Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory976.6 KiB
Average record size in memory100.0 B

Variable types

DateTime2
Categorical4
Numeric1
Text4

Dataset

Description판교제로시티 CCTV 데이터 제로셔틀 경로추적 조회
Author차세대융합기술연구원
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=E1ZM1WF65YZ5NW0RCJMQ31892174&infSeq=1

Alerts

이미지너비 has constant value ""Constant
이미지높이 has constant value ""Constant
이미지고유번호 is highly overall correlated with 날씨정보 and 1 other fieldsHigh correlation
날씨정보 is highly overall correlated with 이미지고유번호 and 1 other fieldsHigh correlation
CCTV고유번호 is highly overall correlated with 이미지고유번호 and 1 other fieldsHigh correlation
이미지고유번호 has unique valuesUnique
이미지파일명 has unique valuesUnique
이미지파일경로 has unique valuesUnique
어노테이션json파일명 has unique valuesUnique
어노테이션json파일경로 has unique valuesUnique

Reproduction

Analysis started2024-03-23 01:39:58.031329
Analysis finished2024-03-23 01:40:01.112666
Duration3.08 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

녹화시작일시
Date

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-05-24 08:40:13
Maximum2021-11-17 08:00:00
2024-03-23T01:40:01.395418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:40:01.997276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

녹화종료일시
Date

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2021-05-24 08:40:43
Maximum2021-11-17 10:00:00
2024-03-23T01:40:02.514065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:40:03.042229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

날씨정보
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
8824 
2
1176 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 8824
88.2%
2 1176
 
11.8%

Length

2024-03-23T01:40:03.567050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T01:40:03.884145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 8824
88.2%
2 1176
 
11.8%

CCTV고유번호
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
ARO-SDB-3062
3479 
ARO-SDB-3072
3364 
ARO-SDB-1012
1527 
ARO-SDB-3082
468 
ARO-SDB-3091
 
321
Other values (16)
841 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowARO-SDB-3062
2nd rowARO-SDB-3062
3rd rowARO-SDB-3072
4th rowARO-SDB-3072
5th rowARO-SDB-1012

Common Values

ValueCountFrequency (%)
ARO-SDB-3062 3479
34.8%
ARO-SDB-3072 3364
33.6%
ARO-SDB-1012 1527
15.3%
ARO-SDB-3082 468
 
4.7%
ARO-SDB-3091 321
 
3.2%
ARO-SDB-3061 310
 
3.1%
ARO-SDB-3092 302
 
3.0%
ARO-SDB-3042 25
 
0.2%
ARO-SDB-1032 23
 
0.2%
ARO-SDB-3011 22
 
0.2%
Other values (11) 159
 
1.6%

Length

2024-03-23T01:40:04.183353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
aro-sdb-3062 3479
34.8%
aro-sdb-3072 3364
33.6%
aro-sdb-1012 1527
15.3%
aro-sdb-3082 468
 
4.7%
aro-sdb-3091 321
 
3.2%
aro-sdb-3061 310
 
3.1%
aro-sdb-3092 302
 
3.0%
aro-sdb-3042 25
 
0.2%
aro-sdb-1032 23
 
0.2%
aro-sdb-3052 22
 
0.2%
Other values (11) 159
 
1.6%

이미지고유번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29650.072
Minimum2127
Maximum60890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T01:40:04.713412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2127
5-th percentile8391.95
Q118846.5
median28212.5
Q338143.25
95-th percentile55823.1
Maximum60890
Range58763
Interquartile range (IQR)19296.75

Descriptive statistics

Standard deviation14133.426
Coefficient of variation (CV)0.47667426
Kurtosis-0.44054403
Mean29650.072
Median Absolute Deviation (MAD)9696.5
Skewness0.43860673
Sum2.9650072 × 108
Variance1.9975373 × 108
MonotonicityNot monotonic
2024-03-23T01:40:05.228563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25895 1
 
< 0.1%
27950 1
 
< 0.1%
29386 1
 
< 0.1%
24485 1
 
< 0.1%
52977 1
 
< 0.1%
18135 1
 
< 0.1%
38143 1
 
< 0.1%
12285 1
 
< 0.1%
58438 1
 
< 0.1%
16919 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
2127 1
< 0.1%
2130 1
< 0.1%
2139 1
< 0.1%
2201 1
< 0.1%
2202 1
< 0.1%
2203 1
< 0.1%
2204 1
< 0.1%
2205 1
< 0.1%
2210 1
< 0.1%
2212 1
< 0.1%
ValueCountFrequency (%)
60890 1
< 0.1%
60886 1
< 0.1%
60884 1
< 0.1%
60881 1
< 0.1%
60879 1
< 0.1%
60878 1
< 0.1%
60875 1
< 0.1%
60874 1
< 0.1%
60866 1
< 0.1%
60855 1
< 0.1%

이미지너비
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1280
10000 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1280
2nd row1280
3rd row1280
4th row1280
5th row1280

Common Values

ValueCountFrequency (%)
1280 10000
100.0%

Length

2024-03-23T01:40:05.764049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T01:40:06.161052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1280 10000
100.0%

이미지높이
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
720
10000 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row720
2nd row720
3rd row720
4th row720
5th row720

Common Values

ValueCountFrequency (%)
720 10000
100.0%

Length

2024-03-23T01:40:06.584923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T01:40:06.917552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
720 10000
100.0%

이미지파일명
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T01:40:07.412207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters180000
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowct_2d_00025895.jpg
2nd rowct_2d_00025659.jpg
3rd rowct_2d_00037220.jpg
4th rowct_2d_00033464.jpg
5th rowct_2d_00011823.jpg
ValueCountFrequency (%)
ct_2d_00025895.jpg 1
 
< 0.1%
ct_2d_00012285.jpg 1
 
< 0.1%
ct_2d_00027323.jpg 1
 
< 0.1%
ct_2d_00022920.jpg 1
 
< 0.1%
ct_2d_00029386.jpg 1
 
< 0.1%
ct_2d_00024485.jpg 1
 
< 0.1%
ct_2d_00052977.jpg 1
 
< 0.1%
ct_2d_00018135.jpg 1
 
< 0.1%
ct_2d_00038143.jpg 1
 
< 0.1%
ct_2d_00027950.jpg 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-03-23T01:40:08.339663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34537
19.2%
_ 20000
11.1%
2 16824
9.3%
c 10000
 
5.6%
t 10000
 
5.6%
g 10000
 
5.6%
p 10000
 
5.6%
j 10000
 
5.6%
. 10000
 
5.6%
d 10000
 
5.6%
Other values (8) 38639
21.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90000
50.0%
Lowercase Letter 60000
33.3%
Connector Punctuation 20000
 
11.1%
Other Punctuation 10000
 
5.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34537
38.4%
2 16824
18.7%
3 6568
 
7.3%
1 6318
 
7.0%
5 5088
 
5.7%
4 4708
 
5.2%
6 4080
 
4.5%
7 4068
 
4.5%
8 3956
 
4.4%
9 3853
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
c 10000
16.7%
t 10000
16.7%
g 10000
16.7%
p 10000
16.7%
j 10000
16.7%
d 10000
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 20000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120000
66.7%
Latin 60000
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34537
28.8%
_ 20000
16.7%
2 16824
14.0%
. 10000
 
8.3%
3 6568
 
5.5%
1 6318
 
5.3%
5 5088
 
4.2%
4 4708
 
3.9%
6 4080
 
3.4%
7 4068
 
3.4%
Other values (2) 7809
 
6.5%
Latin
ValueCountFrequency (%)
c 10000
16.7%
t 10000
16.7%
g 10000
16.7%
p 10000
16.7%
j 10000
16.7%
d 10000
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34537
19.2%
_ 20000
11.1%
2 16824
9.3%
c 10000
 
5.6%
t 10000
 
5.6%
g 10000
 
5.6%
p 10000
 
5.6%
j 10000
 
5.6%
. 10000
 
5.6%
d 10000
 
5.6%
Other values (8) 38639
21.5%

이미지파일경로
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T01:40:09.135044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length71
Mean length71
Min length71

Characters and Unicode

Total characters710000
Distinct characters32
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025895.jpg
2nd rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025659.jpg
3rd rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00037220.jpg
4th rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00033464.jpg
5th rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00011823.jpg
ValueCountFrequency (%)
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025895.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00012285.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00027323.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00022920.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00029386.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00024485.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00052977.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00018135.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00038143.jpg 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00027950.jpg 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-03-23T01:40:10.219421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 80000
 
11.3%
0 74537
 
10.5%
2 66824
 
9.4%
t 60000
 
8.5%
c 40000
 
5.6%
r 30000
 
4.2%
d 30000
 
4.2%
. 30000
 
4.2%
g 30000
 
4.2%
p 30000
 
4.2%
Other values (22) 238639
33.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 360000
50.7%
Decimal Number 200000
28.2%
Other Punctuation 120000
 
16.9%
Connector Punctuation 20000
 
2.8%
Dash Punctuation 10000
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 60000
16.7%
c 40000
11.1%
r 30000
8.3%
d 30000
8.3%
g 30000
8.3%
p 30000
8.3%
o 30000
8.3%
a 20000
 
5.6%
n 10000
 
2.8%
v 10000
 
2.8%
Other values (7) 70000
19.4%
Decimal Number
ValueCountFrequency (%)
0 74537
37.3%
2 66824
33.4%
1 16318
 
8.2%
9 13853
 
6.9%
3 6568
 
3.3%
5 5088
 
2.5%
4 4708
 
2.4%
6 4080
 
2.0%
7 4068
 
2.0%
8 3956
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 80000
66.7%
. 30000
 
25.0%
: 10000
 
8.3%
Connector Punctuation
ValueCountFrequency (%)
_ 20000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 360000
50.7%
Common 350000
49.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 60000
16.7%
c 40000
11.1%
r 30000
8.3%
d 30000
8.3%
g 30000
8.3%
p 30000
8.3%
o 30000
8.3%
a 20000
 
5.6%
n 10000
 
2.8%
v 10000
 
2.8%
Other values (7) 70000
19.4%
Common
ValueCountFrequency (%)
/ 80000
22.9%
0 74537
21.3%
2 66824
19.1%
. 30000
 
8.6%
_ 20000
 
5.7%
1 16318
 
4.7%
9 13853
 
4.0%
- 10000
 
2.9%
: 10000
 
2.9%
3 6568
 
1.9%
Other values (5) 21900
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 710000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 80000
 
11.3%
0 74537
 
10.5%
2 66824
 
9.4%
t 60000
 
8.5%
c 40000
 
5.6%
r 30000
 
4.2%
d 30000
 
4.2%
. 30000
 
4.2%
g 30000
 
4.2%
p 30000
 
4.2%
Other values (22) 238639
33.6%

어노테이션json파일명
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T01:40:10.747586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters190000
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowct_2d_00025895.json
2nd rowct_2d_00025659.json
3rd rowct_2d_00037220.json
4th rowct_2d_00033464.json
5th rowct_2d_00011823.json
ValueCountFrequency (%)
ct_2d_00025895.json 1
 
< 0.1%
ct_2d_00012285.json 1
 
< 0.1%
ct_2d_00027323.json 1
 
< 0.1%
ct_2d_00022920.json 1
 
< 0.1%
ct_2d_00029386.json 1
 
< 0.1%
ct_2d_00024485.json 1
 
< 0.1%
ct_2d_00052977.json 1
 
< 0.1%
ct_2d_00018135.json 1
 
< 0.1%
ct_2d_00038143.json 1
 
< 0.1%
ct_2d_00027950.json 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-03-23T01:40:11.780668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 34537
18.2%
_ 20000
10.5%
2 16824
 
8.9%
c 10000
 
5.3%
t 10000
 
5.3%
n 10000
 
5.3%
o 10000
 
5.3%
s 10000
 
5.3%
j 10000
 
5.3%
. 10000
 
5.3%
Other values (9) 48639
25.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90000
47.4%
Lowercase Letter 70000
36.8%
Connector Punctuation 20000
 
10.5%
Other Punctuation 10000
 
5.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 34537
38.4%
2 16824
18.7%
3 6568
 
7.3%
1 6318
 
7.0%
5 5088
 
5.7%
4 4708
 
5.2%
6 4080
 
4.5%
7 4068
 
4.5%
8 3956
 
4.4%
9 3853
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
c 10000
14.3%
t 10000
14.3%
n 10000
14.3%
o 10000
14.3%
s 10000
14.3%
j 10000
14.3%
d 10000
14.3%
Connector Punctuation
ValueCountFrequency (%)
_ 20000
100.0%
Other Punctuation
ValueCountFrequency (%)
. 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120000
63.2%
Latin 70000
36.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 34537
28.8%
_ 20000
16.7%
2 16824
14.0%
. 10000
 
8.3%
3 6568
 
5.5%
1 6318
 
5.3%
5 5088
 
4.2%
4 4708
 
3.9%
6 4080
 
3.4%
7 4068
 
3.4%
Other values (2) 7809
 
6.5%
Latin
ValueCountFrequency (%)
c 10000
14.3%
t 10000
14.3%
n 10000
14.3%
o 10000
14.3%
s 10000
14.3%
j 10000
14.3%
d 10000
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 34537
18.2%
_ 20000
10.5%
2 16824
 
8.9%
c 10000
 
5.3%
t 10000
 
5.3%
n 10000
 
5.3%
o 10000
 
5.3%
s 10000
 
5.3%
j 10000
 
5.3%
. 10000
 
5.3%
Other values (9) 48639
25.6%

어노테이션json파일경로
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-03-23T01:40:12.664198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length72
Mean length72
Min length72

Characters and Unicode

Total characters720000
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10000 ?
Unique (%)100.0%

Sample

1st rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025895.json
2nd rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025659.json
3rd rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00037220.json
4th rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00033464.json
5th rowhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00011823.json
ValueCountFrequency (%)
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025895.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00012285.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00027323.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00022920.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00029386.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00024485.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00052977.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00018135.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00038143.json 1
 
< 0.1%
http://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00027950.json 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-03-23T01:40:14.057916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 80000
 
11.1%
0 74537
 
10.4%
2 66824
 
9.3%
t 60000
 
8.3%
o 40000
 
5.6%
c 40000
 
5.6%
r 30000
 
4.2%
d 30000
 
4.2%
. 30000
 
4.2%
_ 20000
 
2.8%
Other values (23) 248639
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 370000
51.4%
Decimal Number 200000
27.8%
Other Punctuation 120000
 
16.7%
Connector Punctuation 20000
 
2.8%
Dash Punctuation 10000
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 60000
16.2%
o 40000
10.8%
c 40000
10.8%
r 30000
 
8.1%
d 30000
 
8.1%
g 20000
 
5.4%
a 20000
 
5.4%
p 20000
 
5.4%
n 20000
 
5.4%
j 10000
 
2.7%
Other values (8) 80000
21.6%
Decimal Number
ValueCountFrequency (%)
0 74537
37.3%
2 66824
33.4%
1 16318
 
8.2%
9 13853
 
6.9%
3 6568
 
3.3%
5 5088
 
2.5%
4 4708
 
2.4%
6 4080
 
2.0%
7 4068
 
2.0%
8 3956
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/ 80000
66.7%
. 30000
 
25.0%
: 10000
 
8.3%
Connector Punctuation
ValueCountFrequency (%)
_ 20000
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 370000
51.4%
Common 350000
48.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 60000
16.2%
o 40000
10.8%
c 40000
10.8%
r 30000
 
8.1%
d 30000
 
8.1%
g 20000
 
5.4%
a 20000
 
5.4%
p 20000
 
5.4%
n 20000
 
5.4%
j 10000
 
2.7%
Other values (8) 80000
21.6%
Common
ValueCountFrequency (%)
/ 80000
22.9%
0 74537
21.3%
2 66824
19.1%
. 30000
 
8.6%
_ 20000
 
5.7%
1 16318
 
4.7%
9 13853
 
4.0%
- 10000
 
2.9%
: 10000
 
2.9%
3 6568
 
1.9%
Other values (5) 21900
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 80000
 
11.1%
0 74537
 
10.4%
2 66824
 
9.3%
t 60000
 
8.3%
o 40000
 
5.6%
c 40000
 
5.6%
r 30000
 
4.2%
d 30000
 
4.2%
. 30000
 
4.2%
_ 20000
 
2.8%
Other values (23) 248639
34.5%

Interactions

2024-03-23T01:39:59.894439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T01:40:14.360505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
녹화시작일시녹화종료일시날씨정보CCTV고유번호이미지고유번호
녹화시작일시1.0001.0001.0000.9990.948
녹화종료일시1.0001.0001.0000.9990.948
날씨정보1.0001.0001.0000.7170.857
CCTV고유번호0.9990.9990.7171.0000.899
이미지고유번호0.9480.9480.8570.8991.000
2024-03-23T01:40:14.722847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
CCTV고유번호날씨정보
CCTV고유번호1.0000.643
날씨정보0.6431.000
2024-03-23T01:40:14.964394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이미지고유번호날씨정보CCTV고유번호
이미지고유번호1.0000.6890.616
날씨정보0.6891.0000.643
CCTV고유번호0.6160.6431.000

Missing values

2024-03-23T01:40:00.297031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T01:40:00.893049image/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

녹화시작일시녹화종료일시날씨정보CCTV고유번호이미지고유번호이미지너비이미지높이이미지파일명이미지파일경로어노테이션json파일명어노테이션json파일경로
150742021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062258951280720ct_2d_00025895.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025895.jpgct_2d_00025895.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025895.json
132742021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062256591280720ct_2d_00025659.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025659.jpgct_2d_00025659.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025659.json
272642021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3072372201280720ct_2d_00037220.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00037220.jpgct_2d_00037220.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00037220.json
267092021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3072334641280720ct_2d_00033464.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00033464.jpgct_2d_00033464.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00033464.json
311202021-06-28 18:19:392021-06-28 18:20:092ARO-SDB-1012118231280720ct_2d_00011823.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00011823.jpgct_2d_00011823.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00011823.json
320152021-07-13 18:21:102021-07-13 18:21:401ARO-SDB-3082599221280720ct_2d_00059922.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00059922.jpgct_2d_00059922.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00059922.json
179022021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3072287141280720ct_2d_00028714.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00028714.jpgct_2d_00028714.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00028714.json
131352021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062249211280720ct_2d_00024921.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00024921.jpgct_2d_00024921.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00024921.json
315442021-07-09 18:36:352021-07-09 18:37:051ARO-SDB-3092539961280720ct_2d_00053996.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00053996.jpgct_2d_00053996.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00053996.json
336262021-06-09 18:13:002021-06-09 18:13:301ARO-SDB-1012113151280720ct_2d_00011315.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00011315.jpgct_2d_00011315.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00011315.json
녹화시작일시녹화종료일시날씨정보CCTV고유번호이미지고유번호이미지너비이미지높이이미지파일명이미지파일경로어노테이션json파일명어노테이션json파일경로
13982021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-1012120941280720ct_2d_00012094.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00012094.jpgct_2d_00012094.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00012094.json
44442021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062153011280720ct_2d_00015301.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00015301.jpgct_2d_00015301.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00015301.json
291972021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3072381731280720ct_2d_00038173.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00038173.jpgct_2d_00038173.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00038173.json
304382021-06-16 08:56:102021-06-16 08:56:401ARO-SDB-3082596531280720ct_2d_00059653.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00059653.jpgct_2d_00059653.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00059653.json
25212021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-1012141651280720ct_2d_00014165.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00014165.jpgct_2d_00014165.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00014165.json
155192021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062261731280720ct_2d_00026173.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00026173.jpgct_2d_00026173.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00026173.json
106692021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062203101280720ct_2d_00020310.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00020310.jpgct_2d_00020310.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00020310.json
214902021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3072320851280720ct_2d_00032085.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00032085.jpgct_2d_00032085.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00032085.json
324032021-07-09 18:36:352021-07-09 18:37:051ARO-SDB-3092539261280720ct_2d_00053926.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00053926.jpgct_2d_00053926.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00053926.json
151562021-06-02 12:00:002021-06-02 12:20:001ARO-SDB-3062259021280720ct_2d_00025902.jpghttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025902.jpgct_2d_00025902.jsonhttp://ggzerocity-data.or.kr/opn/02/cctv/2d/20210902/ct_2d_00025902.json