Overview

Dataset statistics

Number of variables4
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory990.0 B
Average record size in memory38.1 B

Variable types

Numeric1
Text3

Dataset

Description경기도 고양시 산모신생아 건강관리 제공기관 목록 현황에 대한 데이터로 각 구별 제공기관명, 소재지, 전화번호를 제공합니다.
URLhttps://www.data.go.kr/data/3078367/fileData.do

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:22:51.839937
Analysis finished2023-12-12 20:22:52.295729
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.961538
Minimum1
Maximum27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T05:22:52.383545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q320.75
95-th percentile25.75
Maximum27
Range26
Interquartile range (IQR)13.5

Descriptive statistics

Standard deviation8.0918763
Coefficient of variation (CV)0.57958342
Kurtosis-1.278212
Mean13.961538
Median Absolute Deviation (MAD)7
Skewness0.015365927
Sum363
Variance65.478462
MonotonicityStrictly increasing
2023-12-13T05:22:52.510692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
16 1
 
3.8%
27 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
27 1
3.8%
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T05:22:52.744863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length14.5
Mean length9
Min length4

Characters and Unicode

Total characters234
Distinct characters80
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

Unique24 ?
Unique (%)92.3%

Sample

1st rowA+고양친정맘
2nd row사임당산후관리
3rd row닥터맘산모도우미
4th row이레아이맘
5th row(고양)아이미래로 일산
ValueCountFrequency (%)
산후도우미 3
 
7.5%
산모피아 2
 
5.0%
일산 2
 
5.0%
파주 2
 
5.0%
㈜아이맘케어 1
 
2.5%
가온보건케어 1
 
2.5%
일산·파주지사 1
 
2.5%
경기)도담도담 1
 
2.5%
고양 1
 
2.5%
산모도우미119 1
 
2.5%
Other values (25) 25
62.5%
2023-12-13T05:22:53.152223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17
 
7.3%
15
 
6.4%
12
 
5.1%
9
 
3.8%
9
 
3.8%
8
 
3.4%
8
 
3.4%
8
 
3.4%
7
 
3.0%
) 7
 
3.0%
Other values (70) 134
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 192
82.1%
Space Separator 15
 
6.4%
Close Punctuation 7
 
3.0%
Open Punctuation 7
 
3.0%
Uppercase Letter 5
 
2.1%
Decimal Number 3
 
1.3%
Math Symbol 2
 
0.9%
Other Punctuation 2
 
0.9%
Other Symbol 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
17
 
8.9%
12
 
6.2%
9
 
4.7%
9
 
4.7%
8
 
4.2%
8
 
4.2%
8
 
4.2%
7
 
3.6%
7
 
3.6%
6
 
3.1%
Other values (58) 101
52.6%
Uppercase Letter
ValueCountFrequency (%)
A 3
60.0%
S 1
 
20.0%
M 1
 
20.0%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
9 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
82.5%
Common 36
 
15.4%
Latin 5
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
17
 
8.8%
12
 
6.2%
9
 
4.7%
9
 
4.7%
8
 
4.1%
8
 
4.1%
8
 
4.1%
7
 
3.6%
7
 
3.6%
6
 
3.1%
Other values (59) 102
52.8%
Common
ValueCountFrequency (%)
15
41.7%
) 7
19.4%
( 7
19.4%
1 2
 
5.6%
+ 2
 
5.6%
, 1
 
2.8%
· 1
 
2.8%
9 1
 
2.8%
Latin
ValueCountFrequency (%)
A 3
60.0%
S 1
 
20.0%
M 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 192
82.1%
ASCII 40
 
17.1%
None 2
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
17
 
8.9%
12
 
6.2%
9
 
4.7%
9
 
4.7%
8
 
4.2%
8
 
4.2%
8
 
4.2%
7
 
3.6%
7
 
3.6%
6
 
3.1%
Other values (58) 101
52.6%
ASCII
ValueCountFrequency (%)
15
37.5%
) 7
17.5%
( 7
17.5%
A 3
 
7.5%
1 2
 
5.0%
+ 2
 
5.0%
, 1
 
2.5%
S 1
 
2.5%
M 1
 
2.5%
9 1
 
2.5%
None
ValueCountFrequency (%)
· 1
50.0%
1
50.0%
Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T05:22:53.424761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length44
Mean length38.576923
Min length28

Characters and Unicode

Total characters1003
Distinct characters121
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

Unique24 ?
Unique (%)92.3%

Sample

1st row경기도 고양시 덕양구 화정로 65, 1209호(한화오벨리스크)
2nd row경기도 고양시 덕양구 지도로 84, 406호(토당동, 영빌딩)
3rd row경기도 고양시 덕양구 마상로102번길 56, 102호 (주교동)
4th row경기도 고양시 덕양구 화중로 96, 2층 212호(화정동, 우정프라자)
5th row경기도 고양시 덕양구 화정로 65, 1410호(한화오벨리스크)
ValueCountFrequency (%)
경기도 26
 
14.1%
고양시 26
 
14.1%
덕양구 11
 
5.9%
일산동구 8
 
4.3%
일산서구 7
 
3.8%
150 3
 
1.6%
자유프라자 3
 
1.6%
주엽로 3
 
1.6%
호수로 2
 
1.1%
4층 2
 
1.1%
Other values (85) 94
50.8%
2023-12-13T05:22:53.829981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
 
15.9%
, 41
 
4.1%
38
 
3.8%
0 37
 
3.7%
1 37
 
3.7%
32
 
3.2%
29
 
2.9%
2 28
 
2.8%
27
 
2.7%
27
 
2.7%
Other values (111) 548
54.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
55.4%
Decimal Number 193
 
19.2%
Space Separator 159
 
15.9%
Other Punctuation 41
 
4.1%
Open Punctuation 22
 
2.2%
Close Punctuation 22
 
2.2%
Dash Punctuation 8
 
0.8%
Uppercase Letter 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
38
 
6.8%
32
 
5.8%
29
 
5.2%
27
 
4.9%
27
 
4.9%
27
 
4.9%
26
 
4.7%
26
 
4.7%
26
 
4.7%
26
 
4.7%
Other values (94) 272
48.9%
Decimal Number
ValueCountFrequency (%)
0 37
19.2%
1 37
19.2%
2 28
14.5%
3 23
11.9%
6 19
9.8%
4 17
8.8%
5 14
 
7.3%
8 10
 
5.2%
7 5
 
2.6%
9 3
 
1.6%
Space Separator
ValueCountFrequency (%)
159
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
55.4%
Common 446
44.5%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
38
 
6.8%
32
 
5.8%
29
 
5.2%
27
 
4.9%
27
 
4.9%
27
 
4.9%
26
 
4.7%
26
 
4.7%
26
 
4.7%
26
 
4.7%
Other values (94) 272
48.9%
Common
ValueCountFrequency (%)
159
35.7%
, 41
 
9.2%
0 37
 
8.3%
1 37
 
8.3%
2 28
 
6.3%
3 23
 
5.2%
( 22
 
4.9%
) 22
 
4.9%
6 19
 
4.3%
4 17
 
3.8%
Other values (6) 41
 
9.2%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
55.4%
ASCII 447
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
35.6%
, 41
 
9.2%
0 37
 
8.3%
1 37
 
8.3%
2 28
 
6.3%
3 23
 
5.1%
( 22
 
4.9%
) 22
 
4.9%
6 19
 
4.3%
4 17
 
3.8%
Other values (7) 42
 
9.4%
Hangul
ValueCountFrequency (%)
38
 
6.8%
32
 
5.8%
29
 
5.2%
27
 
4.9%
27
 
4.9%
27
 
4.9%
26
 
4.7%
26
 
4.7%
26
 
4.7%
26
 
4.7%
Other values (94) 272
48.9%
Distinct25
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T05:22:53.999563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12
Min length11

Characters and Unicode

Total characters312
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

Unique24 ?
Unique (%)92.3%

Sample

1st row031-966-5279
2nd row031-972-3575
3rd row031-998-5945
4th row031-968-0521
5th row031-921-5992
ValueCountFrequency (%)
031-814-3525 2
 
7.7%
031-966-5279 1
 
3.8%
031-914-3579 1
 
3.8%
031-923-5001 1
 
3.8%
031-912-3559 1
 
3.8%
031-976-2939 1
 
3.8%
031-912-8181 1
 
3.8%
031-812-3456 1
 
3.8%
031-918-3519 1
 
3.8%
031-8070-7090 1
 
3.8%
Other values (15) 15
57.7%
2023-12-13T05:22:54.283609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 52
16.7%
3 45
14.4%
1 45
14.4%
0 43
13.8%
9 33
10.6%
5 24
7.7%
8 17
 
5.4%
2 17
 
5.4%
6 14
 
4.5%
7 13
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 45
17.3%
1 45
17.3%
0 43
16.5%
9 33
12.7%
5 24
9.2%
8 17
 
6.5%
2 17
 
6.5%
6 14
 
5.4%
7 13
 
5.0%
4 9
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 52
16.7%
3 45
14.4%
1 45
14.4%
0 43
13.8%
9 33
10.6%
5 24
7.7%
8 17
 
5.4%
2 17
 
5.4%
6 14
 
4.5%
7 13
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 52
16.7%
3 45
14.4%
1 45
14.4%
0 43
13.8%
9 33
10.6%
5 24
7.7%
8 17
 
5.4%
2 17
 
5.4%
6 14
 
4.5%
7 13
 
4.2%

Interactions

2023-12-13T05:22:52.060323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/