Overview

Dataset statistics

Number of variables3
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1016.0 B
Average record size in memory29.9 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description부산광역시남구의료급여대상자현황_20200516
Author부산광역시 남구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3081435

Alerts

인원 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:04:58.404395
Analysis finished2023-12-10 17:04:59.162683
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종별
Categorical

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
1
17 
2
17 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 17
50.0%
2 17
50.0%

Length

2023-12-11T02:04:59.393389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:04:59.610269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
50.0%
2 17
50.0%

구분
Text

Distinct17
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T02:04:59.916835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.8823529
Min length3

Characters and Unicode

Total characters132
Distinct characters18
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

Unique0 ?
Unique (%)0.0%

Sample

1st row대연1동
2nd row대연3동
3rd row대연4동
4th row대연5동
5th row대연6동
ValueCountFrequency (%)
대연1동 2
 
5.9%
용당동 2
 
5.9%
문현4동 2
 
5.9%
문현3동 2
 
5.9%
문현2동 2
 
5.9%
문현1동 2
 
5.9%
감만2동 2
 
5.9%
감만1동 2
 
5.9%
용호4동 2
 
5.9%
대연3동 2
 
5.9%
Other values (7) 14
41.2%
2023-12-11T02:05:00.523529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 34
25.8%
대 10
 
7.6%
용 10
 
7.6%
연 10
 
7.6%
현 8
 
6.1%
문 8
 
6.1%
호 8
 
6.1%
1 8
 
6.1%
4 6
 
4.5%
2 6
 
4.5%
Other values (8) 24
18.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102
77.3%
Decimal Number 30
 
22.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 34
33.3%
대 10
 
9.8%
용 10
 
9.8%
연 10
 
9.8%
현 8
 
7.8%
문 8
 
7.8%
호 8
 
7.8%
감 4
 
3.9%
만 4
 
3.9%
당 2
 
2.0%
Other values (2) 4
 
3.9%
Decimal Number
ValueCountFrequency (%)
1 8
26.7%
4 6
20.0%
2 6
20.0%
3 6
20.0%
6 2
 
6.7%
5 2
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102
77.3%
Common 30
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 34
33.3%
대 10
 
9.8%
용 10
 
9.8%
연 10
 
9.8%
현 8
 
7.8%
문 8
 
7.8%
호 8
 
7.8%
감 4
 
3.9%
만 4
 
3.9%
당 2
 
2.0%
Other values (2) 4
 
3.9%
Common
ValueCountFrequency (%)
1 8
26.7%
4 6
20.0%
2 6
20.0%
3 6
20.0%
6 2
 
6.7%
5 2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102
77.3%
ASCII 30
 
22.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 34
33.3%
대 10
 
9.8%
용 10
 
9.8%
연 10
 
9.8%
현 8
 
7.8%
문 8
 
7.8%
호 8
 
7.8%
감 4
 
3.9%
만 4
 
3.9%
당 2
 
2.0%
Other values (2) 4
 
3.9%
ASCII
ValueCountFrequency (%)
1 8
26.7%
4 6
20.0%
2 6
20.0%
3 6
20.0%
6 2
 
6.7%
5 2
 
6.7%

인원
Real number (ℝ)

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean407.20588
Minimum185
Maximum903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-11T02:05:00.766589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum185
5-th percentile224.4
Q1291.25
median367.5
Q3488.25
95-th percentile719.45
Maximum903
Range718
Interquartile range (IQR)197

Descriptive statistics

Standard deviation162.28609
Coefficient of variation (CV)0.39853572
Kurtosis1.4954215
Mean407.20588
Median Absolute Deviation (MAD)98
Skewness1.2134381
Sum13845
Variance26336.775
MonotonicityNot monotonic
2023-12-11T02:05:01.020705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
404 1
 
2.9%
251 1
 
2.9%
402 1
 
2.9%
230 1
 
2.9%
903 1
 
2.9%
346 1
 
2.9%
587 1
 
2.9%
318 1
 
2.9%
710 1
 
2.9%
332 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
185 1
2.9%
214 1
2.9%
230 1
2.9%
251 1
2.9%
264 1
2.9%
268 1
2.9%
271 1
2.9%
275 1
2.9%
291 1
2.9%
292 1
2.9%
ValueCountFrequency (%)
903 1
2.9%
737 1
2.9%
710 1
2.9%
587 1
2.9%
581 1
2.9%
574 1
2.9%
533 1
2.9%
517 1
2.9%
493 1
2.9%
474 1
2.9%

Interactions

2023-12-11T02:04:58.674515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:05:01.215785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별구분인원
종별1.0000.0000.484
구분0.0001.0000.690
인원0.4840.6901.000
2023-12-11T02:05:01.378872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인원종별
인원1.0000.298
종별0.2981.000

Missing values

2023-12-11T02:04:58.906512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:04:59.107739image/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.

Sample

종별구분인원
01대연1동404
11대연3동275
21대연4동325
31대연5동292
41대연6동185
51용호1동737
61용호2동291
71용호3동493
81용호4동268
91용당동214
종별구분인원
242용호3동587
252용호4동318
262용당동251
272감만1동710
282감만2동315
292문현1동581
302문현2동533
312문현3동467
322문현4동357
332우암동378