Overview

Dataset statistics

Number of variables6
Number of observations2899
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory144.5 KiB
Average record size in memory51.0 B

Variable types

Categorical2
Text1
Numeric2
DateTime1

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author영등포구
URLhttps://data.seoul.go.kr/dataList/OA-20942/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
CCTV 수량 has constant value ""Constant
수정 일시 has constant value ""Constant
안심 주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 18:32:09.567932
Analysis finished2024-03-13 18:32:10.302709
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.8 KiB
영등포구
2899 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영등포구 2899
100.0%

Length

2024-03-14T03:32:10.348893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T03:32:10.416015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영등포구 2899
100.0%

안심 주소
Text

UNIQUE 

Distinct2899
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size22.8 KiB
2024-03-14T03:32:10.639832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length47
Mean length25.631252
Min length7

Characters and Unicode

Total characters74305
Distinct characters318
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2899 ?
Unique (%)100.0%

Sample

1st row경찰-01 도영로 18,근처 횡단보도앞 인도
2nd row경찰-02 가마산로61길 20-8
3rd row경찰-03 신길로56길 7
4th row경찰-04 도신로54길 12-13
5th row경찰-05 영등포로5길 31
ValueCountFrequency (%)
도림로 79
 
0.8%
신길동 55
 
0.6%
앞 52
 
0.5%
2 50
 
0.5%
사거리앞 48
 
0.5%
48
 
0.5%
15 48
 
0.5%
6 47
 
0.5%
디지털로 45
 
0.5%
5 45
 
0.5%
Other values (4566) 9155
94.7%
2024-03-14T03:32:11.015119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 6842
 
9.2%
6807
 
9.2%
1 5131
 
6.9%
2 3474
 
4.7%
길 3160
 
4.3%
로 2852
 
3.8%
3 2735
 
3.7%
방 2271
 
3.1%
( 2142
 
2.9%
) 2135
 
2.9%
Other values (308) 36756
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33563
45.2%
Decimal Number 21362
28.7%
Dash Punctuation 6842
 
9.2%
Space Separator 6807
 
9.2%
Open Punctuation 2142
 
2.9%
Close Punctuation 2135
 
2.9%
Other Punctuation 1013
 
1.4%
Uppercase Letter 387
 
0.5%
Math Symbol 40
 
0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
길 3160
 
9.4%
로 2852
 
8.5%
방 2271
 
6.8%
범 2073
 
6.2%
신 1554
 
4.6%
림 1342
 
4.0%
대 1202
 
3.6%
영 954
 
2.8%
도 878
 
2.6%
앞 807
 
2.4%
Other values (271) 16470
49.1%
Uppercase Letter
ValueCountFrequency (%)
A 107
27.6%
P 102
26.4%
T 99
25.6%
U 14
 
3.6%
G 12
 
3.1%
K 11
 
2.8%
B 10
 
2.6%
S 9
 
2.3%
L 9
 
2.3%
C 6
 
1.6%
Other values (4) 8
 
2.1%
Decimal Number
ValueCountFrequency (%)
1 5131
24.0%
2 3474
16.3%
3 2735
12.8%
0 2084
9.8%
4 1899
 
8.9%
5 1586
 
7.4%
6 1438
 
6.7%
7 1209
 
5.7%
8 1004
 
4.7%
9 802
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
c 4
28.6%
n 3
21.4%
k 3
21.4%
v 2
14.3%
t 2
14.3%
Other Punctuation
ValueCountFrequency (%)
, 879
86.8%
# 86
 
8.5%
/ 48
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 6842
100.0%
Space Separator
ValueCountFrequency (%)
6807
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2142
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2135
100.0%
Math Symbol
ValueCountFrequency (%)
~ 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40341
54.3%
Hangul 33563
45.2%
Latin 401
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
길 3160
 
9.4%
로 2852
 
8.5%
방 2271
 
6.8%
범 2073
 
6.2%
신 1554
 
4.6%
림 1342
 
4.0%
대 1202
 
3.6%
영 954
 
2.8%
도 878
 
2.6%
앞 807
 
2.4%
Other values (271) 16470
49.1%
Latin
ValueCountFrequency (%)
A 107
26.7%
P 102
25.4%
T 99
24.7%
U 14
 
3.5%
G 12
 
3.0%
K 11
 
2.7%
B 10
 
2.5%
S 9
 
2.2%
L 9
 
2.2%
C 6
 
1.5%
Other values (9) 22
 
5.5%
Common
ValueCountFrequency (%)
- 6842
17.0%
6807
16.9%
1 5131
12.7%
2 3474
8.6%
3 2735
 
6.8%
( 2142
 
5.3%
) 2135
 
5.3%
0 2084
 
5.2%
4 1899
 
4.7%
5 1586
 
3.9%
Other values (8) 5506
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40742
54.8%
Hangul 33563
45.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 6842
16.8%
6807
16.7%
1 5131
12.6%
2 3474
8.5%
3 2735
 
6.7%
( 2142
 
5.3%
) 2135
 
5.2%
0 2084
 
5.1%
4 1899
 
4.7%
5 1586
 
3.9%
Other values (27) 5907
14.5%
Hangul
ValueCountFrequency (%)
길 3160
 
9.4%
로 2852
 
8.5%
방 2271
 
6.8%
범 2073
 
6.2%
신 1554
 
4.6%
림 1342
 
4.0%
대 1202
 
3.6%
영 954
 
2.8%
도 878
 
2.6%
앞 807
 
2.4%
Other values (271) 16470
49.1%

위도
Real number (ℝ)

Distinct545
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.508664
Minimum37.4826
Maximum37.5419
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.6 KiB
2024-03-14T03:32:11.134846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.4826
5-th percentile37.4875
Q137.4984
median37.5085
Q337.5182
95-th percentile37.53171
Maximum37.5419
Range0.0593
Interquartile range (IQR)0.0198

Descriptive statistics

Standard deviation0.013283069
Coefficient of variation (CV)0.00035413335
Kurtosis-0.57766253
Mean37.508664
Median Absolute Deviation (MAD)0.0098
Skewness0.17404727
Sum108737.62
Variance0.00017643992
MonotonicityNot monotonic
2024-03-14T03:32:11.258419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5079 18
 
0.6%
37.5064 16
 
0.6%
37.505 15
 
0.5%
37.5114 15
 
0.5%
37.5058 15
 
0.5%
37.5086 15
 
0.5%
37.5092 15
 
0.5%
37.511 15
 
0.5%
37.508 14
 
0.5%
37.5121 14
 
0.5%
Other values (535) 2747
94.8%
ValueCountFrequency (%)
37.4826 2
0.1%
37.4827 3
0.1%
37.4828 1
 
< 0.1%
37.4831 1
 
< 0.1%
37.4832 1
 
< 0.1%
37.4835 1
 
< 0.1%
37.4838 1
 
< 0.1%
37.4839 1
 
< 0.1%
37.484 1
 
< 0.1%
37.4842 1
 
< 0.1%
ValueCountFrequency (%)
37.5419 1
 
< 0.1%
37.5418 2
0.1%
37.5413 2
0.1%
37.5412 1
 
< 0.1%
37.5411 1
 
< 0.1%
37.541 2
0.1%
37.5409 3
0.1%
37.5408 1
 
< 0.1%
37.5407 2
0.1%
37.5406 1
 
< 0.1%

경도
Real number (ℝ)

Distinct459
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.90384
Minimum126.881
Maximum126.9389
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size25.6 KiB
2024-03-14T03:32:11.614717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.881
5-th percentile126.8881
Q1126.8972
median126.9034
Q3126.9091
95-th percentile126.9214
Maximum126.9389
Range0.0579
Interquartile range (IQR)0.0119

Descriptive statistics

Standard deviation0.0099717414
Coefficient of variation (CV)7.8577148 × 10-5
Kurtosis0.36432846
Mean126.90384
Median Absolute Deviation (MAD)0.006
Skewness0.44336312
Sum367894.22
Variance9.9435627 × 10-5
MonotonicityNot monotonic
2024-03-14T03:32:11.721381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9058 23
 
0.8%
126.8988 22
 
0.8%
126.9036 22
 
0.8%
126.9056 20
 
0.7%
126.9014 20
 
0.7%
126.8967 20
 
0.7%
126.903 19
 
0.7%
126.9038 19
 
0.7%
126.9052 19
 
0.7%
126.9086 19
 
0.7%
Other values (449) 2696
93.0%
ValueCountFrequency (%)
126.881 2
0.1%
126.8811 4
0.1%
126.8813 2
0.1%
126.8817 1
 
< 0.1%
126.8818 1
 
< 0.1%
126.882 1
 
< 0.1%
126.8823 1
 
< 0.1%
126.8824 1
 
< 0.1%
126.8825 3
0.1%
126.8828 4
0.1%
ValueCountFrequency (%)
126.9389 1
< 0.1%
126.9387 1
< 0.1%
126.9386 1
< 0.1%
126.9378 2
0.1%
126.9376 1
< 0.1%
126.9373 1
< 0.1%
126.9372 1
< 0.1%
126.9371 1
< 0.1%
126.937 1
< 0.1%
126.9366 1
< 0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.8 KiB
1
2899 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 2899
100.0%

Length

2024-03-14T03:32:11.823875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T03:32:11.890733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2899
100.0%

수정 일시
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.8 KiB
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-03-14T03:32:11.946446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T03:32:12.013214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-14T03:32:09.968748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T03:32:09.814850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T03:32:10.045081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T03:32:09.894118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T03:32:12.062900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.668
경도0.6681.000
2024-03-14T03:32:12.129276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.152
경도-0.1521.000

Missing values

2024-03-14T03:32:10.172330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T03:32:10.266581image/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

자치구안심 주소위도경도CCTV 수량수정 일시
0영등포구경찰-01 도영로 18,근처 횡단보도앞 인도37.5053126.894512022-12-01
1영등포구경찰-02 가마산로61길 20-837.5042126.90412022-12-01
2영등포구경찰-03 신길로56길 737.5096126.910312022-12-01
3영등포구경찰-04 도신로54길 12-1337.5072126.913912022-12-01
4영등포구경찰-05 영등포로5길 3137.5218126.883912022-12-01
5영등포구경찰-06 시흥대로 589-8,LG신대림자이APT 202동 주차장출입구앞 부근37.4828126.901412022-12-01
6영등포구경찰-07 디지털로69나길 10-137.4908126.902112022-12-01
7영등포구경찰-08 도영로 2-5,대림코오롱APT 104동 부근 APT출입구앞37.5042126.893412022-12-01
8영등포구경찰-09 영중로18길 12,영상빌딩앞37.5183126.905512022-12-01
9영등포구당산1-공원-01 당산로27길 12, 당산근린공원#137.5229126.894412022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
2889영등포구영등포본-주정차-06(4) 영등포로64길 15 청소년문화의집앞37.5108126.91612022-12-01
2890영등포구영등포본-주정차-07 신길로24037.5104126.910112022-12-01
2891영등포구영등포본-주정차-07(1) 신길로24037.5105126.910112022-12-01
2892영등포구영등포본-주정차-07(2) 신길로24037.5104126.9112022-12-01
2893영등포구영등포본-주정차-08 도림로112길 25-1537.5074126.901712022-12-01
2894영등포구영등포본-주정차-09 도신로65길 237.5103126.917112022-12-01
2895영등포구영등포본-주정차-09(1) 도신로65길 237.5103126.917212022-12-01
2896영등포구영등포본-주정차-09(2) 도신로65길 237.5102126.91712022-12-01
2897영등포구통합관제센터37.5238126.894812022-12-01
2898영등포구통합관제센터 뒷편37.5239126.894812022-12-01