Overview

Dataset statistics

Number of variables15
Number of observations271
Missing cells26
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.9 KiB
Average record size in memory124.5 B

Variable types

Numeric4
Text3
DateTime1
Categorical7

Dataset

Description대전광역시 동구 어린이놀이시설 현황 데이터로 놀이시설명, 시설세부주소, 설치일자, 설치장소 등을 포함한 데이터입니다.
URLhttps://www.data.go.kr/data/15067232/fileData.do

Alerts

운영구분 has constant value ""Constant
안전검사여부 has constant value ""Constant
데이터기준일자 has constant value ""Constant
실내외구분 is highly overall correlated with 설치장소High correlation
설치장소 is highly overall correlated with 민공구분 and 1 other fieldsHigh correlation
우편번호 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
경도 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
지역분류 is highly overall correlated with 우편번호 and 2 other fieldsHigh correlation
민공구분 is highly overall correlated with 설치장소High correlation
설치장소 is highly imbalanced (51.3%)Imbalance
실내외구분 is highly imbalanced (66.2%)Imbalance
우편번호 has 5 (1.8%) missing valuesMissing
시설 도로명주소 has 21 (7.7%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:02:54.866892
Analysis finished2023-12-12 05:02:58.501760
Duration3.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct271
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean136
Minimum1
Maximum271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T14:02:58.598456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.5
Q168.5
median136
Q3203.5
95-th percentile257.5
Maximum271
Range270
Interquartile range (IQR)135

Descriptive statistics

Standard deviation78.375166
Coefficient of variation (CV)0.57628799
Kurtosis-1.2
Mean136
Median Absolute Deviation (MAD)68
Skewness0
Sum36856
Variance6142.6667
MonotonicityStrictly increasing
2023-12-12T14:02:58.791347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
180 1
 
0.4%
186 1
 
0.4%
185 1
 
0.4%
184 1
 
0.4%
183 1
 
0.4%
182 1
 
0.4%
181 1
 
0.4%
179 1
 
0.4%
2 1
 
0.4%
Other values (261) 261
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
271 1
0.4%
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%

시설명
Text

Distinct268
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T14:02:59.108510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length14.619926
Min length2

Characters and Unicode

Total characters3962
Distinct characters273
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique267 ?
Unique (%)98.5%

Sample

1st row석천들주공임대아파트 유아 놀이터
2nd row큰솔(3차)아파트 놀이터
3rd row큰솔(1차)아파트 놀이터
4th row평화아파트 놀이터
5th row석천들주공임대아파트 111동 놀이터
ValueCountFrequency (%)
놀이터 115
 
17.7%
1단지 12
 
1.8%
용방마을아파트 9
 
1.4%
이스트시티 9
 
1.4%
유아놀이터 8
 
1.2%
삼정그린코아 7
 
1.1%
106동 7
 
1.1%
대전에코포레 6
 
0.9%
대전판암4단지 6
 
0.9%
102동 6
 
0.9%
Other values (300) 465
71.5%
2023-12-12T14:02:59.571705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
379
 
9.6%
이 335
 
8.5%
놀 216
 
5.5%
터 210
 
5.3%
동 166
 
4.2%
1 157
 
4.0%
아 148
 
3.7%
트 117
 
3.0%
파 111
 
2.8%
어 111
 
2.8%
Other values (263) 2012
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2972
75.0%
Decimal Number 468
 
11.8%
Space Separator 379
 
9.6%
Open Punctuation 49
 
1.2%
Close Punctuation 49
 
1.2%
Uppercase Letter 30
 
0.8%
Other Punctuation 9
 
0.2%
Dash Punctuation 3
 
0.1%
Lowercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 335
 
11.3%
놀 216
 
7.3%
터 210
 
7.1%
동 166
 
5.6%
아 148
 
5.0%
트 117
 
3.9%
파 111
 
3.7%
어 111
 
3.7%
린 106
 
3.6%
지 74
 
2.5%
Other values (238) 1378
46.4%
Decimal Number
ValueCountFrequency (%)
1 157
33.5%
0 93
19.9%
2 71
15.2%
3 55
 
11.8%
4 30
 
6.4%
5 17
 
3.6%
6 17
 
3.6%
8 14
 
3.0%
7 11
 
2.4%
9 3
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
E 10
33.3%
W 4
 
13.3%
S 4
 
13.3%
K 4
 
13.3%
V 4
 
13.3%
I 4
 
13.3%
Other Punctuation
ValueCountFrequency (%)
. 4
44.4%
, 3
33.3%
? 2
22.2%
Lowercase Letter
ValueCountFrequency (%)
e 2
66.7%
i 1
33.3%
Space Separator
ValueCountFrequency (%)
379
100.0%
Open Punctuation
ValueCountFrequency (%)
( 49
100.0%
Close Punctuation
ValueCountFrequency (%)
) 49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2972
75.0%
Common 957
 
24.2%
Latin 33
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 335
 
11.3%
놀 216
 
7.3%
터 210
 
7.1%
동 166
 
5.6%
아 148
 
5.0%
트 117
 
3.9%
파 111
 
3.7%
어 111
 
3.7%
린 106
 
3.6%
지 74
 
2.5%
Other values (238) 1378
46.4%
Common
ValueCountFrequency (%)
379
39.6%
1 157
16.4%
0 93
 
9.7%
2 71
 
7.4%
3 55
 
5.7%
( 49
 
5.1%
) 49
 
5.1%
4 30
 
3.1%
5 17
 
1.8%
6 17
 
1.8%
Other values (7) 40
 
4.2%
Latin
ValueCountFrequency (%)
E 10
30.3%
W 4
 
12.1%
S 4
 
12.1%
K 4
 
12.1%
V 4
 
12.1%
I 4
 
12.1%
e 2
 
6.1%
i 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2972
75.0%
ASCII 990
 
25.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
379
38.3%
1 157
15.9%
0 93
 
9.4%
2 71
 
7.2%
3 55
 
5.6%
( 49
 
4.9%
) 49
 
4.9%
4 30
 
3.0%
5 17
 
1.7%
6 17
 
1.7%
Other values (15) 73
 
7.4%
Hangul
ValueCountFrequency (%)
이 335
 
11.3%
놀 216
 
7.3%
터 210
 
7.1%
동 166
 
5.6%
아 148
 
5.0%
트 117
 
3.9%
파 111
 
3.7%
어 111
 
3.7%
린 106
 
3.6%
지 74
 
2.5%
Other values (238) 1378
46.4%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct100
Distinct (%)37.6%
Missing5
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean34623.169
Minimum34500
Maximum34712
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T14:02:59.760403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34500
5-th percentile34513
Q134557
median34642
Q334681
95-th percentile34705
Maximum34712
Range212
Interquartile range (IQR)124

Descriptive statistics

Standard deviation66.99252
Coefficient of variation (CV)0.0019349043
Kurtosis-1.3204634
Mean34623.169
Median Absolute Deviation (MAD)50
Skewness-0.42131382
Sum9209763
Variance4487.9977
MonotonicityNot monotonic
2023-12-12T14:02:59.930425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34660 10
 
3.7%
34681 8
 
3.0%
34519 8
 
3.0%
34686 8
 
3.0%
34637 7
 
2.6%
34675 7
 
2.6%
34674 7
 
2.6%
34698 7
 
2.6%
34705 6
 
2.2%
34557 6
 
2.2%
Other values (90) 192
70.8%
ValueCountFrequency (%)
34500 1
 
0.4%
34501 1
 
0.4%
34502 3
1.1%
34503 1
 
0.4%
34505 1
 
0.4%
34506 1
 
0.4%
34507 2
0.7%
34509 2
0.7%
34512 1
 
0.4%
34513 2
0.7%
ValueCountFrequency (%)
34712 6
2.2%
34711 1
 
0.4%
34709 1
 
0.4%
34706 1
 
0.4%
34705 6
2.2%
34704 1
 
0.4%
34703 3
1.1%
34702 1
 
0.4%
34701 3
1.1%
34698 7
2.6%

시설 지번주소
Text

Distinct167
Distinct (%)61.6%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T14:03:00.380329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length27
Mean length17.376384
Min length14

Characters and Unicode

Total characters4709
Distinct characters83
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

Unique117 ?
Unique (%)43.2%

Sample

1st row대전광역시 동구 낭월동 611
2nd row대전광역시 동구 가양2동 162-11
3rd row대전광역시 동구 용전동 48-22
4th row대전광역시 동구 가양2동 46-2
5th row대전광역시 동구 낭월동 611
ValueCountFrequency (%)
대전광역시 271
24.2%
동구 271
24.2%
용운동 31
 
2.8%
가오동 23
 
2.1%
판암동 19
 
1.7%
대동 17
 
1.5%
용전동 17
 
1.5%
홍도동 16
 
1.4%
낭월동 15
 
1.3%
천동 15
 
1.3%
Other values (195) 425
37.9%
2023-12-12T14:03:01.072407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
849
18.0%
동 548
11.6%
대 301
 
6.4%
전 288
 
6.1%
구 272
 
5.8%
광 271
 
5.8%
역 271
 
5.8%
시 271
 
5.8%
1 179
 
3.8%
2 149
 
3.2%
Other values (73) 1310
27.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2790
59.2%
Decimal Number 961
 
20.4%
Space Separator 849
 
18.0%
Dash Punctuation 109
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 548
19.6%
대 301
10.8%
전 288
10.3%
구 272
9.7%
광 271
9.7%
역 271
9.7%
시 271
9.7%
가 51
 
1.8%
용 48
 
1.7%
성 35
 
1.3%
Other values (61) 434
15.6%
Decimal Number
ValueCountFrequency (%)
1 179
18.6%
2 149
15.5%
3 120
12.5%
5 100
10.4%
4 96
10.0%
0 72
7.5%
6 68
 
7.1%
7 65
 
6.8%
9 59
 
6.1%
8 53
 
5.5%
Space Separator
ValueCountFrequency (%)
849
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2790
59.2%
Common 1919
40.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 548
19.6%
대 301
10.8%
전 288
10.3%
구 272
9.7%
광 271
9.7%
역 271
9.7%
시 271
9.7%
가 51
 
1.8%
용 48
 
1.7%
성 35
 
1.3%
Other values (61) 434
15.6%
Common
ValueCountFrequency (%)
849
44.2%
1 179
 
9.3%
2 149
 
7.8%
3 120
 
6.3%
- 109
 
5.7%
5 100
 
5.2%
4 96
 
5.0%
0 72
 
3.8%
6 68
 
3.5%
7 65
 
3.4%
Other values (2) 112
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2790
59.2%
ASCII 1919
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
849
44.2%
1 179
 
9.3%
2 149
 
7.8%
3 120
 
6.3%
- 109
 
5.7%
5 100
 
5.2%
4 96
 
5.0%
0 72
 
3.8%
6 68
 
3.5%
7 65
 
3.4%
Other values (2) 112
 
5.8%
Hangul
ValueCountFrequency (%)
동 548
19.6%
대 301
10.8%
전 288
10.3%
구 272
9.7%
광 271
9.7%
역 271
9.7%
시 271
9.7%
가 51
 
1.8%
용 48
 
1.7%
성 35
 
1.3%
Other values (61) 434
15.6%

시설 도로명주소
Text

MISSING 

Distinct151
Distinct (%)60.4%
Missing21
Missing (%)7.7%
Memory size2.2 KiB
2023-12-12T14:03:01.484088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length34
Mean length24.412
Min length15

Characters and Unicode

Total characters6103
Distinct characters143
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

Unique104 ?
Unique (%)41.6%

Sample

1st row대전광역시 동구 산내로1257번길 40 (낭월동)
2nd row대전광역시 동구 충정로18번길 60 (가양동)
3rd row대전광역시 동구 계족로512번길 52 (용전동)
4th row대전광역시 동구 비래서로62번길 5 (가양동)
5th row대전광역시 동구 산내로1257번길 40 (낭월동)
ValueCountFrequency (%)
대전광역시 250
20.0%
동구 250
20.0%
판암동 25
 
2.0%
용운동 21
 
1.7%
가양동 21
 
1.7%
가오동 19
 
1.5%
대전로 18
 
1.4%
용운로 16
 
1.3%
용전동 16
 
1.3%
천동 15
 
1.2%
Other values (237) 601
48.0%
2023-12-12T14:03:02.051327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1002
16.4%
동 525
 
8.6%
대 339
 
5.6%
전 322
 
5.3%
구 263
 
4.3%
시 251
 
4.1%
광 250
 
4.1%
역 250
 
4.1%
로 245
 
4.0%
( 211
 
3.5%
Other values (133) 2445
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3640
59.6%
Space Separator 1002
 
16.4%
Decimal Number 974
 
16.0%
Open Punctuation 211
 
3.5%
Close Punctuation 211
 
3.5%
Dash Punctuation 35
 
0.6%
Other Punctuation 30
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 525
14.4%
대 339
 
9.3%
전 322
 
8.8%
구 263
 
7.2%
시 251
 
6.9%
광 250
 
6.9%
역 250
 
6.9%
로 245
 
6.7%
길 117
 
3.2%
번 112
 
3.1%
Other values (118) 966
26.5%
Decimal Number
ValueCountFrequency (%)
1 165
16.9%
5 115
11.8%
2 114
11.7%
3 109
11.2%
4 108
11.1%
6 88
9.0%
7 84
8.6%
0 84
8.6%
8 57
 
5.9%
9 50
 
5.1%
Space Separator
ValueCountFrequency (%)
1002
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3640
59.6%
Common 2463
40.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 525
14.4%
대 339
 
9.3%
전 322
 
8.8%
구 263
 
7.2%
시 251
 
6.9%
광 250
 
6.9%
역 250
 
6.9%
로 245
 
6.7%
길 117
 
3.2%
번 112
 
3.1%
Other values (118) 966
26.5%
Common
ValueCountFrequency (%)
1002
40.7%
( 211
 
8.6%
) 211
 
8.6%
1 165
 
6.7%
5 115
 
4.7%
2 114
 
4.6%
3 109
 
4.4%
4 108
 
4.4%
6 88
 
3.6%
7 84
 
3.4%
Other values (5) 256
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3640
59.6%
ASCII 2463
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1002
40.7%
( 211
 
8.6%
) 211
 
8.6%
1 165
 
6.7%
5 115
 
4.7%
2 114
 
4.6%
3 109
 
4.4%
4 108
 
4.4%
6 88
 
3.6%
7 84
 
3.4%
Other values (5) 256
 
10.4%
Hangul
ValueCountFrequency (%)
동 525
14.4%
대 339
 
9.3%
전 322
 
8.8%
구 263
 
7.2%
시 251
 
6.9%
광 250
 
6.9%
역 250
 
6.9%
로 245
 
6.7%
길 117
 
3.2%
번 112
 
3.1%
Other values (118) 966
26.5%

설치일자
Date

Distinct153
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum1968-03-05 00:00:00
Maximum2023-07-15 00:00:00
2023-12-12T14:03:02.213917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:03:02.377322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

설치장소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
주택단지
183 
도시공원
36 
어린이집
30 
식품접객업소
 
8
놀이제공영업소
 
4
Other values (5)
 
10

Length

Max length7
Median length4
Mean length4.1328413
Min length3

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
주택단지 183
67.5%
도시공원 36
 
13.3%
어린이집 30
 
11.1%
식품접객업소 8
 
3.0%
놀이제공영업소 4
 
1.5%
아동복지시설 3
 
1.1%
자연휴양림 3
 
1.1%
야영장 2
 
0.7%
목욕장업소 1
 
0.4%
종교시설 1
 
0.4%

Length

2023-12-12T14:03:02.584676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:03:02.725641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택단지 183
67.5%
도시공원 36
 
13.3%
어린이집 30
 
11.1%
식품접객업소 8
 
3.0%
놀이제공영업소 4
 
1.5%
아동복지시설 3
 
1.1%
자연휴양림 3
 
1.1%
야영장 2
 
0.7%
목욕장업소 1
 
0.4%
종교시설 1
 
0.4%

운영구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
운영
271 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
운영 271
100.0%

Length

2023-12-12T14:03:02.858599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:03:02.956820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 271
100.0%

지역분류
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
판암동
34 
용운동
31 
가양동
28 
가오동
22 
용전동
17 
Other values (20)
139 

Length

Max length3
Median length3
Mean length2.8523985
Min length2

Unique

Unique7 ?
Unique (%)2.6%

Sample

1st row낭월동
2nd row가양동
3rd row용전동
4th row가양동
5th row낭월동

Common Values

ValueCountFrequency (%)
판암동 34
12.5%
용운동 31
11.4%
가양동 28
10.3%
가오동 22
 
8.1%
용전동 17
 
6.3%
홍도동 16
 
5.9%
낭월동 15
 
5.5%
천동 15
 
5.5%
신흥동 14
 
5.2%
성남동 13
 
4.8%
Other values (15) 66
24.4%

Length

2023-12-12T14:03:03.075521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
판암동 34
12.5%
용운동 31
11.4%
가양동 28
10.3%
가오동 22
 
8.1%
용전동 17
 
6.3%
홍도동 16
 
5.9%
낭월동 15
 
5.5%
천동 15
 
5.5%
신흥동 14
 
5.2%
성남동 13
 
4.8%
Other values (15) 66
24.4%

민공구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
민간
222 
공공
49 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
민간 222
81.9%
공공 49
 
18.1%

Length

2023-12-12T14:03:03.226157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:03:03.330097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 222
81.9%
공공 49
 
18.1%

실내외구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
실외
254 
실내
 
17

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
실외 254
93.7%
실내 17
 
6.3%

Length

2023-12-12T14:03:03.438924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:03:03.556171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 254
93.7%
실내 17
 
6.3%

안전검사여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
검사완료
271 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
검사완료 271
100.0%

Length

2023-12-12T14:03:03.681014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:03:03.804725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사완료 271
100.0%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct162
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.324025
Minimum36.20218
Maximum36.368266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T14:03:03.921167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.20218
5-th percentile36.278472
Q136.315487
median36.326672
Q336.342721
95-th percentile36.353657
Maximum36.368266
Range0.16608612
Interquartile range (IQR)0.027234128

Descriptive statistics

Standard deviation0.02484504
Coefficient of variation (CV)0.00068398366
Kurtosis5.5779213
Mean36.324025
Median Absolute Deviation (MAD)0.014867553
Skewness-1.7913843
Sum9843.8109
Variance0.000617276
MonotonicityNot monotonic
2023-12-12T14:03:04.066853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.3266723173 9
 
3.3%
36.3210793799 7
 
2.6%
36.328721 6
 
2.2%
36.3271378175 6
 
2.2%
36.2782466427 4
 
1.5%
36.343044125 4
 
1.5%
36.3404238179 4
 
1.5%
36.3148163911 4
 
1.5%
36.315486569 4
 
1.5%
36.3162158705 4
 
1.5%
Other values (152) 219
80.8%
ValueCountFrequency (%)
36.2021796082 2
0.7%
36.218628125 1
 
0.4%
36.231439003 1
 
0.4%
36.237996861 2
0.7%
36.2581177196 1
 
0.4%
36.275438197 1
 
0.4%
36.2767551567 1
 
0.4%
36.2782466427 4
1.5%
36.2782766703 1
 
0.4%
36.278667079 1
 
0.4%
ValueCountFrequency (%)
36.3682657282 1
 
0.4%
36.35856122 3
1.1%
36.3579992059 1
 
0.4%
36.3562203183 1
 
0.4%
36.3561032419 1
 
0.4%
36.3557882013 1
 
0.4%
36.35547035 1
 
0.4%
36.3553072924 3
1.1%
36.3543121395 1
 
0.4%
36.3541314593 1
 
0.4%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct162
Distinct (%)59.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.44868
Minimum127.41907
Maximum127.50809
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2023-12-12T14:03:04.218802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.41907
5-th percentile127.4252
Q1127.43991
median127.4502
Q3127.45847
95-th percentile127.46746
Maximum127.50809
Range0.089022838
Interquartile range (IQR)0.018557555

Descriptive statistics

Standard deviation0.013053673
Coefficient of variation (CV)0.00010242297
Kurtosis0.61985141
Mean127.44868
Median Absolute Deviation (MAD)0.0090322848
Skewness0.076653474
Sum34538.592
Variance0.00017039837
MonotonicityNot monotonic
2023-12-12T14:03:04.399311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.4504240885 9
 
3.3%
127.4608177902 7
 
2.6%
127.462787 6
 
2.2%
127.437849845 6
 
2.2%
127.4674643136 4
 
1.5%
127.4339152506 4
 
1.5%
127.4411661815 4
 
1.5%
127.4429102797 4
 
1.5%
127.4460444432 4
 
1.5%
127.4483868225 4
 
1.5%
Other values (152) 219
80.8%
ValueCountFrequency (%)
127.4190692529 1
 
0.4%
127.422135038 1
 
0.4%
127.4227475064 1
 
0.4%
127.4230101702 1
 
0.4%
127.4234772002 4
1.5%
127.4235314298 1
 
0.4%
127.4243135857 1
 
0.4%
127.4246622536 1
 
0.4%
127.4252 3
1.1%
127.4252006998 1
 
0.4%
ValueCountFrequency (%)
127.5080920908 1
 
0.4%
127.4802162229 1
 
0.4%
127.4758775748 1
 
0.4%
127.4712315824 1
 
0.4%
127.4704141415 2
0.7%
127.4701193232 1
 
0.4%
127.4690840145 1
 
0.4%
127.4689691953 2
0.7%
127.4677016737 1
 
0.4%
127.4674643136 4
1.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-07-31
271 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-31
2nd row2023-07-31
3rd row2023-07-31
4th row2023-07-31
5th row2023-07-31

Common Values

ValueCountFrequency (%)
2023-07-31 271
100.0%

Length

2023-12-12T14:03:04.536330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:03:04.626678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-31 271
100.0%

Interactions

2023-12-12T14:02:57.527320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:55.752929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.263767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.729479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:57.634845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:55.878894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.384192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:57.178859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:57.728318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.017258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.492528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:57.296780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:57.857221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.134334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:56.622554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:02:57.413796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:03:04.699493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호설치장소지역분류민공구분실내외구분위도경도
연번1.0000.6220.5730.6790.4940.3830.5210.361
우편번호0.6221.0000.3320.9340.3200.0000.8770.763
설치장소0.5730.3321.0000.7570.9860.9900.8700.246
지역분류0.6790.9340.7571.0000.4640.2300.9750.977
민공구분0.4940.3200.9860.4641.0000.1280.4040.322
실내외구분0.3830.0000.9900.2300.1281.0000.0000.000
위도0.5210.8770.8700.9750.4040.0001.0000.765
경도0.3610.7630.2460.9770.3220.0000.7651.000
2023-12-12T14:03:04.888006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
실내외구분지역분류설치장소민공구분
실내외구분1.0000.1890.9000.082
지역분류0.1891.0000.3710.385
설치장소0.9000.3711.0000.882
민공구분0.0820.3850.8821.000
2023-12-12T14:03:05.368817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호위도경도설치장소지역분류민공구분실내외구분
연번1.0000.024-0.0930.0190.2070.3040.3800.289
우편번호0.0241.000-0.8980.4760.1070.6850.2390.000
위도-0.093-0.8981.000-0.6460.4490.8050.3060.000
경도0.0190.476-0.6461.0000.1190.8430.2390.000
설치장소0.2070.1070.4490.1191.0000.3710.8820.900
지역분류0.3040.6850.8050.8430.3711.0000.3850.189
민공구분0.3800.2390.3060.2390.8820.3851.0000.082
실내외구분0.2890.0000.0000.0000.9000.1890.0821.000

Missing values

2023-12-12T14:02:58.034226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:02:58.311824image/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.
2023-12-12T14:02:58.441503image/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

연번시설명우편번호시설 지번주소시설 도로명주소설치일자설치장소운영구분지역분류민공구분실내외구분안전검사여부위도경도데이터기준일자
01석천들주공임대아파트 유아 놀이터34705대전광역시 동구 낭월동 611대전광역시 동구 산내로1257번길 40 (낭월동)2004-11-01주택단지운영낭월동민간실외검사완료36.278247127.4674642023-07-31
12큰솔(3차)아파트 놀이터34507대전광역시 동구 가양2동 162-11대전광역시 동구 충정로18번길 60 (가양동)2002-07-31주택단지운영가양동민간실외검사완료36.347039127.4508392023-07-31
23큰솔(1차)아파트 놀이터34542대전광역시 동구 용전동 48-22대전광역시 동구 계족로512번길 52 (용전동)1999-12-30주택단지운영용전동민간실외검사완료36.355788127.434822023-07-31
34평화아파트 놀이터34528대전광역시 동구 가양2동 46-2대전광역시 동구 비래서로62번길 5 (가양동)1994-09-01주택단지운영가양동민간실외검사완료36.354131127.4517832023-07-31
45석천들주공임대아파트 111동 놀이터34705대전광역시 동구 낭월동 611대전광역시 동구 산내로1257번길 40 (낭월동)2004-11-01주택단지운영낭월동민간실외검사완료36.278247127.4674642023-07-31
56방주아파트 놀이터34676대전광역시 동구 판암1동 328대전광역시 동구 동구청로204번길 46 (판암동)1995-08-01주택단지운영판암동민간실외검사완료36.31552127.4589552023-07-31
67파밀리에4단지아파트놀이터(110동)34555대전광역시 동구 홍도동 1002대전광역시 동구 동산초교로 47 (홍도동)2005-05-14주택단지운영홍도동민간실외검사완료36.348067127.4243142023-07-31
78파밀리에3단지아파트놀이터(112동)34555대전광역시 동구 홍도동 1001대전광역시 동구 동산초교로55번길 20 (홍도동)2005-05-14주택단지운영홍도동민간실외검사완료36.34829127.4235312023-07-31
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