Overview

Dataset statistics

Number of variables10
Number of observations36
Missing cells88
Missing cells (%)24.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory83.6 B

Variable types

Categorical4
Text2
DateTime3
Boolean1

Dataset

Description전북특별자치도 시군별 산후조리원 점검 및 이송 보고(산후조리원명, 정기점검일, 민원등 부정기점검일, 위반내용 등) 데이터입니다.
Author전북특별자치도
URLhttps://www.data.go.kr/data/15055587/fileData.do

Alerts

이송 의료기관 is highly overall correlated with 시군구(보건소) and 2 other fieldsHigh correlation
시군구(보건소) is highly overall correlated with 위반내용 and 3 other fieldsHigh correlation
대상자 is highly overall correlated with 시군구(보건소) and 2 other fieldsHigh correlation
이송후 산후조리원 퇴소 여부 is highly overall correlated with 시군구(보건소) and 1 other fieldsHigh correlation
위반내용 is highly overall correlated with 시군구(보건소) and 3 other fieldsHigh correlation
위반내용 is highly imbalanced (77.0%)Imbalance
민원등 부정기점검일 has 22 (61.1%) missing valuesMissing
이송일 has 22 (61.1%) missing valuesMissing
증상 또는 사고유형 has 22 (61.1%) missing valuesMissing
이송후 산후조리원 퇴소 여부 has 22 (61.1%) missing valuesMissing

Reproduction

Analysis started2024-03-15 02:08:32.307762
Analysis finished2024-03-15 02:08:33.865654
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구(보건소)
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size416.0 B
전주시
20 
군산시보건소
8 
익산시
4 
정읍시
 
2
김제시보건소
 
2

Length

Max length6
Median length3
Mean length3.8333333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 20
55.6%
군산시보건소 8
 
22.2%
익산시 4
 
11.1%
정읍시 2
 
5.6%
김제시보건소 2
 
5.6%

Length

2024-03-15T11:08:33.992078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:08:34.220486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 20
55.6%
군산시보건소 8
 
22.2%
익산시 4
 
11.1%
정읍시 2
 
5.6%
김제시보건소 2
 
5.6%

산후조리원명
Text

Distinct20
Distinct (%)55.6%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-15T11:08:34.923487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length11
Mean length9.2777778
Min length2

Characters and Unicode

Total characters334
Distinct characters48
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

Unique16 ?
Unique (%)44.4%

Sample

1st row한별산후조리원
2nd row한나산후조리원
3rd row한나산후조리원
4th row한나산후조리원
5th row푸른산후조리원
ValueCountFrequency (%)
원광대학교전주,한방병원산후조리원 9
22.0%
미래와 4
 
9.8%
여성 4
 
9.8%
은혜 4
 
9.8%
한나산후조리원 3
 
7.3%
한별산후조리원 1
 
2.4%
미래와여성 1
 
2.4%
한사랑산후조리원 1
 
2.4%
서울산후조리원 1
 
2.4%
현대산후조리원 1
 
2.4%
Other values (12) 12
29.3%
2024-03-15T11:08:35.923563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 46
 
13.8%
조 29
 
8.7%
산 28
 
8.4%
리 28
 
8.4%
후 28
 
8.4%
한 15
 
4.5%
대 10
 
3.0%
방 10
 
3.0%
광 9
 
2.7%
주 9
 
2.7%
Other values (38) 122
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 320
95.8%
Other Punctuation 9
 
2.7%
Space Separator 5
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 46
14.4%
조 29
 
9.1%
산 28
 
8.8%
리 28
 
8.8%
후 28
 
8.8%
한 15
 
4.7%
대 10
 
3.1%
방 10
 
3.1%
광 9
 
2.8%
주 9
 
2.8%
Other values (36) 108
33.8%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 320
95.8%
Common 14
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 46
14.4%
조 29
 
9.1%
산 28
 
8.8%
리 28
 
8.8%
후 28
 
8.8%
한 15
 
4.7%
대 10
 
3.1%
방 10
 
3.1%
광 9
 
2.8%
주 9
 
2.8%
Other values (36) 108
33.8%
Common
ValueCountFrequency (%)
, 9
64.3%
5
35.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 320
95.8%
ASCII 14
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 46
14.4%
조 29
 
9.1%
산 28
 
8.8%
리 28
 
8.8%
후 28
 
8.8%
한 15
 
4.7%
대 10
 
3.1%
방 10
 
3.1%
광 9
 
2.8%
주 9
 
2.8%
Other values (36) 108
33.8%
ASCII
ValueCountFrequency (%)
, 9
64.3%
5
35.7%

정기점검일
Date

Distinct16
Distinct (%)44.4%
Missing0
Missing (%)0.0%
Memory size416.0 B
Minimum2013-03-29 00:00:00
Maximum2014-05-07 00:00:00
2024-03-15T11:08:36.270000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:08:36.641655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

민원등 부정기점검일
Date

MISSING 

Distinct10
Distinct (%)71.4%
Missing22
Missing (%)61.1%
Memory size416.0 B
Minimum2014-05-09 00:00:00
Maximum2014-07-04 00:00:00
2024-03-15T11:08:36.994387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:08:37.277256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)

위반내용
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size416.0 B
위반사항 없음
34 
4대보험 의무가입 및 신생아 격리시설 적정운영적정 인력기준 준수
 
1
4대보험 의무가입, 세탁실 위생관리 신생아 격리시설 적정운영 ,인력기준 준수
 
1

Length

Max length65
Median length7
Mean length9.4444444
Min length7

Unique

Unique2 ?
Unique (%)5.6%

Sample

1st row위반사항 없음
2nd row위반사항 없음
3rd row위반사항 없음
4th row위반사항 없음
5th row위반사항 없음

Common Values

ValueCountFrequency (%)
위반사항 없음 34
94.4%
4대보험 의무가입 및 신생아 격리시설 적정운영적정 인력기준 준수 1
 
2.8%
4대보험 의무가입, 세탁실 위생관리 신생아 격리시설 적정운영 ,인력기준 준수 1
 
2.8%

Length

2024-03-15T11:08:37.486663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:08:37.732861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
위반사항 34
40.0%
없음 34
40.0%
4대보험 2
 
2.4%
의무가입 2
 
2.4%
신생아 2
 
2.4%
격리시설 2
 
2.4%
인력기준 2
 
2.4%
준수 2
 
2.4%
및 1
 
1.2%
적정운영적정 1
 
1.2%
Other values (3) 3
 
3.5%

이송일
Date

MISSING 

Distinct13
Distinct (%)92.9%
Missing22
Missing (%)61.1%
Memory size416.0 B
Minimum2014-01-01 00:00:00
Maximum2014-06-26 00:00:00
2024-03-15T11:08:37.981988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T11:08:38.198774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

대상자
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size416.0 B
<NA>
22 
신생아
12 
산모
 
2

Length

Max length4
Median length4
Mean length3.5555556
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row신생아
3rd row신생아
4th row신생아
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 22
61.1%
신생아 12
33.3%
산모 2
 
5.6%

Length

2024-03-15T11:08:38.536022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:08:38.788175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
61.1%
신생아 12
33.3%
산모 2
 
5.6%

증상 또는 사고유형
Text

MISSING 

Distinct11
Distinct (%)78.6%
Missing22
Missing (%)61.1%
Memory size416.0 B
2024-03-15T11:08:39.521197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length13
Mean length9.7142857
Min length2

Characters and Unicode

Total characters136
Distinct characters59
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

Unique8 ?
Unique (%)57.1%

Sample

1st row오심, 구토, 수유량 감소, 황달 관찰 되며 복부팽만 증상
2nd row수유량이 적고,바는 힘이 약한 듯함
3rd row갈색구토 1회, 혈변3회 관찰
4th row황달
5th row봉화직염
ValueCountFrequency (%)
황달 3
 
9.4%
증상(구토 2
 
6.2%
기타(발열 2
 
6.2%
관찰 2
 
6.2%
장관계 2
 
6.2%
약한 1
 
3.1%
감염 1
 
3.1%
기타(요로 1
 
3.1%
기타(수술부위염증 1
 
3.1%
기타(불명열 1
 
3.1%
Other values (16) 16
50.0%
2024-03-15T11:08:40.621130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18
 
13.2%
( 7
 
5.1%
) 7
 
5.1%
, 5
 
3.7%
증 5
 
3.7%
기 5
 
3.7%
타 5
 
3.7%
토 4
 
2.9%
관 4
 
2.9%
구 4
 
2.9%
Other values (49) 72
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 97
71.3%
Space Separator 18
 
13.2%
Open Punctuation 7
 
5.1%
Close Punctuation 7
 
5.1%
Other Punctuation 5
 
3.7%
Decimal Number 2
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
증 5
 
5.2%
기 5
 
5.2%
타 5
 
5.2%
토 4
 
4.1%
관 4
 
4.1%
구 4
 
4.1%
염 3
 
3.1%
수 3
 
3.1%
달 3
 
3.1%
열 3
 
3.1%
Other values (43) 58
59.8%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 97
71.3%
Common 39
28.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
증 5
 
5.2%
기 5
 
5.2%
타 5
 
5.2%
토 4
 
4.1%
관 4
 
4.1%
구 4
 
4.1%
염 3
 
3.1%
수 3
 
3.1%
달 3
 
3.1%
열 3
 
3.1%
Other values (43) 58
59.8%
Common
ValueCountFrequency (%)
18
46.2%
( 7
 
17.9%
) 7
 
17.9%
, 5
 
12.8%
3 1
 
2.6%
1 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 97
71.3%
ASCII 39
28.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18
46.2%
( 7
 
17.9%
) 7
 
17.9%
, 5
 
12.8%
3 1
 
2.6%
1 1
 
2.6%
Hangul
ValueCountFrequency (%)
증 5
 
5.2%
기 5
 
5.2%
타 5
 
5.2%
토 4
 
4.1%
관 4
 
4.1%
구 4
 
4.1%
염 3
 
3.1%
수 3
 
3.1%
달 3
 
3.1%
열 3
 
3.1%
Other values (43) 58
59.8%

이송 의료기관
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size416.0 B
<NA>
22 
종합병원(소아과)
6 
종합병원(신생아실)
5 
종합병원(산부인과)
 
2
종합병원(신생아 중환자실)
 
1

Length

Max length14
Median length4
Mean length6.2777778
Min length4

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row<NA>
2nd row종합병원(신생아실)
3rd row종합병원(신생아실)
4th row종합병원(신생아실)
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 22
61.1%
종합병원(소아과) 6
 
16.7%
종합병원(신생아실) 5
 
13.9%
종합병원(산부인과) 2
 
5.6%
종합병원(신생아 중환자실) 1
 
2.8%

Length

2024-03-15T11:08:41.241224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T11:08:41.637296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 22
59.5%
종합병원(소아과 6
 
16.2%
종합병원(신생아실 5
 
13.5%
종합병원(산부인과 2
 
5.4%
종합병원(신생아 1
 
2.7%
중환자실 1
 
2.7%

이송후 산후조리원 퇴소 여부
Boolean

HIGH CORRELATION  MISSING 

Distinct2
Distinct (%)14.3%
Missing22
Missing (%)61.1%
Memory size200.0 B
True
7 
False
7 
(Missing)
22 
ValueCountFrequency (%)
True 7
 
19.4%
False 7
 
19.4%
(Missing) 22
61.1%
2024-03-15T11:08:41.967214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T11:08:42.174107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구(보건소)산후조리원명정기점검일민원등 부정기점검일위반내용이송일대상자증상 또는 사고유형이송 의료기관이송후 산후조리원 퇴소 여부
시군구(보건소)1.0001.0000.9241.0000.684NaNNaNNaNNaNNaN
산후조리원명1.0001.0000.0000.0001.0001.0000.0000.7710.7520.728
정기점검일0.9240.0001.0001.0000.0000.6560.3040.5650.0000.470
민원등 부정기점검일1.0000.0001.0001.000NaN0.7780.3160.6360.0000.000
위반내용0.6841.0000.000NaN1.000NaNNaNNaNNaNNaN
이송일NaN1.0000.6560.778NaN1.0000.0000.9130.6791.000
대상자NaN0.0000.3040.316NaN0.0001.0001.0001.0000.000
증상 또는 사고유형NaN0.7710.5650.636NaN0.9131.0001.0000.4990.723
이송 의료기관NaN0.7520.0000.000NaN0.6791.0000.4991.0000.309
이송후 산후조리원 퇴소 여부NaN0.7280.4700.000NaN1.0000.0000.7230.3091.000
2024-03-15T11:08:42.517673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이송 의료기관시군구(보건소)대상자이송후 산후조리원 퇴소 여부위반내용
이송 의료기관1.0001.0000.9130.1351.000
시군구(보건소)1.0001.0001.0001.0000.640
대상자0.9131.0001.0000.0001.000
이송후 산후조리원 퇴소 여부0.1351.0000.0001.0001.000
위반내용1.0000.6401.0001.0001.000
2024-03-15T11:08:42.776405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구(보건소)위반내용대상자이송 의료기관이송후 산후조리원 퇴소 여부
시군구(보건소)1.0000.6401.0001.0001.000
위반내용0.6401.0001.0001.0001.000
대상자1.0001.0001.0000.9130.000
이송 의료기관1.0001.0000.9131.0000.135
이송후 산후조리원 퇴소 여부1.0001.0000.0000.1351.000

Missing values

2024-03-15T11:08:33.064398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T11:08:33.476986image/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.
2024-03-15T11:08:33.725766image/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

시군구(보건소)산후조리원명정기점검일민원등 부정기점검일위반내용이송일대상자증상 또는 사고유형이송 의료기관이송후 산후조리원 퇴소 여부
0전주시한별산후조리원2014-04-17<NA>위반사항 없음<NA><NA><NA><NA><NA>
1전주시한나산후조리원2014-04-162014-05-09위반사항 없음2014-03-19신생아오심, 구토, 수유량 감소, 황달 관찰 되며 복부팽만 증상종합병원(신생아실)Y
2전주시한나산후조리원2014-04-172014-05-10위반사항 없음2014-05-24신생아수유량이 적고,바는 힘이 약한 듯함종합병원(신생아실)Y
3전주시한나산후조리원2014-04-182014-05-11위반사항 없음2014-06-26신생아갈색구토 1회, 혈변3회 관찰종합병원(신생아실)Y
4전주시푸른산후조리원2014-04-17<NA>위반사항 없음<NA><NA><NA><NA><NA>
5전주시미르피아산후조리원2014-04-18<NA>위반사항 없음2014-06-25신생아황달종합병원(신생아실)N
6전주시참조은산후조리원2014-04-18<NA>위반사항 없음<NA><NA><NA><NA><NA>
7전주시세나산후조리원2014-04-16<NA>위반사항 없음2014-05-07신생아봉화직염종합병원(신생아실)Y
8전주시정성산후조리원2014-04-17<NA>위반사항 없음<NA><NA><NA><NA><NA>
9전주시원광대학교전주,한방병원산후조리원2014-04-162014-05-09위반사항 없음2014-01-01산모기타(불명열)종합병원(산부인과)Y
시군구(보건소)산후조리원명정기점검일민원등 부정기점검일위반내용이송일대상자증상 또는 사고유형이송 의료기관이송후 산후조리원 퇴소 여부
26군산시보건소은혜2013-09-03<NA>위반사항 없음<NA><NA><NA><NA><NA>
27군산시보건소은혜2013-12-20<NA>위반사항 없음<NA><NA><NA><NA><NA>
28익산시휴산후조리원2014-05-07<NA>위반사항 없음<NA><NA><NA><NA><NA>
29익산시제일맘산후조리원2014-05-02<NA>위반사항 없음<NA><NA><NA><NA><NA>
30익산시미래와여성산후조리원2014-05-07<NA>위반사항 없음<NA><NA><NA><NA><NA>
31익산시영등한방산후조리원2014-05-07<NA>위반사항 없음<NA><NA><NA><NA><NA>
32정읍시현대산후조리원2014-03-132014-07-04위반사항 없음<NA><NA><NA><NA><NA>
33정읍시서울산후조리원2014-03-132014-07-04위반사항 없음<NA><NA><NA><NA><NA>
34김제시보건소한사랑산후조리원2014-05-07<NA>4대보험 의무가입 및 신생아 격리시설 적정운영적정 인력기준 준수<NA><NA><NA><NA><NA>
35김제시보건소미래와여성 산후조리원2014-05-07<NA>4대보험 의무가입, 세탁실 위생관리 신생아 격리시설 적정운영 ,인력기준 준수<NA><NA><NA><NA><NA>