported1
Numeric2
DateTime1

Dataset

Description경상북도 김천시에서 제공하는 CCTV설치현황 데이터로 관리기관명, 소재지, 설치목적, 카메라모델, 제조사, 카메라대수, 카메라화소, 촬영방면, 보관일수, 설치연도, 관리기관 전화번호 등의 정보를 포함하고 있습니다.
Author경상북도 김천시
URLhttps://www.data.go.kr/data/15099745/fileData.do

Alerts

관리기관명 has constant value ""Constant
카메라화소수 has constant value ""Constant
보관일수 has constant value ""Constant
데이터기준일자 has constant value ""Constant
Dataset has 1 (< 0.1%) duplicate rowsDuplicates
설치목적구분 is highly overall correlated with 제조사 and 1 other fieldsHigh correlation
관리기관전화번호 is highly overall correlated with 설치목적구분High correlation
제조사 is highly overall correlated with 설치목적구분High correlation
카메라대수 is highly imbalanced (97.4%)Imbalance
관리기관전화번호 is highly imbalanced (70.2%)Imbalance
소재지도로명주소 has 1509 (69.9%) missing valuesMissing
소재지지번주소 has 649 (30.1%) missing valuesMissing
설치연도 has 2159 (100.0%) missing valuesMissing
설치연도 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 06:11:01.571887
Analysis finished2023-12-12 06:11:03.873089
Duration2.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
경상북도 김천시청
2159 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상북도 김천시청
2nd row경상북도 김천시청
3rd row경상북도 김천시청
4th row경상북도 김천시청
5th row경상북도 김천시청

Common Values

ValueCountFrequency (%)
경상북도 김천시청 2159
100.0%

Length

2023-12-12T15:11:03.959541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:04.084724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상북도 2159
50.0%
김천시청 2159
50.0%

소재지도로명주소
Text

MISSING 

Distinct306
Distinct (%)47.1%
Missing1509
Missing (%)69.9%
Memory size17.0 KiB
2023-12-12T15:11:04.406010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length18.509231
Min length12

Characters and Unicode

Total characters12031
Distinct characters168
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

Unique180 ?
Unique (%)27.7%

Sample

1st row경상북도 김천시 혁신5로 11 (SP-02)
2nd row경상북도 김천시 율곡동 혁신4로 70(SP03)
3rd row경상북도 김천시 혁신2로 26(SC02)
4th row경상북도 김천시 율곡동 혁신8로 119(SS02)
5th row경상북도 김천시 율곡동 용전3로 10
ValueCountFrequency (%)
경상북도 650
24.0%
김천시 650
24.0%
평화남산동 57
 
2.1%
감천로100 55
 
2.0%
6 24
 
0.9%
영남대로 21
 
0.8%
7 21
 
0.8%
남면 19
 
0.7%
김천로 18
 
0.7%
모암사랑10길 17
 
0.6%
Other values (429) 1177
43.4%
2023-12-12T15:11:04.977098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2065
17.2%
천 737
 
6.1%
시 679
 
5.6%
김 674
 
5.6%
상 661
 
5.5%
경 650
 
5.4%
북 650
 
5.4%
도 650
 
5.4%
1 482
 
4.0%
길 351
 
2.9%
Other values (158) 4432
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7594
63.1%
Space Separator 2065
 
17.2%
Decimal Number 2050
 
17.0%
Dash Punctuation 145
 
1.2%
Uppercase Letter 83
 
0.7%
Open Punctuation 45
 
0.4%
Close Punctuation 44
 
0.4%
Other Punctuation 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 737
 
9.7%
시 679
 
8.9%
김 674
 
8.9%
상 661
 
8.7%
경 650
 
8.6%
북 650
 
8.6%
도 650
 
8.6%
길 351
 
4.6%
로 284
 
3.7%
산 128
 
1.7%
Other values (138) 2130
28.0%
Decimal Number
ValueCountFrequency (%)
1 482
23.5%
3 259
12.6%
2 253
12.3%
0 245
12.0%
4 161
 
7.9%
6 159
 
7.8%
5 159
 
7.8%
9 116
 
5.7%
8 115
 
5.6%
7 101
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
S 46
55.4%
C 15
 
18.1%
P 8
 
9.6%
M 7
 
8.4%
H 7
 
8.4%
Space Separator
ValueCountFrequency (%)
2065
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 145
100.0%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7594
63.1%
Common 4354
36.2%
Latin 83
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 737
 
9.7%
시 679
 
8.9%
김 674
 
8.9%
상 661
 
8.7%
경 650
 
8.6%
북 650
 
8.6%
도 650
 
8.6%
길 351
 
4.6%
로 284
 
3.7%
산 128
 
1.7%
Other values (138) 2130
28.0%
Common
ValueCountFrequency (%)
2065
47.4%
1 482
 
11.1%
3 259
 
5.9%
2 253
 
5.8%
0 245
 
5.6%
4 161
 
3.7%
6 159
 
3.7%
5 159
 
3.7%
- 145
 
3.3%
9 116
 
2.7%
Other values (5) 310
 
7.1%
Latin
ValueCountFrequency (%)
S 46
55.4%
C 15
 
18.1%
P 8
 
9.6%
M 7
 
8.4%
H 7
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7594
63.1%
ASCII 4437
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2065
46.5%
1 482
 
10.9%
3 259
 
5.8%
2 253
 
5.7%
0 245
 
5.5%
4 161
 
3.6%
6 159
 
3.6%
5 159
 
3.6%
- 145
 
3.3%
9 116
 
2.6%
Other values (10) 393
 
8.9%
Hangul
ValueCountFrequency (%)
천 737
 
9.7%
시 679
 
8.9%
김 674
 
8.9%
상 661
 
8.7%
경 650
 
8.6%
북 650
 
8.6%
도 650
 
8.6%
길 351
 
4.6%
로 284
 
3.7%
산 128
 
1.7%
Other values (138) 2130
28.0%

소재지지번주소
Text

MISSING 

Distinct849
Distinct (%)56.2%
Missing649
Missing (%)30.1%
Memory size17.0 KiB
2023-12-12T15:11:05.367642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length19.496689
Min length13

Characters and Unicode

Total characters29440
Distinct characters168
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

Unique509 ?
Unique (%)33.7%

Sample

1st row경상북도 김천시 성내동 155-1
2nd row경상북도 김천시 성내동 120-7
3rd row경상북도 김천시 성내동 162
4th row경상북도 김천시 성내동 146-4
5th row경상북도 김천시 성내동 120-7
ValueCountFrequency (%)
경상북도 1510
22.7%
김천시 1510
22.7%
부곡동 110
 
1.7%
평화동 95
 
1.4%
신음동 93
 
1.4%
봉산면 77
 
1.2%
아포읍 75
 
1.1%
율곡동 74
 
1.1%
어모면 59
 
0.9%
황금동 58
 
0.9%
Other values (993) 2995
45.0%
2023-12-12T15:11:05.945328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5200
17.7%
천 1625
 
5.5%
도 1536
 
5.2%
상 1528
 
5.2%
북 1511
 
5.1%
김 1511
 
5.1%
경 1510
 
5.1%
시 1510
 
5.1%
1 1241
 
4.2%
- 956
 
3.2%
Other values (158) 11312
38.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17297
58.8%
Decimal Number 5705
 
19.4%
Space Separator 5200
 
17.7%
Dash Punctuation 956
 
3.2%
Uppercase Letter 160
 
0.5%
Open Punctuation 61
 
0.2%
Close Punctuation 60
 
0.2%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 1625
 
9.4%
도 1536
 
8.9%
상 1528
 
8.8%
북 1511
 
8.7%
김 1511
 
8.7%
경 1510
 
8.7%
시 1510
 
8.7%
동 842
 
4.9%
리 702
 
4.1%
면 626
 
3.6%
Other values (137) 4396
25.4%
Decimal Number
ValueCountFrequency (%)
1 1241
21.8%
2 722
12.7%
3 622
10.9%
5 518
9.1%
7 508
8.9%
4 493
 
8.6%
8 424
 
7.4%
6 422
 
7.4%
0 408
 
7.2%
9 347
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
S 50
31.2%
C 47
29.4%
M 41
25.6%
H 13
 
8.1%
R 8
 
5.0%
K 1
 
0.6%
Space Separator
ValueCountFrequency (%)
5200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 956
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17297
58.8%
Common 11983
40.7%
Latin 160
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 1625
 
9.4%
도 1536
 
8.9%
상 1528
 
8.8%
북 1511
 
8.7%
김 1511
 
8.7%
경 1510
 
8.7%
시 1510
 
8.7%
동 842
 
4.9%
리 702
 
4.1%
면 626
 
3.6%
Other values (137) 4396
25.4%
Common
ValueCountFrequency (%)
5200
43.4%
1 1241
 
10.4%
- 956
 
8.0%
2 722
 
6.0%
3 622
 
5.2%
5 518
 
4.3%
7 508
 
4.2%
4 493
 
4.1%
8 424
 
3.5%
6 422
 
3.5%
Other values (5) 877
 
7.3%
Latin
ValueCountFrequency (%)
S 50
31.2%
C 47
29.4%
M 41
25.6%
H 13
 
8.1%
R 8
 
5.0%
K 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17297
58.8%
ASCII 12143
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5200
42.8%
1 1241
 
10.2%
- 956
 
7.9%
2 722
 
5.9%
3 622
 
5.1%
5 518
 
4.3%
7 508
 
4.2%
4 493
 
4.1%
8 424
 
3.5%
6 422
 
3.5%
Other values (11) 1037
 
8.5%
Hangul
ValueCountFrequency (%)
천 1625
 
9.4%
도 1536
 
8.9%
상 1528
 
8.8%
북 1511
 
8.7%
김 1511
 
8.7%
경 1510
 
8.7%
시 1510
 
8.7%
동 842
 
4.9%
리 702
 
4.1%
면 626
 
3.6%
Other values (137) 4396
25.4%

설치목적구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
다목적
1308 
어린이보호
608 
쓰레기단속
 
114
교통단속
 
90
시설물관리
 
28

Length

Max length5
Median length3
Mean length3.7313571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
다목적 1308
60.6%
어린이보호 608
28.2%
쓰레기단속 114
 
5.3%
교통단속 90
 
4.2%
시설물관리 28
 
1.3%
기타 11
 
0.5%

Length

2023-12-12T15:11:06.146852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:06.270097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다목적 1308
60.6%
어린이보호 608
28.2%
쓰레기단속 114
 
5.3%
교통단속 90
 
4.2%
시설물관리 28
 
1.3%
기타 11
 
0.5%

카메라모델명
Text

Distinct86
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
2023-12-12T15:11:06.508108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length10.522001
Min length3

Characters and Unicode

Total characters22717
Distinct characters56
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

Unique22 ?
Unique (%)1.0%

Sample

1st rowCMNS-230IR
2nd rowCMNS-230IR
3rd rowCMNS-230IR
4th rowCMNS-230IR
5th rowCMNS-230IR
ValueCountFrequency (%)
tn-b22032rc 415
17.6%
tn-b2212k2r-c 178
 
7.6%
sno-6011r 158
 
6.7%
q1615-e 121
 
5.1%
vbr-10004 96
 
4.1%
xno-6085r 93
 
4.0%
iho-i2170 93
 
4.0%
tn-p5230w12r 87
 
3.7%
snc-wr630 84
 
3.6%
ihb-i2100 77
 
3.3%
Other values (79) 951
40.4%
2023-12-12T15:11:06.920938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2971
 
13.1%
- 2232
 
9.8%
0 1793
 
7.9%
R 1562
 
6.9%
1 1509
 
6.6%
N 1479
 
6.5%
3 980
 
4.3%
B 946
 
4.2%
T 908
 
4.0%
C 906
 
4.0%
Other values (46) 7431
32.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 10169
44.8%
Decimal Number 9062
39.9%
Dash Punctuation 2232
 
9.8%
Lowercase Letter 988
 
4.3%
Space Separator 194
 
0.9%
Close Punctuation 23
 
0.1%
Open Punctuation 23
 
0.1%
Connector Punctuation 23
 
0.1%
Other Letter 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 1562
15.4%
N 1479
14.5%
B 946
9.3%
T 908
8.9%
C 906
8.9%
S 595
 
5.9%
I 510
 
5.0%
D 505
 
5.0%
O 438
 
4.3%
H 331
 
3.3%
Other values (15) 1989
19.6%
Lowercase Letter
ValueCountFrequency (%)
o 150
15.2%
m 150
15.2%
r 148
15.0%
i 122
12.3%
n 77
7.8%
e 75
7.6%
v 74
7.5%
a 48
 
4.9%
c 48
 
4.9%
b 46
 
4.7%
Other values (3) 50
 
5.1%
Decimal Number
ValueCountFrequency (%)
2 2971
32.8%
0 1793
19.8%
1 1509
16.7%
3 980
 
10.8%
6 729
 
8.0%
5 506
 
5.6%
8 204
 
2.3%
4 195
 
2.2%
7 143
 
1.6%
9 32
 
0.4%
Other Letter
ValueCountFrequency (%)
레 1
33.3%
코 1
33.3%
딩 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 2232
100.0%
Space Separator
ValueCountFrequency (%)
194
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11557
50.9%
Latin 11157
49.1%
Hangul 3
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 1562
14.0%
N 1479
13.3%
B 946
 
8.5%
T 908
 
8.1%
C 906
 
8.1%
S 595
 
5.3%
I 510
 
4.6%
D 505
 
4.5%
O 438
 
3.9%
H 331
 
3.0%
Other values (28) 2977
26.7%
Common
ValueCountFrequency (%)
2 2971
25.7%
- 2232
19.3%
0 1793
15.5%
1 1509
13.1%
3 980
 
8.5%
6 729
 
6.3%
5 506
 
4.4%
8 204
 
1.8%
4 195
 
1.7%
194
 
1.7%
Other values (5) 244
 
2.1%
Hangul
ValueCountFrequency (%)
레 1
33.3%
코 1
33.3%
딩 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22714
> 99.9%
Hangul 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 2971
 
13.1%
- 2232
 
9.8%
0 1793
 
7.9%
R 1562
 
6.9%
1 1509
 
6.6%
N 1479
 
6.5%
3 980
 
4.3%
B 946
 
4.2%
T 908
 
4.0%
C 906
 
4.0%
Other values (43) 7428
32.7%
Hangul
ValueCountFrequency (%)
레 1
33.3%
코 1
33.3%
딩 1
33.3%

제조사
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
TRUEN
811 
SAMSUNG
319 
INNODEP INC.
177 
AXIS
158 
HANWHA TECHWIN
156 
Other values (18)
538 

Length

Max length18
Median length14
Mean length6.6303844
Min length3

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
TRUEN 811
37.6%
SAMSUNG 319
 
14.8%
INNODEP INC. 177
 
8.2%
AXIS 158
 
7.3%
HANWHA TECHWIN 156
 
7.2%
<NA> 124
 
5.7%
SONY 95
 
4.4%
IDIS 76
 
3.5%
HIKVISION 75
 
3.5%
HUVIRON 29
 
1.3%
Other values (13) 139
 
6.4%

Length

2023-12-12T15:11:07.077695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
truen 811
32.5%
samsung 319
 
12.8%
innodep 177
 
7.1%
inc 177
 
7.1%
axis 158
 
6.3%
hanwha 156
 
6.3%
techwin 156
 
6.3%
na 124
 
5.0%
sony 95
 
3.8%
idis 76
 
3.0%
Other values (16) 244
 
9.8%

카메라대수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
1
2147 
4
 
5
2
 
4
3
 
2
8
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
1 2147
99.4%
4 5
 
0.2%
2 4
 
0.2%
3 2
 
0.1%
8 1
 
< 0.1%

Length

2023-12-12T15:11:07.264863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:07.370191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2147
99.4%
4 5
 
0.2%
2 4
 
0.2%
3 2
 
0.1%
8 1
 
< 0.1%

카메라화소수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
200
2159 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
200 2159
100.0%

Length

2023-12-12T15:11:07.469901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:07.587586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
200 2159
100.0%

촬영방면정보
Text

Distinct2157
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
2023-12-12T15:11:07.864228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length10.289949
Min length2

Characters and Unicode

Total characters22216
Distinct characters475
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2155 ?
Unique (%)99.8%

Sample

1st row골드클래스
2nd row천년나무2단지
3rd row대한법률구조공단
4th row국립 종자원
5th rowLH아파트4차
ValueCountFrequency (%)
앞 166
 
4.1%
전통시장 93
 
2.3%
입구 69
 
1.7%
평화남산동 58
 
1.4%
앞-1 45
 
1.1%
앞-2 45
 
1.1%
황금동 36
 
0.9%
삼거리 34
 
0.8%
마을입구 31
 
0.8%
입구-2 28
 
0.7%
Other values (2232) 3465
85.1%
2023-12-12T15:11:08.368675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1937
 
8.7%
- 1585
 
7.1%
1 840
 
3.8%
2 656
 
3.0%
리 550
 
2.5%
교 494
 
2.2%
초 435
 
2.0%
구 434
 
2.0%
앞 365
 
1.6%
학 364
 
1.6%
Other values (465) 14556
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15452
69.6%
Decimal Number 2458
 
11.1%
Space Separator 1937
 
8.7%
Dash Punctuation 1585
 
7.1%
Close Punctuation 247
 
1.1%
Open Punctuation 245
 
1.1%
Uppercase Letter 212
 
1.0%
Lowercase Letter 46
 
0.2%
Other Punctuation 18
 
0.1%
Connector Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 550
 
3.6%
교 494
 
3.2%
초 435
 
2.8%
구 434
 
2.8%
앞 365
 
2.4%
학 364
 
2.4%
입 346
 
2.2%
마 304
 
2.0%
장 276
 
1.8%
동 272
 
1.8%
Other values (421) 11612
75.1%
Uppercase Letter
ValueCountFrequency (%)
C 58
27.4%
A 38
17.9%
B 23
 
10.8%
T 22
 
10.4%
K 14
 
6.6%
S 14
 
6.6%
G 8
 
3.8%
P 7
 
3.3%
X 5
 
2.4%
H 5
 
2.4%
Other values (8) 18
 
8.5%
Decimal Number
ValueCountFrequency (%)
1 840
34.2%
2 656
26.7%
0 280
 
11.4%
3 191
 
7.8%
4 125
 
5.1%
5 99
 
4.0%
6 88
 
3.6%
8 62
 
2.5%
9 59
 
2.4%
7 58
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
s 23
50.0%
i 8
 
17.4%
m 4
 
8.7%
n 4
 
8.7%
k 2
 
4.3%
t 2
 
4.3%
u 1
 
2.2%
c 1
 
2.2%
e 1
 
2.2%
Space Separator
ValueCountFrequency (%)
1937
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1585
100.0%
Close Punctuation
ValueCountFrequency (%)
) 247
100.0%
Open Punctuation
ValueCountFrequency (%)
( 245
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15452
69.6%
Common 6506
29.3%
Latin 258
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 550
 
3.6%
교 494
 
3.2%
초 435
 
2.8%
구 434
 
2.8%
앞 365
 
2.4%
학 364
 
2.4%
입 346
 
2.2%
마 304
 
2.0%
장 276
 
1.8%
동 272
 
1.8%
Other values (421) 11612
75.1%
Latin
ValueCountFrequency (%)
C 58
22.5%
A 38
14.7%
s 23
 
8.9%
B 23
 
8.9%
T 22
 
8.5%
K 14
 
5.4%
S 14
 
5.4%
i 8
 
3.1%
G 8
 
3.1%
P 7
 
2.7%
Other values (17) 43
16.7%
Common
ValueCountFrequency (%)
1937
29.8%
- 1585
24.4%
1 840
12.9%
2 656
 
10.1%
0 280
 
4.3%
) 247
 
3.8%
( 245
 
3.8%
3 191
 
2.9%
4 125
 
1.9%
5 99
 
1.5%
Other values (7) 301
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15452
69.6%
ASCII 6764
30.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1937
28.6%
- 1585
23.4%
1 840
12.4%
2 656
 
9.7%
0 280
 
4.1%
) 247
 
3.7%
( 245
 
3.6%
3 191
 
2.8%
4 125
 
1.8%
5 99
 
1.5%
Other values (34) 559
 
8.3%
Hangul
ValueCountFrequency (%)
리 550
 
3.6%
교 494
 
3.2%
초 435
 
2.8%
구 434
 
2.8%
앞 365
 
2.4%
학 364
 
2.4%
입 346
 
2.2%
마 304
 
2.0%
장 276
 
1.8%
동 272
 
1.8%
Other values (421) 11612
75.1%

보관일수
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
30
2159 

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 2159
100.0%

Length

2023-12-12T15:11:08.572059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:08.722103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 2159
100.0%

설치연도
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2159
Missing (%)100.0%
Memory size19.1 KiB

관리기관전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
054-420-6881
2045 
054-420-6183
 
114

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row054-420-6881
2nd row054-420-6881
3rd row054-420-6881
4th row054-420-6881
5th row054-420-6881

Common Values

ValueCountFrequency (%)
054-420-6881 2045
94.7%
054-420-6183 114
 
5.3%

Length

2023-12-12T15:11:08.847506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:08.963649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
054-420-6881 2045
94.7%
054-420-6183 114
 
5.3%

위도
Real number (ℝ)

Distinct1271
Distinct (%)59.0%
Missing3
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean36.113207
Minimum35.854088
Maximum36.246811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.1 KiB
2023-12-12T15:11:09.093287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.854088
5-th percentile35.985851
Q136.116522
median36.123042
Q336.133553
95-th percentile36.181074
Maximum36.246811
Range0.39272259
Interquartile range (IQR)0.0170317

Descriptive statistics

Standard deviation0.057278882
Coefficient of variation (CV)0.0015860924
Kurtosis4.7106208
Mean36.113207
Median Absolute Deviation (MAD)0.00752906
Skewness-1.8834259
Sum77860.074
Variance0.0032808703
MonotonicityNot monotonic
2023-12-12T15:11:09.290265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.1229406 16
 
0.7%
36.11850086 16
 
0.7%
36.11844595 15
 
0.7%
36.12605809 15
 
0.7%
36.12226022 15
 
0.7%
36.12550175 15
 
0.7%
36.15278805 15
 
0.7%
36.15977111 14
 
0.6%
36.13135117 14
 
0.6%
36.12200032 14
 
0.6%
Other values (1261) 2007
93.0%
ValueCountFrequency (%)
35.85408841 1
< 0.1%
35.86204935 1
< 0.1%
35.86429604 2
0.1%
35.86900346 1
< 0.1%
35.87262316 1
< 0.1%
35.87394126 1
< 0.1%
35.87553192 1
< 0.1%
35.87644602 2
0.1%
35.87987885 1
< 0.1%
35.88235904 1
< 0.1%
ValueCountFrequency (%)
36.246811 1
 
< 0.1%
36.241848 2
 
0.1%
36.23556165 1
 
< 0.1%
36.23261724 1
 
< 0.1%
36.23208562 6
0.3%
36.23205614 1
 
< 0.1%
36.23160987 3
0.1%
36.23127641 1
 
< 0.1%
36.23035549 1
 
< 0.1%
36.22963255 1
 
< 0.1%

경도
Real number (ℝ)

Distinct1271
Distinct (%)59.0%
Missing3
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean128.11669
Minimum127.903
Maximum128.29844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.1 KiB
2023-12-12T15:11:09.456095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.903
5-th percentile128.00818
Q1128.094
median128.11771
Q3128.13998
95-th percentile128.22533
Maximum128.29844
Range0.3954436
Interquartile range (IQR)0.0459812

Descriptive statistics

Standard deviation0.061428008
Coefficient of variation (CV)0.00047946922
Kurtosis1.1650718
Mean128.11669
Median Absolute Deviation (MAD)0.02371135
Skewness-0.27308728
Sum276219.58
Variance0.0037734001
MonotonicityNot monotonic
2023-12-12T15:11:09.629848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.1212243 16
 
0.7%
128.0218981 16
 
0.7%
128.1751499 15
 
0.7%
128.1468769 15
 
0.7%
128.0284754 15
 
0.7%
128.0765178 15
 
0.7%
128.1242984 15
 
0.7%
128.2455867 14
 
0.6%
128.1217668 14
 
0.6%
128.1791735 14
 
0.6%
Other values (1261) 2007
93.0%
ValueCountFrequency (%)
127.9029969 1
< 0.1%
127.9047708 1
< 0.1%
127.9065317 1
< 0.1%
127.9164984 1
< 0.1%
127.9169125 1
< 0.1%
127.9189769 1
< 0.1%
127.9220084 1
< 0.1%
127.9220183 1
< 0.1%
127.9230873 1
< 0.1%
127.9233348 1
< 0.1%
ValueCountFrequency (%)
128.2984405 1
< 0.1%
128.284529 1
< 0.1%
128.2841932 1
< 0.1%
128.2795293 1
< 0.1%
128.2790859 2
0.1%
128.277585 1
< 0.1%
128.2755781 1
< 0.1%
128.2726649 1
< 0.1%
128.271865 2
0.1%
128.2717021 1
< 0.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.0 KiB
Minimum2022-04-07 00:00:00
Maximum2022-04-07 00:00:00
2023-12-12T15:11:09.754512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:09.836396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T15:11:02.898932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:02.529558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:03.026178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:02.767286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:11:09.904614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치목적구분카메라모델명제조사카메라대수관리기관전화번호위도경도
설치목적구분1.0000.9450.8640.1101.0000.1800.305
카메라모델명0.9451.0001.0000.4890.8250.5250.623
제조사0.8641.0001.0000.4840.4570.3390.445
카메라대수0.1100.4890.4841.0000.0000.0000.166
관리기관전화번호1.0000.8250.4570.0001.0000.1130.129
위도0.1800.5250.3390.0000.1131.0000.741
경도0.3050.6230.4450.1660.1290.7411.000
2023-12-12T15:11:10.002925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
제조사설치목적구분카메라대수관리기관전화번호
제조사1.0000.6220.2630.361
설치목적구분0.6221.0000.0750.999
카메라대수0.2630.0751.0000.000
관리기관전화번호0.3610.9990.0001.000
2023-12-12T15:11:10.091308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도설치목적구분제조사카메라대수관리기관전화번호
위도1.0000.1270.0950.1320.0000.087
경도0.1271.0000.1660.1810.0700.099
설치목적구분0.0950.1661.0000.6220.0750.999
제조사0.1320.1810.6221.0000.2630.361
카메라대수0.0000.0700.0750.2631.0000.000
관리기관전화번호0.0870.0990.9990.3610.0001.000

Missing values

2023-12-12T15:11:03.205531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:11:03.538770image/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.
2023-12-12T15:11:03.769221image/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

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라모델명제조사카메라대수카메라화소수촬영방면정보보관일수설치연도관리기관전화번호위도경도데이터기준일자
0경상북도 김천시청경상북도 김천시 혁신5로 11 (SP-02)<NA>다목적CMNS-230IRCAMTRON1200골드클래스30<NA>054-420-688136.11896128.1785522022-04-07
1경상북도 김천시청경상북도 김천시 율곡동 혁신4로 70(SP03)<NA>다목적CMNS-230IRCAMTRON1200천년나무2단지30<NA>054-420-688136.120014128.1910042022-04-07
2경상북도 김천시청경상북도 김천시 혁신2로 26(SC02)<NA>다목적CMNS-230IRCAMTRON1200대한법률구조공단30<NA>054-420-688136.115649128.1831922022-04-07
3경상북도 김천시청경상북도 김천시 율곡동 혁신8로 119(SS02)<NA>다목적CMNS-230IRCAMTRON1200국립 종자원30<NA>054-420-688136.124944128.1932942022-04-07
4경상북도 김천시청경상북도 김천시 율곡동 용전3로 10<NA>다목적CMNS-230IRCAMTRON1200LH아파트4차30<NA>054-420-688136.120418128.1748922022-04-07
5경상북도 김천시청경상북도 김천시 율곡동 용전로 119(SH06)<NA>다목적CMNS-230IRCAMTRON1200주사랑 교회30<NA>054-420-688136.121678128.1963512022-04-07
6경상북도 김천시청경상북도 김천시 율곡동 혁신4로 70(SP03)<NA>다목적TN-B22032RCTRUEN1200천년나무2단지-130<NA>054-420-688136.120014128.1910042022-04-07
7경상북도 김천시청경상북도 김천시 혁신5로 11 (SP-02)<NA>다목적TN-B22032RCTRUEN1200골드클래스-130<NA>054-420-688136.11896128.1785522022-04-07
8경상북도 김천시청경상북도 김천시 혁신2로 26(SC02)<NA>다목적TN-B22032RCTRUEN1200대한법률구조공단-130<NA>054-420-688136.115649128.1831922022-04-07
9경상북도 김천시청경상북도 김천시 혁신2로 26(SC02)<NA>다목적TN-B22032RCTRUEN1200대한법률구조공단-230<NA>054-420-688136.115649128.1831922022-04-07
관리기관명소재지도로명주소소재지지번주소설치목적구분카메라모델명제조사카메라대수카메라화소수촬영방면정보보관일수설치연도관리기관전화번호위도경도데이터기준일자
2149경상북도 김천시청<NA>경상북도 김천시 아포읍 봉산리쓰레기단속D4S-AV1115DNARECONTVISION1200봉산교(영남대로 방향)30<NA>054-420-618336.15704128.2252452022-04-07
2150경상북도 김천시청<NA>경상북도 김천시 봉산면 덕천리 용배교쓰레기단속D4S-AV1115DNARECONTVISION1200용배교 사거리30<NA>054-420-618336.137868128.0383372022-04-07
2151경상북도 김천시청<NA>경상북도 김천시 지례면 여배리 산90-53쓰레기단속D4S-AV1115DNARECONTVISION1200지례면 여배리 산90-5330<NA>054-420-618335.941476128.0179752022-04-07
2152경상북도 김천시청경상북도 김천시 새터3길 74<NA>쓰레기단속D4S-AV1115DNARECONTVISION1200새터3길 74 앞 삼거리30<NA>054-420-618336.101708128.116162022-04-07
2153경상북도 김천시청<NA>경상북도 김천시 대신터널다목적TN-P5236W12RTRUEN8200대신터널30<NA>054-420-688136.138676128.1206762022-04-07
2154경상북도 김천시청경상북도 김천시 아포읍 한지2길 56<NA>다목적XNO-6085RHANWHA TECHWIN2200명성한우 앞30<NA>054-420-688136.158552128.2622182022-04-07
2155경상북도 김천시청<NA>경상북도 김천시 아포읍 송천리 685다목적XNO-6085RHANWHA TECHWIN1200아포지게차 앞30<NA>054-420-688136.150729128.2775852022-04-07
2156경상북도 김천시청경상북도 김천시 아포읍 아포공단길 123<NA>다목적XNO-6085RHANWHA TECHWIN2200대윤지오텍 앞-130<NA>054-420-688136.16502128.2504432022-04-07
2157경상북도 김천시청경상북도 김천시 아포읍 한지2길 10<NA>다목적XNO-6085RHANWHA TECHWIN1200건강한마을약국 부근-230<NA>054-420-688136.159022128.2598172022-04-07
2158경상북도 김천시청경상북도 김천시 강변공원길 169<NA>다목적XNP-6371RHHANWHA TECHWIN2200강변공원 주차장 입구30<NA>054-420-688136.128881128.0905142022-04-07

Duplicate rows

Most frequently occurring

관리기관명소재지도로명주소소재지지번주소설치목적구분카메라모델명제조사카메라대수카메라화소수촬영방면정보보관일수관리기관전화번호위도경도데이터기준일자# duplicates
0경상북도 김천시청경상북도 김천시 가메실4길 6-5<NA>교통단속SK-N511HHUVIRON1200인천국제공항버스 정류장-검지130054-420-688136.123634128.1031362022-04-072