Overview

Dataset statistics

Number of variables11
Number of observations535
Missing cells254
Missing cells (%)4.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory46.6 KiB
Average record size in memory89.2 B

Variable types

Text3
Numeric1
DateTime1
Categorical6

Dataset

Description어린이놀이시설 안전관리법을 근거로 하는 대전광역시 서구 어린이놀이시설 관리 현황(시설명, 설치장소, 안전검사여부 등)
URLhttps://www.data.go.kr/data/15084435/fileData.do

Alerts

설치장소 is highly overall correlated with 민공구분 and 1 other fieldsHigh correlation
민공구분 is highly overall correlated with 설치장소High correlation
실내외구분 is highly overall correlated with 설치장소High correlation
설치장소 is highly imbalanced (51.2%)Imbalance
운영구분 is highly imbalanced (98.0%)Imbalance
실내외구분 is highly imbalanced (65.1%)Imbalance
안전검사여부 is highly imbalanced (98.0%)Imbalance
주소(지번주소) has 149 (27.9%) missing valuesMissing
주소(도로명주소) has 105 (19.6%) missing valuesMissing
놀이시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 21:12:10.123876
Analysis finished2023-12-12 21:12:11.385448
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

놀이시설명
Text

UNIQUE 

Distinct535
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
2023-12-13T06:12:11.568468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length27
Mean length14.480374
Min length3

Characters and Unicode

Total characters7747
Distinct characters366
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique535 ?
Unique (%)100.0%

Sample

1st row소망어린이집 놀이터
2nd row초록1단지 물방울놀이터
3rd row초록1단지 물결놀이터
4th row구봉아파트 5단지-1
5th row초록마을2단지 어린이놀이터2(210동)
ValueCountFrequency (%)
놀이터 198
 
15.6%
어린이놀이터 45
 
3.6%
앞 40
 
3.2%
아파트 23
 
1.8%
옆 15
 
1.2%
101동 12
 
0.9%
실내놀이시설 10
 
0.8%
구봉마을 10
 
0.8%
유아놀이터 8
 
0.6%
어린이 8
 
0.6%
Other values (614) 898
70.9%
2023-12-13T06:12:12.055413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
732
 
9.4%
이 717
 
9.3%
놀 449
 
5.8%
터 402
 
5.2%
아 286
 
3.7%
1 279
 
3.6%
린 262
 
3.4%
어 245
 
3.2%
트 235
 
3.0%
파 233
 
3.0%
Other values (356) 3907
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5924
76.5%
Decimal Number 783
 
10.1%
Space Separator 732
 
9.4%
Open Punctuation 111
 
1.4%
Close Punctuation 111
 
1.4%
Dash Punctuation 48
 
0.6%
Uppercase Letter 26
 
0.3%
Other Punctuation 7
 
0.1%
Lowercase Letter 4
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 717
 
12.1%
놀 449
 
7.6%
터 402
 
6.8%
아 286
 
4.8%
린 262
 
4.4%
어 245
 
4.1%
트 235
 
4.0%
파 233
 
3.9%
동 213
 
3.6%
원 141
 
2.4%
Other values (326) 2741
46.3%
Uppercase Letter
ValueCountFrequency (%)
E 6
23.1%
L 4
15.4%
H 3
11.5%
A 3
11.5%
B 3
11.5%
I 2
 
7.7%
D 1
 
3.8%
C 1
 
3.8%
S 1
 
3.8%
K 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
1 279
35.6%
2 143
18.3%
0 126
16.1%
3 68
 
8.7%
4 44
 
5.6%
5 34
 
4.3%
8 33
 
4.2%
7 24
 
3.1%
9 17
 
2.2%
6 15
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
. 2
28.6%
! 1
 
14.3%
Space Separator
ValueCountFrequency (%)
732
100.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5923
76.5%
Common 1793
 
23.1%
Latin 30
 
0.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 717
 
12.1%
놀 449
 
7.6%
터 402
 
6.8%
아 286
 
4.8%
린 262
 
4.4%
어 245
 
4.1%
트 235
 
4.0%
파 233
 
3.9%
동 213
 
3.6%
원 141
 
2.4%
Other values (325) 2740
46.3%
Common
ValueCountFrequency (%)
732
40.8%
1 279
 
15.6%
2 143
 
8.0%
0 126
 
7.0%
( 111
 
6.2%
) 111
 
6.2%
3 68
 
3.8%
- 48
 
2.7%
4 44
 
2.5%
5 34
 
1.9%
Other values (8) 97
 
5.4%
Latin
ValueCountFrequency (%)
E 6
20.0%
L 4
13.3%
e 4
13.3%
H 3
10.0%
A 3
10.0%
B 3
10.0%
I 2
 
6.7%
D 1
 
3.3%
C 1
 
3.3%
S 1
 
3.3%
Other values (2) 2
 
6.7%
Han
ValueCountFrequency (%)
內 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5923
76.5%
ASCII 1823
 
23.5%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
732
40.2%
1 279
 
15.3%
2 143
 
7.8%
0 126
 
6.9%
( 111
 
6.1%
) 111
 
6.1%
3 68
 
3.7%
- 48
 
2.6%
4 44
 
2.4%
5 34
 
1.9%
Other values (20) 127
 
7.0%
Hangul
ValueCountFrequency (%)
이 717
 
12.1%
놀 449
 
7.6%
터 402
 
6.8%
아 286
 
4.8%
린 262
 
4.4%
어 245
 
4.1%
트 235
 
4.0%
파 233
 
3.9%
동 213
 
3.6%
원 141
 
2.4%
Other values (325) 2740
46.3%
CJK
ValueCountFrequency (%)
內 1
100.0%

우편번호
Real number (ℝ)

Distinct164
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42799.211
Minimum35200
Maximum302840
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.8 KiB
2023-12-13T06:12:12.233753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35200
5-th percentile35206
Q135249
median35340
Q335376
95-th percentile35412
Maximum302840
Range267640
Interquartile range (IQR)127

Descriptive statistics

Standard deviation44115.853
Coefficient of variation (CV)1.0307632
Kurtosis30.99556
Mean42799.211
Median Absolute Deviation (MAD)56
Skewness5.7340729
Sum22897578
Variance1.9462085 × 109
MonotonicityNot monotonic
2023-12-13T06:12:12.397178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35384 14
 
2.6%
35404 12
 
2.2%
35205 12
 
2.2%
35373 11
 
2.1%
302243 10
 
1.9%
35350 10
 
1.9%
35379 9
 
1.7%
35407 7
 
1.3%
35371 7
 
1.3%
35284 7
 
1.3%
Other values (154) 436
81.5%
ValueCountFrequency (%)
35200 2
 
0.4%
35201 6
1.1%
35202 3
 
0.6%
35203 1
 
0.2%
35204 1
 
0.2%
35205 12
2.2%
35206 3
 
0.6%
35207 3
 
0.6%
35208 5
0.9%
35209 1
 
0.2%
ValueCountFrequency (%)
302840 1
 
0.2%
302816 1
 
0.2%
302243 10
1.9%
302170 2
 
0.4%
302120 1
 
0.2%
35428 1
 
0.2%
35426 3
 
0.6%
35416 1
 
0.2%
35415 3
 
0.6%
35414 2
 
0.4%

주소(지번주소)
Text

MISSING 

Distinct260
Distinct (%)67.4%
Missing149
Missing (%)27.9%
Memory size4.3 KiB
2023-12-13T06:12:12.676152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length37
Mean length15.84456
Min length11

Characters and Unicode

Total characters6116
Distinct characters115
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

Unique194 ?
Unique (%)50.3%

Sample

1st row대전 서구 내동 30-26
2nd row대전시 서구 복수동 611
3rd row대전시 서구 복수동 611
4th row대전 서구 관저동 1137
5th row대전광역시 서구 복수동 612
ValueCountFrequency (%)
서구 390
26.0%
대전 268
17.9%
대전광역시 90
 
6.0%
관저동 53
 
3.5%
대전시 28
 
1.9%
둔산동 28
 
1.9%
복수동 19
 
1.3%
정림동 18
 
1.2%
갈마동 18
 
1.2%
월평동 17
 
1.1%
Other values (308) 572
38.1%
2023-12-13T06:12:13.078599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1115
18.2%
동 398
 
6.5%
구 394
 
6.4%
서 391
 
6.4%
대 390
 
6.4%
전 390
 
6.4%
1 350
 
5.7%
2 189
 
3.1%
3 163
 
2.7%
8 138
 
2.3%
Other values (105) 2198
35.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3393
55.5%
Decimal Number 1465
24.0%
Space Separator 1115
 
18.2%
Dash Punctuation 109
 
1.8%
Open Punctuation 9
 
0.1%
Close Punctuation 9
 
0.1%
Other Punctuation 8
 
0.1%
Uppercase Letter 5
 
0.1%
Lowercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 398
11.7%
구 394
11.6%
서 391
11.5%
대 390
11.5%
전 390
11.5%
시 125
 
3.7%
광 92
 
2.7%
역 92
 
2.7%
관 89
 
2.6%
저 89
 
2.6%
Other values (86) 943
27.8%
Decimal Number
ValueCountFrequency (%)
1 350
23.9%
2 189
12.9%
3 163
11.1%
8 138
 
9.4%
4 135
 
9.2%
0 117
 
8.0%
5 112
 
7.6%
9 112
 
7.6%
7 78
 
5.3%
6 71
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
C 3
60.0%
B 1
 
20.0%
L 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3393
55.5%
Common 2715
44.4%
Latin 8
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 398
11.7%
구 394
11.6%
서 391
11.5%
대 390
11.5%
전 390
11.5%
시 125
 
3.7%
광 92
 
2.7%
역 92
 
2.7%
관 89
 
2.6%
저 89
 
2.6%
Other values (86) 943
27.8%
Common
ValueCountFrequency (%)
1115
41.1%
1 350
 
12.9%
2 189
 
7.0%
3 163
 
6.0%
8 138
 
5.1%
4 135
 
5.0%
0 117
 
4.3%
5 112
 
4.1%
9 112
 
4.1%
- 109
 
4.0%
Other values (5) 175
 
6.4%
Latin
ValueCountFrequency (%)
C 3
37.5%
e 3
37.5%
B 1
 
12.5%
L 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3393
55.5%
ASCII 2723
44.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1115
40.9%
1 350
 
12.9%
2 189
 
6.9%
3 163
 
6.0%
8 138
 
5.1%
4 135
 
5.0%
0 117
 
4.3%
5 112
 
4.1%
9 112
 
4.1%
- 109
 
4.0%
Other values (9) 183
 
6.7%
Hangul
ValueCountFrequency (%)
동 398
11.7%
구 394
11.6%
서 391
11.5%
대 390
11.5%
전 390
11.5%
시 125
 
3.7%
광 92
 
2.7%
역 92
 
2.7%
관 89
 
2.6%
저 89
 
2.6%
Other values (86) 943
27.8%

주소(도로명주소)
Text

MISSING 

Distinct261
Distinct (%)60.7%
Missing105
Missing (%)19.6%
Memory size4.3 KiB
2023-12-13T06:12:13.389357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length42
Mean length26.048837
Min length20

Characters and Unicode

Total characters11201
Distinct characters214
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique180 ?
Unique (%)41.9%

Sample

1st row대전광역시 서구 동서대로1030번길 5-4 (내동)
2nd row대전광역시 서구 복수동로 21-19 (복수동)
3rd row대전광역시 서구 복수동로 21-19 (복수동)
4th row대전광역시 서구 관저로 51 (관저동)
5th row대전광역시 서구 복수동로 21-20 (복수동)
ValueCountFrequency (%)
서구 431
 
19.0%
대전광역시 430
 
18.9%
관저동 69
 
3.0%
둔산동 63
 
2.8%
월평동 39
 
1.7%
청사로 32
 
1.4%
관저로 29
 
1.3%
도안동 26
 
1.1%
갈마동 26
 
1.1%
내동 22
 
1.0%
Other values (419) 1104
48.6%
2023-12-13T06:12:13.855498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1841
 
16.4%
동 506
 
4.5%
대 472
 
4.2%
서 466
 
4.2%
구 443
 
4.0%
전 438
 
3.9%
시 437
 
3.9%
역 433
 
3.9%
( 433
 
3.9%
광 433
 
3.9%
Other values (204) 5299
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6894
61.5%
Space Separator 1841
 
16.4%
Decimal Number 1453
 
13.0%
Open Punctuation 433
 
3.9%
Close Punctuation 433
 
3.9%
Other Punctuation 92
 
0.8%
Dash Punctuation 42
 
0.4%
Lowercase Letter 9
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 506
 
7.3%
대 472
 
6.8%
서 466
 
6.8%
구 443
 
6.4%
전 438
 
6.4%
시 437
 
6.3%
역 433
 
6.3%
광 433
 
6.3%
로 421
 
6.1%
관 167
 
2.4%
Other values (181) 2678
38.8%
Decimal Number
ValueCountFrequency (%)
1 337
23.2%
2 194
13.4%
5 163
11.2%
0 125
 
8.6%
4 123
 
8.5%
3 122
 
8.4%
8 117
 
8.1%
6 115
 
7.9%
7 97
 
6.7%
9 60
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
I 1
25.0%
B 1
25.0%
K 1
25.0%
S 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 6
66.7%
s 2
 
22.2%
k 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 87
94.6%
， 5
 
5.4%
Space Separator
ValueCountFrequency (%)
1841
100.0%
Open Punctuation
ValueCountFrequency (%)
( 433
100.0%
Close Punctuation
ValueCountFrequency (%)
) 433
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6894
61.5%
Common 4294
38.3%
Latin 13
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 506
 
7.3%
대 472
 
6.8%
서 466
 
6.8%
구 443
 
6.4%
전 438
 
6.4%
시 437
 
6.3%
역 433
 
6.3%
광 433
 
6.3%
로 421
 
6.1%
관 167
 
2.4%
Other values (181) 2678
38.8%
Common
ValueCountFrequency (%)
1841
42.9%
( 433
 
10.1%
) 433
 
10.1%
1 337
 
7.8%
2 194
 
4.5%
5 163
 
3.8%
0 125
 
2.9%
4 123
 
2.9%
3 122
 
2.8%
8 117
 
2.7%
Other values (6) 406
 
9.5%
Latin
ValueCountFrequency (%)
e 6
46.2%
s 2
 
15.4%
I 1
 
7.7%
B 1
 
7.7%
K 1
 
7.7%
k 1
 
7.7%
S 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6894
61.5%
ASCII 4302
38.4%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1841
42.8%
( 433
 
10.1%
) 433
 
10.1%
1 337
 
7.8%
2 194
 
4.5%
5 163
 
3.8%
0 125
 
2.9%
4 123
 
2.9%
3 122
 
2.8%
8 117
 
2.7%
Other values (12) 414
 
9.6%
Hangul
ValueCountFrequency (%)
동 506
 
7.3%
대 472
 
6.8%
서 466
 
6.8%
구 443
 
6.4%
전 438
 
6.4%
시 437
 
6.3%
역 433
 
6.3%
광 433
 
6.3%
로 421
 
6.1%
관 167
 
2.4%
Other values (181) 2678
38.8%
None
ValueCountFrequency (%)
， 5
100.0%

설치일자
Date

Distinct275
Distinct (%)51.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
Minimum1970-11-05 00:00:00
Maximum2023-06-02 00:00:00
2023-12-13T06:12:14.013331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T06:12:14.176288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

설치장소
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct10
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
주택단지
338 
도시공원
109 
어린이집
51 
식품접객업소
 
14
놀이제공영업소
 
14
Other values (5)
 
9

Length

Max length7
Median length4
Mean length4.1439252
Min length4

Unique

Unique2 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
주택단지 338
63.2%
도시공원 109
 
20.4%
어린이집 51
 
9.5%
식품접객업소 14
 
2.6%
놀이제공영업소 14
 
2.6%
종교시설 3
 
0.6%
아동복지시설 2
 
0.4%
목욕장업소 2
 
0.4%
공공도서관 1
 
0.2%
의료기관 1
 
0.2%

Length

2023-12-13T06:12:14.301540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:12:14.401206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주택단지 338
63.2%
도시공원 109
 
20.4%
어린이집 51
 
9.5%
식품접객업소 14
 
2.6%
놀이제공영업소 14
 
2.6%
종교시설 3
 
0.6%
아동복지시설 2
 
0.4%
목욕장업소 2
 
0.4%
공공도서관 1
 
0.2%
의료기관 1
 
0.2%

운영구분
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
운영
534 
이용금지
 
1

Length

Max length4
Median length2
Mean length2.0037383
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
운영 534
99.8%
이용금지 1
 
0.2%

Length

2023-12-13T06:12:14.514090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:12:14.598239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
운영 534
99.8%
이용금지 1
 
0.2%

지역분류
Categorical

Distinct18
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
대전 서구 관저동
121 
대전 서구 둔산동
77 
대전 서구 월평동
44 
대전 서구 도안동
43 
대전 서구 갈마동
36 
Other values (13)
214 

Length

Max length10
Median length9
Mean length8.9757009
Min length8

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row대전 서구 내동
2nd row대전 서구 복수동
3rd row대전 서구 복수동
4th row대전 서구 관저동
5th row대전 서구 복수동

Common Values

ValueCountFrequency (%)
대전 서구 관저동 121
22.6%
대전 서구 둔산동 77
14.4%
대전 서구 월평동 44
 
8.2%
대전 서구 도안동 43
 
8.0%
대전 서구 갈마동 36
 
6.7%
대전 서구 복수동 33
 
6.2%
대전 서구 도마동 31
 
5.8%
대전 서구 탄방동 29
 
5.4%
대전 서구 내동 25
 
4.7%
대전 서구 가수원동 21
 
3.9%
Other values (8) 75
14.0%

Length

2023-12-13T06:12:14.706290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대전 535
33.3%
서구 535
33.3%
관저동 121
 
7.5%
둔산동 77
 
4.8%
월평동 44
 
2.7%
도안동 43
 
2.7%
갈마동 36
 
2.2%
복수동 33
 
2.1%
도마동 31
 
1.9%
탄방동 29
 
1.8%
Other values (10) 121
 
7.5%

민공구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
민간
418 
공공
117 

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 418
78.1%
공공 117
 
21.9%

Length

2023-12-13T06:12:14.827880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:12:14.902710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간 418
78.1%
공공 117
 
21.9%

실내외구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
실외
500 
실내
 
35

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 500
93.5%
실내 35
 
6.5%

Length

2023-12-13T06:12:14.980770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:12:15.058117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
실외 500
93.5%
실내 35
 
6.5%

안전검사여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.3 KiB
검사완료
534 
불합격
 
1

Length

Max length4
Median length4
Mean length3.9981308
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
검사완료 534
99.8%
불합격 1
 
0.2%

Length

2023-12-13T06:12:15.146687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T06:12:15.235059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
검사완료 534
99.8%
불합격 1
 
0.2%

Interactions

2023-12-13T06:12:10.887082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T06:12:15.358816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호설치장소운영구분지역분류민공구분실내외구분안전검사여부
우편번호1.0000.2890.0000.1450.3450.0000.000
설치장소0.2891.0000.0000.2940.9970.9900.000
운영구분0.0000.0001.0000.0000.0000.0000.704
지역분류0.1450.2940.0001.0000.2240.1230.000
민공구분0.3450.9970.0000.2241.0000.1630.000
실내외구분0.0000.9900.0000.1230.1631.0000.000
안전검사여부0.0000.0000.7040.0000.0000.0001.000
2023-12-13T06:12:15.452017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류안전검사여부설치장소민공구분실내외구분운영구분
지역분류1.0000.0000.1160.1740.0950.000
안전검사여부0.0001.0000.0000.0000.0000.498
설치장소0.1160.0001.0000.9470.9050.000
민공구분0.1740.0000.9471.0000.1040.000
실내외구분0.0950.0000.9050.1041.0000.000
운영구분0.0000.4980.0000.0000.0001.000
2023-12-13T06:12:15.542374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
우편번호설치장소운영구분지역분류민공구분실내외구분안전검사여부
우편번호1.0000.2160.0000.1130.2210.0000.000
설치장소0.2161.0000.0000.1160.9470.9050.000
운영구분0.0000.0001.0000.0000.0000.0000.498
지역분류0.1130.1160.0001.0000.1740.0950.000
민공구분0.2210.9470.0000.1741.0000.1040.000
실내외구분0.0000.9050.0000.0950.1041.0000.000
안전검사여부0.0000.0000.4980.0000.0000.0001.000

Missing values

2023-12-13T06:12:11.059821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T06:12:11.203341image/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.
2023-12-13T06:12:11.332464image/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

놀이시설명우편번호주소(지번주소)주소(도로명주소)설치일자설치장소운영구분지역분류민공구분실내외구분안전검사여부
0소망어린이집 놀이터35326대전 서구 내동 30-26대전광역시 서구 동서대로1030번길 5-4 (내동)2004-01-01어린이집운영대전 서구 내동민간실외검사완료
1초록1단지 물방울놀이터35407대전시 서구 복수동 611대전광역시 서구 복수동로 21-19 (복수동)2005-11-14주택단지운영대전 서구 복수동민간실외검사완료
2초록1단지 물결놀이터35407대전시 서구 복수동 611대전광역시 서구 복수동로 21-19 (복수동)2005-11-14주택단지운영대전 서구 복수동민간실외검사완료
3구봉아파트 5단지-135371대전 서구 관저동 1137대전광역시 서구 관저로 51 (관저동)2000-06-21주택단지운영대전 서구 관저동민간실외검사완료
4초록마을2단지 어린이놀이터2(210동)35407대전광역시 서구 복수동 612대전광역시 서구 복수동로 21-20 (복수동)2005-03-05주택단지운영대전 서구 복수동민간실외검사완료
5초록마을2단지 어린이놀이터1(202동)35407대전광역시 서구 복수동 612대전광역시 서구 복수동로 21-20 (복수동)2005-03-05주택단지운영대전 서구 복수동민간실외검사완료
6느리울아파트13단지 어린이놀이터 235384대전광역시 서구 관저동 1394대전광역시 서구 관저동로 42 (관저동)2002-10-19주택단지운영대전 서구 관저동민간실외검사완료
7느리울아파트13단지 어린이놀이터 335384대전광역시 서구 관저동 1394대전광역시 서구 관저동로 42 (관저동)2002-10-19주택단지운영대전 서구 관저동민간실외검사완료
8서낭당어린이공원 놀이터35412대전 서구 복수동 569<NA>1996-06-25도시공원운영대전 서구 복수동공공실외검사완료
9천변어린이공원 놀이터35415대전 서구 복수동 689<NA>1996-06-25도시공원운영대전 서구 복수동공공실외검사완료
놀이시설명우편번호주소(지번주소)주소(도로명주소)설치일자설치장소운영구분지역분류민공구분실내외구분안전검사여부
525육아종합지원센터 너와나우리놀이터35354<NA>대전광역시 서구 원도안로242번길 33 (도안동)행정복지센터2022-06-17어린이집운영대전 서구 도안동공공실내검사완료
526인생1년차 실내놀이시설35221<NA>대전광역시 서구 한밭대로570번길 40-11 (월평동)1층2022-08-15놀이제공영업소운영대전 서구 월평동민간실내검사완료
527플레이535350<NA>대전광역시 서구 도안북로117번길 32 (도안동)102호2022-11-08놀이제공영업소운영대전 서구 도안동민간실내검사완료
528운동회 실내놀이시설35382<NA>대전광역시 서구 관저중로64번길 58 (관저동)201호2022-11-15놀이제공영업소운영대전 서구 관저동민간실내검사완료
529우리끼리키즈카페 빛나는마을 월평선사점35213<NA>대전광역시 서구 월평북로 89 (월평동)테마빌딩 402호2022-11-08놀이제공영업소운영대전 서구 월평동민간실내검사완료
530대전광역시교육청 직장어린이집35239<NA>대전광역시 서구 둔산로 89 (둔산동)대전광역시교육청 직장어린이집2022-12-14어린이집운영대전 서구 둔산동공공실외검사완료
531공공어린이재활병원35358<NA>대전광역시 서구 도안중로 133 (관저동)2023-03-30의료기관운영대전 서구 관저동민간실외검사완료
532우리노리 키즈룸35262<NA>대전광역시 서구 계룡로553번안길 23 (탄방동)301호2023-05-01놀이제공영업소운영대전 서구 탄방동민간실외검사완료
533섭이네닭갈비 內 실내놀이시설35294<NA>대전광역시 서구 가장로 88 (괴정동)1층2023-05-01식품접객업소운영대전 서구 괴정동민간실내검사완료
534대전교회 실내놀이시설35279<NA>대전광역시 서구 월드컵대로484번길 82-11 (월평동)2023-06-02종교시설운영대전 서구 월평동민간실내검사완료