Overview

Dataset statistics

Number of variables6
Number of observations3845
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory191.6 KiB
Average record size in memory51.0 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20938/S/1/datasetView.do

Alerts

자치구 has constant value ""Constant
CCTV 수량 has constant value ""Constant
수정 일시 has constant value ""Constant

Reproduction

Analysis started2024-04-20 23:30:16.255659
Analysis finished2024-04-20 23:30:18.087594
Duration1.83 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.2 KiB
양천구
3845 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
양천구 3845
100.0%

Length

2024-04-21T08:30:18.141624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:30:18.219485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
양천구 3845
100.0%

안심 주소
Text

Distinct3844
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size30.2 KiB
2024-04-21T08:30:18.432418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length61
Mean length30.045514
Min length14

Characters and Unicode

Total characters115525
Distinct characters436
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3843 ?
Unique (%)99.9%

Sample

1st row(공원 리모델링 공사 중)공원018 경인어린이공원 (신월3동 196) - 2020 성능개
2nd row(공원 리모델링 공사 중)공원018 경인어린이공원 (신월3동 196)_검지(메가)
3rd row(비상벨)고신정063 은정초교 육교 중앙
4th row(비상벨)공원087 신정동 621 (신정산 유아숲체험원)
5th row(비상벨)공원089 신월동 331-5 (지양산 유아숲체험원)
ValueCountFrequency (%)
검지1 450
 
2.3%
검지2 405
 
2.1%
신정4동 331
 
1.7%
신정3동 323
 
1.7%
목2동 307
 
1.6%
앞 297
 
1.5%
회전 275
 
1.4%
검지3 256
 
1.3%
목4동 251
 
1.3%
신월1동 247
 
1.3%
Other values (4840) 16340
83.9%
2024-04-21T08:30:18.849368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15732
 
13.6%
1 7906
 
6.8%
0 6422
 
5.6%
2 5616
 
4.9%
신 5273
 
4.6%
동 4729
 
4.1%
3 4195
 
3.6%
- 3561
 
3.1%
4 3401
 
2.9%
지 3171
 
2.7%
Other values (426) 55519
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49299
42.7%
Decimal Number 39868
34.5%
Space Separator 15732
 
13.6%
Dash Punctuation 3561
 
3.1%
Close Punctuation 2458
 
2.1%
Open Punctuation 2454
 
2.1%
Connector Punctuation 1825
 
1.6%
Other Punctuation 161
 
0.1%
Uppercase Letter 146
 
0.1%
Math Symbol 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
신 5273
 
10.7%
동 4729
 
9.6%
지 3171
 
6.4%
목 3031
 
6.1%
검 2881
 
5.8%
정 2857
 
5.8%
월 2648
 
5.4%
로 1307
 
2.7%
어 1091
 
2.2%
리 1039
 
2.1%
Other values (392) 21272
43.1%
Uppercase Letter
ValueCountFrequency (%)
S 35
24.0%
A 23
15.8%
M 14
 
9.6%
O 13
 
8.9%
P 12
 
8.2%
B 10
 
6.8%
I 9
 
6.2%
T 9
 
6.2%
K 6
 
4.1%
C 4
 
2.7%
Other values (4) 11
 
7.5%
Decimal Number
ValueCountFrequency (%)
1 7906
19.8%
0 6422
16.1%
2 5616
14.1%
3 4195
10.5%
4 3401
8.5%
5 2847
 
7.1%
7 2640
 
6.6%
9 2609
 
6.5%
6 2350
 
5.9%
8 1882
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 152
94.4%
/ 5
 
3.1%
: 2
 
1.2%
. 2
 
1.2%
Space Separator
ValueCountFrequency (%)
15732
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3561
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2458
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2454
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1825
100.0%
Math Symbol
ValueCountFrequency (%)
~ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66080
57.2%
Hangul 49299
42.7%
Latin 146
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
신 5273
 
10.7%
동 4729
 
9.6%
지 3171
 
6.4%
목 3031
 
6.1%
검 2881
 
5.8%
정 2857
 
5.8%
월 2648
 
5.4%
로 1307
 
2.7%
어 1091
 
2.2%
리 1039
 
2.1%
Other values (392) 21272
43.1%
Common
ValueCountFrequency (%)
15732
23.8%
1 7906
12.0%
0 6422
9.7%
2 5616
 
8.5%
3 4195
 
6.3%
- 3561
 
5.4%
4 3401
 
5.1%
5 2847
 
4.3%
7 2640
 
4.0%
9 2609
 
3.9%
Other values (10) 11151
16.9%
Latin
ValueCountFrequency (%)
S 35
24.0%
A 23
15.8%
M 14
 
9.6%
O 13
 
8.9%
P 12
 
8.2%
B 10
 
6.8%
I 9
 
6.2%
T 9
 
6.2%
K 6
 
4.1%
C 4
 
2.7%
Other values (4) 11
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66226
57.3%
Hangul 49297
42.7%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15732
23.8%
1 7906
11.9%
0 6422
9.7%
2 5616
 
8.5%
3 4195
 
6.3%
- 3561
 
5.4%
4 3401
 
5.1%
5 2847
 
4.3%
7 2640
 
4.0%
9 2609
 
3.9%
Other values (24) 11297
17.1%
Hangul
ValueCountFrequency (%)
신 5273
 
10.7%
동 4729
 
9.6%
지 3171
 
6.4%
목 3031
 
6.1%
검 2881
 
5.8%
정 2857
 
5.8%
월 2648
 
5.4%
로 1307
 
2.7%
어 1091
 
2.2%
리 1039
 
2.1%
Other values (391) 21270
43.1%
Compat Jamo
ValueCountFrequency (%)
ㄱ 2
100.0%

위도
Real number (ℝ)

Distinct403
Distinct (%)10.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.527738
Minimum37.5054
Maximum37.5508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.9 KiB
2024-04-21T08:30:18.988941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.5054
5-th percentile37.511
Q137.5202
median37.5261
Q337.5363
95-th percentile37.5454
Maximum37.5508
Range0.0454
Interquartile range (IQR)0.0161

Descriptive statistics

Standard deviation0.010519208
Coefficient of variation (CV)0.00028030488
Kurtosis-0.89416635
Mean37.527738
Median Absolute Deviation (MAD)0.008
Skewness0.1425031
Sum144294.15
Variance0.00011065374
MonotonicityNot monotonic
2024-04-21T08:30:19.116944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5212 38
 
1.0%
37.5241 38
 
1.0%
37.523 32
 
0.8%
37.5219 30
 
0.8%
37.5221 30
 
0.8%
37.524 29
 
0.8%
37.5204 28
 
0.7%
37.5265 27
 
0.7%
37.5216 27
 
0.7%
37.5463 26
 
0.7%
Other values (393) 3540
92.1%
ValueCountFrequency (%)
37.5054 2
 
0.1%
37.5056 3
0.1%
37.5058 2
 
0.1%
37.5059 3
0.1%
37.506 3
0.1%
37.5065 3
0.1%
37.5068 6
0.2%
37.5069 4
0.1%
37.507 3
0.1%
37.5071 4
0.1%
ValueCountFrequency (%)
37.5508 2
 
0.1%
37.5505 2
 
0.1%
37.55 6
0.2%
37.5497 3
0.1%
37.5496 1
 
< 0.1%
37.5493 3
0.1%
37.5492 4
0.1%
37.549 3
0.1%
37.5489 4
0.1%
37.5487 3
0.1%

경도
Real number (ℝ)

Distinct504
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.8542
Minimum126.823
Maximum126.888
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.9 KiB
2024-04-21T08:30:19.250262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.823
5-th percentile126.8283
Q1126.8378
median126.8559
Q3126.8687
95-th percentile126.8771
Maximum126.888
Range0.065
Interquartile range (IQR)0.0309

Descriptive statistics

Standard deviation0.016760937
Coefficient of variation (CV)0.00013212757
Kurtosis-1.3052362
Mean126.8542
Median Absolute Deviation (MAD)0.0147
Skewness-0.15472617
Sum487754.39
Variance0.000280929
MonotonicityNot monotonic
2024-04-21T08:30:19.404402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.8642 34
 
0.9%
126.8688 33
 
0.9%
126.8695 29
 
0.8%
126.8705 25
 
0.7%
126.876 24
 
0.6%
126.8674 23
 
0.6%
126.8725 22
 
0.6%
126.8738 21
 
0.5%
126.8651 21
 
0.5%
126.837 21
 
0.5%
Other values (494) 3592
93.4%
ValueCountFrequency (%)
126.823 2
 
0.1%
126.8239 2
 
0.1%
126.8241 6
0.2%
126.8242 4
0.1%
126.8244 5
0.1%
126.8245 1
 
< 0.1%
126.8246 1
 
< 0.1%
126.8248 7
0.2%
126.825 5
0.1%
126.8251 3
0.1%
ValueCountFrequency (%)
126.888 3
0.1%
126.887 4
0.1%
126.8868 1
 
< 0.1%
126.8862 3
0.1%
126.8858 3
0.1%
126.8856 3
0.1%
126.8853 4
0.1%
126.8847 5
0.1%
126.8843 2
 
0.1%
126.8841 3
0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.2 KiB
1
3845 

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 3845
100.0%

Length

2024-04-21T08:30:19.543717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:30:19.621767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3845
100.0%

수정 일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size30.2 KiB
2022-12-01
3845 

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 3845
100.0%

Length

2024-04-21T08:30:19.716917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T08:30:19.807164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 3845
100.0%

Interactions

2024-04-21T08:30:17.768283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:30:17.541637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:30:17.849029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T08:30:17.672342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T08:30:19.858243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.669
경도0.6691.000
2024-04-21T08:30:19.932072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.198
경도0.1981.000

Missing values

2024-04-21T08:30:17.960553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T08:30:18.046304image/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
0양천구(공원 리모델링 공사 중)공원018 경인어린이공원 (신월3동 196) - 2020 성능개37.532126.828812022-12-01
1양천구(공원 리모델링 공사 중)공원018 경인어린이공원 (신월3동 196)_검지(메가)37.532126.828812022-12-01
2양천구(비상벨)고신정063 은정초교 육교 중앙37.5119126.867712022-12-01
3양천구(비상벨)공원087 신정동 621 (신정산 유아숲체험원)37.5104126.856512022-12-01
4양천구(비상벨)공원089 신월동 331-5 (지양산 유아숲체험원)37.5212126.829512022-12-01
5양천구(비상벨)공원091 목동 199-51 (용왕산 유아숲체험원)37.5394126.873112022-12-01
6양천구(비상벨)신월046 신월5동 81-7 (남부순환로 35길 16)37.5367126.829912022-12-01
7양천구(비상벨)신월056 신월1동 232-2337.528126.836712022-12-01
8양천구(비상벨)신월078 신월1동 230-1(반곡공원 주변) 반곡공원37.529126.835512022-12-01
9양천구(비상벨)신월088 신월5동 74-8 (가로공원로 67길 12-3)37.5375126.83112022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
3835양천구어신정095 신정4동 990-1호 991-15호사이 사거리37.5252126.861712022-12-01
3836양천구어신정095 신정4동 990-1호 991-15호사이 사거리_검지137.5252126.861712022-12-01
3837양천구어신정095 신정4동 990-1호 991-15호사이 사거리_검지237.5252126.861712022-12-01
3838양천구어신정095 신정4동 990-1호 991-15호사이 사거리_검지337.5252126.861712022-12-01
3839양천구어신정096 신정4동 889-2_검지137.5277126.860112022-12-01
3840양천구어신정097 신정7동 갈산초교 횡단보도_200만 회전37.5122126.870512022-12-01
3841양천구어신정097 신정7동 갈산초교 횡단보도_검지137.5122126.870512022-12-01
3842양천구어신정097 신정7동 갈산초교 횡단보도_검지237.5122126.870512022-12-01
3843양천구어신정097 신정7동 갈산초교 횡단보도_검지337.5122126.870512022-12-01
3844양천구화비001 목3동시장 고객지원센터(목동중앙북로6길5)37.5482126.865112022-12-01