Overview

Dataset statistics

Number of variables6
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.9 KiB
Average record size in memory50.3 B

Variable types

Text3
Numeric1
Categorical2

Dataset

Description파일 다운로드
Author중랑구
URLhttps://data.seoul.go.kr/dataList/OA-20478/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
현장구분 has constant value ""Constant
단속지점명 has unique valuesUnique

Reproduction

Analysis started2024-04-29 20:33:19.899110
Analysis finished2024-04-29 20:33:21.766661
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

고정형CCTV지번주소
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-30T05:33:21.901980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length15.45
Min length13

Characters and Unicode

Total characters1545
Distinct characters55
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

Unique96 ?
Unique (%)96.0%

Sample

1st row서울특별시중랑구용마산로115길92
2nd row서울특별시중랑구용마산로409
3rd row서울특별시중랑구동일로557
4th row서울특별시중랑구동일로157길60
5th row서울특별시중랑구공릉로2길60
ValueCountFrequency (%)
서울특별시중랑구상봉동 3
 
2.9%
서울특별시중랑구망우로322 2
 
1.9%
서울특별시중랑구숙선옹주로6-9 2
 
1.9%
서울특별시중랑구신내동255-3 1
 
1.0%
282-6 1
 
1.0%
서울특별시중랑구봉화산로188 1
 
1.0%
서울특별시중랑구신내역로1길164 1
 
1.0%
서울특별시중랑구숙선옹주로109 1
 
1.0%
서울특별시중랑구양원역로20 1
 
1.0%
서울특별시중랑구용마산로285 1
 
1.0%
Other values (90) 90
86.5%
2024-04-30T05:33:22.229702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
중 107
 
6.9%
랑 106
 
6.9%
서 100
 
6.5%
특 100
 
6.5%
별 100
 
6.5%
시 100
 
6.5%
구 100
 
6.5%
울 100
 
6.5%
로 91
 
5.9%
1 59
 
3.8%
Other values (45) 582
37.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1189
77.0%
Decimal Number 340
 
22.0%
Dash Punctuation 12
 
0.8%
Space Separator 4
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 107
9.0%
랑 106
8.9%
서 100
8.4%
특 100
8.4%
별 100
8.4%
시 100
8.4%
구 100
8.4%
울 100
8.4%
로 91
 
7.7%
길 39
 
3.3%
Other values (33) 246
20.7%
Decimal Number
ValueCountFrequency (%)
1 59
17.4%
2 57
16.8%
4 39
11.5%
3 33
9.7%
8 31
9.1%
0 30
8.8%
5 30
8.8%
6 25
7.4%
9 24
7.1%
7 12
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1189
77.0%
Common 356
 
23.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 107
9.0%
랑 106
8.9%
서 100
8.4%
특 100
8.4%
별 100
8.4%
시 100
8.4%
구 100
8.4%
울 100
8.4%
로 91
 
7.7%
길 39
 
3.3%
Other values (33) 246
20.7%
Common
ValueCountFrequency (%)
1 59
16.6%
2 57
16.0%
4 39
11.0%
3 33
9.3%
8 31
8.7%
0 30
8.4%
5 30
8.4%
6 25
7.0%
9 24
6.7%
7 12
 
3.4%
Other values (2) 16
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1189
77.0%
ASCII 356
 
23.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
중 107
9.0%
랑 106
8.9%
서 100
8.4%
특 100
8.4%
별 100
8.4%
시 100
8.4%
구 100
8.4%
울 100
8.4%
로 91
 
7.7%
길 39
 
3.3%
Other values (33) 246
20.7%
ASCII
ValueCountFrequency (%)
1 59
16.6%
2 57
16.0%
4 39
11.0%
3 33
9.3%
8 31
8.7%
0 30
8.4%
5 30
8.4%
6 25
7.0%
9 24
6.7%
7 12
 
3.4%
Other values (2) 16
 
4.5%

위도
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-30T05:33:22.450228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.74
Min length8

Characters and Unicode

Total characters1074
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique98 ?
Unique (%)98.0%

Sample

1st row37.59817051
2nd row37.58787
3rd row37.58010022
4th row37.609507
5th row37.61209926
ValueCountFrequency (%)
37.5960455 2
 
2.0%
37.61655503 1
 
1.0%
37.5831545 1
 
1.0%
37.60656604 1
 
1.0%
37.61710468 1
 
1.0%
37.61793823 1
 
1.0%
37.60208061 1
 
1.0%
37.57821715 1
 
1.0%
37.59065601 1
 
1.0%
37.60281434 1
 
1.0%
Other values (89) 89
89.0%
2024-04-30T05:33:22.759327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 169
15.7%
3 151
14.1%
5 137
12.8%
. 100
9.3%
6 93
8.7%
1 79
7.4%
9 78
7.3%
8 73
6.8%
0 66
 
6.1%
2 65
 
6.1%
Other values (2) 63
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 973
90.6%
Other Punctuation 101
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 169
17.4%
3 151
15.5%
5 137
14.1%
6 93
9.6%
1 79
8.1%
9 78
8.0%
8 73
7.5%
0 66
 
6.8%
2 65
 
6.7%
4 62
 
6.4%
Other Punctuation
ValueCountFrequency (%)
. 100
99.0%
? 1
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1074
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7 169
15.7%
3 151
14.1%
5 137
12.8%
. 100
9.3%
6 93
8.7%
1 79
7.4%
9 78
7.3%
8 73
6.8%
0 66
 
6.1%
2 65
 
6.1%
Other values (2) 63
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1074
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 169
15.7%
3 151
14.1%
5 137
12.8%
. 100
9.3%
6 93
8.7%
1 79
7.4%
9 78
7.3%
8 73
6.8%
0 66
 
6.1%
2 65
 
6.1%
Other values (2) 63
 
5.9%

경도
Real number (ℝ)

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.08845
Minimum127.0734
Maximum127.1089
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-30T05:33:22.888811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0734
5-th percentile127.07547
Q1127.08222
median127.08767
Q3127.09389
95-th percentile127.10397
Maximum127.1089
Range0.0354926
Interquartile range (IQR)0.011671225

Descriptive statistics

Standard deviation0.0087574776
Coefficient of variation (CV)6.8908523 × 10-5
Kurtosis-0.58989176
Mean127.08845
Median Absolute Deviation (MAD)0.00621585
Skewness0.29384606
Sum12708.845
Variance7.6693414 × 10-5
MonotonicityNot monotonic
2024-04-30T05:33:23.008329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0876185 2
 
2.0%
127.0952777 1
 
1.0%
127.0837968 1
 
1.0%
127.0938972 1
 
1.0%
127.1088974 1
 
1.0%
127.0869655 1
 
1.0%
127.1083644 1
 
1.0%
127.0907049 1
 
1.0%
127.0973022 1
 
1.0%
127.0869883 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
127.0734048 1
1.0%
127.0736484 1
1.0%
127.0737844 1
1.0%
127.0744882 1
1.0%
127.074493 1
1.0%
127.0755182 1
1.0%
127.0765064 1
1.0%
127.0766907 1
1.0%
127.0769969 1
1.0%
127.0770524 1
1.0%
ValueCountFrequency (%)
127.1088974 1
1.0%
127.1083644 1
1.0%
127.1066531 1
1.0%
127.1059924 1
1.0%
127.1043234 1
1.0%
127.1039536 1
1.0%
127.1027683 1
1.0%
127.1018718 1
1.0%
127.1009167 1
1.0%
127.1008128 1
1.0%

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
중랑구
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중랑구 100
100.0%

Length

2024-04-30T05:33:23.137841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:33:23.225128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중랑구 100
100.0%

단속지점명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-30T05:33:23.356789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length14.63
Min length4

Characters and Unicode

Total characters1463
Distinct characters239
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row망우로60길(구맛솜씨길) 봉구비어(한국SGI사거리)
2nd row구 서일대입구(LG대리점)
3rd row동일로(구 신우아파트)
4th row묵현초등학교 (기림빌딩)
5th row신안아파트3차(은혜성)
ValueCountFrequency (%)
앞 26
 
10.7%
맞은편 7
 
2.9%
사거리 6
 
2.5%
삼거리 5
 
2.1%
정문 4
 
1.6%
인도 3
 
1.2%
인근 3
 
1.2%
도로변 3
 
1.2%
후문 3
 
1.2%
사이 2
 
0.8%
Other values (169) 181
74.5%
2024-04-30T05:33:23.643995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
133
 
9.1%
( 57
 
3.9%
) 57
 
3.9%
리 35
 
2.4%
앞 34
 
2.3%
초 30
 
2.1%
동 27
 
1.8%
교 26
 
1.8%
구 24
 
1.6%
봉 24
 
1.6%
Other values (229) 1016
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1139
77.9%
Space Separator 133
 
9.1%
Open Punctuation 57
 
3.9%
Close Punctuation 57
 
3.9%
Decimal Number 40
 
2.7%
Uppercase Letter 15
 
1.0%
Control 11
 
0.8%
Other Punctuation 11
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 35
 
3.1%
앞 34
 
3.0%
초 30
 
2.6%
동 27
 
2.4%
교 26
 
2.3%
구 24
 
2.1%
봉 24
 
2.1%
트 23
 
2.0%
거 23
 
2.0%
상 22
 
1.9%
Other values (208) 871
76.5%
Decimal Number
ValueCountFrequency (%)
1 10
25.0%
2 8
20.0%
0 6
15.0%
3 6
15.0%
5 5
12.5%
4 3
 
7.5%
6 1
 
2.5%
7 1
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
G 4
26.7%
S 3
20.0%
C 3
20.0%
U 3
20.0%
L 1
 
6.7%
I 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 8
72.7%
@ 2
 
18.2%
/ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
133
100.0%
Open Punctuation
ValueCountFrequency (%)
( 57
100.0%
Close Punctuation
ValueCountFrequency (%)
) 57
100.0%
Control
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1138
77.8%
Common 309
 
21.1%
Latin 15
 
1.0%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 35
 
3.1%
앞 34
 
3.0%
초 30
 
2.6%
동 27
 
2.4%
교 26
 
2.3%
구 24
 
2.1%
봉 24
 
2.1%
트 23
 
2.0%
거 23
 
2.0%
상 22
 
1.9%
Other values (207) 870
76.4%
Common
ValueCountFrequency (%)
133
43.0%
( 57
18.4%
) 57
18.4%
11
 
3.6%
1 10
 
3.2%
2 8
 
2.6%
, 8
 
2.6%
0 6
 
1.9%
3 6
 
1.9%
5 5
 
1.6%
Other values (5) 8
 
2.6%
Latin
ValueCountFrequency (%)
G 4
26.7%
S 3
20.0%
C 3
20.0%
U 3
20.0%
L 1
 
6.7%
I 1
 
6.7%
Han
ValueCountFrequency (%)
前 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1138
77.8%
ASCII 324
 
22.1%
CJK 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
133
41.0%
( 57
17.6%
) 57
17.6%
11
 
3.4%
1 10
 
3.1%
2 8
 
2.5%
, 8
 
2.5%
0 6
 
1.9%
3 6
 
1.9%
5 5
 
1.5%
Other values (11) 23
 
7.1%
Hangul
ValueCountFrequency (%)
리 35
 
3.1%
앞 34
 
3.0%
초 30
 
2.6%
동 27
 
2.4%
교 26
 
2.3%
구 24
 
2.1%
봉 24
 
2.1%
트 23
 
2.0%
거 23
 
2.0%
상 22
 
1.9%
Other values (207) 870
76.4%
CJK
ValueCountFrequency (%)
前 1
100.0%

현장구분
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
불법주정차구역
100 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
불법주정차구역 100
100.0%

Length

2024-04-30T05:33:23.754302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:33:23.838932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
불법주정차구역 100
100.0%

Interactions

2024-04-30T05:33:21.443470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T05:33:23.885754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고정형CCTV지번주소위도경도단속지점명
고정형CCTV지번주소1.0001.0001.0001.000
위도1.0001.0001.0001.000
경도1.0001.0001.0001.000
단속지점명1.0001.0001.0001.000

Missing values

2024-04-30T05:33:21.614616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T05:33:21.722055image/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

고정형CCTV지번주소위도경도자치구단속지점명현장구분
0서울특별시중랑구용마산로115길9237.59817051127.095278중랑구망우로60길(구맛솜씨길) 봉구비어(한국SGI사거리)불법주정차구역
1서울특별시중랑구용마산로40937.58787127.096188중랑구구 서일대입구(LG대리점)불법주정차구역
2서울특별시중랑구동일로55737.58010022127.079474중랑구동일로(구 신우아파트)불법주정차구역
3서울특별시중랑구동일로157길6037.609507127.073648중랑구묵현초등학교 (기림빌딩)불법주정차구역
4서울특별시중랑구공릉로2길6037.61209926127.081457중랑구신안아파트3차(은혜성)불법주정차구역
5서울특별시중랑구신내로8237.60685835127.095429중랑구중랑구청사거리(1001안경)불법주정차구역
6서울특별시중랑구동일로79537.60151758127.079252중랑구중화역 파리바게트(중화2동)불법주정차구역
7서울특별시중랑구면목로48037.59473057127.086142중랑구상봉역3번출구 파리바게트 (상봉2동)불법주정차구역
8서울특별시중랑구겸재로18137.58851091127.08773중랑구면목역 파리바게트(면목동)불법주정차구역
9서울특별시중랑구상봉로7337.59244882127.093234중랑구상봉로(동방빌딩)불법주정차구역
고정형CCTV지번주소위도경도자치구단속지점명현장구분
90서울특별시중랑구망우로32237.5960455127.087619중랑구상봉역유보라퍼스트리브오피스텔 좌측불법주정차구역
91서울특별시중랑구망우로32237.5960455127.087619중랑구상봉역유보라퍼스트리브오피스텔 남측불법주정차구역
92서울특별시중랑구면목로23길2337.5733752127.082935중랑구중곡초 후문불법주정차구역
93서울특별시중랑구용마산로100길2037.5909724127.100635중랑구면일초 정문불법주정차구역
94서울특별시중랑구겸재로28길42?37.5855521127.082987중랑구마젤란아파트 맞은편불법주정차구역
95서울특별시중랑구용마산로139가길4637.6166381127.100917중랑구동양주류 앞불법주정차구역
96서울특별시중랑구용마산로118길6037.600961127.103954중랑구정암유치원 옆불법주정차구역
97서울특별시중랑구상봉동 282-637.6012672127.089357중랑구상봉어린이집, 상봉중학교 옆불법주정차구역
98서울특별시중랑구신내동255-337.6195522127.106653중랑구신내동 골드프라자 맞은편불법주정차구역
99서울특별시중랑구동일로123길12537.5999191127.073784중랑구세화어린이집 맞은편불법주정차구역