Overview

Dataset statistics

Number of variables6
Number of observations2655
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory132.4 KiB
Average record size in memory51.0 B

Variable types

Categorical2
Text1
Numeric2
DateTime1

Dataset

Description자치구,안심 주소,위도,경도,CCTV 수량,수정 일시
Author노원구
URLhttps://data.seoul.go.kr/dataList/OA-20934/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 13:15:00.825823
Analysis finished2024-03-13 13:15:01.867909
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

자치구
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
노원구
2655 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노원구 2655
100.0%

Length

2024-03-13T22:15:01.948684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:02.031637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노원구 2655
100.0%

안심 주소
Text

UNIQUE 

Distinct2655
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
2024-03-13T22:15:02.271466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length47
Mean length29.058757
Min length8

Characters and Unicode

Total characters77151
Distinct characters447
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

Unique2655 ?
Unique (%)100.0%

Sample

1st row공원001(1).D(마들)한아름공원2(상계로1길34 상계10동)
2nd row공원001(2).(마들)한아름공원2(상계로1길34 상계10동)
3rd row공원002(1).(마들)용화공원1(동일로221길32 상계10동)
4th row공원002(2).(마들)용화공원2(동일로221길32 상계10동)
5th row공원003(1).D(마들)종달새공원1(한글비석로54길92 상계9동)
ValueCountFrequency (%)
공릉1동 42
 
0.7%
공원 41
 
0.7%
상계2동 39
 
0.6%
앞 34
 
0.6%
산 32
 
0.5%
공원3차 31
 
0.5%
상계3,4동 26
 
0.4%
공릉2동 25
 
0.4%
상계1동 23
 
0.4%
하계1동 22
 
0.4%
Other values (4213) 5694
94.8%
2024-03-13T22:15:02.743825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 5154
 
6.7%
( 5150
 
6.7%
1 4423
 
5.7%
3538
 
4.6%
2 3234
 
4.2%
. 2655
 
3.4%
계 2554
 
3.3%
3 2420
 
3.1%
동 2307
 
3.0%
0 2295
 
3.0%
Other values (437) 43421
56.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 36261
47.0%
Decimal Number 21708
28.1%
Close Punctuation 5170
 
6.7%
Open Punctuation 5166
 
6.7%
Space Separator 3538
 
4.6%
Other Punctuation 2911
 
3.8%
Uppercase Letter 1140
 
1.5%
Dash Punctuation 1075
 
1.4%
Lowercase Letter 173
 
0.2%
Connector Punctuation 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 2554
 
7.0%
동 2307
 
6.4%
로 1796
 
5.0%
원 1568
 
4.3%
공 1523
 
4.2%
방 1414
 
3.9%
범 1409
 
3.9%
길 1391
 
3.8%
상 1334
 
3.7%
릉 790
 
2.2%
Other values (387) 20175
55.6%
Uppercase Letter
ValueCountFrequency (%)
D 1028
90.2%
G 28
 
2.5%
K 14
 
1.2%
M 11
 
1.0%
S 10
 
0.9%
V 7
 
0.6%
E 7
 
0.6%
T 7
 
0.6%
A 6
 
0.5%
N 5
 
0.4%
Other values (7) 17
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
c 80
46.2%
h 78
45.1%
t 3
 
1.7%
a 3
 
1.7%
e 2
 
1.2%
l 2
 
1.2%
n 1
 
0.6%
i 1
 
0.6%
z 1
 
0.6%
v 1
 
0.6%
Decimal Number
ValueCountFrequency (%)
1 4423
20.4%
2 3234
14.9%
3 2420
11.1%
0 2295
10.6%
4 2118
9.8%
5 1709
 
7.9%
6 1504
 
6.9%
7 1414
 
6.5%
9 1301
 
6.0%
8 1290
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 2655
91.2%
, 211
 
7.2%
* 41
 
1.4%
/ 4
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 5154
99.7%
] 16
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 5150
99.7%
[ 16
 
0.3%
Space Separator
ValueCountFrequency (%)
3538
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1075
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39577
51.3%
Hangul 36261
47.0%
Latin 1313
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 2554
 
7.0%
동 2307
 
6.4%
로 1796
 
5.0%
원 1568
 
4.3%
공 1523
 
4.2%
방 1414
 
3.9%
범 1409
 
3.9%
길 1391
 
3.8%
상 1334
 
3.7%
릉 790
 
2.2%
Other values (387) 20175
55.6%
Latin
ValueCountFrequency (%)
D 1028
78.3%
c 80
 
6.1%
h 78
 
5.9%
G 28
 
2.1%
K 14
 
1.1%
M 11
 
0.8%
S 10
 
0.8%
V 7
 
0.5%
E 7
 
0.5%
T 7
 
0.5%
Other values (18) 43
 
3.3%
Common
ValueCountFrequency (%)
) 5154
13.0%
( 5150
13.0%
1 4423
11.2%
3538
8.9%
2 3234
8.2%
. 2655
 
6.7%
3 2420
 
6.1%
0 2295
 
5.8%
4 2118
 
5.4%
5 1709
 
4.3%
Other values (12) 6881
17.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40890
53.0%
Hangul 36261
47.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 5154
12.6%
( 5150
12.6%
1 4423
10.8%
3538
8.7%
2 3234
 
7.9%
. 2655
 
6.5%
3 2420
 
5.9%
0 2295
 
5.6%
4 2118
 
5.2%
5 1709
 
4.2%
Other values (40) 8194
20.0%
Hangul
ValueCountFrequency (%)
계 2554
 
7.0%
동 2307
 
6.4%
로 1796
 
5.0%
원 1568
 
4.3%
공 1523
 
4.2%
방 1414
 
3.9%
범 1409
 
3.9%
길 1391
 
3.8%
상 1334
 
3.7%
릉 790
 
2.2%
Other values (387) 20175
55.6%

위도
Real number (ℝ)

Distinct620
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.645818
Minimum37.6146
Maximum37.6876
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.5 KiB
2024-03-13T22:15:02.902516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.6146
5-th percentile37.619
Q137.6266
median37.6473
Q337.66265
95-th percentile37.6744
Maximum37.6876
Range0.073
Interquartile range (IQR)0.03605

Descriptive statistics

Standard deviation0.019342287
Coefficient of variation (CV)0.00051379643
Kurtosis-1.3727058
Mean37.645818
Median Absolute Deviation (MAD)0.0185
Skewness0.063622143
Sum99949.647
Variance0.00037412407
MonotonicityNot monotonic
2024-03-13T22:15:03.089270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6252 18
 
0.7%
37.652 16
 
0.6%
37.6597 16
 
0.6%
37.6247 16
 
0.6%
37.6298 15
 
0.6%
37.6231 15
 
0.6%
37.6223 15
 
0.6%
37.6578 15
 
0.6%
37.6674 14
 
0.5%
37.6232 14
 
0.5%
Other values (610) 2501
94.2%
ValueCountFrequency (%)
37.6146 1
 
< 0.1%
37.6147 2
 
0.1%
37.6149 1
 
< 0.1%
37.615 5
0.2%
37.6151 1
 
< 0.1%
37.6152 7
0.3%
37.6153 4
0.2%
37.6154 1
 
< 0.1%
37.6155 1
 
< 0.1%
37.6156 3
0.1%
ValueCountFrequency (%)
37.6876 1
< 0.1%
37.687 1
< 0.1%
37.6868 1
< 0.1%
37.6867 1
< 0.1%
37.6865 1
< 0.1%
37.6861 1
< 0.1%
37.6852 1
< 0.1%
37.6851 1
< 0.1%
37.6848 1
< 0.1%
37.6846 2
0.1%

경도
Real number (ℝ)

Distinct462
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06908
Minimum127.0418
Maximum127.1119
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.5 KiB
2024-03-13T22:15:03.241451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0418
5-th percentile127.0519
Q1127.06005
median127.0697
Q3127.07665
95-th percentile127.0854
Maximum127.1119
Range0.0701
Interquartile range (IQR)0.0166

Descriptive statistics

Standard deviation0.011190185
Coefficient of variation (CV)8.806379 × 10-5
Kurtosis0.2827009
Mean127.06908
Median Absolute Deviation (MAD)0.0082
Skewness0.29731756
Sum337368.42
Variance0.00012522024
MonotonicityNot monotonic
2024-03-13T22:15:03.775559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0578 21
 
0.8%
127.0673 21
 
0.8%
127.0625 19
 
0.7%
127.0743 19
 
0.7%
127.0709 18
 
0.7%
127.0739 18
 
0.7%
127.0808 17
 
0.6%
127.0723 17
 
0.6%
127.0712 17
 
0.6%
127.0768 16
 
0.6%
Other values (452) 2472
93.1%
ValueCountFrequency (%)
127.0418 1
 
< 0.1%
127.0426 2
 
0.1%
127.0427 2
 
0.1%
127.0435 3
0.1%
127.0436 1
 
< 0.1%
127.0438 1
 
< 0.1%
127.0439 1
 
< 0.1%
127.044 1
 
< 0.1%
127.0443 5
0.2%
127.0445 1
 
< 0.1%
ValueCountFrequency (%)
127.1119 1
 
< 0.1%
127.1117 1
 
< 0.1%
127.1113 2
0.1%
127.1112 1
 
< 0.1%
127.1108 2
0.1%
127.1107 4
0.2%
127.1099 1
 
< 0.1%
127.1089 1
 
< 0.1%
127.108 1
 
< 0.1%
127.1072 1
 
< 0.1%

CCTV 수량
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
1
2655 

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 2655
100.0%

Length

2024-03-13T22:15:03.950830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T22:15:04.057305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2655
100.0%

수정 일시
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size20.9 KiB
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-03-13T22:15:04.145296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:04.239378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-13T22:15:01.476424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:01.221848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:01.586723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T22:15:01.372798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T22:15:04.309546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.655
경도0.6551.000
2024-03-13T22:15:04.396844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.122
경도-0.1221.000

Missing values

2024-03-13T22:15:01.721134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:15:01.818110image/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
0노원구공원001(1).D(마들)한아름공원2(상계로1길34 상계10동)37.6578127.061312022-12-01
1노원구공원001(2).(마들)한아름공원2(상계로1길34 상계10동)37.6575127.061412022-12-01
2노원구공원002(1).(마들)용화공원1(동일로221길32 상계10동)37.6591127.056812022-12-01
3노원구공원002(2).(마들)용화공원2(동일로221길32 상계10동)37.659127.056512022-12-01
4노원구공원003(1).D(마들)종달새공원1(한글비석로54길92 상계9동)37.6683127.06212022-12-01
5노원구공원003(2).D(마들)종달새공원2(한글비석로54길92 상계9동)37.6679127.062112022-12-01
6노원구공원003(3).D(마들)종달새공원3(한글비석로54길92 상계9동)37.6682127.062212022-12-01
7노원구공원004(1).D(마들)민들레공원1(노원로564 상계8동)37.6627127.056212022-12-01
8노원구공원004(2).(마들)민들레공원2(노원로564 상계8동)37.6629127.056612022-12-01
9노원구공원004(3).(마들)민들레공원3(노원로564 상계8동)37.663127.056112022-12-01
자치구안심 주소위도경도CCTV 수량수정 일시
2645노원구학교040(1).*ADT보안*(화랑)태릉초 운동장37.623127.085412022-12-01
2646노원구학교040(2).(화랑)태릉초 정문37.623127.085412022-12-01
2647노원구학교041(1).(월계)한천초1-1학교정문5ch37.6205127.068912022-12-01
2648노원구학교041(2).(월계)한천초1-2서관좌측뒷편6ch37.6205127.068912022-12-01
2649노원구학교041(3).(월계)한천초1-3본관좌측뒷편7ch37.6205127.068812022-12-01
2650노원구학교041(4).(월계)한천초1-4본관우측뒷편8ch37.6205127.068912022-12-01
2651노원구학교042(1).(화랑)화랑초137.6282127.093912022-12-01
2652노원구학교042(2).(화랑)화랑초237.6282127.093912022-12-01
2653노원구학교042(3).(화랑)화랑초337.6282127.093912022-12-01
2654노원구학교042(4).(화랑)화랑초437.6282127.093912022-12-01