Overview

Dataset statistics

Number of variables11
Number of observations1559
Missing cells1526
Missing cells (%)8.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory140.2 KiB
Average record size in memory92.1 B

Variable types

Numeric4
Text4
Categorical3

Dataset

Description아이디,geometry,관리번호,관할경찰서,구,동,시설명,시설구분,주소,x좌표,y좌표
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-20448/S/1/datasetView.do

Alerts

구 is highly overall correlated with 아이디 and 4 other fieldsHigh correlation
관할경찰서 is highly overall correlated with 아이디 and 4 other fieldsHigh correlation
아이디 is highly overall correlated with x좌표 and 3 other fieldsHigh correlation
관리번호 is highly overall correlated with 관할경찰서 and 2 other fieldsHigh correlation
x좌표 is highly overall correlated with 아이디 and 2 other fieldsHigh correlation
y좌표 is highly overall correlated with 아이디 and 2 other fieldsHigh correlation
시설구분 is highly overall correlated with 관리번호High correlation
동 has 1526 (97.9%) missing valuesMissing
아이디 has unique valuesUnique
geometry has unique valuesUnique
관리번호 has 1426 (91.5%) zerosZeros

Reproduction

Analysis started2023-12-11 09:01:43.485551
Analysis finished2023-12-11 09:01:46.906700
Duration3.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct1559
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2455
Minimum1676
Maximum3234
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.8 KiB
2023-12-11T18:01:46.984847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1676
5-th percentile1753.9
Q12065.5
median2455
Q32844.5
95-th percentile3156.1
Maximum3234
Range1558
Interquartile range (IQR)779

Descriptive statistics

Standard deviation450.18885
Coefficient of variation (CV)0.18337631
Kurtosis-1.2
Mean2455
Median Absolute Deviation (MAD)390
Skewness0
Sum3827345
Variance202670
MonotonicityNot monotonic
2023-12-11T18:01:47.139607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1676 1
 
0.1%
2693 1
 
0.1%
2715 1
 
0.1%
2714 1
 
0.1%
2713 1
 
0.1%
2712 1
 
0.1%
2711 1
 
0.1%
2710 1
 
0.1%
2709 1
 
0.1%
2708 1
 
0.1%
Other values (1549) 1549
99.4%
ValueCountFrequency (%)
1676 1
0.1%
1677 1
0.1%
1678 1
0.1%
1679 1
0.1%
1680 1
0.1%
1681 1
0.1%
1682 1
0.1%
1683 1
0.1%
1684 1
0.1%
1685 1
0.1%
ValueCountFrequency (%)
3234 1
0.1%
3233 1
0.1%
3232 1
0.1%
3231 1
0.1%
3230 1
0.1%
3229 1
0.1%
3228 1
0.1%
3227 1
0.1%
3226 1
0.1%
3225 1
0.1%

geometry
Text

UNIQUE 

Distinct1559
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2023-12-11T18:01:47.375746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length45
Mean length44.764593
Min length42

Characters and Unicode

Total characters69788
Distinct characters22
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1559 ?
Unique (%)100.0%

Sample

1st rowMULTIPOINT(940171.377319983 1951156.86643105)
2nd rowMULTIPOINT(941481.739880848 1949806.32386183)
3rd rowMULTIPOINT(942024.423450618 1948312.2431702)
4th rowMULTIPOINT(941557.595955593 1948294.99871383)
5th rowMULTIPOINT(941611.621488849 1949180.52713669)
ValueCountFrequency (%)
multipoint(940171.377319983 1
 
< 0.1%
multipoint(967231.410133158 1
 
< 0.1%
multipoint(966937.193191544 1
 
< 0.1%
1950414.66528315 1
 
< 0.1%
multipoint(969336.558678788 1
 
< 0.1%
1949864.23192046 1
 
< 0.1%
multipoint(970313.310625373 1
 
< 0.1%
1949713.48052927 1
 
< 0.1%
multipoint(967577.180948068 1
 
< 0.1%
1949903.75433249 1
 
< 0.1%
Other values (3108) 3108
99.7%
2023-12-11T18:01:47.721280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 7087
 
10.2%
1 5498
 
7.9%
4 5130
 
7.4%
5 4956
 
7.1%
6 4460
 
6.4%
3 4000
 
5.7%
7 3937
 
5.6%
8 3908
 
5.6%
2 3863
 
5.5%
0 3564
 
5.1%
Other values (12) 23385
33.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46403
66.5%
Uppercase Letter 15590
 
22.3%
Other Punctuation 3118
 
4.5%
Open Punctuation 1559
 
2.2%
Space Separator 1559
 
2.2%
Close Punctuation 1559
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 7087
15.3%
1 5498
11.8%
4 5130
11.1%
5 4956
10.7%
6 4460
9.6%
3 4000
8.6%
7 3937
8.5%
8 3908
8.4%
2 3863
8.3%
0 3564
7.7%
Uppercase Letter
ValueCountFrequency (%)
I 3118
20.0%
T 3118
20.0%
U 1559
10.0%
N 1559
10.0%
O 1559
10.0%
P 1559
10.0%
L 1559
10.0%
M 1559
10.0%
Other Punctuation
ValueCountFrequency (%)
. 3118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1559
100.0%
Space Separator
ValueCountFrequency (%)
1559
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1559
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 54198
77.7%
Latin 15590
 
22.3%

Most frequent character per script

Common
ValueCountFrequency (%)
9 7087
13.1%
1 5498
10.1%
4 5130
9.5%
5 4956
9.1%
6 4460
8.2%
3 4000
7.4%
7 3937
7.3%
8 3908
7.2%
2 3863
7.1%
0 3564
6.6%
Other values (4) 7795
14.4%
Latin
ValueCountFrequency (%)
I 3118
20.0%
T 3118
20.0%
U 1559
10.0%
N 1559
10.0%
O 1559
10.0%
P 1559
10.0%
L 1559
10.0%
M 1559
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69788
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 7087
 
10.2%
1 5498
 
7.9%
4 5130
 
7.4%
5 4956
 
7.1%
6 4460
 
6.4%
3 4000
 
5.7%
7 3937
 
5.6%
8 3908
 
5.6%
2 3863
 
5.5%
0 3564
 
5.1%
Other values (12) 23385
33.5%

관리번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct134
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.710712
Minimum0
Maximum708
Zeros1426
Zeros (%)91.5%
Negative0
Negative (%)0.0%
Memory size13.8 KiB
2023-12-11T18:01:47.854678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile615.1
Maximum708
Range708
Interquartile range (IQR)0

Descriptive statistics

Standard deviation159.20489
Coefficient of variation (CV)3.6422398
Kurtosis10.646252
Mean43.710712
Median Absolute Deviation (MAD)0
Skewness3.533186
Sum68145
Variance25346.198
MonotonicityNot monotonic
2023-12-11T18:01:48.022367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1426
91.5%
611 1
 
0.1%
640 1
 
0.1%
633 1
 
0.1%
632 1
 
0.1%
631 1
 
0.1%
630 1
 
0.1%
629 1
 
0.1%
626 1
 
0.1%
625 1
 
0.1%
Other values (124) 124
 
8.0%
ValueCountFrequency (%)
0 1426
91.5%
84 1
 
0.1%
85 1
 
0.1%
86 1
 
0.1%
87 1
 
0.1%
88 1
 
0.1%
89 1
 
0.1%
90 1
 
0.1%
91 1
 
0.1%
92 1
 
0.1%
ValueCountFrequency (%)
708 1
0.1%
707 1
0.1%
706 1
0.1%
705 1
0.1%
704 1
0.1%
703 1
0.1%
702 1
0.1%
701 1
0.1%
700 1
0.1%
699 1
0.1%

관할경찰서
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
노원서
 
100
양천경찰서
 
96
송파경찰서
 
83
강동경찰서
 
82
광진경찰서
 
80
Other values (27)
1118 

Length

Max length12
Median length5
Mean length5.5214881
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
노원서 100
 
6.4%
양천경찰서 96
 
6.2%
송파경찰서 83
 
5.3%
강동경찰서 82
 
5.3%
광진경찰서 80
 
5.1%
강서경찰서 68
 
4.4%
수서경찰서 68
 
4.4%
영등포경찰서 65
 
4.2%
서울관악경찰서 65
 
4.2%
도봉경찰서 65
 
4.2%
Other values (22) 787
50.5%

Length

2023-12-11T18:01:48.160939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 124
 
7.4%
노원서 100
 
5.9%
양천경찰서 96
 
5.7%
송파경찰서 83
 
4.9%
강동경찰서 82
 
4.9%
광진경찰서 80
 
4.8%
강서경찰서 68
 
4.0%
수서경찰서 68
 
4.0%
영등포경찰서 65
 
3.9%
서울관악경찰서 65
 
3.9%
Other values (23) 852
50.6%

구
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
서울구
222 
노원구
100 
양천구
 
96
송파구
 
83
강동구
 
82
Other values (21)
976 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울구 222
 
14.2%
노원구 100
 
6.4%
양천구 96
 
6.2%
송파구 83
 
5.3%
강동구 82
 
5.3%
광진구 80
 
5.1%
강서구 68
 
4.4%
수서구 68
 
4.4%
영등구 65
 
4.2%
도봉구 65
 
4.2%
Other values (16) 630
40.4%

Length

2023-12-11T18:01:48.288647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울구 222
 
14.2%
노원구 100
 
6.4%
양천구 96
 
6.2%
송파구 83
 
5.3%
강동구 82
 
5.3%
광진구 80
 
5.1%
강서구 68
 
4.4%
수서구 68
 
4.4%
영등구 65
 
4.2%
도봉구 65
 
4.2%
Other values (16) 630
40.4%

동
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing1526
Missing (%)97.9%
Memory size12.3 KiB
2023-12-11T18:01:48.441707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.5757576
Min length2

Characters and Unicode

Total characters118
Distinct characters29
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row후암동
2nd row산천동
3rd row이촌
4th row원효로2가
5th row서빙고
ValueCountFrequency (%)
이촌동 6
18.2%
이태원동 3
 
9.1%
후암동 3
 
9.1%
산천동 3
 
9.1%
보광동 2
 
6.1%
한남동 2
 
6.1%
한강로2가 1
 
3.0%
용산동6가 1
 
3.0%
동빙고동 1
 
3.0%
청파동2가 1
 
3.0%
Other values (10) 10
30.3%
2023-12-11T18:01:48.751877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 28
23.7%
이 11
 
9.3%
가 7
 
5.9%
촌 7
 
5.9%
원 6
 
5.1%
한 5
 
4.2%
산 5
 
4.2%
2 5
 
4.2%
태 4
 
3.4%
로 3
 
2.5%
Other values (19) 37
31.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 109
92.4%
Decimal Number 9
 
7.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 28
25.7%
이 11
 
10.1%
가 7
 
6.4%
촌 7
 
6.4%
원 6
 
5.5%
한 5
 
4.6%
산 5
 
4.6%
태 4
 
3.7%
로 3
 
2.8%
남 3
 
2.8%
Other values (15) 30
27.5%
Decimal Number
ValueCountFrequency (%)
2 5
55.6%
3 2
 
22.2%
6 1
 
11.1%
1 1
 
11.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 109
92.4%
Common 9
 
7.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 28
25.7%
이 11
 
10.1%
가 7
 
6.4%
촌 7
 
6.4%
원 6
 
5.5%
한 5
 
4.6%
산 5
 
4.6%
태 4
 
3.7%
로 3
 
2.8%
남 3
 
2.8%
Other values (15) 30
27.5%
Common
ValueCountFrequency (%)
2 5
55.6%
3 2
 
22.2%
6 1
 
11.1%
1 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 109
92.4%
ASCII 9
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 28
25.7%
이 11
 
10.1%
가 7
 
6.4%
촌 7
 
6.4%
원 6
 
5.5%
한 5
 
4.6%
산 5
 
4.6%
태 4
 
3.7%
로 3
 
2.8%
남 3
 
2.8%
Other values (15) 30
27.5%
ASCII
ValueCountFrequency (%)
2 5
55.6%
3 2
 
22.2%
6 1
 
11.1%
1 1
 
11.1%

시설명
Text

Distinct1488
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2023-12-11T18:01:49.049979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length5.857601
Min length1

Characters and Unicode

Total characters9132
Distinct characters393
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1431 ?
Unique (%)91.8%

Sample

1st row공진초등학교병설유치원
2nd row윤희유치원
3rd row새화곡유치원
4th row수미유치원
5th row신월초등학교
ValueCountFrequency (%)
어린이집 14
 
0.9%
중복 8
 
0.5%
이화어린이집 4
 
0.3%
예일유치원 4
 
0.3%
서울유치원 3
 
0.2%
상아유치원 3
 
0.2%
새싹유치원 3
 
0.2%
연꽃어린이집 3
 
0.2%
삼성어린이집 3
 
0.2%
색동유치원 3
 
0.2%
Other values (1484) 1537
97.0%
2023-12-11T18:01:49.559101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
초 591
 
6.5%
교 576
 
6.3%
원 534
 
5.8%
유 482
 
5.3%
치 471
 
5.2%
등 454
 
5.0%
이 448
 
4.9%
학 443
 
4.9%
린 410
 
4.5%
어 405
 
4.4%
Other values (383) 4318
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9022
98.8%
Space Separator 26
 
0.3%
Open Punctuation 23
 
0.3%
Close Punctuation 23
 
0.3%
Decimal Number 21
 
0.2%
Uppercase Letter 13
 
0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 591
 
6.6%
교 576
 
6.4%
원 534
 
5.9%
유 482
 
5.3%
치 471
 
5.2%
등 454
 
5.0%
이 448
 
5.0%
학 443
 
4.9%
린 410
 
4.5%
어 405
 
4.5%
Other values (364) 4208
46.6%
Uppercase Letter
ValueCountFrequency (%)
C 2
15.4%
G 2
15.4%
S 2
15.4%
L 2
15.4%
E 1
7.7%
K 1
7.7%
D 1
7.7%
B 1
7.7%
O 1
7.7%
Decimal Number
ValueCountFrequency (%)
3 6
28.6%
2 5
23.8%
1 4
19.0%
4 3
14.3%
5 3
14.3%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9022
98.8%
Common 97
 
1.1%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
초 591
 
6.6%
교 576
 
6.4%
원 534
 
5.9%
유 482
 
5.3%
치 471
 
5.2%
등 454
 
5.0%
이 448
 
5.0%
학 443
 
4.9%
린 410
 
4.5%
어 405
 
4.5%
Other values (364) 4208
46.6%
Common
ValueCountFrequency (%)
26
26.8%
( 23
23.7%
) 23
23.7%
3 6
 
6.2%
2 5
 
5.2%
1 4
 
4.1%
4 3
 
3.1%
5 3
 
3.1%
, 2
 
2.1%
. 2
 
2.1%
Latin
ValueCountFrequency (%)
C 2
15.4%
G 2
15.4%
S 2
15.4%
L 2
15.4%
E 1
7.7%
K 1
7.7%
D 1
7.7%
B 1
7.7%
O 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9022
98.8%
ASCII 110
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
초 591
 
6.6%
교 576
 
6.4%
원 534
 
5.9%
유 482
 
5.3%
치 471
 
5.2%
등 454
 
5.0%
이 448
 
5.0%
학 443
 
4.9%
린 410
 
4.5%
어 405
 
4.5%
Other values (364) 4208
46.6%
ASCII
ValueCountFrequency (%)
26
23.6%
( 23
20.9%
) 23
20.9%
3 6
 
5.5%
2 5
 
4.5%
1 4
 
3.6%
4 3
 
2.7%
5 3
 
2.7%
, 2
 
1.8%
. 2
 
1.8%
Other values (9) 13
11.8%

시설구분
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
초등학교
537 
유치원
506 
어린이집
443 
초교
 
42
특수학교
 
26
Other values (3)
 
5

Length

Max length5
Median length4
Mean length3.6183451
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row유치원
2nd row유치원
3rd row유치원
4th row유치원
5th row초등학교

Common Values

ValueCountFrequency (%)
초등학교 537
34.4%
유치원 506
32.5%
어린이집 443
28.4%
초교 42
 
2.7%
특수학교 26
 
1.7%
학원 3
 
0.2%
외국인학교 1
 
0.1%
국제학교 1
 
0.1%

Length

2023-12-11T18:01:49.739487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T18:01:49.877317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등학교 537
34.4%
유치원 506
32.5%
어린이집 443
28.4%
초교 42
 
2.7%
특수학교 26
 
1.7%
학원 3
 
0.2%
외국인학교 1
 
0.1%
국제학교 1
 
0.1%

주소
Text

Distinct1532
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size12.3 KiB
2023-12-11T18:01:50.287237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length32
Mean length19.296344
Min length14

Characters and Unicode

Total characters30083
Distinct characters290
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1505 ?
Unique (%)96.5%

Sample

1st row서울특별시 강서구 마곡서로 33 (마곡동)
2nd row서울특별시 강서구 강서로 216-23
3rd row서울특별시 강서구 강서로15길 40 (화곡동)
4th row서울특별시 강서구 강서로17길 130 (화곡동)
5th row서울특별시 강서구 강서로31길 48 (화곡동)
ValueCountFrequency (%)
서울특별시 1425
 
22.2%
서울시 122
 
1.9%
강남구 100
 
1.6%
노원구 100
 
1.6%
양천구 96
 
1.5%
성북구 89
 
1.4%
송파구 83
 
1.3%
강동구 82
 
1.3%
광진구 80
 
1.2%
은평구 75
 
1.2%
Other values (1791) 4165
64.9%
2023-12-11T18:01:50.909859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4859
16.2%
서 1788
 
5.9%
구 1663
 
5.5%
시 1579
 
5.2%
울 1563
 
5.2%
로 1491
 
5.0%
특 1427
 
4.7%
별 1427
 
4.7%
1 1135
 
3.8%
길 1034
 
3.4%
Other values (280) 12117
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19181
63.8%
Decimal Number 5604
 
18.6%
Space Separator 4859
 
16.2%
Dash Punctuation 221
 
0.7%
Open Punctuation 105
 
0.3%
Close Punctuation 104
 
0.3%
Other Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1788
 
9.3%
구 1663
 
8.7%
시 1579
 
8.2%
울 1563
 
8.1%
로 1491
 
7.8%
특 1427
 
7.4%
별 1427
 
7.4%
길 1034
 
5.4%
동 569
 
3.0%
강 315
 
1.6%
Other values (264) 6325
33.0%
Decimal Number
ValueCountFrequency (%)
1 1135
20.3%
2 817
14.6%
3 687
12.3%
4 572
10.2%
5 495
8.8%
6 469
8.4%
7 397
 
7.1%
0 366
 
6.5%
9 334
 
6.0%
8 332
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 6
66.7%
@ 3
33.3%
Space Separator
ValueCountFrequency (%)
4859
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Open Punctuation
ValueCountFrequency (%)
( 105
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19181
63.8%
Common 10902
36.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1788
 
9.3%
구 1663
 
8.7%
시 1579
 
8.2%
울 1563
 
8.1%
로 1491
 
7.8%
특 1427
 
7.4%
별 1427
 
7.4%
길 1034
 
5.4%
동 569
 
3.0%
강 315
 
1.6%
Other values (264) 6325
33.0%
Common
ValueCountFrequency (%)
4859
44.6%
1 1135
 
10.4%
2 817
 
7.5%
3 687
 
6.3%
4 572
 
5.2%
5 495
 
4.5%
6 469
 
4.3%
7 397
 
3.6%
0 366
 
3.4%
9 334
 
3.1%
Other values (6) 771
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19181
63.8%
ASCII 10902
36.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4859
44.6%
1 1135
 
10.4%
2 817
 
7.5%
3 687
 
6.3%
4 572
 
5.2%
5 495
 
4.5%
6 469
 
4.3%
7 397
 
3.6%
0 366
 
3.4%
9 334
 
3.1%
Other values (6) 771
 
7.1%
Hangul
ValueCountFrequency (%)
서 1788
 
9.3%
구 1663
 
8.7%
시 1579
 
8.2%
울 1563
 
8.1%
로 1491
 
7.8%
특 1427
 
7.4%
별 1427
 
7.4%
길 1034
 
5.4%
동 569
 
3.0%
강 315
 
1.6%
Other values (264) 6325
33.0%

x좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct1547
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99483
Minimum126.80466
Maximum127.18027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.8 KiB
2023-12-11T18:01:51.101383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.80466
5-th percentile126.84085
Q1126.9168
median127.01463
Q3127.06551
95-th percentile127.13397
Maximum127.18027
Range0.37560476
Interquartile range (IQR)0.1487114

Descriptive statistics

Standard deviation0.090404765
Coefficient of variation (CV)0.00071187751
Kurtosis-0.99724641
Mean126.99483
Median Absolute Deviation (MAD)0.0686537
Skewness-0.19745174
Sum197984.94
Variance0.0081730216
MonotonicityNot monotonic
2023-12-11T18:01:51.269789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9058482 2
 
0.1%
127.100154 2
 
0.1%
126.9341059 2
 
0.1%
127.087327 2
 
0.1%
127.087521 2
 
0.1%
126.9166531 2
 
0.1%
126.9188333 2
 
0.1%
126.9074411 2
 
0.1%
126.9429033 2
 
0.1%
126.834631 2
 
0.1%
Other values (1537) 1539
98.7%
ValueCountFrequency (%)
126.8046641 1
0.1%
126.807498848 1
0.1%
126.808358 1
0.1%
126.809662 1
0.1%
126.810033 1
0.1%
126.8108471 1
0.1%
126.8110312 1
0.1%
126.81324 1
0.1%
126.8135129 1
0.1%
126.8146107 1
0.1%
ValueCountFrequency (%)
127.180268863 1
0.1%
127.1785799 1
0.1%
127.178320637 1
0.1%
127.1771117 1
0.1%
127.1749825 1
0.1%
127.1733219 1
0.1%
127.1723531 1
0.1%
127.1721839 1
0.1%
127.1694389 1
0.1%
127.169247681 1
0.1%

y좌표
Real number (ℝ)

HIGH CORRELATION 

Distinct1552
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.551865
Minimum37.440234
Maximum37.69452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size13.8 KiB
2023-12-11T18:01:51.443677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.440234
5-th percentile37.475241
Q137.505001
median37.546567
Q337.592014
95-th percentile37.652887
Maximum37.69452
Range0.2542862
Interquartile range (IQR)0.087012505

Descriptive statistics

Standard deviation0.05515548
Coefficient of variation (CV)0.0014687814
Kurtosis-0.74950167
Mean37.551865
Median Absolute Deviation (MAD)0.0430646
Skewness0.35258252
Sum58543.357
Variance0.003042127
MonotonicityNot monotonic
2023-12-11T18:01:51.913426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.52208 2
 
0.1%
37.534572 2
 
0.1%
37.497352 2
 
0.1%
37.5001667 2
 
0.1%
37.5796975 2
 
0.1%
37.5548546 2
 
0.1%
37.4808067 2
 
0.1%
37.5512241 1
 
0.1%
37.5409577 1
 
0.1%
37.5598384 1
 
0.1%
Other values (1542) 1542
98.9%
ValueCountFrequency (%)
37.440234 1
0.1%
37.441816 1
0.1%
37.446647 1
0.1%
37.446718 1
0.1%
37.447009 1
0.1%
37.447427 1
0.1%
37.447737 1
0.1%
37.448229 1
0.1%
37.448573 1
0.1%
37.448853 1
0.1%
ValueCountFrequency (%)
37.6945202 1
0.1%
37.6869304 1
0.1%
37.6863357 1
0.1%
37.6840158 1
0.1%
37.6796451 1
0.1%
37.6793783 1
0.1%
37.677656 1
0.1%
37.6761817 1
0.1%
37.6732055 1
0.1%
37.6729961 1
0.1%

Interactions

2023-12-11T18:01:46.180985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:44.517015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.116536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.702742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:46.289046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:44.660374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.293554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.826771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:46.390816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:44.800784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.443104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.935935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:46.505010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:44.952928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:45.585707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T18:01:46.055099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T18:01:52.053898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디관리번호관할경찰서구동시설구분x좌표y좌표
아이디1.0000.6820.9860.9710.8930.3900.8520.826
관리번호0.6821.0000.9720.945NaN0.8910.4460.592
관할경찰서0.9860.9721.0001.0000.0000.6080.9410.921
구0.9710.9451.0001.000NaN0.5650.9230.896
동0.893NaN0.000NaN1.0000.7490.8901.000
시설구분0.3900.8910.6080.5650.7491.0000.1960.316
x좌표0.8520.4460.9410.9230.8900.1961.0000.600
y좌표0.8260.5920.9210.8961.0000.3160.6001.000
2023-12-11T18:01:52.207904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구시설구분관할경찰서
구1.0000.2630.998
시설구분0.2631.0000.260
관할경찰서0.9980.2601.000
2023-12-11T18:01:52.315473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디관리번호x좌표y좌표관할경찰서구시설구분
아이디1.0000.3610.6970.6850.8940.8320.198
관리번호0.3611.0000.1930.3270.8050.8070.584
x좌표0.6970.1931.0000.2150.7050.6630.094
y좌표0.6850.3270.2151.0000.6460.5990.156
관할경찰서0.8940.8050.7050.6461.0000.9980.260
구0.8320.8070.6630.5990.9981.0000.263
시설구분0.1980.5840.0940.1560.2600.2631.000

Missing values

2023-12-11T18:01:46.669852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T18:01:46.830490image/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

아이디geometry관리번호관할경찰서구동시설명시설구분주소x좌표y좌표
01676MULTIPOINT(940171.377319983 1951156.86643105)0강서경찰서강서구<NA>공진초등학교병설유치원유치원서울특별시 강서구 마곡서로 33 (마곡동)126.82261137.557822
11677MULTIPOINT(941481.739880848 1949806.32386183)0강서경찰서강서구<NA>윤희유치원유치원서울특별시 강서구 강서로 216-23126.83755437.545734
21678MULTIPOINT(942024.423450618 1948312.2431702)0강서경찰서강서구<NA>새화곡유치원유치원서울특별시 강서구 강서로15길 40 (화곡동)126.84381537.532302
31679MULTIPOINT(941557.595955593 1948294.99871383)0강서경찰서강서구<NA>수미유치원유치원서울특별시 강서구 강서로17길 130 (화곡동)126.83853337.532117
41680MULTIPOINT(941611.621488849 1949180.52713669)0강서경찰서강서구<NA>신월초등학교초등학교서울특별시 강서구 강서로31길 48 (화곡동)126.83907437.540102
51681MULTIPOINT(940908.781288464 1950319.2395906)0강서경찰서강서구<NA>발산초등학교초등학교서울특별시 강서구 강서로45길 113 (내발산동)126.83102737.55032
61682MULTIPOINT(941498.992001786 1950418.01195721)0강서경찰서강서구<NA>내발산초등학교초등학교서울특별시 강서구 강서로46길 23 (내발산동)126.837737.551248
71683MULTIPOINT(940748.531735935 1950690.91428737)0강서경찰서강서구<NA>예일유치원유치원서울특별시 강서구 강서로47길 126126.82918337.55366
81684MULTIPOINT(941732.49644434 1951612.0899309)0강서경찰서강서구<NA>상아어린이집어린이집서울특별시 강서구 강서로56가길 55 (등촌동)126.84024937.562025
91685MULTIPOINT(942124.368255292 1951917.55934563)0강서경찰서강서구<NA>등양초등학교초등학교서울특별시 강서구 강서로56나길 140 (등촌동)126.84466237.564803
아이디geometry관리번호관할경찰서구동시설명시설구분주소x좌표y좌표
15493225MULTIPOINT(963017.627245734 1961253.93986542)692노원서노원구<NA>중계어린이집서울시 노원구 중계본동 364-5127.08076137.65003
15503226MULTIPOINT(961709.478998076 1962505.5564125)695노원서노원구<NA>상계삼성어린이집서울시 노원구 상계2동 430-5127.06586637.661258
15513227MULTIPOINT(961592.341084769 1961031.90108247)696노원서노원구<NA>성서대부설어린이집서울시 노원구 상계7동 205-1127.06461637.64797
15523228MULTIPOINT(962636.343987735 1959802.22901231)697노원서노원구<NA>하계어린이집서울시 노원구 하계1동 252-13127.07651337.63693
15533229MULTIPOINT(963251.054630275 1963685.92532543)701노원서노원구<NA>상계4동어린이집서울시 노원구 상계4동 48-11127.08328537.67196
15543230MULTIPOINT(962308.441537807 1960892.6519456)702노원서노원구<NA>꿈동산어린이집서울시 노원구 중계1동361-1127.0727437.646745
15553231MULTIPOINT(962360.408469301 1960632.07482687)704노원서노원구<NA>동천특수학교서울시 노원구 하계1동 288-1127.07334337.644399
15563232MULTIPOINT(962336.814524342 1959473.73714359)705노원서노원구<NA>정민특수학교서울시 노원구 공릉로58길 24127.07313537.633957
15573233MULTIPOINT(962141.991224926 1959486.86333818)707노원서노원구<NA>청솔창의어린이집서울시 노원구 공릉로59가길 13127.07092737.634068
15583234MULTIPOINT(963211.386262706 1960816.09481985)708노원서노원구<NA>중계행복어린이집서울시 노원구 중계로8길 17127.0829837.646092