Overview

Dataset statistics

Number of variables6
Number of observations5060
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory252.1 KiB
Average record size in memory51.0 B

Variable types

Categorical3
Text1
Numeric2

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author서초구
URLhttps://data.seoul.go.kr/dataList/OA-20945/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 10:33:31.322987
Analysis finished2024-03-13 10:33:32.229799
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.7 KiB
서초구
5060 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서초구 5060
100.0%

Length

2024-03-13T19:33:32.283200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T19:33:32.357810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서초구 5060
100.0%

안심 주소
Text

UNIQUE 

Distinct5060
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size39.7 KiB
2024-03-13T19:33:32.564266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length51
Mean length36.631621
Min length25

Characters and Unicode

Total characters185356
Distinct characters594
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5060 ?
Unique (%)100.0%

Sample

1st rowA13002;1/1rxxxx3;서초3동 1488-4;상명달어린이공원 시소앞
2nd rowA13003;1/1rxxxx3;서초3동 1518-1;하명달어린이공원 미끄럼틀앞
3rd rowA13004;1/1rlxxx3;반포1동 720;언구비어린이공원 그네앞
4th rowA13005;1/1rxxxx4;반포4동 53-1;미도어린이공원 시소옆
5th rowA13006;1/1rxxxx3;방배3동 593-43;동덕어린이공원 운동시설앞
ValueCountFrequency (%)
공영주차장 384
 
2.7%
주변 316
 
2.3%
삼거리 180
 
1.3%
앞 133
 
1.0%
사거리 110
 
0.8%
부근 106
 
0.8%
입구 95
 
0.7%
b1 92
 
0.7%
우면동 81
 
0.6%
신원동 63
 
0.5%
Other values (7350) 12432
88.9%
2024-03-13T19:33:33.105841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
x 18126
 
9.8%
; 15170
 
8.2%
1 13959
 
7.5%
0 13469
 
7.3%
2 9707
 
5.2%
8936
 
4.8%
3 8042
 
4.3%
4 6353
 
3.4%
동 6056
 
3.3%
/ 5060
 
2.7%
Other values (584) 80478
43.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66961
36.1%
Other Letter 52589
28.4%
Lowercase Letter 25319
 
13.7%
Other Punctuation 20243
 
10.9%
Space Separator 8936
 
4.8%
Uppercase Letter 6318
 
3.4%
Dash Punctuation 4287
 
2.3%
Close Punctuation 313
 
0.2%
Open Punctuation 310
 
0.2%
Connector Punctuation 79
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6056
 
11.5%
방 1960
 
3.7%
서 1925
 
3.7%
초 1914
 
3.6%
배 1806
 
3.4%
주 1395
 
2.7%
원 1347
 
2.6%
양 1272
 
2.4%
재 1261
 
2.4%
반 1142
 
2.2%
Other values (515) 32511
61.8%
Uppercase Letter
ValueCountFrequency (%)
P 2307
36.5%
N 1143
18.1%
B 484
 
7.7%
T 428
 
6.8%
A 347
 
5.5%
C 227
 
3.6%
H 178
 
2.8%
F 153
 
2.4%
G 134
 
2.1%
S 115
 
1.8%
Other values (16) 802
 
12.7%
Lowercase Letter
ValueCountFrequency (%)
x 18126
71.6%
s 3517
 
13.9%
r 1530
 
6.0%
d 446
 
1.8%
t 406
 
1.6%
q 330
 
1.3%
m 323
 
1.3%
b 242
 
1.0%
c 196
 
0.8%
p 86
 
0.3%
Other values (10) 117
 
0.5%
Decimal Number
ValueCountFrequency (%)
1 13959
20.8%
0 13469
20.1%
2 9707
14.5%
3 8042
12.0%
4 6353
9.5%
5 3731
 
5.6%
7 3460
 
5.2%
6 3098
 
4.6%
9 2661
 
4.0%
8 2481
 
3.7%
Other Punctuation
ValueCountFrequency (%)
; 15170
74.9%
/ 5060
 
25.0%
# 8
 
< 0.1%
, 4
 
< 0.1%
& 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 302
96.5%
] 11
 
3.5%
Open Punctuation
ValueCountFrequency (%)
( 299
96.5%
[ 11
 
3.5%
Space Separator
ValueCountFrequency (%)
8936
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4287
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 79
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 101130
54.6%
Hangul 52589
28.4%
Latin 31637
 
17.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6056
 
11.5%
방 1960
 
3.7%
서 1925
 
3.7%
초 1914
 
3.6%
배 1806
 
3.4%
주 1395
 
2.7%
원 1347
 
2.6%
양 1272
 
2.4%
재 1261
 
2.4%
반 1142
 
2.2%
Other values (515) 32511
61.8%
Latin
ValueCountFrequency (%)
x 18126
57.3%
s 3517
 
11.1%
P 2307
 
7.3%
r 1530
 
4.8%
N 1143
 
3.6%
B 484
 
1.5%
d 446
 
1.4%
T 428
 
1.4%
t 406
 
1.3%
A 347
 
1.1%
Other values (36) 2903
 
9.2%
Common
ValueCountFrequency (%)
; 15170
15.0%
1 13959
13.8%
0 13469
13.3%
2 9707
9.6%
8936
8.8%
3 8042
8.0%
4 6353
6.3%
/ 5060
 
5.0%
- 4287
 
4.2%
5 3731
 
3.7%
Other values (13) 12416
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132767
71.6%
Hangul 52589
 
28.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
x 18126
13.7%
; 15170
11.4%
1 13959
10.5%
0 13469
10.1%
2 9707
 
7.3%
8936
 
6.7%
3 8042
 
6.1%
4 6353
 
4.8%
/ 5060
 
3.8%
- 4287
 
3.2%
Other values (59) 29658
22.3%
Hangul
ValueCountFrequency (%)
동 6056
 
11.5%
방 1960
 
3.7%
서 1925
 
3.7%
초 1914
 
3.6%
배 1806
 
3.4%
주 1395
 
2.7%
원 1347
 
2.6%
양 1272
 
2.4%
재 1261
 
2.4%
반 1142
 
2.2%
Other values (515) 32511
61.8%

위도
Real number (ℝ)

Distinct653
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.485978
Minimum37.4305
Maximum37.5244
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-03-13T19:33:33.242471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.4305
5-th percentile37.4565
Q137.477
median37.48705
Q337.4963
95-th percentile37.5105
Maximum37.5244
Range0.0939
Interquartile range (IQR)0.0193

Descriptive statistics

Standard deviation0.015508116
Coefficient of variation (CV)0.00041370445
Kurtosis0.26367989
Mean37.485978
Median Absolute Deviation (MAD)0.00965
Skewness-0.41164543
Sum189679.05
Variance0.00024050166
MonotonicityNot monotonic
2024-03-13T19:33:33.376248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4857 40
 
0.8%
37.4905 36
 
0.7%
37.4717 34
 
0.7%
37.4927 33
 
0.7%
37.4914 33
 
0.7%
37.4963 30
 
0.6%
37.4893 29
 
0.6%
37.489 29
 
0.6%
37.4716 28
 
0.6%
37.49 27
 
0.5%
Other values (643) 4741
93.7%
ValueCountFrequency (%)
37.4305 3
0.1%
37.4321 2
 
< 0.1%
37.4346 4
0.1%
37.4348 3
0.1%
37.4351 1
 
< 0.1%
37.4354 1
 
< 0.1%
37.4355 5
0.1%
37.4356 4
0.1%
37.4373 1
 
< 0.1%
37.4404 3
0.1%
ValueCountFrequency (%)
37.5244 3
0.1%
37.5217 1
 
< 0.1%
37.5215 1
 
< 0.1%
37.5214 1
 
< 0.1%
37.5208 1
 
< 0.1%
37.5206 1
 
< 0.1%
37.5205 5
0.1%
37.5201 2
 
< 0.1%
37.52 1
 
< 0.1%
37.5199 2
 
< 0.1%

경도
Real number (ℝ)

Distinct737
Distinct (%)14.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.01398
Minimum126.9798
Maximum127.0918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.6 KiB
2024-03-13T19:33:33.505827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.9798
5-th percentile126.9849
Q1126.9945
median127.0136
Q3127.0268
95-th percentile127.053
Maximum127.0918
Range0.112
Interquartile range (IQR)0.0323

Descriptive statistics

Standard deviation0.02180046
Coefficient of variation (CV)0.00017163827
Kurtosis-0.16618371
Mean127.01398
Median Absolute Deviation (MAD)0.0169
Skewness0.56116829
Sum642690.73
Variance0.00047526005
MonotonicityNot monotonic
2024-03-13T19:33:33.629081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0105 39
 
0.8%
126.9853 27
 
0.5%
127.0213 26
 
0.5%
127.0268 26
 
0.5%
126.9866 26
 
0.5%
127.0175 25
 
0.5%
126.9914 24
 
0.5%
127.0195 24
 
0.5%
126.9854 22
 
0.4%
126.9855 22
 
0.4%
Other values (727) 4799
94.8%
ValueCountFrequency (%)
126.9798 1
 
< 0.1%
126.9806 1
 
< 0.1%
126.9807 4
0.1%
126.9811 6
0.1%
126.9818 4
0.1%
126.9819 6
0.1%
126.9821 4
0.1%
126.9822 9
0.2%
126.9824 5
0.1%
126.9825 5
0.1%
ValueCountFrequency (%)
127.0918 1
 
< 0.1%
127.091 1
 
< 0.1%
127.0907 1
 
< 0.1%
127.0901 7
0.1%
127.089 2
 
< 0.1%
127.0889 2
 
< 0.1%
127.088 1
 
< 0.1%
127.0869 4
0.1%
127.0867 1
 
< 0.1%
127.0853 4
0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.7 KiB
1
5060 

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 5060
100.0%

Length

2024-03-13T19:33:33.753761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T19:33:33.854880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5060
100.0%

수정 일시
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.7 KiB
2022-12-01
5060 

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 5060
100.0%

Length

2024-03-13T19:33:33.945575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T19:33:34.038398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-12-01 5060
100.0%

Interactions

2024-03-13T19:33:31.894677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T19:33:31.738382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T19:33:31.977987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T19:33:31.815215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T19:33:34.086916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.826
경도0.8261.000
2024-03-13T19:33:34.158071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.351
경도-0.3511.000

Missing values

2024-03-13T19:33:32.103748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T19:33:32.190936image/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
0서초구A13002;1/1rxxxx3;서초3동 1488-4;상명달어린이공원 시소앞37.4822127.005712022-12-01
1서초구A13003;1/1rxxxx3;서초3동 1518-1;하명달어린이공원 미끄럼틀앞37.4859127.005512022-12-01
2서초구A13004;1/1rlxxx3;반포1동 720;언구비어린이공원 그네앞37.509127.020212022-12-01
3서초구A13005;1/1rxxxx4;반포4동 53-1;미도어린이공원 시소옆37.5018127.010812022-12-01
4서초구A13006;1/1rxxxx3;방배3동 593-43;동덕어린이공원 운동시설앞37.4757126.993612022-12-01
5서초구A13008;1/1rxxxx4;양재1동 103-4;종열어린이공원 그네앞37.474127.033912022-12-01
6서초구A13009;1/1rxxxx3;양재1동 (우면동) 55;효자어린이공원 시소옆37.4735127.024312022-12-01
7서초구A13010;1/1rxxxx4;양재2동 311;양재근린공원 화장실앞37.4717127.042412022-12-01
8서초구A13011;1/1rxxxx4;양재2동 311;양재근린공원 미끄럼틀앞37.4721127.04312022-12-01
9서초구A14001;1/1rxxxx3;서초4동 1313-17;명달근린공원 정자옆37.4984127.021212022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
5050서초구Y17005;3/4rxxxx0;반포4동 94-1;서래펌프장_제진기37.4995126.997712022-12-01
5051서초구Y17005;4/4rxxxx0;반포4동 94-1;서래펌프장_집수정37.4996126.997712022-12-01
5052서초구Y17006;1/5rxxxx0;반포1동 119-2;사평펌프장_전기실37.5037127.017612022-12-01
5053서초구Y17006;2/5rxxxx0;반포1동 119-2;사평펌프장_스크린실37.5036127.017912022-12-01
5054서초구Y17006;3/5rxxxx0;반포1동 119-2;사평펌프장_펌프실37.5035127.017712022-12-01
5055서초구Y17006;4/5rxxxx0;반포1동 119-2;사평펌프장_정문37.5034127.017712022-12-01
5056서초구Y17006;5/5rxxxx0;반포1동 119-2;사평펌프장_유출수문37.5038127.017812022-12-01
5057서초구Y17007;1/1rxxxx0;잠원동 51-45;잠원펌프장_정문37.5199127.015312022-12-01
5058서초구Y18001;1/2rxxxx0;방배4동 821-1;방배펌프장_배수문37.4899126.986812022-12-01
5059서초구Y18001;2/2rxxxx0;방배4동 821-1;방배펌프장_정문37.49126.98712022-12-01