Overview

Dataset statistics

Number of variables6
Number of observations22
Missing cells20
Missing cells (%)15.2%
Duplicate rows1
Duplicate rows (%)4.5%
Total size in memory1.2 KiB
Average record size in memory54.0 B

Variable types

Unsupported1
Categorical2
Text3

Dataset

Description산후조리원현황20181231기준
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=203090

Alerts

Dataset has 1 (4.5%) duplicate rowsDuplicates
Unnamed: 1 is highly overall correlated with Unnamed: 2High correlation
Unnamed: 2 is highly overall correlated with Unnamed: 1High correlation
산후조리원 현황(2018.12.31.기준) has 5 (22.7%) missing valuesMissing
Unnamed: 3 has 5 (22.7%) missing valuesMissing
Unnamed: 4 has 5 (22.7%) missing valuesMissing
Unnamed: 5 has 5 (22.7%) missing valuesMissing
산후조리원 현황(2018.12.31.기준) is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 01:29:39.455639
Analysis finished2024-03-14 01:29:40.242024
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산후조리원 현황(2018.12.31.기준)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing5
Missing (%)22.7%
Memory size308.0 B

Unnamed: 1
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size308.0 B
전북
16 
<NA>
5 
시도
 
1

Length

Max length4
Median length2
Mean length2.4545455
Min length2

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
전북 16
72.7%
<NA> 5
 
22.7%
시도 1
 
4.5%

Length

2024-03-14T10:29:40.303065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:29:40.393168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북 16
72.7%
na 5
 
22.7%
시도 1
 
4.5%

Unnamed: 2
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)27.3%
Missing0
Missing (%)0.0%
Memory size308.0 B
전주시
9 
<NA>
5 
익산시
3 
군산시
2 
정읍시
2 

Length

Max length4
Median length3
Mean length3.2272727
Min length3

Unique

Unique1 ?
Unique (%)4.5%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 9
40.9%
<NA> 5
22.7%
익산시 3
 
13.6%
군산시 2
 
9.1%
정읍시 2
 
9.1%
시군구 1
 
4.5%

Length

2024-03-14T10:29:40.495153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:29:40.593715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전주시 9
40.9%
na 5
22.7%
익산시 3
 
13.6%
군산시 2
 
9.1%
정읍시 2
 
9.1%
시군구 1
 
4.5%

Unnamed: 3
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing5
Missing (%)22.7%
Memory size308.0 B
2024-03-14T10:29:40.738696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length8.5882353
Min length6

Characters and Unicode

Total characters146
Distinct characters45
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)100.0%

Sample

1st row산후조리원명
2nd row한별산후조리원
3rd row미르피아산후조리원
4th row푸른산부인과 산후조리원
5th row정성산후조리원
ValueCountFrequency (%)
산후조리원 3
 
14.3%
산후조리원명 1
 
4.8%
한방병원산후조리원 1
 
4.8%
서울산후조리원 1
 
4.8%
휴산후조리원 1
 
4.8%
제일맘 1
 
4.8%
미래와여성 1
 
4.8%
미래와여성산후조리원 1
 
4.8%
은혜산후조리원 1
 
4.8%
세인트포레산후조리원 1
 
4.8%
Other values (9) 9
42.9%
2024-03-14T10:29:40.991638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 18
12.3%
원 18
12.3%
조 17
 
11.6%
리 17
 
11.6%
후 17
 
11.6%
4
 
2.7%
한 3
 
2.1%
미 3
 
2.1%
래 3
 
2.1%
나 3
 
2.1%
Other values (35) 43
29.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 142
97.3%
Control 4
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 18
12.7%
원 18
12.7%
조 17
12.0%
리 17
12.0%
후 17
12.0%
한 3
 
2.1%
미 3
 
2.1%
래 3
 
2.1%
나 3
 
2.1%
성 3
 
2.1%
Other values (34) 40
28.2%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 142
97.3%
Common 4
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 18
12.7%
원 18
12.7%
조 17
12.0%
리 17
12.0%
후 17
12.0%
한 3
 
2.1%
미 3
 
2.1%
래 3
 
2.1%
나 3
 
2.1%
성 3
 
2.1%
Other values (34) 40
28.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 142
97.3%
ASCII 4
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 18
12.7%
원 18
12.7%
조 17
12.0%
리 17
12.0%
후 17
12.0%
한 3
 
2.1%
미 3
 
2.1%
래 3
 
2.1%
나 3
 
2.1%
성 3
 
2.1%
Other values (34) 40
28.2%
ASCII
ValueCountFrequency (%)
4
100.0%

Unnamed: 4
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing5
Missing (%)22.7%
Memory size308.0 B
2024-03-14T10:29:41.151586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length15
Min length2

Characters and Unicode

Total characters255
Distinct characters59
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

Unique17 ?
Unique (%)100.0%

Sample

1st row주소
2nd row전주시 덕진구 견훤로 215
3rd row전주시 완산구 쑥고개로 343
4th row전주시 덕진구 가재미로 7
5th row전주시 덕진구 도당산4길 8-18
ValueCountFrequency (%)
전주시 9
 
13.8%
전라북도 7
 
10.8%
덕진구 5
 
7.7%
완산구 4
 
6.2%
익산시 3
 
4.6%
군산시 2
 
3.1%
정읍시 2
 
3.1%
배산로 1
 
1.5%
월명로 1
 
1.5%
144 1
 
1.5%
Other values (30) 30
46.2%
2024-03-14T10:29:41.475356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
48
18.8%
전 16
 
6.3%
시 16
 
6.3%
로 15
 
5.9%
산 13
 
5.1%
주 10
 
3.9%
1 9
 
3.5%
구 9
 
3.5%
도 8
 
3.1%
4 8
 
3.1%
Other values (49) 103
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 162
63.5%
Space Separator 48
 
18.8%
Decimal Number 43
 
16.9%
Dash Punctuation 2
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 16
 
9.9%
시 16
 
9.9%
로 15
 
9.3%
산 13
 
8.0%
주 10
 
6.2%
구 9
 
5.6%
도 8
 
4.9%
북 7
 
4.3%
라 7
 
4.3%
진 5
 
3.1%
Other values (37) 56
34.6%
Decimal Number
ValueCountFrequency (%)
1 9
20.9%
4 8
18.6%
5 6
14.0%
6 5
11.6%
8 4
9.3%
2 4
9.3%
3 3
 
7.0%
0 2
 
4.7%
7 1
 
2.3%
9 1
 
2.3%
Space Separator
ValueCountFrequency (%)
48
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 162
63.5%
Common 93
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 16
 
9.9%
시 16
 
9.9%
로 15
 
9.3%
산 13
 
8.0%
주 10
 
6.2%
구 9
 
5.6%
도 8
 
4.9%
북 7
 
4.3%
라 7
 
4.3%
진 5
 
3.1%
Other values (37) 56
34.6%
Common
ValueCountFrequency (%)
48
51.6%
1 9
 
9.7%
4 8
 
8.6%
5 6
 
6.5%
6 5
 
5.4%
8 4
 
4.3%
2 4
 
4.3%
3 3
 
3.2%
0 2
 
2.2%
- 2
 
2.2%
Other values (2) 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 162
63.5%
ASCII 93
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
48
51.6%
1 9
 
9.7%
4 8
 
8.6%
5 6
 
6.5%
6 5
 
5.4%
8 4
 
4.3%
2 4
 
4.3%
3 3
 
3.2%
0 2
 
2.2%
- 2
 
2.2%
Other values (2) 2
 
2.2%
Hangul
ValueCountFrequency (%)
전 16
 
9.9%
시 16
 
9.9%
로 15
 
9.3%
산 13
 
8.0%
주 10
 
6.2%
구 9
 
5.6%
도 8
 
4.9%
북 7
 
4.3%
라 7
 
4.3%
진 5
 
3.1%
Other values (37) 56
34.6%

Unnamed: 5
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing5
Missing (%)22.7%
Memory size308.0 B
2024-03-14T10:29:41.631115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length12
Mean length12.529412
Min length12

Characters and Unicode

Total characters213
Distinct characters26
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

Unique17 ?
Unique (%)100.0%

Sample

1st row전화번호 (산후조리원 대표번호)
2nd row063-244-3559
3rd row063-211-1004
4th row063-247-2114
5th row063-244-4755
ValueCountFrequency (%)
전화번호 1
 
5.3%
063-220-8300 1
 
5.3%
063-532-9600 1
 
5.3%
063-840-5060 1
 
5.3%
063-840-7600 1
 
5.3%
063-857-5533 1
 
5.3%
063-441-1170 1
 
5.3%
063-471-2955 1
 
5.3%
063-236-1052 1
 
5.3%
063-250-3400 1
 
5.3%
Other values (9) 9
47.4%
2024-03-14T10:29:41.906165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
17.4%
- 32
15.0%
3 27
12.7%
6 21
9.9%
2 19
8.9%
5 16
7.5%
4 15
7.0%
1 11
 
5.2%
7 6
 
2.8%
8 5
 
2.3%
Other values (16) 24
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 160
75.1%
Dash Punctuation 32
 
15.0%
Other Letter 13
 
6.1%
Space Separator 4
 
1.9%
Control 2
 
0.9%
Close Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 2
15.4%
호 2
15.4%
전 1
7.7%
화 1
7.7%
대 1
7.7%
원 1
7.7%
리 1
7.7%
조 1
7.7%
후 1
7.7%
산 1
7.7%
Decimal Number
ValueCountFrequency (%)
0 37
23.1%
3 27
16.9%
6 21
13.1%
2 19
11.9%
5 16
10.0%
4 15
9.4%
1 11
 
6.9%
7 6
 
3.8%
8 5
 
3.1%
9 3
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 200
93.9%
Hangul 13
 
6.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
18.5%
- 32
16.0%
3 27
13.5%
6 21
10.5%
2 19
9.5%
5 16
8.0%
4 15
7.5%
1 11
 
5.5%
7 6
 
3.0%
8 5
 
2.5%
Other values (5) 11
 
5.5%
Hangul
ValueCountFrequency (%)
번 2
15.4%
호 2
15.4%
전 1
7.7%
화 1
7.7%
대 1
7.7%
원 1
7.7%
리 1
7.7%
조 1
7.7%
후 1
7.7%
산 1
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 200
93.9%
Hangul 13
 
6.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
18.5%
- 32
16.0%
3 27
13.5%
6 21
10.5%
2 19
9.5%
5 16
8.0%
4 15
7.5%
1 11
 
5.5%
7 6
 
3.0%
8 5
 
2.5%
Other values (5) 11
 
5.5%
Hangul
ValueCountFrequency (%)
번 2
15.4%
호 2
15.4%
전 1
7.7%
화 1
7.7%
대 1
7.7%
원 1
7.7%
리 1
7.7%
조 1
7.7%
후 1
7.7%
산 1
7.7%

Correlations

2024-03-14T10:29:42.031944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
Unnamed: 11.0001.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.0001.000
Unnamed: 41.0001.0001.0001.0001.000
Unnamed: 51.0001.0001.0001.0001.000
2024-03-14T10:29:42.131617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 2Unnamed: 1
Unnamed: 21.0000.894
Unnamed: 10.8941.000
2024-03-14T10:29:42.210898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2
Unnamed: 11.0000.894
Unnamed: 20.8941.000

Missing values

2024-03-14T10:29:39.685056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:29:39.851308image/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.
2024-03-14T10:29:39.941925image/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

산후조리원 현황(2018.12.31.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
0NaN<NA><NA><NA><NA><NA>
1NaN<NA><NA><NA><NA><NA>
2연번시도시군구산후조리원명주소전화번호 (산후조리원 대표번호)
3NaN<NA><NA><NA><NA><NA>
4NaN<NA><NA><NA><NA><NA>
5NaN<NA><NA><NA><NA><NA>
61전북전주시한별산후조리원전주시 덕진구 견훤로 215063-244-3559
72전북전주시미르피아산후조리원전주시 완산구 쑥고개로 343063-211-1004
83전북전주시푸른산부인과 산후조리원전주시 덕진구 가재미로 7063-247-2114
94전북전주시정성산후조리원전주시 덕진구 도당산4길 8-18063-244-4755
산후조리원 현황(2018.12.31.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5
127전북전주시한나산후조리원전주시 덕진구 기린대로 489063-250-3400
138전북전주시우석대부속전주 한방병원산후조리원전주시 완산구 어은로 46063-220-8300
149전북전주시세인트포레산후조리원전주시 완산구 홍산로 245063-236-1052
1510전북군산시은혜산후조리원전라북도 군산시 월명로 144063-471-2955
1611전북군산시미래와여성산후조리원전라북도 군산시 문화로 164063-441-1170
1712전북익산시미래와여성 산후조리원전라북도 익산시 배산로 66063-857-5533
1813전북익산시제일맘 산후조리원전라북도 익산시 동서로 231063-840-7600
1914전북익산시휴산후조리원전라북도 익산시 무왕로 1018063-840-5060
2015전북정읍시서울산후조리원전라북도 정읍시 상동중앙로 55-1063-532-9600
2116전북정읍시현대산후조리원전라북도 정읍시 중앙로 20063-532-5300

Duplicate rows

Most frequently occurring

Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5# duplicates
0<NA><NA><NA><NA><NA>5