Overview

Dataset statistics

Number of variables5
Number of observations300
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.4 KiB
Average record size in memory42.4 B

Variable types

Categorical3
Text1
Numeric1

Dataset

Description- 읍면동 및 종류별 제주마 등록 현황 정보를 제공합니다. - 데이터 제공처: 제주마등록관리 정보시스템
Author제주특별자치도 미래성장과
URLhttps://www.jejudatahub.net/data/view/data/898

Alerts

데이터 기준일 has constant value ""Constant
등록 수(마리) has 115 (38.3%) zerosZeros

Reproduction

Analysis started2023-12-11 20:09:16.413489
Analysis finished2023-12-11 20:09:16.892035
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구
Categorical

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
제주시
224 
서귀포시
76 

Length

Max length4
Median length3
Mean length3.2533333
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 224
74.7%
서귀포시 76
 
25.3%

Length

2023-12-12T05:09:16.969531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:09:17.106913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 224
74.7%
서귀포시 76
 
25.3%

읍면동
Text

Distinct56
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T05:09:17.374995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.2266667
Min length2

Characters and Unicode

Total characters968
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
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 row강정동
2nd row강정동
3rd row강정동
4th row강정동
5th row남원읍
ValueCountFrequency (%)
강정동 8
 
2.7%
대정읍 8
 
2.7%
하효동 8
 
2.7%
신효동 8
 
2.7%
하원동 8
 
2.7%
표선면 8
 
2.7%
토평동 8
 
2.7%
중문동 8
 
2.7%
안덕면 8
 
2.7%
성산읍 8
 
2.7%
Other values (46) 220
73.3%
2023-12-12T05:09:17.797658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 244
25.2%
도 56
 
5.8%
이 52
 
5.4%
읍 40
 
4.1%
일 32
 
3.3%
효 24
 
2.5%
서 24
 
2.5%
면 24
 
2.5%
평 20
 
2.1%
정 16
 
1.7%
Other values (57) 436
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 968
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 244
25.2%
도 56
 
5.8%
이 52
 
5.4%
읍 40
 
4.1%
일 32
 
3.3%
효 24
 
2.5%
서 24
 
2.5%
면 24
 
2.5%
평 20
 
2.1%
정 16
 
1.7%
Other values (57) 436
45.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 968
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 244
25.2%
도 56
 
5.8%
이 52
 
5.4%
읍 40
 
4.1%
일 32
 
3.3%
효 24
 
2.5%
서 24
 
2.5%
면 24
 
2.5%
평 20
 
2.1%
정 16
 
1.7%
Other values (57) 436
45.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 968
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 244
25.2%
도 56
 
5.8%
이 52
 
5.4%
읍 40
 
4.1%
일 32
 
3.3%
효 24
 
2.5%
서 24
 
2.5%
면 24
 
2.5%
평 20
 
2.1%
정 16
 
1.7%
Other values (57) 436
45.0%

말 종류
Categorical

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
기초마
75 
혈통마
75 
고등마
75 
씨수마
75 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기초마
2nd row혈통마
3rd row고등마
4th row씨수마
5th row기초마

Common Values

ValueCountFrequency (%)
기초마 75
25.0%
혈통마 75
25.0%
고등마 75
25.0%
씨수마 75
25.0%

Length

2023-12-12T05:09:17.937639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:09:18.085581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기초마 75
25.0%
혈통마 75
25.0%
고등마 75
25.0%
씨수마 75
25.0%

등록 수(마리)
Real number (ℝ)

ZEROS 

Distinct47
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.496667
Minimum0
Maximum1162
Zeros115
Zeros (%)38.3%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2023-12-12T05:09:18.261216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q36
95-th percentile136.7
Maximum1162
Range1162
Interquartile range (IQR)6

Descriptive statistics

Standard deviation106.11735
Coefficient of variation (CV)4.0049322
Kurtosis60.876378
Mean26.496667
Median Absolute Deviation (MAD)1
Skewness7.1507653
Sum7949
Variance11260.893
MonotonicityNot monotonic
2023-12-12T05:09:18.492438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0 115
38.3%
1 40
 
13.3%
2 30
 
10.0%
5 14
 
4.7%
6 13
 
4.3%
3 11
 
3.7%
7 8
 
2.7%
4 8
 
2.7%
64 3
 
1.0%
8 3
 
1.0%
Other values (37) 55
18.3%
ValueCountFrequency (%)
0 115
38.3%
1 40
 
13.3%
2 30
 
10.0%
3 11
 
3.7%
4 8
 
2.7%
5 14
 
4.7%
6 13
 
4.3%
7 8
 
2.7%
8 3
 
1.0%
9 2
 
0.7%
ValueCountFrequency (%)
1162 1
0.3%
798 1
0.3%
757 1
0.3%
404 1
0.3%
396 2
0.7%
281 1
0.3%
266 1
0.3%
250 2
0.7%
226 1
0.3%
169 2
0.7%

데이터 기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
20211123
300 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20211123
2nd row20211123
3rd row20211123
4th row20211123
5th row20211123

Common Values

ValueCountFrequency (%)
20211123 300
100.0%

Length

2023-12-12T05:09:18.657769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T05:09:18.751742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20211123 300
100.0%

Interactions

2023-12-12T05:09:16.593969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:09:18.844646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구읍면동말 종류등록 수(마리)
시군구1.0000.5290.0000.000
읍면동0.5291.0000.0000.543
말 종류0.0000.0001.0000.331
등록 수(마리)0.0000.5430.3311.000
2023-12-12T05:09:18.959306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구말 종류
시군구1.0000.000
말 종류0.0001.000
2023-12-12T05:09:19.069960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록 수(마리)시군구말 종류
등록 수(마리)1.0000.0000.218
시군구0.0001.0000.000
말 종류0.2180.0001.000

Missing values

2023-12-12T05:09:16.726407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:09:16.843285image/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

시군구읍면동말 종류등록 수(마리)데이터 기준일
0서귀포시강정동기초마020211123
1서귀포시강정동혈통마2920211123
2서귀포시강정동고등마120211123
3서귀포시강정동씨수마120211123
4서귀포시남원읍기초마120211123
5서귀포시남원읍혈통마15020211123
6서귀포시남원읍고등마520211123
7서귀포시남원읍씨수마520211123
8서귀포시대정읍기초마020211123
9서귀포시대정읍혈통마4120211123
시군구읍면동말 종류등록 수(마리)데이터 기준일
290제주시해안동고등마220211123
291제주시해안동씨수마220211123
292제주시화북일동기초마020211123
293제주시화북일동혈통마220211123
294제주시화북일동고등마020211123
295제주시화북일동씨수마020211123
296제주시회천동기초마220211123
297제주시회천동혈통마12620211123
298제주시회천동고등마220211123
299제주시회천동씨수마220211123