Overview

Dataset statistics

Number of variables5
Number of observations24
Missing cells5
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory49.5 B

Variable types

Text1
Numeric2
Categorical2

Dataset

Description경상북도 각 시군 병원 개업 및 폐업에 대한 데이터로 각 병원의 폐업, 개원, 휴업에 관한 현황입니다. 참고하시기바랍니다.
Author경상북도
URLhttps://www.data.go.kr/data/15039077/fileData.do

Alerts

폐업 is highly overall correlated with 병원 개소 수 and 2 other fieldsHigh correlation
병원 개소 수 is highly overall correlated with 폐업 and 1 other fieldsHigh correlation
휴업 is highly overall correlated with 폐업High correlation
개원 is highly overall correlated with 폐업 and 1 other fieldsHigh correlation
휴업 is highly imbalanced (50.5%)Imbalance
개원 is highly imbalanced (50.5%)Imbalance
폐업 has 4 (16.7%) missing valuesMissing
병원 개소 수 has 1 (4.2%) missing valuesMissing
시군 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:33:20.281336
Analysis finished2023-12-12 23:33:21.158697
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-13T08:33:21.274964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5
Min length4

Characters and Unicode

Total characters120
Distinct characters37
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

Unique24 ?
Unique (%)100.0%

Sample

1st row 포항남구
2nd row포항북구
3rd row 경주시
4th row 김천시
5th row 안동시
ValueCountFrequency (%)
포항남구 1
 
4.2%
포항북구 1
 
4.2%
울진군 1
 
4.2%
봉화군 1
 
4.2%
예천군 1
 
4.2%
칠곡군 1
 
4.2%
성주군 1
 
4.2%
고령군 1
 
4.2%
청도군 1
 
4.2%
영덕군 1
 
4.2%
Other values (14) 14
58.3%
2023-12-13T08:33:21.572867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
38.3%
군 14
 
11.7%
시 9
 
7.5%
주 4
 
3.3%
영 4
 
3.3%
구 3
 
2.5%
경 3
 
2.5%
천 3
 
2.5%
항 2
 
1.7%
청 2
 
1.7%
Other values (27) 30
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 74
61.7%
Space Separator 46
38.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 14
18.9%
시 9
 
12.2%
주 4
 
5.4%
영 4
 
5.4%
구 3
 
4.1%
경 3
 
4.1%
천 3
 
4.1%
항 2
 
2.7%
청 2
 
2.7%
울 2
 
2.7%
Other values (26) 28
37.8%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 74
61.7%
Common 46
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 14
18.9%
시 9
 
12.2%
주 4
 
5.4%
영 4
 
5.4%
구 3
 
4.1%
경 3
 
4.1%
천 3
 
4.1%
항 2
 
2.7%
청 2
 
2.7%
울 2
 
2.7%
Other values (26) 28
37.8%
Common
ValueCountFrequency (%)
46
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 74
61.7%
ASCII 46
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
100.0%
Hangul
ValueCountFrequency (%)
군 14
18.9%
시 9
 
12.2%
주 4
 
5.4%
영 4
 
5.4%
구 3
 
4.1%
경 3
 
4.1%
천 3
 
4.1%
항 2
 
2.7%
청 2
 
2.7%
울 2
 
2.7%
Other values (26) 28
37.8%

폐업
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)80.0%
Missing4
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean12.85
Minimum1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:33:21.696729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12.75
median6.5
Q320.25
95-th percentile36.2
Maximum40
Range39
Interquartile range (IQR)17.5

Descriptive statistics

Standard deviation12.786815
Coefficient of variation (CV)0.99508286
Kurtosis-0.34405541
Mean12.85
Median Absolute Deviation (MAD)5.5
Skewness0.9734948
Sum257
Variance163.50263
MonotonicityNot monotonic
2023-12-13T08:33:21.790997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 3
12.5%
2 2
 
8.3%
6 2
 
8.3%
19 1
 
4.2%
36 1
 
4.2%
4 1
 
4.2%
18 1
 
4.2%
40 1
 
4.2%
15 1
 
4.2%
25 1
 
4.2%
Other values (6) 6
25.0%
(Missing) 4
16.7%
ValueCountFrequency (%)
1 3
12.5%
2 2
8.3%
3 1
 
4.2%
4 1
 
4.2%
5 1
 
4.2%
6 2
8.3%
7 1
 
4.2%
8 1
 
4.2%
15 1
 
4.2%
18 1
 
4.2%
ValueCountFrequency (%)
40 1
4.2%
36 1
4.2%
34 1
4.2%
25 1
4.2%
24 1
4.2%
19 1
4.2%
18 1
4.2%
15 1
4.2%
8 1
4.2%
7 1
4.2%

휴업
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
20 
1
3 
2
 
1

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row<NA>
2nd row1
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
83.3%
1 3
 
12.5%
2 1
 
4.2%

Length

2023-12-13T08:33:21.895858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:33:21.976578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
83.3%
1 3
 
12.5%
2 1
 
4.2%

개원
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
<NA>
20 
1
3 
2
 
1

Length

Max length4
Median length4
Mean length3.5
Min length1

Unique

Unique1 ?
Unique (%)4.2%

Sample

1st row<NA>
2nd row<NA>
3rd row2
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 20
83.3%
1 3
 
12.5%
2 1
 
4.2%

Length

2023-12-13T08:33:22.062661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:33:22.139239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 20
83.3%
1 3
 
12.5%
2 1
 
4.2%

병원 개소 수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct14
Distinct (%)60.9%
Missing1
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean9.7391304
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-13T08:33:22.214544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median7
Q311
95-th percentile30.3
Maximum35
Range34
Interquartile range (IQR)8

Descriptive statistics

Standard deviation9.5404278
Coefficient of variation (CV)0.9795975
Kurtosis1.5694348
Mean9.7391304
Median Absolute Deviation (MAD)4
Skewness1.4829868
Sum224
Variance91.019763
MonotonicityNot monotonic
2023-12-13T08:33:22.326287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
7 4
16.7%
1 3
12.5%
3 3
12.5%
11 2
8.3%
2 2
8.3%
35 1
 
4.2%
31 1
 
4.2%
18 1
 
4.2%
24 1
 
4.2%
8 1
 
4.2%
Other values (4) 4
16.7%
ValueCountFrequency (%)
1 3
12.5%
2 2
8.3%
3 3
12.5%
4 1
 
4.2%
7 4
16.7%
8 1
 
4.2%
9 1
 
4.2%
10 1
 
4.2%
11 2
8.3%
18 1
 
4.2%
ValueCountFrequency (%)
35 1
 
4.2%
31 1
 
4.2%
24 1
 
4.2%
19 1
 
4.2%
18 1
 
4.2%
11 2
8.3%
10 1
 
4.2%
9 1
 
4.2%
8 1
 
4.2%
7 4
16.7%

Interactions

2023-12-13T08:33:20.665253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:33:20.471384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:33:20.766931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:33:20.565689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:33:22.393372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군폐업휴업개원병원 개소 수
시군1.0001.0001.0001.0001.000
폐업1.0001.0001.0001.0000.816
휴업1.0001.0001.000NaN0.000
개원1.0001.000NaN1.0001.000
병원 개소 수1.0000.8160.0001.0001.000
2023-12-13T08:33:22.472344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
휴업개원
휴업1.000NaN
개원NaN1.000
2023-12-13T08:33:22.541732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐업병원 개소 수휴업개원
폐업1.0000.8631.0001.000
병원 개소 수0.8631.0000.0001.000
휴업1.0000.0001.0000.000
개원1.0001.0000.0001.000

Missing values

2023-12-13T08:33:20.895037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:33:20.984419image/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.
2023-12-13T08:33:21.101079image/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

시군폐업휴업개원병원 개소 수
0포항남구8<NA><NA>11
1포항북구401<NA>35
2경주시34<NA>231
3김천시15<NA><NA>7
4안동시19<NA><NA>18
5구미시36<NA><NA>24
6영주시41<NA>11
7영천시18<NA><NA>8
8상주시6<NA>17
9문경시2<NA><NA>4
시군폐업휴업개원병원 개소 수
14영양군<NA><NA><NA>1
15영덕군6<NA><NA>2
16청도군51<NA>7
17고령군1<NA><NA>3
18성주군7<NA><NA>7
19칠곡군<NA><NA>19
20예천군1<NA><NA>3
21봉화군1<NA><NA>2
22울진군2<NA><NA>3
23울릉군<NA><NA><NA>1