Overview

Dataset statistics

Number of variables3
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory678.0 B
Average record size in memory32.3 B

Variable types

Numeric2
Text1

Dataset

Description해당 데이터는 인천광역시 남동구의 제설함현황에 관련된 자료로서, 인천광역시 남동구 제설함현황의 구분, 수량, 비고 의 정보를 확인할 수 있다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15104002&srcSe=7661IVAWM27C61E190

Alerts

연번 has unique valuesUnique
구분 has unique valuesUnique
수량 has 1 (4.8%) zerosZeros

Reproduction

Analysis started2024-03-18 05:15:15.019497
Analysis finished2024-03-18 05:15:16.052783
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-18T14:15:16.101765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-03-18T14:15:16.200814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

구분
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-18T14:15:16.348274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.4761905
Min length4

Characters and Unicode

Total characters94
Distinct characters30
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row구월 1동
2nd row구월 2동
3rd row구월 3동
4th row구월 4동
5th row간석1동
ValueCountFrequency (%)
구월 4
 
16.0%
1동 1
 
4.0%
논현고잔동 1
 
4.0%
논현2동 1
 
4.0%
논현1동 1
 
4.0%
남촌도림동 1
 
4.0%
서창2동 1
 
4.0%
장수서창동 1
 
4.0%
만수6동 1
 
4.0%
만수5동 1
 
4.0%
Other values (12) 12
48.0%
2024-03-18T14:15:16.613215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 21
22.3%
수 7
 
7.4%
만 6
 
6.4%
2 5
 
5.3%
구 4
 
4.3%
4
 
4.3%
1 4
 
4.3%
간 4
 
4.3%
석 4
 
4.3%
월 4
 
4.3%
Other values (20) 31
33.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73
77.7%
Decimal Number 17
 
18.1%
Space Separator 4
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 21
28.8%
수 7
 
9.6%
만 6
 
8.2%
구 4
 
5.5%
간 4
 
5.5%
석 4
 
5.5%
월 4
 
5.5%
현 3
 
4.1%
논 3
 
4.1%
창 2
 
2.7%
Other values (13) 15
20.5%
Decimal Number
ValueCountFrequency (%)
2 5
29.4%
1 4
23.5%
3 3
17.6%
4 3
17.6%
6 1
 
5.9%
5 1
 
5.9%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73
77.7%
Common 21
 
22.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 21
28.8%
수 7
 
9.6%
만 6
 
8.2%
구 4
 
5.5%
간 4
 
5.5%
석 4
 
5.5%
월 4
 
5.5%
현 3
 
4.1%
논 3
 
4.1%
창 2
 
2.7%
Other values (13) 15
20.5%
Common
ValueCountFrequency (%)
2 5
23.8%
4
19.0%
1 4
19.0%
3 3
14.3%
4 3
14.3%
6 1
 
4.8%
5 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73
77.7%
ASCII 21
 
22.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 21
28.8%
수 7
 
9.6%
만 6
 
8.2%
구 4
 
5.5%
간 4
 
5.5%
석 4
 
5.5%
월 4
 
5.5%
현 3
 
4.1%
논 3
 
4.1%
창 2
 
2.7%
Other values (13) 15
20.5%
ASCII
ValueCountFrequency (%)
2 5
23.8%
4
19.0%
1 4
19.0%
3 3
14.3%
4 3
14.3%
6 1
 
4.8%
5 1
 
4.8%

수량
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.047619
Minimum0
Maximum68
Zeros1
Zeros (%)4.8%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-18T14:15:16.725263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q116
median21
Q340
95-th percentile49
Maximum68
Range68
Interquartile range (IQR)24

Descriptive statistics

Standard deviation16.304834
Coefficient of variation (CV)0.62596256
Kurtosis0.65112796
Mean26.047619
Median Absolute Deviation (MAD)9
Skewness0.86414071
Sum547
Variance265.84762
MonotonicityNot monotonic
2024-03-18T14:15:16.835730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
17 2
 
9.5%
10 2
 
9.5%
41 1
 
4.8%
0 1
 
4.8%
18 1
 
4.8%
11 1
 
4.8%
49 1
 
4.8%
28 1
 
4.8%
44 1
 
4.8%
20 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
0 1
4.8%
10 2
9.5%
11 1
4.8%
13 1
4.8%
16 1
4.8%
17 2
9.5%
18 1
4.8%
20 1
4.8%
21 1
4.8%
25 1
4.8%
ValueCountFrequency (%)
68 1
4.8%
49 1
4.8%
44 1
4.8%
43 1
4.8%
41 1
4.8%
40 1
4.8%
30 1
4.8%
28 1
4.8%
26 1
4.8%
25 1
4.8%

Interactions

2024-03-18T14:15:15.726005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:15:15.558606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:15:15.813335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:15:15.647977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:15:16.914334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분수량
연번1.0001.0000.000
구분1.0001.0001.000
수량0.0001.0001.000
2024-03-18T14:15:16.997804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수량
연번1.000-0.319
수량-0.3191.000

Missing values

2024-03-18T14:15:15.951751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:15:16.022539image/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

연번구분수량
01구월 1동41
12구월 2동26
23구월 3동16
34구월 4동43
45간석1동40
56간석2동21
67간석3동68
78간석4동10
89만수1동13
910만수2동25
연번구분수량
1112만수4동17
1213만수5동20
1314만수6동10
1415장수서창동44
1516서창2동28
1617남촌도림동49
1718논현1동11
1819논현2동17
1920논현고잔동18
2021남동공단사업소0