Overview

Dataset statistics

Number of variables6
Number of observations2650
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.1 KiB
Average record size in memory51.0 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author동작구
URLhttps://data.seoul.go.kr/dataList/OA-20943/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 started2024-04-29 20:48:00.633542
Analysis finished2024-04-29 20:48:02.627543
Duration1.99 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
동작구
2650 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동작구 2650
100.0%

Length

2024-04-30T05:48:02.684262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:48:02.756211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동작구 2650
100.0%

안심 주소
Text

UNIQUE 

Distinct2650
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
2024-04-30T05:48:02.968932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length44
Mean length25.416604
Min length16

Characters and Unicode

Total characters67354
Distinct characters248
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

Unique2650 ?
Unique (%)100.0%

Sample

1st row공원-001(1).대방동 23-176 (메인)
2nd row공원-001(2).대방동 23-176 (메인)
3rd row공원-001(2).대방동 23-176 (보조1)
4th row공원-001(3).대방동 23-176 (메인)
5th row공원-001(3).대방동 23-176 (보조1)
ValueCountFrequency (%)
메인 885
 
10.2%
보조1 637
 
7.3%
보조2 619
 
7.1%
보조3 355
 
4.1%
앞 80
 
0.9%
보조4 71
 
0.8%
삼거리 44
 
0.5%
맞은편 40
 
0.5%
31
 
0.4%
산 18
 
0.2%
Other values (2039) 5920
68.0%
2024-04-30T05:48:03.308887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6059
 
9.0%
- 5128
 
7.6%
1 4837
 
7.2%
2 3945
 
5.9%
3 3144
 
4.7%
0 2914
 
4.3%
( 2725
 
4.0%
) 2725
 
4.0%
동 2663
 
4.0%
. 2649
 
3.9%
Other values (238) 30565
45.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 24168
35.9%
Other Letter 23763
35.3%
Space Separator 6059
 
9.0%
Dash Punctuation 5128
 
7.6%
Open Punctuation 2725
 
4.0%
Close Punctuation 2725
 
4.0%
Other Punctuation 2651
 
3.9%
Connector Punctuation 75
 
0.1%
Uppercase Letter 57
 
0.1%
Math Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 2663
 
11.2%
방 2233
 
9.4%
보 1698
 
7.1%
조 1689
 
7.1%
범 1683
 
7.1%
도 944
 
4.0%
상 906
 
3.8%
메 886
 
3.7%
인 885
 
3.7%
사 795
 
3.3%
Other values (210) 9381
39.5%
Decimal Number
ValueCountFrequency (%)
1 4837
20.0%
2 3945
16.3%
3 3144
13.0%
0 2914
12.1%
4 2649
11.0%
5 1546
 
6.4%
6 1495
 
6.2%
7 1243
 
5.1%
9 1215
 
5.0%
8 1180
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
C 9
15.8%
P 8
14.0%
U 8
14.0%
G 7
12.3%
A 7
12.3%
W 4
7.0%
Y 4
7.0%
S 4
7.0%
L 3
 
5.3%
T 3
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 2649
99.9%
, 2
 
0.1%
Space Separator
ValueCountFrequency (%)
6059
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5128
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2725
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2725
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 75
100.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 43534
64.6%
Hangul 23763
35.3%
Latin 57
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 2663
 
11.2%
방 2233
 
9.4%
보 1698
 
7.1%
조 1689
 
7.1%
범 1683
 
7.1%
도 944
 
4.0%
상 906
 
3.8%
메 886
 
3.7%
인 885
 
3.7%
사 795
 
3.3%
Other values (210) 9381
39.5%
Common
ValueCountFrequency (%)
6059
13.9%
- 5128
11.8%
1 4837
11.1%
2 3945
9.1%
3 3144
7.2%
0 2914
6.7%
( 2725
6.3%
) 2725
6.3%
. 2649
 
6.1%
4 2649
 
6.1%
Other values (8) 6759
15.5%
Latin
ValueCountFrequency (%)
C 9
15.8%
P 8
14.0%
U 8
14.0%
G 7
12.3%
A 7
12.3%
W 4
7.0%
Y 4
7.0%
S 4
7.0%
L 3
 
5.3%
T 3
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 43591
64.7%
Hangul 23763
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6059
13.9%
- 5128
11.8%
1 4837
11.1%
2 3945
9.1%
3 3144
7.2%
0 2914
6.7%
( 2725
 
6.3%
) 2725
 
6.3%
. 2649
 
6.1%
4 2649
 
6.1%
Other values (18) 6816
15.6%
Hangul
ValueCountFrequency (%)
동 2663
 
11.2%
방 2233
 
9.4%
보 1698
 
7.1%
조 1689
 
7.1%
범 1683
 
7.1%
도 944
 
4.0%
상 906
 
3.8%
메 886
 
3.7%
인 885
 
3.7%
사 795
 
3.3%
Other values (210) 9381
39.5%

위도
Real number (ℝ)

Distinct331
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.496995
Minimum37.4762
Maximum37.5162
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.4 KiB
2024-04-30T05:48:03.428992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.4762
5-th percentile37.47959
Q137.4889
median37.49775
Q337.5049
95-th percentile37.5118
Maximum37.5162
Range0.04
Interquartile range (IQR)0.016

Descriptive statistics

Standard deviation0.0099680364
Coefficient of variation (CV)0.00026583561
Kurtosis-0.9234195
Mean37.496995
Median Absolute Deviation (MAD)0.00785
Skewness-0.23003848
Sum99367.037
Variance9.9361749 × 10-5
MonotonicityNot monotonic
2024-04-30T05:48:03.550338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4955 25
 
0.9%
37.5033 25
 
0.9%
37.5048 24
 
0.9%
37.4822 22
 
0.8%
37.4886 22
 
0.8%
37.4992 22
 
0.8%
37.4969 22
 
0.8%
37.5083 20
 
0.8%
37.4899 20
 
0.8%
37.5028 19
 
0.7%
Other values (321) 2429
91.7%
ValueCountFrequency (%)
37.4762 4
 
0.2%
37.4764 3
 
0.1%
37.477 10
0.4%
37.4771 11
0.4%
37.4773 10
0.4%
37.4774 4
 
0.2%
37.4776 4
 
0.2%
37.4777 5
 
0.2%
37.4778 15
0.6%
37.4781 3
 
0.1%
ValueCountFrequency (%)
37.5162 9
0.3%
37.5161 1
 
< 0.1%
37.5155 1
 
< 0.1%
37.5147 1
 
< 0.1%
37.5146 2
 
0.1%
37.5144 1
 
< 0.1%
37.5143 12
0.5%
37.5141 10
0.4%
37.5139 7
0.3%
37.5137 1
 
< 0.1%

경도
Real number (ℝ)

Distinct518
Distinct (%)19.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.94924
Minimum126.9046
Maximum126.983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.4 KiB
2024-04-30T05:48:03.670438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.9046
5-th percentile126.9133
Q1126.9343
median126.9472
Q3126.9683
95-th percentile126.9799
Maximum126.983
Range0.0784
Interquartile range (IQR)0.034

Descriptive statistics

Standard deviation0.020124429
Coefficient of variation (CV)0.00015852343
Kurtosis-0.98627255
Mean126.94924
Median Absolute Deviation (MAD)0.01605
Skewness-0.064985808
Sum336415.5
Variance0.00040499266
MonotonicityNot monotonic
2024-04-30T05:48:03.788378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9795 24
 
0.9%
126.9522 19
 
0.7%
126.9441 18
 
0.7%
126.9352 17
 
0.6%
126.98 17
 
0.6%
126.9781 16
 
0.6%
126.936 15
 
0.6%
126.9449 15
 
0.6%
126.9463 15
 
0.6%
126.9705 15
 
0.6%
Other values (508) 2479
93.5%
ValueCountFrequency (%)
126.9046 1
 
< 0.1%
126.9047 1
 
< 0.1%
126.905 3
0.1%
126.9055 1
 
< 0.1%
126.9058 1
 
< 0.1%
126.906 1
 
< 0.1%
126.9062 4
0.2%
126.9068 4
0.2%
126.907 5
0.2%
126.9075 1
 
< 0.1%
ValueCountFrequency (%)
126.983 2
 
0.1%
126.9825 4
0.2%
126.9824 4
0.2%
126.9823 4
0.2%
126.982 4
0.2%
126.9819 9
0.3%
126.9817 6
0.2%
126.9816 3
 
0.1%
126.9815 3
 
0.1%
126.9814 1
 
< 0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
1
2650 

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 2650
100.0%

Length

2024-04-30T05:48:03.893147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:48:03.972782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2650
100.0%

수정 일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.8 KiB
2022-12-01
2650 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-12-01
2nd row2022-12-01
3rd row2022-12-01
4th row2022-12-01
5th row2022-12-01

Common Values

ValueCountFrequency (%)
2022-12-01 2650
100.0%

Length

2024-04-30T05:48:04.053475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-30T05:48:04.133507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 2650
100.0%

Interactions

2024-04-30T05:48:02.277805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:48:02.024913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:48:02.375048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T05:48:02.176502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T05:48:04.179161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.789
경도0.7891.000
2024-04-30T05:48:04.250666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.396
경도-0.3961.000

Missing values

2024-04-30T05:48:02.492211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T05:48:02.583481image/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
0동작구공원-001(1).대방동 23-176 (메인)37.5097126.928212022-12-01
1동작구공원-001(2).대방동 23-176 (메인)37.5097126.928412022-12-01
2동작구공원-001(2).대방동 23-176 (보조1)37.5097126.928412022-12-01
3동작구공원-001(3).대방동 23-176 (메인)37.5108126.929512022-12-01
4동작구공원-001(3).대방동 23-176 (보조1)37.5108126.929512022-12-01
5동작구공원-002(1).대방동 23-181 (메인)37.5036126.930812022-12-01
6동작구공원-002(2).대방동 23-181 (메인)37.5036126.930812022-12-01
7동작구공원-003(1).노량진동 152-3 (메인)37.5135126.949212022-12-01
8동작구공원-003(2).노량진1동 152-3 (메인)37.5134126.949912022-12-01
9동작구공원-003(3).노량진1동 152-3 (메인)37.5137126.949712022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
2640동작구주정차-054.신대방2동 357-4 건너편 (메인)37.498126.925812022-12-01
2641동작구주정차-055.신대방동 686-48 (메인)37.4864126.904612022-12-01
2642동작구주정차-056.신대방동 697 (메인)37.4858126.905512022-12-01
2643동작구주정차-057.동작동 102-31 (메인)37.4966126.982512022-12-01
2644동작구주정차-058.노량진동 240-18 (메인)37.5113126.9412022-12-01
2645동작구주정차-059.상도동 28-13 (메인)37.5039126.944312022-12-01
2646동작구주정차-060.상도동 207-5 (메인)37.4992126.94412022-12-01
2647동작구주정차-061.신대방동 644-10 (메인)37.4877126.912712022-12-01
2648동작구주정차-062.대방동 395-5 (메인)37.5002126.925412022-12-01
2649동작구주정차-063.사당동 64-237 (메인)37.4925126.976712022-12-01