Overview

Dataset statistics

Number of variables22
Number of observations200
Missing cells424
Missing cells (%)9.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.5 KiB
Average record size in memory186.7 B

Variable types

Numeric4
Text4
Categorical12
Unsupported2

Dataset

Description대전광역시 서구 관내에 교통단속 및 재난재해 등의 정보수집을 위해 설치된 CCTV의 정보(소재지주소, 위경도 좌표, 제한속도 등)를 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15124396/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
소재지도로명주소 has 19 (9.5%) missing valuesMissing
소재지지번주소 has 4 (2.0%) missing valuesMissing
단속구간위치구분 has 200 (100.0%) missing valuesMissing
과속단속구간길이 has 200 (100.0%) missing valuesMissing
순번 has unique valuesUnique
단속구간위치구분 is an unsupported type, check if it needs cleaning or further analysisUnsupported
과속단속구간길이 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 08:54:57.789984
Analysis finished2023-12-12 08:54:58.249615
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.5
Minimum1
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:54:58.337096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.95
Q150.75
median100.5
Q3150.25
95-th percentile190.05
Maximum200
Range199
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation57.879185
Coefficient of variation (CV)0.57591228
Kurtosis-1.2
Mean100.5
Median Absolute Deviation (MAD)50
Skewness0
Sum20100
Variance3350
MonotonicityNot monotonic
2023-12-12T17:54:58.608500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
139 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
Other values (190) 190
95.0%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%

무인교통단속카메라관리번호
Text

Distinct101
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T17:54:59.029387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters1000
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st rowG6769
2nd rowG6770
3rd rowG6771
4th rowG6823
5th rowG6824
ValueCountFrequency (%)
g6769 2
 
1.0%
g2894 2
 
1.0%
g1707 2
 
1.0%
g1706 2
 
1.0%
g1705 2
 
1.0%
g1704 2
 
1.0%
g3378 2
 
1.0%
g3128 2
 
1.0%
g3127 2
 
1.0%
g2898 2
 
1.0%
Other values (91) 180
90.0%
2023-12-12T17:54:59.600472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 170
17.0%
6 168
16.8%
3 136
13.6%
7 87
8.7%
2 85
8.5%
1 62
 
6.2%
8 60
 
6.0%
0 60
 
6.0%
9 59
 
5.9%
4 45
 
4.5%
Other values (2) 68
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 800
80.0%
Uppercase Letter 200
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 168
21.0%
3 136
17.0%
7 87
10.9%
2 85
10.6%
1 62
 
7.8%
8 60
 
7.5%
0 60
 
7.5%
9 59
 
7.4%
4 45
 
5.6%
5 38
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
G 170
85.0%
F 30
 
15.0%

Most occurring scripts

ValueCountFrequency (%)
Common 800
80.0%
Latin 200
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 168
21.0%
3 136
17.0%
7 87
10.9%
2 85
10.6%
1 62
 
7.8%
8 60
 
7.5%
0 60
 
7.5%
9 59
 
7.4%
4 45
 
5.6%
5 38
 
4.8%
Latin
ValueCountFrequency (%)
G 170
85.0%
F 30
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
G 170
17.0%
6 168
16.8%
3 136
13.6%
7 87
8.7%
2 85
8.5%
1 62
 
6.2%
8 60
 
6.0%
0 60
 
6.0%
9 59
 
5.9%
4 45
 
4.5%
Other values (2) 68
 
6.8%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
대전광역시
200 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 200
100.0%

Length

2023-12-12T17:54:59.769793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:54:59.914881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 200
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
서구
200 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서구 200
100.0%

Length

2023-12-12T17:55:00.047374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:00.188207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서구 200
100.0%

도로종류
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
일반국도
100 
시도
100 

Length

Max length4
Median length3
Mean length3
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반국도 100
50.0%
시도 100
50.0%

Length

2023-12-12T17:55:00.363426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:00.508790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반국도 100
50.0%
시도 100
50.0%

도로노선번호
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
100 
해당없음
95 
4번
 
3
32번
 
2

Length

Max length4
Median length4
Mean length3.96
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 100
50.0%
해당없음 95
47.5%
4번 3
 
1.5%
32번 2
 
1.0%

Length

2023-12-12T17:55:00.666744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:00.827077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 100
50.0%
해당없음 95
47.5%
4번 3
 
1.5%
32번 2
 
1.0%

도로노선명
Categorical

Distinct42
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
벌곡로
15 
계백로
14 
계룡로
 
12
관저로
 
12
대덕대로
 
12
Other values (37)
135 

Length

Max length8
Median length3
Mean length3.53
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계룡로
2nd row대덕대로
3rd row한밭대로
4th row갈마로
5th row벌곡로

Common Values

ValueCountFrequency (%)
벌곡로 15
 
7.5%
계백로 14
 
7.0%
계룡로 12
 
6.0%
관저로 12
 
6.0%
대덕대로 12
 
6.0%
한밭대로 10
 
5.0%
신갈마로 8
 
4.0%
유등로 8
 
4.0%
둔산로 7
 
3.5%
관저중로 6
 
3.0%
Other values (32) 96
48.0%

Length

2023-12-12T17:55:01.005524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
벌곡로 15
 
7.5%
계백로 14
 
7.0%
계룡로 12
 
6.0%
관저로 12
 
6.0%
대덕대로 12
 
6.0%
한밭대로 10
 
5.0%
신갈마로 8
 
4.0%
유등로 8
 
4.0%
둔산로 7
 
3.5%
관저중로 6
 
3.0%
Other values (32) 96
48.0%

도로노선방향
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
100 
2
57 
1
41 
3
 
2

Length

Max length4
Median length2.5
Mean length2.5
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 100
50.0%
2 57
28.5%
1 41
20.5%
3 2
 
1.0%

Length

2023-12-12T17:55:01.168540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:01.320437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 100
50.0%
2 57
28.5%
1 41
20.5%
3 2
 
1.0%

소재지도로명주소
Text

MISSING 

Distinct92
Distinct (%)50.8%
Missing19
Missing (%)9.5%
Memory size1.7 KiB
2023-12-12T17:55:01.717599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length16.856354
Min length14

Characters and Unicode

Total characters3051
Distinct characters91
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)10.5%

Sample

1st row대전광역시 서구 계룡로 376
2nd row대전광역시 서구 대덕대로 270
3rd row대전광역시 서구 한밭대로 둔산동 2155
4th row대전광역시 서구 갈마로 160 KT인재개발원 앞 삼거리
5th row대전광역시 서구 벌곡로 650 흑석네거리(실버존)
ValueCountFrequency (%)
대전광역시 181
24.4%
서구 181
24.4%
계백로 14
 
1.9%
관저로 14
 
1.9%
계룡로 10
 
1.3%
벌곡로 9
 
1.2%
신갈마로 8
 
1.1%
둔산동 7
 
0.9%
관저중로 6
 
0.8%
월평서로 6
 
0.8%
Other values (134) 306
41.2%
2023-12-12T17:55:02.320046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
561
18.4%
대 196
 
6.4%
서 189
 
6.2%
구 185
 
6.1%
역 185
 
6.1%
시 183
 
6.0%
전 181
 
5.9%
광 181
 
5.9%
로 158
 
5.2%
1 128
 
4.2%
Other values (81) 904
29.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1944
63.7%
Space Separator 561
 
18.4%
Decimal Number 526
 
17.2%
Dash Punctuation 12
 
0.4%
Uppercase Letter 4
 
0.1%
Close Punctuation 2
 
0.1%
Open Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 196
10.1%
서 189
9.7%
구 185
9.5%
역 185
9.5%
시 183
9.4%
전 181
9.3%
광 181
9.3%
로 158
 
8.1%
동 32
 
1.6%
관 26
 
1.3%
Other values (65) 428
22.0%
Decimal Number
ValueCountFrequency (%)
1 128
24.3%
2 80
15.2%
6 49
 
9.3%
3 48
 
9.1%
7 44
 
8.4%
0 43
 
8.2%
9 42
 
8.0%
5 38
 
7.2%
4 27
 
5.1%
8 27
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
T 2
50.0%
K 2
50.0%
Space Separator
ValueCountFrequency (%)
561
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1944
63.7%
Common 1103
36.2%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 196
10.1%
서 189
9.7%
구 185
9.5%
역 185
9.5%
시 183
9.4%
전 181
9.3%
광 181
9.3%
로 158
 
8.1%
동 32
 
1.6%
관 26
 
1.3%
Other values (65) 428
22.0%
Common
ValueCountFrequency (%)
561
50.9%
1 128
 
11.6%
2 80
 
7.3%
6 49
 
4.4%
3 48
 
4.4%
7 44
 
4.0%
0 43
 
3.9%
9 42
 
3.8%
5 38
 
3.4%
4 27
 
2.4%
Other values (4) 43
 
3.9%
Latin
ValueCountFrequency (%)
T 2
50.0%
K 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1944
63.7%
ASCII 1107
36.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
561
50.7%
1 128
 
11.6%
2 80
 
7.2%
6 49
 
4.4%
3 48
 
4.3%
7 44
 
4.0%
0 43
 
3.9%
9 42
 
3.8%
5 38
 
3.4%
4 27
 
2.4%
Other values (6) 47
 
4.2%
Hangul
ValueCountFrequency (%)
대 196
10.1%
서 189
9.7%
구 185
9.5%
역 185
9.5%
시 183
9.4%
전 181
9.3%
광 181
9.3%
로 158
 
8.1%
동 32
 
1.6%
관 26
 
1.3%
Other values (65) 428
22.0%

소재지지번주소
Text

MISSING 

Distinct97
Distinct (%)49.5%
Missing4
Missing (%)2.0%
Memory size1.7 KiB
2023-12-12T17:55:02.725298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length16.954082
Min length13

Characters and Unicode

Total characters3323
Distinct characters56
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)6.1%

Sample

1st row대전광역시 서구 갈마동 308-1
2nd row대전광역시 서구 둔산동 1375
3rd row대전광역시 서구 둔산동 2155
4th row대전광역시 괴정동 130-1
5th row대전광역시 흑석동 945
ValueCountFrequency (%)
대전광역시 196
25.4%
서구 193
25.0%
둔산동 33
 
4.3%
관저동 30
 
3.9%
월평동 24
 
3.1%
갈마동 12
 
1.6%
도마동 10
 
1.3%
탄방동 10
 
1.3%
도안동 8
 
1.0%
가수원동 8
 
1.0%
Other values (108) 247
32.0%
2023-12-12T17:55:03.293434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
575
17.3%
1 200
 
6.0%
대 196
 
5.9%
광 196
 
5.9%
역 196
 
5.9%
시 196
 
5.9%
전 196
 
5.9%
구 194
 
5.8%
서 193
 
5.8%
동 192
 
5.8%
Other values (46) 989
29.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1953
58.8%
Decimal Number 730
 
22.0%
Space Separator 575
 
17.3%
Dash Punctuation 65
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 196
10.0%
광 196
10.0%
역 196
10.0%
시 196
10.0%
전 196
10.0%
구 194
9.9%
서 193
9.9%
동 192
9.8%
둔 37
 
1.9%
산 37
 
1.9%
Other values (34) 320
16.4%
Decimal Number
ValueCountFrequency (%)
1 200
27.4%
2 99
13.6%
3 82
11.2%
4 64
 
8.8%
8 64
 
8.8%
0 52
 
7.1%
9 50
 
6.8%
6 44
 
6.0%
5 40
 
5.5%
7 35
 
4.8%
Space Separator
ValueCountFrequency (%)
575
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1953
58.8%
Common 1370
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 196
10.0%
광 196
10.0%
역 196
10.0%
시 196
10.0%
전 196
10.0%
구 194
9.9%
서 193
9.9%
동 192
9.8%
둔 37
 
1.9%
산 37
 
1.9%
Other values (34) 320
16.4%
Common
ValueCountFrequency (%)
575
42.0%
1 200
 
14.6%
2 99
 
7.2%
3 82
 
6.0%
- 65
 
4.7%
4 64
 
4.7%
8 64
 
4.7%
0 52
 
3.8%
9 50
 
3.6%
6 44
 
3.2%
Other values (2) 75
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1953
58.8%
ASCII 1370
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
575
42.0%
1 200
 
14.6%
2 99
 
7.2%
3 82
 
6.0%
- 65
 
4.7%
4 64
 
4.7%
8 64
 
4.7%
0 52
 
3.8%
9 50
 
3.6%
6 44
 
3.2%
Other values (2) 75
 
5.5%
Hangul
ValueCountFrequency (%)
대 196
10.0%
광 196
10.0%
역 196
10.0%
시 196
10.0%
전 196
10.0%
구 194
9.9%
서 193
9.9%
동 192
9.8%
둔 37
 
1.9%
산 37
 
1.9%
Other values (34) 320
16.4%

위도
Real number (ℝ)

Distinct100
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.327668
Minimum36.239115
Maximum36.368194
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:55:03.506437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.239115
5-th percentile36.271301
Q136.303758
median36.332216
Q336.354259
95-th percentile36.362539
Maximum36.368194
Range0.129079
Interquartile range (IQR)0.05050125

Descriptive statistics

Standard deviation0.030444952
Coefficient of variation (CV)0.00083806515
Kurtosis0.0047661388
Mean36.327668
Median Absolute Deviation (MAD)0.024648
Skewness-0.74079604
Sum7265.5336
Variance0.00092689513
MonotonicityNot monotonic
2023-12-12T17:55:03.695676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.367472 4
 
2.0%
36.358053 2
 
1.0%
36.362309 2
 
1.0%
36.368194 2
 
1.0%
36.351435 2
 
1.0%
36.356072 2
 
1.0%
36.323794 2
 
1.0%
36.305099 2
 
1.0%
36.353243 2
 
1.0%
36.344433 2
 
1.0%
Other values (90) 178
89.0%
ValueCountFrequency (%)
36.239115 1
0.5%
36.239236 2
1.0%
36.250548 2
1.0%
36.254328 2
1.0%
36.254514 2
1.0%
36.271301 2
1.0%
36.275985 2
1.0%
36.293295 2
1.0%
36.295226 2
1.0%
36.295258 2
1.0%
ValueCountFrequency (%)
36.368194 2
1.0%
36.367472 4
2.0%
36.367221 2
1.0%
36.364833 2
1.0%
36.362418 2
1.0%
36.362309 2
1.0%
36.361277 2
1.0%
36.361061 2
1.0%
36.359955 2
1.0%
36.359575 2
1.0%

경도
Real number (ℝ)

Distinct101
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.36641
Minimum127.31818
Maximum127.4019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:55:03.885425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.31818
5-th percentile127.32951
Q1127.3459
median127.36986
Q3127.37981
95-th percentile127.39652
Maximum127.4019
Range0.083725
Interquartile range (IQR)0.033905

Descriptive statistics

Standard deviation0.021230331
Coefficient of variation (CV)0.00016668705
Kurtosis-0.81546046
Mean127.36641
Median Absolute Deviation (MAD)0.0152705
Skewness-0.33899851
Sum25473.283
Variance0.00045072696
MonotonicityNot monotonic
2023-12-12T17:55:04.054835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.369858 2
 
1.0%
127.379654 2
 
1.0%
127.374453 2
 
1.0%
127.373251 2
 
1.0%
127.395335 2
 
1.0%
127.356811 2
 
1.0%
127.370372 2
 
1.0%
127.352966 2
 
1.0%
127.368861 2
 
1.0%
127.379821 2
 
1.0%
Other values (91) 180
90.0%
ValueCountFrequency (%)
127.318176 1
0.5%
127.318298 2
1.0%
127.325789 2
1.0%
127.327237 2
1.0%
127.328161 2
1.0%
127.329512 2
1.0%
127.329555 2
1.0%
127.329581 2
1.0%
127.334888 2
1.0%
127.335102 2
1.0%
ValueCountFrequency (%)
127.401901 2
1.0%
127.401681 2
1.0%
127.401433 2
1.0%
127.400349 2
1.0%
127.396612 2
1.0%
127.396513 2
1.0%
127.395519 1
0.5%
127.395387 2
1.0%
127.395335 2
1.0%
127.395156 2
1.0%

설치장소
Text

Distinct101
Distinct (%)50.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T17:55:04.324204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length34
Mean length24.31
Min length5

Characters and Unicode

Total characters4862
Distinct characters168
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)1.0%

Sample

1st row대전광역시 서구 계룡로 갈마삼거리
2nd row대전광역시 서구 대덕대로 정부청사역네거리(→보라매4)
3rd row대전광역시 서구 한밭대로 한밭대교네거리
4th row대전시 서구 갈마로 160 (괴정동 130-1) KT인재개발원 앞 삼거리
5th row대전시 서구 벌곡로 650 (흑석동 945) 흑석네거리(실버존)
ValueCountFrequency (%)
서구 199
 
18.2%
대전광역시 193
 
17.6%
앞 49
 
4.5%
옆 34
 
3.1%
삼거리 28
 
2.6%
입구 26
 
2.4%
네거리 20
 
1.8%
계백로 14
 
1.3%
관저로 14
 
1.3%
벌곡로 13
 
1.2%
Other values (190) 504
46.1%
2023-12-12T17:55:05.181154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
894
18.4%
구 239
 
4.9%
대 237
 
4.9%
서 215
 
4.4%
역 205
 
4.2%
전 205
 
4.2%
시 201
 
4.1%
광 193
 
4.0%
로 187
 
3.8%
리 161
 
3.3%
Other values (158) 2125
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3694
76.0%
Space Separator 894
 
18.4%
Decimal Number 114
 
2.3%
Close Punctuation 60
 
1.2%
Open Punctuation 60
 
1.2%
Math Symbol 34
 
0.7%
Uppercase Letter 4
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 239
 
6.5%
대 237
 
6.4%
서 215
 
5.8%
역 205
 
5.5%
전 205
 
5.5%
시 201
 
5.4%
광 193
 
5.2%
로 187
 
5.1%
리 161
 
4.4%
거 141
 
3.8%
Other values (141) 1710
46.3%
Decimal Number
ValueCountFrequency (%)
1 20
17.5%
0 18
15.8%
4 18
15.8%
3 16
14.0%
5 10
8.8%
2 8
 
7.0%
9 8
 
7.0%
6 8
 
7.0%
7 6
 
5.3%
8 2
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
T 2
50.0%
Space Separator
ValueCountFrequency (%)
894
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Math Symbol
ValueCountFrequency (%)
→ 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3694
76.0%
Common 1164
 
23.9%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 239
 
6.5%
대 237
 
6.4%
서 215
 
5.8%
역 205
 
5.5%
전 205
 
5.5%
시 201
 
5.4%
광 193
 
5.2%
로 187
 
5.1%
리 161
 
4.4%
거 141
 
3.8%
Other values (141) 1710
46.3%
Common
ValueCountFrequency (%)
894
76.8%
) 60
 
5.2%
( 60
 
5.2%
→ 34
 
2.9%
1 20
 
1.7%
0 18
 
1.5%
4 18
 
1.5%
3 16
 
1.4%
5 10
 
0.9%
2 8
 
0.7%
Other values (5) 26
 
2.2%
Latin
ValueCountFrequency (%)
K 2
50.0%
T 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3694
76.0%
ASCII 1134
 
23.3%
Arrows 34
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
894
78.8%
) 60
 
5.3%
( 60
 
5.3%
1 20
 
1.8%
0 18
 
1.6%
4 18
 
1.6%
3 16
 
1.4%
5 10
 
0.9%
2 8
 
0.7%
9 8
 
0.7%
Other values (6) 22
 
1.9%
Hangul
ValueCountFrequency (%)
구 239
 
6.5%
대 237
 
6.4%
서 215
 
5.8%
역 205
 
5.5%
전 205
 
5.5%
시 201
 
5.4%
광 193
 
5.2%
로 187
 
5.1%
리 161
 
4.4%
거 141
 
3.8%
Other values (141) 1710
46.3%
Arrows
ValueCountFrequency (%)
→ 34
100.0%

단속구분
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
156 
1
43 
99
 
1

Length

Max length2
Median length1
Mean length1.005
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
2 156
78.0%
1 43
 
21.5%
99 1
 
0.5%

Length

2023-12-12T17:55:05.359164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:05.504578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 156
78.0%
1 43
 
21.5%
99 1
 
0.5%

제한속도
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
30
107 
50
71 
60
20 
40
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50
2nd row50
3rd row50
4th row50
5th row60

Common Values

ValueCountFrequency (%)
30 107
53.5%
50 71
35.5%
60 20
 
10.0%
40 2
 
1.0%

Length

2023-12-12T17:55:05.642929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:05.783289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30 107
53.5%
50 71
35.5%
60 20
 
10.0%
40 2
 
1.0%

단속구간위치구분
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

과속단속구간길이
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing200
Missing (%)100.0%
Memory size1.9 KiB

보호구역구분
Categorical

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2
102 
<NA>
94 
1
 
4

Length

Max length4
Median length1
Mean length2.41
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
2 102
51.0%
<NA> 94
47.0%
1 4
 
2.0%

Length

2023-12-12T17:55:05.932545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:06.069011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 102
51.0%
na 94
47.0%
1 4
 
2.0%

설치연도
Real number (ℝ)

Distinct11
Distinct (%)5.5%
Missing1
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean2019.206
Minimum2009
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:55:06.209808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2009
5-th percentile2010
Q12019
median2021
Q32021
95-th percentile2021
Maximum2021
Range12
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2243962
Coefficient of variation (CV)0.0015968634
Kurtosis2.5786665
Mean2019.206
Median Absolute Deviation (MAD)0
Skewness-1.9317217
Sum401822
Variance10.396731
MonotonicityNot monotonic
2023-12-12T17:55:06.400651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2021 122
61.0%
2020 20
 
10.0%
2019 12
 
6.0%
2018 10
 
5.0%
2010 10
 
5.0%
2014 9
 
4.5%
2017 6
 
3.0%
2013 4
 
2.0%
2016 2
 
1.0%
2009 2
 
1.0%
ValueCountFrequency (%)
2009 2
 
1.0%
2010 10
5.0%
2011 2
 
1.0%
2013 4
 
2.0%
2014 9
4.5%
2016 2
 
1.0%
2017 6
 
3.0%
2018 10
5.0%
2019 12
6.0%
2020 20
10.0%
ValueCountFrequency (%)
2021 122
61.0%
2020 20
 
10.0%
2019 12
 
6.0%
2018 10
 
5.0%
2017 6
 
3.0%
2016 2
 
1.0%
2014 9
 
4.5%
2013 4
 
2.0%
2011 2
 
1.0%
2010 10
 
5.0%

관리기관전화번호
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
042-609-2852
100 
042-120
100 

Length

Max length12
Median length9.5
Mean length9.5
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row042-609-2852
2nd row042-609-2852
3rd row042-609-2852
4th row042-609-2852
5th row042-609-2852

Common Values

ValueCountFrequency (%)
042-609-2852 100
50.0%
042-120 100
50.0%

Length

2023-12-12T17:55:06.564543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:06.698415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
042-609-2852 100
50.0%
042-120 100
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2022-12-15
200 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-15
2nd row2022-12-15
3rd row2022-12-15
4th row2022-12-15
5th row2022-12-15

Common Values

ValueCountFrequency (%)
2022-12-15 200
100.0%

Length

2023-12-12T17:55:06.856076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:07.001631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-15 200
100.0%

제공기관명
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
경찰청 대전광역시경찰청
100 
<NA>
100 

Length

Max length12
Median length8
Mean length8
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경찰청 대전광역시경찰청
2nd row경찰청 대전광역시경찰청
3rd row경찰청 대전광역시경찰청
4th row경찰청 대전광역시경찰청
5th row경찰청 대전광역시경찰청

Common Values

ValueCountFrequency (%)
경찰청 대전광역시경찰청 100
50.0%
<NA> 100
50.0%

Length

2023-12-12T17:55:07.136883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:55:07.261154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경찰청 100
33.3%
대전광역시경찰청 100
33.3%
na 100
33.3%

Sample

순번무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지도로명주소소재지지번주소위도경도설치장소단속구분제한속도단속구간위치구분과속단속구간길이보호구역구분설치연도관리기관전화번호데이터기준일자제공기관명
01G6769대전광역시서구일반국도해당없음계룡로<NA>대전광역시 서구 계룡로 376대전광역시 서구 갈마동 308-136.352041127.369858대전광역시 서구 계룡로 갈마삼거리250<NA><NA><NA>2021042-609-28522022-12-15경찰청 대전광역시경찰청
12G6770대전광역시서구일반국도해당없음대덕대로<NA>대전광역시 서구 대덕대로 270대전광역시 서구 둔산동 137536.357528127.379751대전광역시 서구 대덕대로 정부청사역네거리(→보라매4)250<NA><NA><NA>2021042-609-28522022-12-15경찰청 대전광역시경찰청
23G6771대전광역시서구일반국도해당없음한밭대로<NA>대전광역시 서구 한밭대로 둔산동 2155대전광역시 서구 둔산동 215536.357381127.401433대전광역시 서구 한밭대로 한밭대교네거리250<NA><NA><NA>2021042-609-28522022-12-15경찰청 대전광역시경찰청
34G6823대전광역시서구일반국도해당없음갈마로<NA>대전광역시 서구 갈마로 160 KT인재개발원 앞 삼거리대전광역시 괴정동 130-136.339406127.374513대전시 서구 갈마로 160 (괴정동 130-1) KT인재개발원 앞 삼거리250<NA><NA><NA>2021042-609-28522022-12-15경찰청 대전광역시경찰청
45G6824대전광역시서구일반국도해당없음벌곡로<NA>대전광역시 서구 벌곡로 650 흑석네거리(실버존)대전광역시 흑석동 94536.254328127.340691대전시 서구 벌곡로 650 (흑석동 945) 흑석네거리(실버존)260<NA><NA>12021042-609-28522022-12-15경찰청 대전광역시경찰청
56G6825대전광역시서구일반국도해당없음둔산로<NA>대전광역시 서구 둔산로 77 시교육청네거리대전광역시 둔산동 126836.351401127.382673대전시 서구 둔산로 77 (둔산동 1268) 시교육청네거리250<NA><NA><NA>2021042-609-28522022-12-15경찰청 대전광역시경찰청
67G6379대전광역시서구일반국도해당없음둔산북로<NA>대전광역시 서구 둔산북로 232-11대전광역시 서구 둔산동 180636.355687127.400349대전광역시 서구 둔산북로 삼천초 입구 문정중옆 삼거리230<NA><NA>22021042-609-28522022-12-15경찰청 대전광역시경찰청
78G6380대전광역시서구일반국도해당없음탄방로<NA>대전광역시 서구 탄방로 15대전광역시 서구 탄방동 81436.345621127.390269대전광역시 서구 탄방로 탄방초교 정문 (→한가람4)230<NA><NA>22021042-609-28522022-12-15경찰청 대전광역시경찰청
89G6381대전광역시서구일반국도해당없음둔산로<NA>대전광역시 서구 둔산로 206대전광역시 서구 둔산동 181436.351358127.396513대전광역시 서구 둔산로 문정초 맞은편 국화(아) 604동 뒤230<NA><NA>22021042-609-28522022-12-15경찰청 대전광역시경찰청
910G6382대전광역시서구일반국도해당없음유등로<NA>대전광역시 서구 유등로 879대전광역시 서구 둔산동 907-136.362418127.393327대전광역시 서구 유등로 샘머리초 정문 맞은편230<NA><NA>22021042-609-28522022-12-15경찰청 대전광역시경찰청
순번무인교통단속카메라관리번호시도명시군구명도로종류도로노선번호도로노선명도로노선방향소재지도로명주소소재지지번주소위도경도설치장소단속구분제한속도단속구간위치구분과속단속구간길이보호구역구분설치연도관리기관전화번호데이터기준일자제공기관명
190191G6379대전광역시서구시도<NA>둔산북로1대전광역시 서구 둔산북로 232-11대전광역시 서구 둔산동 180636.355687127.400349대전광역시 서구 둔산북로 삼천초 입구 문정중옆 삼거리230<NA><NA>22021042-1202022-12-15<NA>
191192G6380대전광역시서구시도<NA>탄방로1대전광역시 서구 탄방로 15대전광역시 서구 탄방동 81436.345621127.390269대전광역시 서구 탄방로 탄방초교 정문 (→한가람4)230<NA><NA>22021042-1202022-12-15<NA>
192193G6381대전광역시서구시도<NA>둔산로1대전광역시 서구 둔산로 206대전광역시 서구 둔산동 181436.351358127.396513대전광역시 서구 둔산로 문정초 맞은편 국화(아) 604동 뒤230<NA><NA>22021042-1202022-12-15<NA>
193194G6382대전광역시서구시도<NA>유등로2대전광역시 서구 유등로 879대전광역시 서구 둔산동 907-136.362418127.393327대전광역시 서구 유등로 샘머리초 정문 맞은편230<NA><NA>22021042-1202022-12-15<NA>
194195G6769대전광역시서구시도<NA>계룡로2대전광역시 서구 계룡로 376대전광역시 서구 갈마동 308-136.352041127.369858대전광역시 서구 계룡로 갈마삼거리250<NA><NA><NA>2021042-1202022-12-15<NA>
195196G6770대전광역시서구시도<NA>대덕대로2대전광역시 서구 대덕대로 270대전광역시 서구 둔산동 137536.357528127.379751대전광역시 서구 대덕대로 정부청사역네거리(→보라매4)250<NA><NA><NA>2021042-1202022-12-15<NA>
196197G6771대전광역시서구시도<NA>한밭대로2<NA>대전광역시 서구 둔산동 215536.357381127.401433대전광역시 서구 한밭대로 한밭대교네거리250<NA><NA><NA>2021042-1202022-12-15<NA>
197198G6823대전광역시서구시도<NA>갈마로2대전광역시 서구 갈마로 160 KT인재개발원 앞 삼거리대전광역시 서구 괴정동 130-136.339406127.374513대전시 서구 갈마로 160 (괴정동 130-1) KT인재개발원 앞 삼거리250<NA><NA><NA>2021042-1202022-12-15<NA>
198199G6824대전광역시서구시도<NA>벌곡로2대전광역시 서구 벌곡로 650 흑석네거리(실버존)대전광역시 서구 흑석동 94536.254328127.340691대전시 서구 벌곡로 650 (흑석동 945) 흑석네거리(실버존)260<NA><NA>12021042-1202022-12-15<NA>
199200G6825대전광역시서구시도<NA>둔산로1대전광역시 서구 둔산로 77 시교육청네거리대전광역시 서구 둔산동 126836.351401127.382673대전시 서구 둔산로 77 (둔산동 1268) 시교육청네거리250<NA><NA><NA>2021042-1202022-12-15<NA>