Overview

Dataset statistics

Number of variables5
Number of observations23
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 KiB
Average record size in memory47.7 B

Variable types

Text2
Numeric2
Categorical1

Dataset

Description인천광역시 서구 행정구역에 대한 데이터로 면적(제곱킬로미터), 구성비(율). 법정동 등의 정보가 포함되어 있습니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15090901

Alerts

데이터기준일자 has constant value ""Constant
면적(제곱킬로미터) is highly overall correlated with 구성비(율)High correlation
구성비(율) is highly overall correlated with 면적(제곱킬로미터)High correlation
동별 has unique valuesUnique
면적(제곱킬로미터) has unique valuesUnique
구성비(율) has unique valuesUnique

Reproduction

Analysis started2024-01-28 14:37:04.980137
Analysis finished2024-01-28 14:37:05.647261
Duration0.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

동별
Text

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-01-28T23:37:05.792762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.9130435
Min length3

Characters and Unicode

Total characters90
Distinct characters36
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

Unique23 ?
Unique (%)100.0%

Sample

1st row검암경서동
2nd row연희동
3rd row청라1동
4th row청라2동
5th row청라3동
ValueCountFrequency (%)
검암경서동 1
 
4.3%
가좌1동 1
 
4.3%
마전동 1
 
4.3%
오류왕길동 1
 
4.3%
당하동 1
 
4.3%
원당동 1
 
4.3%
불로대곡동 1
 
4.3%
검단동 1
 
4.3%
가좌4동 1
 
4.3%
가좌3동 1
 
4.3%
Other values (13) 13
56.5%
2024-01-28T23:37:06.459420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 23
25.6%
가 7
 
7.8%
좌 4
 
4.4%
라 4
 
4.4%
1 4
 
4.4%
2 4
 
4.4%
3 4
 
4.4%
석 3
 
3.3%
정 3
 
3.3%
남 3
 
3.3%
Other values (26) 31
34.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 77
85.6%
Decimal Number 13
 
14.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 23
29.9%
가 7
 
9.1%
좌 4
 
5.2%
라 4
 
5.2%
석 3
 
3.9%
정 3
 
3.9%
남 3
 
3.9%
청 3
 
3.9%
당 2
 
2.6%
원 2
 
2.6%
Other values (22) 23
29.9%
Decimal Number
ValueCountFrequency (%)
1 4
30.8%
2 4
30.8%
3 4
30.8%
4 1
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 77
85.6%
Common 13
 
14.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 23
29.9%
가 7
 
9.1%
좌 4
 
5.2%
라 4
 
5.2%
석 3
 
3.9%
정 3
 
3.9%
남 3
 
3.9%
청 3
 
3.9%
당 2
 
2.6%
원 2
 
2.6%
Other values (22) 23
29.9%
Common
ValueCountFrequency (%)
1 4
30.8%
2 4
30.8%
3 4
30.8%
4 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 77
85.6%
ASCII 13
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 23
29.9%
가 7
 
9.1%
좌 4
 
5.2%
라 4
 
5.2%
석 3
 
3.9%
정 3
 
3.9%
남 3
 
3.9%
청 3
 
3.9%
당 2
 
2.6%
원 2
 
2.6%
Other values (22) 23
29.9%
ASCII
ValueCountFrequency (%)
1 4
30.8%
2 4
30.8%
3 4
30.8%
4 1
 
7.7%

면적(제곱킬로미터)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2634783
Minimum0.58
Maximum16.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T23:37:06.566965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.58
5-th percentile0.767
Q11.7
median2.71
Q38.715
95-th percentile15.003
Maximum16.69
Range16.11
Interquartile range (IQR)7.015

Descriptive statistics

Standard deviation4.7831519
Coefficient of variation (CV)0.90874354
Kurtosis0.28984835
Mean5.2634783
Median Absolute Deviation (MAD)1.63
Skewness1.110452
Sum121.06
Variance22.878542
MonotonicityNot monotonic
2024-01-28T23:37:06.664442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
16.69 1
 
4.3%
9.5 1
 
4.3%
3.72 1
 
4.3%
1.13 1
 
4.3%
15.47 1
 
4.3%
2.36 1
 
4.3%
6.59 1
 
4.3%
10.8 1
 
4.3%
7.93 1
 
4.3%
2.01 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
0.58 1
4.3%
0.73 1
4.3%
1.1 1
4.3%
1.13 1
4.3%
1.29 1
4.3%
1.46 1
4.3%
1.94 1
4.3%
2.01 1
4.3%
2.28 1
4.3%
2.36 1
4.3%
ValueCountFrequency (%)
16.69 1
4.3%
15.47 1
4.3%
10.8 1
4.3%
10.49 1
4.3%
9.82 1
4.3%
9.5 1
4.3%
7.93 1
4.3%
6.59 1
4.3%
5.52 1
4.3%
4.34 1
4.3%

구성비(율)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.3478261
Minimum0.48
Maximum13.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2024-01-28T23:37:06.794772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.48
5-th percentile0.631
Q11.405
median2.24
Q37.2
95-th percentile12.394
Maximum13.79
Range13.31
Interquartile range (IQR)5.795

Descriptive statistics

Standard deviation3.9517303
Coefficient of variation (CV)0.90889797
Kurtosis0.29112449
Mean4.3478261
Median Absolute Deviation (MAD)1.34
Skewness1.1110165
Sum100
Variance15.616172
MonotonicityNot monotonic
2024-01-28T23:37:06.900688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
13.79 1
 
4.3%
7.85 1
 
4.3%
3.07 1
 
4.3%
0.93 1
 
4.3%
12.78 1
 
4.3%
1.95 1
 
4.3%
5.44 1
 
4.3%
8.92 1
 
4.3%
6.55 1
 
4.3%
1.66 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
0.48 1
4.3%
0.6 1
4.3%
0.91 1
4.3%
0.93 1
4.3%
1.07 1
4.3%
1.21 1
4.3%
1.6 1
4.3%
1.66 1
4.3%
1.88 1
4.3%
1.95 1
4.3%
ValueCountFrequency (%)
13.79 1
4.3%
12.78 1
4.3%
8.92 1
4.3%
8.67 1
4.3%
8.11 1
4.3%
7.85 1
4.3%
6.55 1
4.3%
5.44 1
4.3%
4.56 1
4.3%
3.58 1
4.3%

법정동
Text

Distinct14
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Memory size316.0 B
2024-01-28T23:37:07.061273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length3
Mean length5.6086957
Min length3

Characters and Unicode

Total characters129
Distinct characters39
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

Unique10 ?
Unique (%)43.5%

Sample

1st row검암동, 경서동, 백석동, 시천동
2nd row연희동, 심곡동, 공촌동
3rd row청라동
4th row청라동
5th row청라동
ValueCountFrequency (%)
가좌동 4
 
11.4%
가정동 3
 
8.6%
석남동 3
 
8.6%
당하동 3
 
8.6%
청라동 3
 
8.6%
마전동 3
 
8.6%
원당동 2
 
5.7%
원창동 1
 
2.9%
오류동 1
 
2.9%
불로동 1
 
2.9%
Other values (11) 11
31.4%
2024-01-28T23:37:07.343134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 35
27.1%
12
 
9.3%
, 12
 
9.3%
가 7
 
5.4%
당 5
 
3.9%
석 4
 
3.1%
좌 4
 
3.1%
남 3
 
2.3%
전 3
 
2.3%
정 3
 
2.3%
Other values (29) 41
31.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
81.4%
Space Separator 12
 
9.3%
Other Punctuation 12
 
9.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 35
33.3%
가 7
 
6.7%
당 5
 
4.8%
석 4
 
3.8%
좌 4
 
3.8%
남 3
 
2.9%
전 3
 
2.9%
정 3
 
2.9%
라 3
 
2.9%
원 3
 
2.9%
Other values (27) 35
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
81.4%
Common 24
 
18.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 35
33.3%
가 7
 
6.7%
당 5
 
4.8%
석 4
 
3.8%
좌 4
 
3.8%
남 3
 
2.9%
전 3
 
2.9%
정 3
 
2.9%
라 3
 
2.9%
원 3
 
2.9%
Other values (27) 35
33.3%
Common
ValueCountFrequency (%)
12
50.0%
, 12
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
81.4%
ASCII 24
 
18.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 35
33.3%
가 7
 
6.7%
당 5
 
4.8%
석 4
 
3.8%
좌 4
 
3.8%
남 3
 
2.9%
전 3
 
2.9%
정 3
 
2.9%
라 3
 
2.9%
원 3
 
2.9%
Other values (27) 35
33.3%
ASCII
ValueCountFrequency (%)
12
50.0%
, 12
50.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2022-09-01
23 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-01
2nd row2022-09-01
3rd row2022-09-01
4th row2022-09-01
5th row2022-09-01

Common Values

ValueCountFrequency (%)
2022-09-01 23
100.0%

Length

2024-01-28T23:37:07.457432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T23:37:07.531883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-01 23
100.0%

Interactions

2024-01-28T23:37:05.327437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:37:05.127282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:37:05.420550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T23:37:05.236333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T23:37:07.577937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동별면적(제곱킬로미터)구성비(율)법정동
동별1.0001.0001.0001.000
면적(제곱킬로미터)1.0001.0001.0000.832
구성비(율)1.0001.0001.0000.832
법정동1.0000.8320.8321.000
2024-01-28T23:37:07.655340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱킬로미터)구성비(율)
면적(제곱킬로미터)1.0001.000
구성비(율)1.0001.000

Missing values

2024-01-28T23:37:05.508144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T23:37:05.605991image/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

동별면적(제곱킬로미터)구성비(율)법정동데이터기준일자
0검암경서동16.6913.79검암동, 경서동, 백석동, 시천동2022-09-01
1연희동9.57.85연희동, 심곡동, 공촌동2022-09-01
2청라1동2.281.88청라동2022-09-01
3청라2동5.524.56청라동2022-09-01
4청라3동10.498.67청라동2022-09-01
5가정1동2.62.15가정동2022-09-01
6가정2동1.291.07가정동2022-09-01
7가정3동0.580.48가정동2022-09-01
8신현원창동9.828.11신현동, 원창동2022-09-01
9석남1동1.10.91석남동2022-09-01
동별면적(제곱킬로미터)구성비(율)법정동데이터기준일자
13가좌2동0.730.6가좌동2022-09-01
14가좌3동1.941.6가좌동2022-09-01
15가좌4동2.011.66가좌동2022-09-01
16검단동7.936.55마전동, 금곡동2022-09-01
17불로대곡동10.88.92대곡동, 불로동2022-09-01
18원당동6.595.44당하동, 원당동2022-09-01
19당하동2.361.95당하동, 마전동2022-09-01
20오류왕길동15.4712.78오류동, 왕길동2022-09-01
21마전동1.130.93마전동2022-09-01
22아라동3.723.07원당동, 당하동2022-09-01