Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells8140
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.0 MiB
Average record size in memory108.0 B

Variable types

Categorical4
Numeric4
Text3
DateTime1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
설치장소 is highly overall correlated with 민간공공구분명 and 1 other fieldsHigh correlation
민간공공구분명 is highly overall correlated with 설치장소High correlation
실내외구분명 is highly overall correlated with 설치장소High correlation
설치장소 is highly imbalanced (63.8%)Imbalance
실내외구분명 is highly imbalanced (70.6%)Imbalance
소재지우편번호 has 713 (7.1%) missing valuesMissing
소재지도로명주소 has 6883 (68.8%) missing valuesMissing
WGS84위도 has 272 (2.7%) missing valuesMissing
WGS84경도 has 272 (2.7%) missing valuesMissing
시설번호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:37:17.949273
Analysis finished2023-12-10 21:37:22.270239
Duration4.32 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
용인시
841 
화성시
839 
수원시
805 
고양시
782 
성남시
 
595
Other values (26)
6138 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화성시
2nd row고양시
3rd row시흥시
4th row용인시
5th row의정부

Common Values

ValueCountFrequency (%)
용인시 841
 
8.4%
화성시 839
 
8.4%
수원시 805
 
8.1%
고양시 782
 
7.8%
성남시 595
 
5.9%
남양주 564
 
5.6%
평택시 540
 
5.4%
시흥시 429
 
4.3%
부천시 404
 
4.0%
파주시 390
 
3.9%
Other values (21) 3811
38.1%

Length

2023-12-11T06:37:22.337910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 841
 
8.4%
화성시 839
 
8.4%
수원시 805
 
8.1%
고양시 782
 
7.8%
성남시 595
 
5.9%
남양주 564
 
5.6%
평택시 540
 
5.4%
시흥시 429
 
4.3%
부천시 404
 
4.0%
파주시 390
 
3.9%
Other values (21) 3811
38.1%

시설번호
Real number (ℝ)

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean327829.64
Minimum47
Maximum585604
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:22.445082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47
5-th percentile2256.35
Q123769.5
median526901
Q3558634.25
95-th percentile579040.15
Maximum585604
Range585557
Interquartile range (IQR)534864.75

Descriptive statistics

Standard deviation261938.41
Coefficient of variation (CV)0.79900771
Kurtosis-1.8864973
Mean327829.64
Median Absolute Deviation (MAD)48454.5
Skewness-0.30849508
Sum3.2782964 × 109
Variance6.8611731 × 1010
MonotonicityNot monotonic
2023-12-11T06:37:22.575843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
560369 1
 
< 0.1%
1188 1
 
< 0.1%
527755 1
 
< 0.1%
538631 1
 
< 0.1%
2488 1
 
< 0.1%
21091 1
 
< 0.1%
19504 1
 
< 0.1%
17981 1
 
< 0.1%
1417 1
 
< 0.1%
31072 1
 
< 0.1%
Other values (9990) 9990
99.9%
ValueCountFrequency (%)
47 1
< 0.1%
70 1
< 0.1%
75 1
< 0.1%
113 1
< 0.1%
133 1
< 0.1%
138 1
< 0.1%
150 1
< 0.1%
151 1
< 0.1%
152 1
< 0.1%
179 1
< 0.1%
ValueCountFrequency (%)
585604 1
< 0.1%
585602 1
< 0.1%
585598 1
< 0.1%
585530 1
< 0.1%
585529 1
< 0.1%
585465 1
< 0.1%
585463 1
< 0.1%
585447 1
< 0.1%
585444 1
< 0.1%
585403 1
< 0.1%

놀이시설명
Text

Distinct9955
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:37:22.847953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length42
Mean length18.5011
Min length2

Characters and Unicode

Total characters185011
Distinct characters784
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9911 ?
Unique (%)99.1%

Sample

1st row양우 내안애 2차 아파트 유아놀이터(어린이집 앞)
2nd row삼송우남퍼스트빌아파트102동앞놀이터
3rd row조남소공원
4th row만현근린공원 놀이터
5th row의정부 열방교회 내 실내놀이시설
ValueCountFrequency (%)
놀이터 2768
 
9.2%
앞 1185
 
4.0%
어린이놀이터 711
 
2.4%
옆 559
 
1.9%
놀이시설 490
 
1.6%
아파트 452
 
1.5%
어린이 409
 
1.4%
어린이공원 344
 
1.1%
유아놀이터 339
 
1.1%
뒤 294
 
1.0%
Other values (10616) 22384
74.8%
2023-12-11T06:37:23.332026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19935
 
10.8%
이 14145
 
7.6%
놀 7885
 
4.3%
터 6852
 
3.7%
1 6550
 
3.5%
동 6062
 
3.3%
아 5698
 
3.1%
린 5238
 
2.8%
어 4956
 
2.7%
트 4867
 
2.6%
Other values (774) 102823
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133876
72.4%
Decimal Number 23213
 
12.5%
Space Separator 19935
 
10.8%
Close Punctuation 2487
 
1.3%
Open Punctuation 2487
 
1.3%
Uppercase Letter 1563
 
0.8%
Dash Punctuation 738
 
0.4%
Lowercase Letter 383
 
0.2%
Other Punctuation 232
 
0.1%
Math Symbol 89
 
< 0.1%
Other values (2) 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 14145
 
10.6%
놀 7885
 
5.9%
터 6852
 
5.1%
동 6062
 
4.5%
아 5698
 
4.3%
린 5238
 
3.9%
어 4956
 
3.7%
트 4867
 
3.6%
파 4710
 
3.5%
지 2945
 
2.2%
Other values (695) 70518
52.7%
Uppercase Letter
ValueCountFrequency (%)
L 335
21.4%
B 198
12.7%
A 198
12.7%
H 140
9.0%
S 118
 
7.5%
C 102
 
6.5%
K 93
 
6.0%
G 61
 
3.9%
I 55
 
3.5%
E 34
 
2.2%
Other values (16) 229
14.7%
Lowercase Letter
ValueCountFrequency (%)
e 189
49.3%
a 23
 
6.0%
c 22
 
5.7%
i 16
 
4.2%
s 15
 
3.9%
m 15
 
3.9%
l 13
 
3.4%
k 13
 
3.4%
d 11
 
2.9%
r 9
 
2.3%
Other values (13) 57
 
14.9%
Decimal Number
ValueCountFrequency (%)
1 6550
28.2%
0 4166
17.9%
2 4087
17.6%
3 2263
 
9.7%
4 1530
 
6.6%
5 1370
 
5.9%
6 1054
 
4.5%
7 841
 
3.6%
8 730
 
3.1%
9 622
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 98
42.2%
. 41
17.7%
/ 34
 
14.7%
& 23
 
9.9%
' 13
 
5.6%
@ 10
 
4.3%
# 8
 
3.4%
· 3
 
1.3%
: 1
 
0.4%
! 1
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 2125
85.4%
] 362
 
14.6%
Open Punctuation
ValueCountFrequency (%)
( 2125
85.4%
[ 362
 
14.6%
Math Symbol
ValueCountFrequency (%)
~ 88
98.9%
+ 1
 
1.1%
Space Separator
ValueCountFrequency (%)
19935
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 738
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 7
100.0%
Other Symbol
ValueCountFrequency (%)
ⓐ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133875
72.4%
Common 49189
 
26.6%
Latin 1946
 
1.1%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 14145
 
10.6%
놀 7885
 
5.9%
터 6852
 
5.1%
동 6062
 
4.5%
아 5698
 
4.3%
린 5238
 
3.9%
어 4956
 
3.7%
트 4867
 
3.6%
파 4710
 
3.5%
지 2945
 
2.2%
Other values (694) 70517
52.7%
Latin
ValueCountFrequency (%)
L 335
17.2%
B 198
10.2%
A 198
10.2%
e 189
9.7%
H 140
 
7.2%
S 118
 
6.1%
C 102
 
5.2%
K 93
 
4.8%
G 61
 
3.1%
I 55
 
2.8%
Other values (39) 457
23.5%
Common
ValueCountFrequency (%)
19935
40.5%
1 6550
 
13.3%
0 4166
 
8.5%
2 4087
 
8.3%
3 2263
 
4.6%
) 2125
 
4.3%
( 2125
 
4.3%
4 1530
 
3.1%
5 1370
 
2.8%
6 1054
 
2.1%
Other values (20) 3984
 
8.1%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133875
72.4%
ASCII 51131
 
27.6%
None 3
 
< 0.1%
CJK 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19935
39.0%
1 6550
 
12.8%
0 4166
 
8.1%
2 4087
 
8.0%
3 2263
 
4.4%
) 2125
 
4.2%
( 2125
 
4.2%
4 1530
 
3.0%
5 1370
 
2.7%
6 1054
 
2.1%
Other values (67) 5926
 
11.6%
Hangul
ValueCountFrequency (%)
이 14145
 
10.6%
놀 7885
 
5.9%
터 6852
 
5.1%
동 6062
 
4.5%
아 5698
 
4.3%
린 5238
 
3.9%
어 4956
 
3.7%
트 4867
 
3.6%
파 4710
 
3.5%
지 2945
 
2.2%
Other values (694) 70517
52.7%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
內 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓐ 1
100.0%

설치일자
Date

Distinct3934
Distinct (%)39.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1979-05-30 00:00:00
Maximum2022-12-12 00:00:00
2023-12-11T06:37:23.490393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:23.635066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

설치장소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
주택단지
6855 
도시공원
1651 
어린이집
1015 
놀이제공영업소
 
155
식품접객업소
 
138
Other values (12)
 
186

Length

Max length7
Median length4
Mean length4.083
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row주택단지
2nd row주택단지
3rd row도시공원
4th row도시공원
5th row종교시설

Common Values

ValueCountFrequency (%)
주택단지 6855
68.5%
도시공원 1651
 
16.5%
어린이집 1015
 
10.2%
놀이제공영업소 155
 
1.6%
식품접객업소 138
 
1.4%
주상복합 50
 
0.5%
종교시설 36
 
0.4%
아동복지시설 30
 
0.3%
목욕장업소 17
 
0.2%
대규모점포 14
 
0.1%
Other values (7) 39
 
0.4%

Length

2023-12-11T06:37:23.787181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
주택단지 6855
68.5%
도시공원 1651
 
16.5%
어린이집 1015
 
10.2%
놀이제공영업소 155
 
1.6%
식품접객업소 138
 
1.4%
주상복합 50
 
0.5%
종교시설 36
 
0.4%
아동복지시설 30
 
0.3%
목욕장업소 17
 
0.2%
대규모점포 14
 
0.1%
Other values (7) 39
 
0.4%

민간공공구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
민간
7909 
공공
2091 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민간
2nd row민간
3rd row민간
4th row공공
5th row민간

Common Values

ValueCountFrequency (%)
민간 7909
79.1%
공공 2091
 
20.9%

Length

2023-12-11T06:37:23.903177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:37:24.011511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 7909
79.1%
공공 2091
 
20.9%

실내외구분명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
실외
9481 
실내
 
519

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row실외
2nd row실외
3rd row실외
4th row실외
5th row실내

Common Values

ValueCountFrequency (%)
실외 9481
94.8%
실내 519
 
5.2%

Length

2023-12-11T06:37:24.117357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:37:24.212212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 9481
94.8%
실내 519
 
5.2%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct3233
Distinct (%)34.8%
Missing713
Missing (%)7.1%
Infinite0
Infinite (%)0.0%
Mean14375.466
Minimum10005
Maximum18632
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:24.405304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10005
5-th percentile10275.9
Q111942
median14426
Q316864.5
95-th percentile18391.7
Maximum18632
Range8627
Interquartile range (IQR)4922.5

Descriptive statistics

Standard deviation2698.9724
Coefficient of variation (CV)0.18774851
Kurtosis-1.3351705
Mean14375.466
Median Absolute Deviation (MAD)2453
Skewness-0.05258228
Sum1.3350496 × 108
Variance7284451.8
MonotonicityNot monotonic
2023-12-11T06:37:24.596557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18477 21
 
0.2%
14996 20
 
0.2%
11812 20
 
0.2%
11801 18
 
0.2%
15010 18
 
0.2%
10073 18
 
0.2%
15002 18
 
0.2%
10077 17
 
0.2%
17821 17
 
0.2%
12248 17
 
0.2%
Other values (3223) 9103
91.0%
(Missing) 713
 
7.1%
ValueCountFrequency (%)
10005 1
 
< 0.1%
10008 1
 
< 0.1%
10012 1
 
< 0.1%
10017 4
< 0.1%
10018 2
 
< 0.1%
10019 7
0.1%
10021 1
 
< 0.1%
10024 1
 
< 0.1%
10031 6
0.1%
10032 3
< 0.1%
ValueCountFrequency (%)
18632 1
 
< 0.1%
18623 1
 
< 0.1%
18618 2
 
< 0.1%
18616 1
 
< 0.1%
18615 3
 
< 0.1%
18614 2
 
< 0.1%
18613 10
0.1%
18612 1
 
< 0.1%
18611 1
 
< 0.1%
18610 7
0.1%

소재지도로명주소
Text

MISSING 

Distinct2505
Distinct (%)80.4%
Missing6883
Missing (%)68.8%
Memory size156.2 KiB
2023-12-11T06:37:24.906250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length19.255374
Min length13

Characters and Unicode

Total characters60019
Distinct characters368
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2090 ?
Unique (%)67.1%

Sample

1st row경기도 화성시 남양읍 시청로32번길 74-2
2nd row경기도 의정부시 부용로 168
3rd row경기도 김포시 김포한강11로 37
4th row경기도 남양주시 순화궁로 458-58
5th row경기도 화성시 노작로4길 18-37
ValueCountFrequency (%)
경기도 3117
 
22.1%
화성시 251
 
1.8%
성남시 246
 
1.7%
수원시 231
 
1.6%
고양시 226
 
1.6%
용인시 173
 
1.2%
분당구 154
 
1.1%
광주시 153
 
1.1%
남양주시 151
 
1.1%
파주시 147
 
1.0%
Other values (2954) 9224
65.5%
2023-12-11T06:37:25.362810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10956
18.3%
기 3242
 
5.4%
경 3235
 
5.4%
도 3205
 
5.3%
시 3200
 
5.3%
로 2827
 
4.7%
1 2371
 
4.0%
2 1610
 
2.7%
길 1368
 
2.3%
3 1216
 
2.0%
Other values (358) 26789
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37281
62.1%
Decimal Number 11124
 
18.5%
Space Separator 10956
 
18.3%
Dash Punctuation 658
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3242
 
8.7%
경 3235
 
8.7%
도 3205
 
8.6%
시 3200
 
8.6%
로 2827
 
7.6%
길 1368
 
3.7%
구 1145
 
3.1%
번 959
 
2.6%
양 888
 
2.4%
성 638
 
1.7%
Other values (346) 16574
44.5%
Decimal Number
ValueCountFrequency (%)
1 2371
21.3%
2 1610
14.5%
3 1216
10.9%
5 989
8.9%
4 943
 
8.5%
0 894
 
8.0%
6 851
 
7.7%
7 848
 
7.6%
8 707
 
6.4%
9 695
 
6.2%
Space Separator
ValueCountFrequency (%)
10956
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 658
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37281
62.1%
Common 22738
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3242
 
8.7%
경 3235
 
8.7%
도 3205
 
8.6%
시 3200
 
8.6%
로 2827
 
7.6%
길 1368
 
3.7%
구 1145
 
3.1%
번 959
 
2.6%
양 888
 
2.4%
성 638
 
1.7%
Other values (346) 16574
44.5%
Common
ValueCountFrequency (%)
10956
48.2%
1 2371
 
10.4%
2 1610
 
7.1%
3 1216
 
5.3%
5 989
 
4.3%
4 943
 
4.1%
0 894
 
3.9%
6 851
 
3.7%
7 848
 
3.7%
8 707
 
3.1%
Other values (2) 1353
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37281
62.1%
ASCII 22738
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10956
48.2%
1 2371
 
10.4%
2 1610
 
7.1%
3 1216
 
5.3%
5 989
 
4.3%
4 943
 
4.1%
0 894
 
3.9%
6 851
 
3.7%
7 848
 
3.7%
8 707
 
3.1%
Other values (2) 1353
 
6.0%
Hangul
ValueCountFrequency (%)
기 3242
 
8.7%
경 3235
 
8.7%
도 3205
 
8.6%
시 3200
 
8.6%
로 2827
 
7.6%
길 1368
 
3.7%
구 1145
 
3.1%
번 959
 
2.6%
양 888
 
2.4%
성 638
 
1.7%
Other values (346) 16574
44.5%

소재지지번주소
Text

Distinct7348
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T06:37:25.682470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length54
Mean length27.28
Min length11

Characters and Unicode

Total characters272800
Distinct characters646
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5609 ?
Unique (%)56.1%

Sample

1st row경기도 화성시 남양읍 남양리 2309-4번지 남양읍 남양리 1813-1
2nd row경기도 고양시 덕양구 신원동 609번지 우남퍼스트빌아파트
3rd row경기도 시흥시 조남동 175-5번지
4th row경기도 용인시 수지구 상현동 37일원
5th row경기도 의정부시 신곡동 767-3번지
ValueCountFrequency (%)
경기도 10014
 
18.4%
화성시 844
 
1.6%
용인시 842
 
1.5%
수원시 807
 
1.5%
고양시 783
 
1.4%
성남시 596
 
1.1%
남양주시 567
 
1.0%
평택시 538
 
1.0%
분당구 471
 
0.9%
시흥시 428
 
0.8%
Other values (10154) 38509
70.8%
2023-12-11T06:37:26.173966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44399
 
16.3%
시 11111
 
4.1%
지 10822
 
4.0%
기 10617
 
3.9%
동 10574
 
3.9%
도 10523
 
3.9%
경 10165
 
3.7%
번 8134
 
3.0%
1 8120
 
3.0%
2 4890
 
1.8%
Other values (636) 143445
52.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182213
66.8%
Space Separator 44399
 
16.3%
Decimal Number 40815
 
15.0%
Dash Punctuation 3842
 
1.4%
Uppercase Letter 688
 
0.3%
Close Punctuation 249
 
0.1%
Open Punctuation 238
 
0.1%
Other Punctuation 184
 
0.1%
Lowercase Letter 156
 
0.1%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 11111
 
6.1%
지 10822
 
5.9%
기 10617
 
5.8%
동 10574
 
5.8%
도 10523
 
5.8%
경 10165
 
5.6%
번 8134
 
4.5%
파 4643
 
2.5%
아 4599
 
2.5%
트 4339
 
2.4%
Other values (567) 96686
53.1%
Uppercase Letter
ValueCountFrequency (%)
L 124
18.0%
H 68
9.9%
B 67
9.7%
A 53
 
7.7%
S 42
 
6.1%
C 40
 
5.8%
K 36
 
5.2%
I 36
 
5.2%
E 32
 
4.7%
G 32
 
4.7%
Other values (15) 158
23.0%
Lowercase Letter
ValueCountFrequency (%)
e 96
61.5%
t 8
 
5.1%
s 8
 
5.1%
h 7
 
4.5%
l 6
 
3.8%
a 6
 
3.8%
k 4
 
2.6%
i 4
 
2.6%
n 4
 
2.6%
r 3
 
1.9%
Other values (5) 10
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 8120
19.9%
2 4890
12.0%
3 4007
9.8%
5 3878
9.5%
6 3686
9.0%
4 3506
8.6%
7 3415
8.4%
0 3317
8.1%
8 3215
 
7.9%
9 2781
 
6.8%
Other Punctuation
ValueCountFrequency (%)
, 74
40.2%
. 45
24.5%
* 27
 
14.7%
& 16
 
8.7%
@ 10
 
5.4%
? 4
 
2.2%
' 3
 
1.6%
· 2
 
1.1%
/ 2
 
1.1%
# 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 238
95.6%
] 11
 
4.4%
Open Punctuation
ValueCountFrequency (%)
( 237
99.6%
[ 1
 
0.4%
Letter Number
ValueCountFrequency (%)
Ⅰ 4
57.1%
Ⅱ 3
42.9%
Space Separator
ValueCountFrequency (%)
44399
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3842
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182213
66.8%
Common 89736
32.9%
Latin 851
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 11111
 
6.1%
지 10822
 
5.9%
기 10617
 
5.8%
동 10574
 
5.8%
도 10523
 
5.8%
경 10165
 
5.6%
번 8134
 
4.5%
파 4643
 
2.5%
아 4599
 
2.5%
트 4339
 
2.4%
Other values (567) 96686
53.1%
Latin
ValueCountFrequency (%)
L 124
14.6%
e 96
 
11.3%
H 68
 
8.0%
B 67
 
7.9%
A 53
 
6.2%
S 42
 
4.9%
C 40
 
4.7%
K 36
 
4.2%
I 36
 
4.2%
E 32
 
3.8%
Other values (32) 257
30.2%
Common
ValueCountFrequency (%)
44399
49.5%
1 8120
 
9.0%
2 4890
 
5.4%
3 4007
 
4.5%
5 3878
 
4.3%
- 3842
 
4.3%
6 3686
 
4.1%
4 3506
 
3.9%
7 3415
 
3.8%
0 3317
 
3.7%
Other values (17) 6676
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182213
66.8%
ASCII 90578
33.2%
Number Forms 7
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44399
49.0%
1 8120
 
9.0%
2 4890
 
5.4%
3 4007
 
4.4%
5 3878
 
4.3%
- 3842
 
4.2%
6 3686
 
4.1%
4 3506
 
3.9%
7 3415
 
3.8%
0 3317
 
3.7%
Other values (56) 7518
 
8.3%
Hangul
ValueCountFrequency (%)
시 11111
 
6.1%
지 10822
 
5.9%
기 10617
 
5.8%
동 10574
 
5.8%
도 10523
 
5.8%
경 10165
 
5.6%
번 8134
 
4.5%
파 4643
 
2.5%
아 4599
 
2.5%
트 4339
 
2.4%
Other values (567) 96686
53.1%
Number Forms
ValueCountFrequency (%)
Ⅰ 4
57.1%
Ⅱ 3
42.9%
None
ValueCountFrequency (%)
· 2
100.0%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6879
Distinct (%)70.7%
Missing272
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean37.427324
Minimum36.917932
Maximum38.186131
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:26.342247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.917932
5-th percentile37.028574
Q137.273307
median37.387994
Q337.6333
95-th percentile37.794989
Maximum38.186131
Range1.2681992
Interquartile range (IQR)0.35999294

Descriptive statistics

Standard deviation0.223819
Coefficient of variation (CV)0.0059800962
Kurtosis-0.6053108
Mean37.427324
Median Absolute Deviation (MAD)0.15205514
Skewness0.18437497
Sum364093
Variance0.050094943
MonotonicityNot monotonic
2023-12-11T06:37:26.524602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6125660977 15
 
0.1%
37.2906724622 15
 
0.1%
37.2824070365 12
 
0.1%
37.2149961413 9
 
0.1%
37.4021652448 8
 
0.1%
37.4037084416 7
 
0.1%
37.8366765785 7
 
0.1%
37.3061998631 7
 
0.1%
37.3886415556 7
 
0.1%
37.7204522899 6
 
0.1%
Other values (6869) 9635
96.4%
(Missing) 272
 
2.7%
ValueCountFrequency (%)
36.9179319073 1
< 0.1%
36.9465248786 1
< 0.1%
36.94945876 1
< 0.1%
36.9512029715 1
< 0.1%
36.9514855353 2
< 0.1%
36.9538844365 1
< 0.1%
36.9593272603 1
< 0.1%
36.9601679407 1
< 0.1%
36.9605574419 1
< 0.1%
36.9608411003 1
< 0.1%
ValueCountFrequency (%)
38.1861311085 1
< 0.1%
38.1588427797 1
< 0.1%
38.1325683156 1
< 0.1%
38.1104969084 1
< 0.1%
38.1071229181 1
< 0.1%
38.1002377523 1
< 0.1%
38.0965747977 1
< 0.1%
38.0964663782 1
< 0.1%
38.0927508943 1
< 0.1%
38.091908273 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct6879
Distinct (%)70.7%
Missing272
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean127.0071
Minimum126.53928
Maximum127.7526
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T06:37:26.692881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53928
5-th percentile126.72939
Q1126.84725
median127.04635
Q3127.11948
95-th percentile127.27525
Maximum127.7526
Range1.2133201
Interquartile range (IQR)0.27223079

Descriptive statistics

Standard deviation0.18529371
Coefficient of variation (CV)0.0014589241
Kurtosis0.34968338
Mean127.0071
Median Absolute Deviation (MAD)0.11364516
Skewness0.3117261
Sum1235525
Variance0.03433376
MonotonicityNot monotonic
2023-12-11T06:37:26.907373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1636654206 15
 
0.1%
126.9822790737 15
 
0.1%
127.1464705534 12
 
0.1%
126.9672021678 9
 
0.1%
126.9409396103 8
 
0.1%
127.1265576724 7
 
0.1%
127.0657668664 7
 
0.1%
127.008950211 7
 
0.1%
126.9252474217 7
 
0.1%
127.4626459361 6
 
0.1%
Other values (6869) 9635
96.4%
(Missing) 272
 
2.7%
ValueCountFrequency (%)
126.5392751662 1
< 0.1%
126.5522087631 1
< 0.1%
126.5537612382 1
< 0.1%
126.5815586321 1
< 0.1%
126.5829156098 1
< 0.1%
126.5832397985 1
< 0.1%
126.5921729358 1
< 0.1%
126.5934489809 1
< 0.1%
126.5939262162 1
< 0.1%
126.5940538809 1
< 0.1%
ValueCountFrequency (%)
127.7525953082 1
< 0.1%
127.7510094024 1
< 0.1%
127.7118364861 1
< 0.1%
127.6737569576 1
< 0.1%
127.6683175492 1
< 0.1%
127.6670927764 1
< 0.1%
127.6610453985 1
< 0.1%
127.6602708537 2
< 0.1%
127.6550106609 1
< 0.1%
127.6521603507 1
< 0.1%

Interactions

2023-12-11T06:37:21.465627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:19.925085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.443347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.843130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:21.556845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.019170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.560777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:21.197256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:21.637958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.168627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.658035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:21.276734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:21.726329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.316373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:20.750640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:37:21.368768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:37:27.036258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명시설번호설치장소민간공공구분명실내외구분명소재지우편번호WGS84위도WGS84경도
시군명1.0000.4460.3260.1320.1290.9910.9520.937
시설번호0.4461.0000.2630.0370.1240.2620.1910.156
설치장소0.3260.2631.0000.8910.8090.1480.2510.208
민간공공구분명0.1320.0370.8911.0000.1290.0860.1010.104
실내외구분명0.1290.1240.8090.1291.0000.0460.0000.074
소재지우편번호0.9910.2620.1480.0860.0461.0000.9120.848
WGS84위도0.9520.1910.2510.1010.0000.9121.0000.639
WGS84경도0.9370.1560.2080.1040.0740.8480.6391.000
2023-12-11T06:37:27.176981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명실내외구분명민간공공구분명설치장소
시군명1.0000.1100.1120.097
실내외구분명0.1101.0000.0830.755
민간공공구분명0.1120.0831.0000.854
설치장소0.0970.7550.8541.000
2023-12-11T06:37:27.611184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설번호소재지우편번호WGS84위도WGS84경도시군명설치장소민간공공구분명실내외구분명
시설번호1.0000.037-0.0660.0810.2530.1460.0610.205
소재지우편번호0.0371.000-0.9240.2400.9260.0580.0660.035
WGS84위도-0.066-0.9241.000-0.2100.7420.1000.0770.000
WGS84경도0.0810.240-0.2101.0000.6920.0820.0800.057
시군명0.2530.9260.7420.6921.0000.0970.1120.110
설치장소0.1460.0580.1000.0820.0971.0000.8540.755
민간공공구분명0.0610.0660.0770.0800.1120.8541.0000.083
실내외구분명0.2050.0350.0000.0570.1100.7550.0831.000

Missing values

2023-12-11T06:37:21.888724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:37:22.058785image/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.
2023-12-11T06:37:22.192769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명시설번호놀이시설명설치일자설치장소민간공공구분명실내외구분명소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도
16776화성시560369양우 내안애 2차 아파트 유아놀이터(어린이집 앞)2017-06-23주택단지민간실외18268경기도 화성시 남양읍 시청로32번길 74-2경기도 화성시 남양읍 남양리 2309-4번지 남양읍 남양리 1813-137.201119126.821616
299고양시552416삼송우남퍼스트빌아파트102동앞놀이터2015-07-21주택단지민간실외10579<NA>경기도 고양시 덕양구 신원동 609번지 우남퍼스트빌아파트37.66807126.889446
9016시흥시572938조남소공원2020-03-01도시공원민간실외14984<NA>경기도 시흥시 조남동 175-5번지37.382385126.857294
12553용인시532042만현근린공원 놀이터2012-04-19도시공원공공실외16928<NA>경기도 용인시 수지구 상현동 37일원37.310542127.089854
13896의정부574189의정부 열방교회 내 실내놀이시설2020-06-02종교시설민간실내11774경기도 의정부시 부용로 168경기도 의정부시 신곡동 767-3번지37.75225127.075512
17326화성시23599한울마을 신창비바패밀리아파트 203동 놀이터2008-05-22주택단지민간실외18297<NA>경기도 화성시 봉담읍 수영리 673번지 한울마을신창비바패밀리아파트37.237603126.953307
9402안산시1296[온누리 놀이터]그린빌12단지 어린이집 앞2009-10-28주택단지민간실외15446<NA>경기도 안산시 단원구 초지동 730번지 그린빌12단지37.308838126.819013
1112고양시524783가좌 벽산블루밍5단지아파트 512동2011-03-04주택단지민간실외10211<NA>경기도 고양시 일산서구 가좌동 1087번지 가좌마을5단지아파트37.691354126.720221
3502김포시562893한강신도시 2차 KCC스위첸아파트 111동 옆 이린이놀이터72018-01-15주택단지민간실외10077경기도 김포시 김포한강11로 37경기도 김포시 운양동 1331-137.64404126.692877
4105남양주578173별가람마을 1-8단지 1801동 옆 어린이놀이터2021-04-20주택단지민간실외12096경기도 남양주시 순화궁로 458-58경기도 남양주시 별내동 82237.667876127.123254
시군명시설번호놀이시설명설치일자설치장소민간공공구분명실내외구분명소재지우편번호소재지도로명주소소재지지번주소WGS84위도WGS84경도
1135고양시42066성저마을10단지건영빌라 놀이터2009-07-08주택단지민간실외10369<NA>경기도 고양시 일산서구 대화동 2000번지 성저마을10단지건영빌라37.685729126.759317
5352부천시38405은혜어린이공원2019-03-25도시공원공공실외<NA><NA>경기도 부천시 심곡동 30237.49243126.775406
9734안성시539144임광그대가1단지 103동앞2007-03-31주택단지민간실외17548<NA>경기도 안성시 공도읍 마정리 592번지 임광그대가아파트1단지37.012253127.209539
4522남양주553237시립진접어린이집놀이터2015-08-01어린이집공공실외12017경기도 남양주시 진접읍 팔야로111번길 59-5경기도 남양주시 진접읍 팔야리 393번지37.75405127.223101
779고양시518282강촌마을8단지 우방아파트 809동 옆 놀이터1993-01-01주택단지민간실외10415경기도 고양시 일산동구 강송로 197경기도 고양시 일산동구 마두동 794번지37.65601126.782297
12545용인시18848성복역리버파크 102동 앞 놀이시설1998-05-09주택단지민간실외16929<NA>경기도 용인시 수지구 상현동 1번지 만현마을동보2차아파트37.313187127.087236
404고양시580519지축3호 어린이공원2021-11-22도시공원공공실외<NA><NA>경기도 고양시 덕양구 지축동 45637.647547126.924255
13233용인시18201쏠티유치원(숲속쏠티어린이집)2008-10-24어린이집민간실외17024경기도 용인시 처인구 포곡읍 성산로341번길 93경기도 용인시 처인구 포곡읍 마성리 415-2번지37.271845127.185794
18006화성시559066롯데캐슬아파트 알바트로스 캐슬리안 카페안 놀이시설2017-02-28주택단지민간실내18482<NA>경기도 화성시 청계동 541번지 롯데알바트로스37.195225127.115204
12185용인시540688기흥 더샵 프라임뷰-새콤달콤과일 놀이대2013-06-15주택단지민간실외16964<NA>경기도 용인시 기흥구 신갈동 733번지 기흥더샵프라임뷰37.281184127.110096