Overview

Dataset statistics

Number of variables4
Number of observations6787
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory225.5 KiB
Average record size in memory34.0 B

Variable types

Numeric2
Text1
Categorical1

Dataset

Description서울특별시 양천구 동물이름 등록현황(동물이름, 건수, 데이터 기준일자) 입니다.등록된 동물이름, 건수, 데이터 기준일자 등의 정보를 제공합니다.
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15049777/fileData.do

Alerts

기준일자 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 22:45:29.221317
Analysis finished2024-03-14 22:45:31.505390
Duration2.28 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct6787
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3394
Minimum1
Maximum6787
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.8 KiB
2024-03-15T07:45:31.715356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile340.3
Q11697.5
median3394
Q35090.5
95-th percentile6447.7
Maximum6787
Range6786
Interquartile range (IQR)3393

Descriptive statistics

Standard deviation1959.3825
Coefficient of variation (CV)0.57730774
Kurtosis-1.2
Mean3394
Median Absolute Deviation (MAD)1697
Skewness0
Sum23035078
Variance3839179.7
MonotonicityStrictly increasing
2024-03-15T07:45:32.165597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
4535 1
 
< 0.1%
4533 1
 
< 0.1%
4532 1
 
< 0.1%
4531 1
 
< 0.1%
4530 1
 
< 0.1%
4529 1
 
< 0.1%
4528 1
 
< 0.1%
4527 1
 
< 0.1%
4526 1
 
< 0.1%
Other values (6777) 6777
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
6787 1
< 0.1%
6786 1
< 0.1%
6785 1
< 0.1%
6784 1
< 0.1%
6783 1
< 0.1%
6782 1
< 0.1%
6781 1
< 0.1%
6780 1
< 0.1%
6779 1
< 0.1%
6778 1
< 0.1%

이름
Text

Distinct6783
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-03-15T07:45:33.823330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length2
Mean length2.3581848
Min length1

Characters and Unicode

Total characters16005
Distinct characters938
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6779 ?
Unique (%)99.9%

Sample

1st row꾸미
2nd row달콤
3rd row별이
4th row삐용
5th rowBARU
ValueCountFrequency (%)
보리 3
 
< 0.1%
별이 3
 
< 0.1%
예삐 3
 
< 0.1%
꾸미 2
 
< 0.1%
미남 2
 
< 0.1%
구름 2
 
< 0.1%
튼튼 2
 
< 0.1%
다롱 2
 
< 0.1%
다롱이 2
 
< 0.1%
단비 2
 
< 0.1%
Other values (6624) 6775
99.7%
2024-03-15T07:45:35.763519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 1389
 
8.7%
리 339
 
2.1%
아 221
 
1.4%
순 211
 
1.3%
미 209
 
1.3%
김 204
 
1.3%
189
 
1.2%
라 154
 
1.0%
돌 154
 
1.0%
지 153
 
1.0%
Other values (928) 12782
79.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15520
97.0%
Space Separator 189
 
1.2%
Lowercase Letter 169
 
1.1%
Uppercase Letter 86
 
0.5%
Close Punctuation 15
 
0.1%
Open Punctuation 15
 
0.1%
Decimal Number 8
 
< 0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1389
 
8.9%
리 339
 
2.2%
아 221
 
1.4%
순 211
 
1.4%
미 209
 
1.3%
김 204
 
1.3%
라 154
 
1.0%
돌 154
 
1.0%
지 153
 
1.0%
비 149
 
1.0%
Other values (872) 12337
79.5%
Uppercase Letter
ValueCountFrequency (%)
E 7
 
8.1%
R 7
 
8.1%
T 6
 
7.0%
B 6
 
7.0%
L 6
 
7.0%
A 5
 
5.8%
O 5
 
5.8%
J 5
 
5.8%
I 4
 
4.7%
W 3
 
3.5%
Other values (16) 32
37.2%
Lowercase Letter
ValueCountFrequency (%)
i 24
14.2%
a 21
12.4%
n 19
11.2%
l 14
8.3%
e 13
 
7.7%
y 12
 
7.1%
u 9
 
5.3%
p 9
 
5.3%
m 8
 
4.7%
c 7
 
4.1%
Other values (11) 33
19.5%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
3 2
25.0%
1 2
25.0%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
, 1
33.3%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
189
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15519
97.0%
Latin 255
 
1.6%
Common 230
 
1.4%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1389
 
9.0%
리 339
 
2.2%
아 221
 
1.4%
순 211
 
1.4%
미 209
 
1.3%
김 204
 
1.3%
라 154
 
1.0%
돌 154
 
1.0%
지 153
 
1.0%
비 149
 
1.0%
Other values (871) 12336
79.5%
Latin
ValueCountFrequency (%)
i 24
 
9.4%
a 21
 
8.2%
n 19
 
7.5%
l 14
 
5.5%
e 13
 
5.1%
y 12
 
4.7%
u 9
 
3.5%
p 9
 
3.5%
m 8
 
3.1%
c 7
 
2.7%
Other values (37) 119
46.7%
Common
ValueCountFrequency (%)
189
82.2%
) 15
 
6.5%
( 15
 
6.5%
2 4
 
1.7%
3 2
 
0.9%
1 2
 
0.9%
. 1
 
0.4%
, 1
 
0.4%
/ 1
 
0.4%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15519
97.0%
ASCII 485
 
3.0%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 1389
 
9.0%
리 339
 
2.2%
아 221
 
1.4%
순 211
 
1.4%
미 209
 
1.3%
김 204
 
1.3%
라 154
 
1.0%
돌 154
 
1.0%
지 153
 
1.0%
비 149
 
1.0%
Other values (871) 12336
79.5%
ASCII
ValueCountFrequency (%)
189
39.0%
i 24
 
4.9%
a 21
 
4.3%
n 19
 
3.9%
) 15
 
3.1%
( 15
 
3.1%
l 14
 
2.9%
e 13
 
2.7%
y 12
 
2.5%
u 9
 
1.9%
Other values (46) 154
31.8%
CJK
ValueCountFrequency (%)
愛 1
100.0%

개수
Real number (ℝ)

Distinct118
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5553264
Minimum1
Maximum549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.8 KiB
2024-03-15T07:45:36.168072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile14
Maximum549
Range548
Interquartile range (IQR)1

Descriptive statistics

Standard deviation18.011556
Coefficient of variation (CV)3.9539551
Kurtosis269.00404
Mean4.5553264
Median Absolute Deviation (MAD)0
Skewness13.61807
Sum30917
Variance324.41615
MonotonicityNot monotonic
2024-03-15T07:45:36.643070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 4348
64.1%
2 888
 
13.1%
3 360
 
5.3%
4 232
 
3.4%
5 159
 
2.3%
6 108
 
1.6%
7 82
 
1.2%
8 70
 
1.0%
9 52
 
0.8%
10 38
 
0.6%
Other values (108) 450
 
6.6%
ValueCountFrequency (%)
1 4348
64.1%
2 888
 
13.1%
3 360
 
5.3%
4 232
 
3.4%
5 159
 
2.3%
6 108
 
1.6%
7 82
 
1.2%
8 70
 
1.0%
9 52
 
0.8%
10 38
 
0.6%
ValueCountFrequency (%)
549 1
< 0.1%
445 1
< 0.1%
395 1
< 0.1%
304 1
< 0.1%
245 1
< 0.1%
234 1
< 0.1%
233 1
< 0.1%
229 1
< 0.1%
227 1
< 0.1%
225 1
< 0.1%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size53.1 KiB
2024-01-20
6787 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-20
2nd row2024-01-20
3rd row2024-01-20
4th row2024-01-20
5th row2024-01-20

Common Values

ValueCountFrequency (%)
2024-01-20 6787
100.0%

Length

2024-03-15T07:45:36.989578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T07:45:37.352196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-20 6787
100.0%

Interactions

2024-03-15T07:45:30.512103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:45:30.085131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:45:30.769254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T07:45:30.261382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T07:45:37.533677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번개수
연번1.0000.024
개수0.0241.000
2024-03-15T07:45:37.734159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번개수
연번1.0000.005
개수0.0051.000

Missing values

2024-03-15T07:45:31.106141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T07:45:31.384612image/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

연번이름개수기준일자
01꾸미12024-01-20
12달콤12024-01-20
23별이12024-01-20
34삐용12024-01-20
45BARU12024-01-20
56Bella12024-01-20
67Benny12024-01-20
78Billy22024-01-20
89Blanc12024-01-20
910Buddy12024-01-20
연번이름개수기준일자
67776778히츠12024-01-20
67786779히틀러12024-01-20
67796780히티12024-01-20
67806781히포32024-01-20
67816782히퐁이12024-01-20
67826783힌트12024-01-20
67836784힐링22024-01-20
67846785힘센이12024-01-20
67856786힘찬22024-01-20
67866787힝구22024-01-20