Overview

Dataset statistics

Number of variables3
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory704.0 B
Average record size in memory32.0 B

Variable types

Numeric2
Text1

Dataset

Description인천광역시 부평구 동별 세대수 현황입니다.(동별,세대수)ex) 부평1동,16681부평2동,7755부평3동,6444부평4동,17675부평5동,15807
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15089248&srcSe=7661IVAWM27C61E190

Alerts

순번 has unique valuesUnique
동별 has unique valuesUnique
세대수 has unique valuesUnique

Reproduction

Analysis started2024-01-28 13:01:08.113149
Analysis finished2024-01-28 13:01:08.577825
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.5
Minimum1
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T22:01:08.628234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.05
Q16.25
median11.5
Q316.75
95-th percentile20.95
Maximum22
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.5646597
Kurtosis-1.2
Mean11.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum253
Variance42.166667
MonotonicityStrictly increasing
2024-01-28T22:01:08.729742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
1 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
21 1
 
4.5%
20 1
 
4.5%
19 1
 
4.5%
18 1
 
4.5%
17 1
 
4.5%
16 1
 
4.5%
15 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
1 1
4.5%
2 1
4.5%
3 1
4.5%
4 1
4.5%
5 1
4.5%
6 1
4.5%
7 1
4.5%
8 1
4.5%
9 1
4.5%
10 1
4.5%
ValueCountFrequency (%)
22 1
4.5%
21 1
4.5%
20 1
4.5%
19 1
4.5%
18 1
4.5%
17 1
4.5%
16 1
4.5%
15 1
4.5%
14 1
4.5%
13 1
4.5%

동별
Text

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size308.0 B
2024-01-28T22:01:08.895361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.9545455
Min length3

Characters and Unicode

Total characters87
Distinct characters20
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

Unique22 ?
Unique (%)100.0%

Sample

1st row부평1동
2nd row부평2동
3rd row부평3동
4th row부평4동
5th row부평5동
ValueCountFrequency (%)
부평1동 1
 
4.5%
부평2동 1
 
4.5%
십정1동 1
 
4.5%
일신동 1
 
4.5%
부개3동 1
 
4.5%
부개2동 1
 
4.5%
부개1동 1
 
4.5%
삼산2동 1
 
4.5%
삼산1동 1
 
4.5%
갈산2동 1
 
4.5%
Other values (12) 12
54.5%
2024-01-28T22:01:09.163142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 22
25.3%
부 9
10.3%
산 8
 
9.2%
1 7
 
8.0%
2 7
 
8.0%
평 6
 
6.9%
곡 4
 
4.6%
3 3
 
3.4%
개 3
 
3.4%
4 2
 
2.3%
Other values (10) 16
18.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
75.9%
Decimal Number 21
 
24.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
청 2
 
3.0%
천 2
 
3.0%
갈 2
 
3.0%
삼 2
 
3.0%
Other values (4) 6
 
9.1%
Decimal Number
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
5 1
 
4.8%
6 1
 
4.8%

Most occurring scripts

ValueCountFrequency (%)
Hangul 66
75.9%
Common 21
 
24.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
청 2
 
3.0%
천 2
 
3.0%
갈 2
 
3.0%
삼 2
 
3.0%
Other values (4) 6
 
9.1%
Common
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
5 1
 
4.8%
6 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 66
75.9%
ASCII 21
 
24.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 22
33.3%
부 9
13.6%
산 8
 
12.1%
평 6
 
9.1%
곡 4
 
6.1%
개 3
 
4.5%
청 2
 
3.0%
천 2
 
3.0%
갈 2
 
3.0%
삼 2
 
3.0%
Other values (4) 6
 
9.1%
ASCII
ValueCountFrequency (%)
1 7
33.3%
2 7
33.3%
3 3
14.3%
4 2
 
9.5%
5 1
 
4.8%
6 1
 
4.8%

세대수
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9997.5455
Minimum3308
Maximum18425
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size330.0 B
2024-01-28T22:01:09.285531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3308
5-th percentile5148.85
Q17318.5
median8533.5
Q312000.75
95-th percentile16615.9
Maximum18425
Range15117
Interquartile range (IQR)4682.25

Descriptive statistics

Standard deviation4010.9411
Coefficient of variation (CV)0.40119259
Kurtosis-0.42344456
Mean9997.5455
Median Absolute Deviation (MAD)2140
Skewness0.59248413
Sum219946
Variance16087649
MonotonicityNot monotonic
2024-01-28T22:01:09.390090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
16636 1
 
4.5%
7293 1
 
4.5%
11367 1
 
4.5%
11232 1
 
4.5%
5075 1
 
4.5%
12212 1
 
4.5%
8347 1
 
4.5%
7958 1
 
4.5%
10234 1
 
4.5%
14430 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
3308 1
4.5%
5075 1
4.5%
6552 1
4.5%
6592 1
4.5%
6997 1
4.5%
7293 1
4.5%
7395 1
4.5%
7414 1
4.5%
7958 1
4.5%
8123 1
4.5%
ValueCountFrequency (%)
18425 1
4.5%
16636 1
4.5%
16234 1
4.5%
14570 1
4.5%
14430 1
4.5%
12212 1
4.5%
11367 1
4.5%
11232 1
4.5%
10832 1
4.5%
10234 1
4.5%

Interactions

2024-01-28T22:01:08.320032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:01:08.184554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:01:08.392999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T22:01:08.245478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T22:01:09.472658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번동별세대수
순번1.0001.0000.401
동별1.0001.0001.000
세대수0.4011.0001.000
2024-01-28T22:01:09.542884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번세대수
순번1.000-0.038
세대수-0.0381.000

Missing values

2024-01-28T22:01:08.487550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T22:01:08.547238image/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

순번동별세대수
01부평1동16636
12부평2동7414
23부평3동6997
34부평4동18425
45부평5동16234
56부평6동7395
67산곡1동6592
78산곡2동10832
89산곡3동8720
910산곡4동6552
순번동별세대수
1213갈산1동7293
1314갈산2동8123
1415삼산1동14430
1516삼산2동10234
1617부개1동7958
1718부개2동8347
1819부개3동12212
1920일신동5075
2021십정1동11232
2122십정2동11367