Overview

Dataset statistics

Number of variables17
Number of observations22
Missing cells165
Missing cells (%)44.1%
Duplicate rows1
Duplicate rows (%)4.5%
Total size in memory3.1 KiB
Average record size in memory146.0 B

Variable types

Text5
Categorical4
Numeric2
DateTime5
Boolean1

Dataset

Description서울특별시 동대문구 공동육아방 시설현황 자료입니다. 시설명, 도로명주소, 직원수, 이용정원, 운영시간 등을 포함하고 있습니다.
Author서울특별시 동대문구
URLhttps://www.data.go.kr/data/15127330/fileData.do

Alerts

평일시작시간 has constant value ""Constant
평일종료시간 has constant value ""Constant
비고 has constant value ""Constant
데이터기준일 has constant value ""Constant
Dataset has 1 (4.5%) duplicate rowsDuplicates
토요일운영여부 is highly overall correlated with 서비스분류명 and 1 other fieldsHigh correlation
관리기관명 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
이용정원 is highly overall correlated with 서비스분류명 and 1 other fieldsHigh correlation
서비스분류명 is highly overall correlated with 위도 and 5 other fieldsHigh correlation
직원 수 is highly overall correlated with 서비스분류명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 서비스분류명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 서비스분류명 and 1 other fieldsHigh correlation
시설명 has 12 (54.5%) missing valuesMissing
도로명주소 has 12 (54.5%) missing valuesMissing
상세주소 has 12 (54.5%) missing valuesMissing
위도 has 12 (54.5%) missing valuesMissing
경도 has 12 (54.5%) missing valuesMissing
평일시작시간 has 12 (54.5%) missing valuesMissing
평일종료시간 has 12 (54.5%) missing valuesMissing
토요일운영여부 has 12 (54.5%) missing valuesMissing
토요일운영시작시간 has 12 (54.5%) missing valuesMissing
토요일운영종료시간 has 12 (54.5%) missing valuesMissing
비고 has 21 (95.5%) missing valuesMissing
전화번호 has 12 (54.5%) missing valuesMissing
데이터기준일 has 12 (54.5%) missing valuesMissing

Reproduction

Analysis started2024-04-06 08:09:06.673007
Analysis finished2024-04-06 08:09:09.847590
Duration3.17 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
2024-04-06T17:09:10.032794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length13.2
Min length12

Characters and Unicode

Total characters132
Distinct characters29
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row꿈자람공동육아방 휘경점
2nd row꿈자람공동육아방 청량리점
3rd row꿈자람공동육아방 제기점
4th row꿈자람공동육아방 제기2호점
5th row꿈자람공동육아방 장안2호점
ValueCountFrequency (%)
꿈자람공동육아방 10
50.0%
휘경점 1
 
5.0%
청량리점 1
 
5.0%
제기점 1
 
5.0%
제기2호점 1
 
5.0%
장안2호점 1
 
5.0%
장안1호점 1
 
5.0%
용신점 1
 
5.0%
배봉산점 1
 
5.0%
답십리점 1
 
5.0%
2024-04-06T17:09:11.018063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
꿈 10
 
7.6%
자 10
 
7.6%
람 10
 
7.6%
공 10
 
7.6%
동 10
 
7.6%
육 10
 
7.6%
아 10
 
7.6%
방 10
 
7.6%
10
 
7.6%
점 10
 
7.6%
Other values (19) 32
24.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
89.4%
Space Separator 10
 
7.6%
Decimal Number 4
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
꿈 10
8.5%
자 10
8.5%
람 10
8.5%
공 10
8.5%
동 10
8.5%
육 10
8.5%
아 10
8.5%
방 10
8.5%
점 10
8.5%
호 4
 
3.4%
Other values (16) 24
20.3%
Decimal Number
ValueCountFrequency (%)
2 3
75.0%
1 1
 
25.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
89.4%
Common 14
 
10.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
꿈 10
8.5%
자 10
8.5%
람 10
8.5%
공 10
8.5%
동 10
8.5%
육 10
8.5%
아 10
8.5%
방 10
8.5%
점 10
8.5%
호 4
 
3.4%
Other values (16) 24
20.3%
Common
ValueCountFrequency (%)
10
71.4%
2 3
 
21.4%
1 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
89.4%
ASCII 14
 
10.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
꿈 10
8.5%
자 10
8.5%
람 10
8.5%
공 10
8.5%
동 10
8.5%
육 10
8.5%
아 10
8.5%
방 10
8.5%
점 10
8.5%
호 4
 
3.4%
Other values (16) 24
20.3%
ASCII
ValueCountFrequency (%)
10
71.4%
2 3
 
21.4%
1 1
 
7.1%

서비스분류명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
12 
공동육아방
10 

Length

Max length5
Median length4
Mean length4.4545455
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 12
54.5%
공동육아방 10
45.5%

Length

2024-04-06T17:09:11.271506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:11.596412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
54.5%
공동육아방 10
45.5%

도로명주소
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
2024-04-06T17:09:11.917763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length19.5
Mean length19.1
Min length17

Characters and Unicode

Total characters191
Distinct characters43
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row서울특별시 동대문구 장안벚꽃로 323
2nd row서울특별시 동대문구 왕산로 239
3rd row서울특별시 동대문구 약령시로7길 19
4th row서울특별시 동대문구 제기로 20
5th row서울특별시 동대문구 한천로28길 9
ValueCountFrequency (%)
서울특별시 10
24.4%
동대문구 10
24.4%
답십리로66길 1
 
2.4%
답십리로45길 1
 
2.4%
62 1
 
2.4%
황물로 1
 
2.4%
97 1
 
2.4%
16길 1
 
2.4%
전농로 1
 
2.4%
89 1
 
2.4%
Other values (13) 13
31.7%
2024-04-06T17:09:12.576519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
16.8%
시 11
 
5.8%
서 10
 
5.2%
대 10
 
5.2%
울 10
 
5.2%
구 10
 
5.2%
문 10
 
5.2%
로 10
 
5.2%
동 10
 
5.2%
특 10
 
5.2%
Other values (33) 68
35.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 130
68.1%
Space Separator 32
 
16.8%
Decimal Number 29
 
15.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 11
 
8.5%
서 10
 
7.7%
대 10
 
7.7%
울 10
 
7.7%
구 10
 
7.7%
문 10
 
7.7%
로 10
 
7.7%
동 10
 
7.7%
특 10
 
7.7%
별 10
 
7.7%
Other values (22) 29
22.3%
Decimal Number
ValueCountFrequency (%)
2 5
17.2%
9 5
17.2%
6 4
13.8%
3 4
13.8%
7 3
10.3%
1 2
 
6.9%
8 2
 
6.9%
4 2
 
6.9%
0 1
 
3.4%
5 1
 
3.4%
Space Separator
ValueCountFrequency (%)
32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 130
68.1%
Common 61
31.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 11
 
8.5%
서 10
 
7.7%
대 10
 
7.7%
울 10
 
7.7%
구 10
 
7.7%
문 10
 
7.7%
로 10
 
7.7%
동 10
 
7.7%
특 10
 
7.7%
별 10
 
7.7%
Other values (22) 29
22.3%
Common
ValueCountFrequency (%)
32
52.5%
2 5
 
8.2%
9 5
 
8.2%
6 4
 
6.6%
3 4
 
6.6%
7 3
 
4.9%
1 2
 
3.3%
8 2
 
3.3%
4 2
 
3.3%
0 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 130
68.1%
ASCII 61
31.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
52.5%
2 5
 
8.2%
9 5
 
8.2%
6 4
 
6.6%
3 4
 
6.6%
7 3
 
4.9%
1 2
 
3.3%
8 2
 
3.3%
4 2
 
3.3%
0 1
 
1.6%
Hangul
ValueCountFrequency (%)
시 11
 
8.5%
서 10
 
7.7%
대 10
 
7.7%
울 10
 
7.7%
구 10
 
7.7%
문 10
 
7.7%
로 10
 
7.7%
동 10
 
7.7%
특 10
 
7.7%
별 10
 
7.7%
Other values (22) 29
22.3%

상세주소
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
2024-04-06T17:09:12.880340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length15.6
Min length2

Characters and Unicode

Total characters156
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row2층
2nd row4층
3rd row동대문구육아종합지원센터 제기점 2층 (제기동)
4th row101동 202호 (제기동, 더푸른빌)
5th row202동 1호 (장안동, 시온아트빌)
ValueCountFrequency (%)
2층 4
 
14.3%
제기동 2
 
7.1%
1층 2
 
7.1%
꿈자람공동육아방 2
 
7.1%
장안동 2
 
7.1%
동대문구육아종합지원센터 2
 
7.1%
101동 1
 
3.6%
202호 1
 
3.6%
더푸른빌 1
 
3.6%
202동 1
 
3.6%
Other values (10) 10
35.7%
2024-04-06T17:09:13.458875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20
 
12.8%
동 13
 
8.3%
2 8
 
5.1%
층 8
 
5.1%
) 6
 
3.8%
( 6
 
3.8%
1 5
 
3.2%
아 5
 
3.2%
육 4
 
2.6%
0 3
 
1.9%
Other values (46) 78
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
66.7%
Space Separator 20
 
12.8%
Decimal Number 18
 
11.5%
Close Punctuation 6
 
3.8%
Open Punctuation 6
 
3.8%
Other Punctuation 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 13
 
12.5%
층 8
 
7.7%
아 5
 
4.8%
육 4
 
3.8%
기 3
 
2.9%
제 3
 
2.9%
터 3
 
2.9%
센 3
 
2.9%
구 3
 
2.9%
문 3
 
2.9%
Other values (37) 56
53.8%
Decimal Number
ValueCountFrequency (%)
2 8
44.4%
1 5
27.8%
0 3
 
16.7%
3 1
 
5.6%
4 1
 
5.6%
Space Separator
ValueCountFrequency (%)
20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
66.7%
Common 52
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 13
 
12.5%
층 8
 
7.7%
아 5
 
4.8%
육 4
 
3.8%
기 3
 
2.9%
제 3
 
2.9%
터 3
 
2.9%
센 3
 
2.9%
구 3
 
2.9%
문 3
 
2.9%
Other values (37) 56
53.8%
Common
ValueCountFrequency (%)
20
38.5%
2 8
 
15.4%
) 6
 
11.5%
( 6
 
11.5%
1 5
 
9.6%
0 3
 
5.8%
, 2
 
3.8%
3 1
 
1.9%
4 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
66.7%
ASCII 52
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20
38.5%
2 8
 
15.4%
) 6
 
11.5%
( 6
 
11.5%
1 5
 
9.6%
0 3
 
5.8%
, 2
 
3.8%
3 1
 
1.9%
4 1
 
1.9%
Hangul
ValueCountFrequency (%)
동 13
 
12.5%
층 8
 
7.7%
아 5
 
4.8%
육 4
 
3.8%
기 3
 
2.9%
제 3
 
2.9%
터 3
 
2.9%
센 3
 
2.9%
구 3
 
2.9%
문 3
 
2.9%
Other values (37) 56
53.8%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing12
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean37.578376
Minimum37.57206
Maximum37.586864
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T17:09:13.667035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.57206
5-th percentile37.572177
Q137.572702
median37.576655
Q337.58356
95-th percentile37.586606
Maximum37.586864
Range0.01480435
Interquartile range (IQR)0.0108578

Descriptive statistics

Standard deviation0.0060671476
Coefficient of variation (CV)0.00016145316
Kurtosis-1.8804217
Mean37.578376
Median Absolute Deviation (MAD)0.004465
Skewness0.33028974
Sum375.78376
Variance3.681028 × 10-5
MonotonicityNot monotonic
2024-04-06T17:09:13.884893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
37.58686435 1
 
4.5%
37.58305825 1
 
4.5%
37.58372765 1
 
4.5%
37.58629 1
 
4.5%
37.57379 1
 
4.5%
37.57234 1
 
4.5%
37.57232 1
 
4.5%
37.5784 1
 
4.5%
37.57206 1
 
4.5%
37.57491 1
 
4.5%
(Missing) 12
54.5%
ValueCountFrequency (%)
37.57206 1
4.5%
37.57232 1
4.5%
37.57234 1
4.5%
37.57379 1
4.5%
37.57491 1
4.5%
37.5784 1
4.5%
37.58305825 1
4.5%
37.58372765 1
4.5%
37.58629 1
4.5%
37.58686435 1
4.5%
ValueCountFrequency (%)
37.58686435 1
4.5%
37.58629 1
4.5%
37.58372765 1
4.5%
37.58305825 1
4.5%
37.5784 1
4.5%
37.57491 1
4.5%
37.57379 1
4.5%
37.57234 1
4.5%
37.57232 1
4.5%
37.57206 1
4.5%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)100.0%
Missing12
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean127.05201
Minimum127.02992
Maximum127.07016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-04-06T17:09:14.117163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.02992
5-th percentile127.03206
Q1127.03836
median127.05164
Q3127.06641
95-th percentile127.06945
Maximum127.07016
Range0.0402391
Interquartile range (IQR)0.028055

Descriptive statistics

Standard deviation0.015191851
Coefficient of variation (CV)0.0001195719
Kurtosis-1.607834
Mean127.05201
Median Absolute Deviation (MAD)0.01623
Skewness-0.2098592
Sum1270.5201
Variance0.00023079235
MonotonicityNot monotonic
2024-04-06T17:09:14.376154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
127.0701591 1
 
4.5%
127.0481847 1
 
4.5%
127.0346759 1
 
4.5%
127.03516 1
 
4.5%
127.06762 1
 
4.5%
127.06859 1
 
4.5%
127.02992 1
 
4.5%
127.06279 1
 
4.5%
127.04795 1
 
4.5%
127.05509 1
 
4.5%
(Missing) 12
54.5%
ValueCountFrequency (%)
127.02992 1
4.5%
127.0346759 1
4.5%
127.03516 1
4.5%
127.04795 1
4.5%
127.0481847 1
4.5%
127.05509 1
4.5%
127.06279 1
4.5%
127.06762 1
4.5%
127.06859 1
4.5%
127.0701591 1
4.5%
ValueCountFrequency (%)
127.0701591 1
4.5%
127.06859 1
4.5%
127.06762 1
4.5%
127.06279 1
4.5%
127.05509 1
4.5%
127.0481847 1
4.5%
127.04795 1
4.5%
127.03516 1
4.5%
127.0346759 1
4.5%
127.02992 1
4.5%

직원 수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
12 
1
8 
2
2 

Length

Max length4
Median length4
Mean length2.6363636
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
<NA> 12
54.5%
1 8
36.4%
2 2
 
9.1%

Length

2024-04-06T17:09:14.696243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:15.038707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
54.5%
1 8
36.4%
2 2
 
9.1%

이용정원
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
12 
25
6 
20
4 

Length

Max length4
Median length4
Mean length3.0909091
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row25
2nd row25
3rd row25
4th row20
5th row20

Common Values

ValueCountFrequency (%)
<NA> 12
54.5%
25 6
27.3%
20 4
 
18.2%

Length

2024-04-06T17:09:15.283243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:15.524298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
54.5%
25 6
27.3%
20 4
 
18.2%

평일시작시간
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)10.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
Minimum2024-04-06 10:00:00
Maximum2024-04-06 10:00:00
2024-04-06T17:09:15.700367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:15.866662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

평일종료시간
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)10.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
Minimum2024-04-06 17:30:00
Maximum2024-04-06 17:30:00
2024-04-06T17:09:16.042825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:16.228522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

토요일운영여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)20.0%
Missing12
Missing (%)54.5%
Memory size176.0 B
True
8 
False
2 
(Missing)
12 
ValueCountFrequency (%)
True 8
36.4%
False 2
 
9.1%
(Missing) 12
54.5%
2024-04-06T17:09:16.459754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

토요일운영시작시간
Date

MISSING 

Distinct2
Distinct (%)20.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
Minimum2024-04-06 00:00:00
Maximum2024-04-06 10:00:00
2024-04-06T17:09:16.703293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:17.044955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

토요일운영종료시간
Date

MISSING 

Distinct2
Distinct (%)20.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
Minimum2024-04-06 00:00:00
Maximum2024-04-06 17:30:00
2024-04-06T17:09:17.316068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:17.517060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

비고
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing21
Missing (%)95.5%
Memory size308.0 B
2024-04-06T17:09:17.767513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row목요일 20시까지 연장운영
ValueCountFrequency (%)
목요일 1
33.3%
20시까지 1
33.3%
연장운영 1
33.3%
2024-04-06T17:09:18.478456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
14.3%
목 1
 
7.1%
요 1
 
7.1%
일 1
 
7.1%
2 1
 
7.1%
0 1
 
7.1%
시 1
 
7.1%
까 1
 
7.1%
지 1
 
7.1%
연 1
 
7.1%
Other values (3) 3
21.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
71.4%
Space Separator 2
 
14.3%
Decimal Number 2
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
목 1
10.0%
요 1
10.0%
일 1
10.0%
시 1
10.0%
까 1
10.0%
지 1
10.0%
연 1
10.0%
장 1
10.0%
운 1
10.0%
영 1
10.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
0 1
50.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
71.4%
Common 4
 
28.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
목 1
10.0%
요 1
10.0%
일 1
10.0%
시 1
10.0%
까 1
10.0%
지 1
10.0%
연 1
10.0%
장 1
10.0%
운 1
10.0%
영 1
10.0%
Common
ValueCountFrequency (%)
2
50.0%
2 1
25.0%
0 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
71.4%
ASCII 4
 
28.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
50.0%
2 1
25.0%
0 1
25.0%
Hangul
ValueCountFrequency (%)
목 1
10.0%
요 1
10.0%
일 1
10.0%
시 1
10.0%
까 1
10.0%
지 1
10.0%
연 1
10.0%
장 1
10.0%
운 1
10.0%
영 1
10.0%

전화번호
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
2024-04-06T17:09:18.783216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12.5
Mean length11.9
Min length11

Characters and Unicode

Total characters119
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)100.0%

Sample

1st row070-4112-7085
2nd row02-3295-2390
3rd row02-923-2272
4th row02-921-9868
5th row02-2212-5844
ValueCountFrequency (%)
070-4112-7085 1
10.0%
02-3295-2390 1
10.0%
02-923-2272 1
10.0%
02-921-9868 1
10.0%
02-2212-5844 1
10.0%
02-2212-0833 1
10.0%
02-921-5801 1
10.0%
02-2212-1975 1
10.0%
02-2237-5800 1
10.0%
070-4121-2005 1
10.0%
2024-04-06T17:09:19.396856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 30
25.2%
0 20
16.8%
- 20
16.8%
1 11
 
9.2%
8 7
 
5.9%
5 7
 
5.9%
9 7
 
5.9%
7 6
 
5.0%
3 6
 
5.0%
4 4
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99
83.2%
Dash Punctuation 20
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30
30.3%
0 20
20.2%
1 11
 
11.1%
8 7
 
7.1%
5 7
 
7.1%
9 7
 
7.1%
7 6
 
6.1%
3 6
 
6.1%
4 4
 
4.0%
6 1
 
1.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 119
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 30
25.2%
0 20
16.8%
- 20
16.8%
1 11
 
9.2%
8 7
 
5.9%
5 7
 
5.9%
9 7
 
5.9%
7 6
 
5.0%
3 6
 
5.0%
4 4
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 119
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 30
25.2%
0 20
16.8%
- 20
16.8%
1 11
 
9.2%
8 7
 
5.9%
5 7
 
5.9%
9 7
 
5.9%
7 6
 
5.0%
3 6
 
5.0%
4 4
 
3.4%

관리기관명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size308.0 B
<NA>
12 
서울특별시 동대문구청
10 

Length

Max length11
Median length4
Mean length7.1818182
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 동대문구청
2nd row서울특별시 동대문구청
3rd row서울특별시 동대문구청
4th row서울특별시 동대문구청
5th row서울특별시 동대문구청

Common Values

ValueCountFrequency (%)
<NA> 12
54.5%
서울특별시 동대문구청 10
45.5%

Length

2024-04-06T17:09:19.731537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:09:20.009779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 12
37.5%
서울특별시 10
31.2%
동대문구청 10
31.2%

데이터기준일
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)10.0%
Missing12
Missing (%)54.5%
Memory size308.0 B
Minimum2024-03-22 00:00:00
Maximum2024-03-22 00:00:00
2024-04-06T17:09:20.239501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:20.442436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-06T17:09:08.176232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:07.768032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:08.364280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:09:07.984993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:09:20.599363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명도로명주소상세주소위도경도직원 수이용정원토요일운영여부토요일운영시작시간토요일운영종료시간전화번호
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상세주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
위도1.0001.0001.0001.0000.4340.0000.0000.0000.0000.0001.000
경도1.0001.0001.0000.4341.0000.0000.2320.8080.0000.0001.000
직원 수1.0001.0001.0000.0000.0001.0000.0000.0000.0000.0001.000
이용정원1.0001.0001.0000.0000.2320.0001.0000.0000.0000.0001.000
토요일운영여부1.0001.0001.0000.0000.8080.0000.0001.0000.5830.5831.000
토요일운영시작시간1.0001.0001.0000.0000.0000.0000.0000.5831.0000.9121.000
토요일운영종료시간1.0001.0001.0000.0000.0000.0000.0000.5830.9121.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-04-06T17:09:20.869235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
토요일운영여부관리기관명이용정원서비스분류명직원 수
토요일운영여부1.0001.0000.0001.0000.000
관리기관명1.0001.0001.0001.0001.000
이용정원0.0001.0001.0001.0000.000
서비스분류명1.0001.0001.0001.0001.000
직원 수0.0001.0000.0001.0001.000
2024-04-06T17:09:21.117243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도서비스분류명직원 수이용정원토요일운영여부관리기관명
위도1.0000.1521.0000.0000.0000.0001.000
경도0.1521.0001.0000.0000.0000.3851.000
서비스분류명1.0001.0001.0001.0001.0001.0001.000
직원 수0.0000.0001.0001.0000.0000.0001.000
이용정원0.0000.0001.0000.0001.0000.0001.000
토요일운영여부0.0000.3851.0000.0000.0001.0001.000
관리기관명1.0001.0001.0001.0001.0001.0001.000

Missing values

2024-04-06T17:09:08.636972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:09:09.043498image/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.
2024-04-06T17:09:09.444234image/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

시설명서비스분류명도로명주소상세주소위도경도직원 수이용정원평일시작시간평일종료시간토요일운영여부토요일운영시작시간토요일운영종료시간비고전화번호관리기관명데이터기준일
0꿈자람공동육아방 휘경점공동육아방서울특별시 동대문구 장안벚꽃로 3232층37.586864127.07015922510:0017:30Y00:0000:00<NA>070-4112-7085서울특별시 동대문구청2024-03-22
1꿈자람공동육아방 청량리점공동육아방서울특별시 동대문구 왕산로 2394층37.583058127.04818512510:0017:30N00:0000:00<NA>02-3295-2390서울특별시 동대문구청2024-03-22
2꿈자람공동육아방 제기점공동육아방서울특별시 동대문구 약령시로7길 19동대문구육아종합지원센터 제기점 2층 (제기동)37.583728127.03467612510:0017:30Y10:0017:30<NA>02-923-2272서울특별시 동대문구청2024-03-22
3꿈자람공동육아방 제기2호점공동육아방서울특별시 동대문구 제기로 20101동 202호 (제기동, 더푸른빌)37.58629127.0351612010:0017:30Y10:0017:30<NA>02-921-9868서울특별시 동대문구청2024-03-22
4꿈자람공동육아방 장안2호점공동육아방서울특별시 동대문구 한천로28길 9202동 1호 (장안동, 시온아트빌)37.57379127.0676212010:0017:30Y10:0017:30<NA>02-2212-5844서울특별시 동대문구청2024-03-22
5꿈자람공동육아방 장안1호점공동육아방서울특별시 동대문구 답십리로66길 3꿈자람공동육아방 1층 (장안동)37.57234127.0685912010:0017:30Y10:0017:30<NA>02-2212-0833서울특별시 동대문구청2024-03-22
6꿈자람공동육아방 용신점공동육아방서울특별시 동대문구 무학로 89동대문구민행복센터 2층 (용두동)37.57232127.0299212510:0017:30Y10:0017:30<NA>02-921-5801서울특별시 동대문구청2024-03-22
7꿈자람공동육아방 배봉산점공동육아방서울특별시 동대문구 전농로 16길 97배봉산숲속도서관 1층 꿈자람공동육아방 배봉산점37.5784127.0627912010:0017:30Y10:0017:30<NA>02-2212-1975서울특별시 동대문구청2024-03-22
8꿈자람공동육아방 답십리점공동육아방서울특별시 동대문구 황물로 62동대문구육아종합지원센터 2층37.57206127.0479522510:0017:30Y10:0017:30목요일 20시까지 연장운영02-2237-5800서울특별시 동대문구청2024-03-22
9꿈자람공동육아방 답십리2호점공동육아방서울특별시 동대문구 답십리로45길 473층 (답십리동)37.57491127.0550912510:0017:30N00:0000:00<NA>070-4121-2005서울특별시 동대문구청2024-03-22
시설명서비스분류명도로명주소상세주소위도경도직원 수이용정원평일시작시간평일종료시간토요일운영여부토요일운영시작시간토요일운영종료시간비고전화번호관리기관명데이터기준일
12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
13<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
14<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시설명서비스분류명도로명주소상세주소위도경도직원 수이용정원평일시작시간평일종료시간토요일운영여부토요일운영시작시간토요일운영종료시간비고전화번호관리기관명데이터기준일# duplicates
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