Overview

Dataset statistics

Number of variables7
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory62.9 B

Variable types

Text2
Numeric4
Categorical1

Dataset

Description연수구 내 이재민 임시주거시설 지정 현황 (시설명, 장소 도로명 주소, 면적, 수용인원 등)<br/>- 시설명, 장소, 임시 주거시설 용도, 면적, 수용인원으로 구분
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15065208&srcSe=7661IVAWM27C61E190

Alerts

면적 (제곱미터) is highly overall correlated with 수용 (명) and 1 other fieldsHigh correlation
수용 (명) is highly overall correlated with 면적 (제곱미터) and 1 other fieldsHigh correlation
임시 주거시설 용도 is highly overall correlated with 면적 (제곱미터) and 1 other fieldsHigh correlation
시설명 has unique valuesUnique
장소 has unique valuesUnique

Reproduction

Analysis started2024-04-06 09:37:43.390727
Analysis finished2024-04-06 09:37:45.360070
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-06T18:37:45.534698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length5.9565217
Min length4

Characters and Unicode

Total characters274
Distinct characters66
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

Unique46 ?
Unique (%)100.0%

Sample

1st row능허대초교
2nd row송도초교
3rd row옥련2동 행정복지센터
4th row옥련초교
5th row선학동 행정복지센터
ValueCountFrequency (%)
행정복지센터 7
 
13.0%
능허대초교 1
 
1.9%
송원초교 1
 
1.9%
미송중학교 1
 
1.9%
송도1동 1
 
1.9%
신송초등학교 1
 
1.9%
먼우금초교 1
 
1.9%
해송고등학교 1
 
1.9%
신정초등학교 1
 
1.9%
신정중학교 1
 
1.9%
Other values (38) 38
70.4%
2024-04-06T18:37:45.913150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 37
 
13.5%
학 30
 
10.9%
초 22
 
8.0%
송 14
 
5.1%
중 11
 
4.0%
동 11
 
4.0%
등 10
 
3.6%
정 9
 
3.3%
8
 
2.9%
센 7
 
2.6%
Other values (56) 115
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
95.3%
Space Separator 8
 
2.9%
Decimal Number 5
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 37
 
14.2%
학 30
 
11.5%
초 22
 
8.4%
송 14
 
5.4%
중 11
 
4.2%
동 11
 
4.2%
등 10
 
3.8%
정 9
 
3.4%
센 7
 
2.7%
터 7
 
2.7%
Other values (52) 103
39.5%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
1 2
40.0%
3 1
20.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 261
95.3%
Common 13
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 37
 
14.2%
학 30
 
11.5%
초 22
 
8.4%
송 14
 
5.4%
중 11
 
4.2%
동 11
 
4.2%
등 10
 
3.8%
정 9
 
3.4%
센 7
 
2.7%
터 7
 
2.7%
Other values (52) 103
39.5%
Common
ValueCountFrequency (%)
8
61.5%
2 2
 
15.4%
1 2
 
15.4%
3 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 261
95.3%
ASCII 13
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 37
 
14.2%
학 30
 
11.5%
초 22
 
8.4%
송 14
 
5.4%
중 11
 
4.2%
동 11
 
4.2%
등 10
 
3.8%
정 9
 
3.4%
센 7
 
2.7%
터 7
 
2.7%
Other values (52) 103
39.5%
ASCII
ValueCountFrequency (%)
8
61.5%
2 2
 
15.4%
1 2
 
15.4%
3 1
 
7.7%

장소
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2024-04-06T18:37:46.220644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length8.5869565
Min length5

Characters and Unicode

Total characters395
Distinct characters65
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row옥련1동 442-1
2nd row비류대로214번길 21
3rd row연수구 옥련로 82
4th row한진로30
5th row선학로54
ValueCountFrequency (%)
아카데미로 2
 
2.8%
청학동 2
 
2.8%
해돋이로 2
 
2.8%
먼우금로 2
 
2.8%
동춘1동 2
 
2.8%
연수3동 2
 
2.8%
능허대로 2
 
2.8%
송도교육로63 1
 
1.4%
컨벤시아대로42번길80 1
 
1.4%
97-72 1
 
1.4%
Other values (55) 55
76.4%
2024-04-06T18:37:46.758523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 36
 
9.1%
1 29
 
7.3%
27
 
6.8%
2 27
 
6.8%
5 19
 
4.8%
4 17
 
4.3%
3 15
 
3.8%
동 14
 
3.5%
8 12
 
3.0%
6 11
 
2.8%
Other values (55) 188
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 206
52.2%
Decimal Number 154
39.0%
Space Separator 27
 
6.8%
Dash Punctuation 8
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 36
 
17.5%
동 14
 
6.8%
번 9
 
4.4%
길 9
 
4.4%
대 9
 
4.4%
아 7
 
3.4%
학 6
 
2.9%
수 5
 
2.4%
금 5
 
2.4%
우 5
 
2.4%
Other values (43) 101
49.0%
Decimal Number
ValueCountFrequency (%)
1 29
18.8%
2 27
17.5%
5 19
12.3%
4 17
11.0%
3 15
9.7%
8 12
7.8%
6 11
 
7.1%
7 9
 
5.8%
0 8
 
5.2%
9 7
 
4.5%
Space Separator
ValueCountFrequency (%)
27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 206
52.2%
Common 189
47.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 36
 
17.5%
동 14
 
6.8%
번 9
 
4.4%
길 9
 
4.4%
대 9
 
4.4%
아 7
 
3.4%
학 6
 
2.9%
수 5
 
2.4%
금 5
 
2.4%
우 5
 
2.4%
Other values (43) 101
49.0%
Common
ValueCountFrequency (%)
1 29
15.3%
27
14.3%
2 27
14.3%
5 19
10.1%
4 17
9.0%
3 15
7.9%
8 12
6.3%
6 11
 
5.8%
7 9
 
4.8%
0 8
 
4.2%
Other values (2) 15
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 206
52.2%
ASCII 189
47.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 36
 
17.5%
동 14
 
6.8%
번 9
 
4.4%
길 9
 
4.4%
대 9
 
4.4%
아 7
 
3.4%
학 6
 
2.9%
수 5
 
2.4%
금 5
 
2.4%
우 5
 
2.4%
Other values (43) 101
49.0%
ASCII
ValueCountFrequency (%)
1 29
15.3%
27
14.3%
2 27
14.3%
5 19
10.1%
4 17
9.0%
3 15
7.9%
8 12
6.3%
6 11
 
5.8%
7 9
 
4.8%
0 8
 
4.2%
Other values (2) 15
7.9%

위도
Real number (ℝ)

Distinct43
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.363102
Minimum35.095365
Maximum37.60396
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-04-06T18:37:47.012213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.095365
5-th percentile37.382661
Q137.397937
median37.411973
Q337.422519
95-th percentile37.426132
Maximum37.60396
Range2.508595
Interquartile range (IQR)0.024581

Descriptive statistics

Standard deviation0.34329196
Coefficient of variation (CV)0.0091879942
Kurtosis45.150468
Mean37.363102
Median Absolute Deviation (MAD)0.0118625
Skewness-6.6858095
Sum1718.7027
Variance0.11784937
MonotonicityNot monotonic
2024-04-06T18:37:47.220208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
37.383912 3
 
6.5%
37.392921 2
 
4.3%
37.424084 1
 
2.2%
37.4266 1
 
2.2%
37.411901 1
 
2.2%
37.390987 1
 
2.2%
37.389889 1
 
2.2%
37.392941 1
 
2.2%
37.382244 1
 
2.2%
37.39732 1
 
2.2%
Other values (33) 33
71.7%
ValueCountFrequency (%)
35.095365 1
 
2.2%
37.37802 1
 
2.2%
37.382244 1
 
2.2%
37.383912 3
6.5%
37.389889 1
 
2.2%
37.390987 1
 
2.2%
37.392921 2
4.3%
37.392941 1
 
2.2%
37.39732 1
 
2.2%
37.39979 1
 
2.2%
ValueCountFrequency (%)
37.60396 1
2.2%
37.4266 1
2.2%
37.426146 1
2.2%
37.42609 1
2.2%
37.425555 1
2.2%
37.425341 1
2.2%
37.42524 1
2.2%
37.42494 1
2.2%
37.424084 1
2.2%
37.423993 1
2.2%

경도
Real number (ℝ)

Distinct43
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.7137
Minimum126.61317
Maximum129.0552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-04-06T18:37:47.402306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.61317
5-th percentile126.62893
Q1126.6459
median126.66419
Q3126.67911
95-th percentile126.69971
Maximum129.0552
Range2.442027
Interquartile range (IQR)0.03320675

Descriptive statistics

Standard deviation0.35356429
Coefficient of variation (CV)0.002790261
Kurtosis45.635844
Mean126.7137
Median Absolute Deviation (MAD)0.0164945
Skewness6.7428451
Sum5828.83
Variance0.12500771
MonotonicityNot monotonic
2024-04-06T18:37:47.574644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
126.643855 3
 
6.5%
126.646044 2
 
4.3%
126.648761 1
 
2.2%
126.65848 1
 
2.2%
126.674698 1
 
2.2%
126.652057 1
 
2.2%
126.657322 1
 
2.2%
126.65432 1
 
2.2%
126.645852 1
 
2.2%
126.644402 1
 
2.2%
Other values (33) 33
71.7%
ValueCountFrequency (%)
126.61317 1
 
2.2%
126.61341 1
 
2.2%
126.628698 1
 
2.2%
126.62964 1
 
2.2%
126.63902 1
 
2.2%
126.64073 1
 
2.2%
126.643855 3
6.5%
126.644402 1
 
2.2%
126.645844 1
 
2.2%
126.645852 1
 
2.2%
ValueCountFrequency (%)
129.055197 1
2.2%
126.701314 1
2.2%
126.700182 1
2.2%
126.698289 1
2.2%
126.694589 1
2.2%
126.690184 1
2.2%
126.688931 1
2.2%
126.686451 1
2.2%
126.68104 1
2.2%
126.680325 1
2.2%

임시 주거시설 용도
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size500.0 B
강당
27 
교사동
6 
공공청사
5 
교육장소
 
2
급식동
 
2
Other values (4)
4 

Length

Max length5
Median length2
Mean length2.6086957
Min length2

Unique

Unique4 ?
Unique (%)8.7%

Sample

1st row강당
2nd row강당
3rd row교육장소
4th row강당
5th row공공청사

Common Values

ValueCountFrequency (%)
강당 27
58.7%
교사동 6
 
13.0%
공공청사 5
 
10.9%
교육장소 2
 
4.3%
급식동 2
 
4.3%
선수대기실 1
 
2.2%
경로당 1
 
2.2%
강당동 1
 
2.2%
체육관 1
 
2.2%

Length

2024-04-06T18:37:47.711137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T18:37:47.870763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강당 27
58.7%
교사동 6
 
13.0%
공공청사 5
 
10.9%
교육장소 2
 
4.3%
급식동 2
 
4.3%
선수대기실 1
 
2.2%
경로당 1
 
2.2%
강당동 1
 
2.2%
체육관 1
 
2.2%

면적 (제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1173.5
Minimum100
Maximum15580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-04-06T18:37:48.015062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile273.5
Q1513.75
median639
Q3899.25
95-th percentile2865.75
Maximum15580
Range15480
Interquartile range (IQR)385.5

Descriptive statistics

Standard deviation2281.3766
Coefficient of variation (CV)1.9440789
Kurtosis37.240323
Mean1173.5
Median Absolute Deviation (MAD)218.5
Skewness5.8850581
Sum53981
Variance5204679.3
MonotonicityNot monotonic
2024-04-06T18:37:48.206798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
612 3
 
6.5%
1402 1
 
2.2%
662 1
 
2.2%
444 1
 
2.2%
872 1
 
2.2%
886 1
 
2.2%
605 1
 
2.2%
308 1
 
2.2%
708 1
 
2.2%
511 1
 
2.2%
Other values (34) 34
73.9%
ValueCountFrequency (%)
100 1
2.2%
144 1
2.2%
268 1
2.2%
290 1
2.2%
308 1
2.2%
364 1
2.2%
405 1
2.2%
422 1
2.2%
444 1
2.2%
495 1
2.2%
ValueCountFrequency (%)
15580 1
2.2%
3851 1
2.2%
3168 1
2.2%
1959 1
2.2%
1775 1
2.2%
1668 1
2.2%
1506 1
2.2%
1402 1
2.2%
1081 1
2.2%
1039 1
2.2%

수용 (명)
Real number (ℝ)

HIGH CORRELATION 

Distinct44
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean473.19565
Minimum30
Maximum4721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2024-04-06T18:37:48.381078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile82.75
Q1157
median220
Q3478.5
95-th percentile1338
Maximum4721
Range4691
Interquartile range (IQR)321.5

Descriptive statistics

Standard deviation811.26109
Coefficient of variation (CV)1.7144306
Kurtosis19.089363
Mean473.19565
Median Absolute Deviation (MAD)93.5
Skewness4.2055229
Sum21767
Variance658144.56
MonotonicityNot monotonic
2024-04-06T18:37:48.514997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
185 2
 
4.3%
505 2
 
4.3%
594 1
 
2.2%
201 1
 
2.2%
135 1
 
2.2%
264 1
 
2.2%
268 1
 
2.2%
183 1
 
2.2%
93 1
 
2.2%
215 1
 
2.2%
Other values (34) 34
73.9%
ValueCountFrequency (%)
30 1
2.2%
44 1
2.2%
81 1
2.2%
88 1
2.2%
93 1
2.2%
110 1
2.2%
123 1
2.2%
128 1
2.2%
135 1
2.2%
150 1
2.2%
ValueCountFrequency (%)
4721 1
2.2%
3177 1
2.2%
1464 1
2.2%
960 1
2.2%
892 1
2.2%
594 1
2.2%
572 1
2.2%
533 1
2.2%
505 2
4.3%
488 1
2.2%

Interactions

2024-04-06T18:37:44.831439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:43.699220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.077485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.416697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.909778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:43.793956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.163663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.505964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.986243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:43.903245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.248806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.601470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:45.075819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.001169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.339894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T18:37:44.713189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T18:37:48.603218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명장소위도경도임시 주거시설 용도면적 (제곱미터)수용 (명)
시설명1.0001.0001.0001.0001.0001.0001.000
장소1.0001.0001.0001.0001.0001.0001.000
위도1.0001.0001.0000.6740.0000.0000.000
경도1.0001.0000.6741.0000.0000.0000.000
임시 주거시설 용도1.0001.0000.0000.0001.0000.8110.773
면적 (제곱미터)1.0001.0000.0000.0000.8111.0000.905
수용 (명)1.0001.0000.0000.0000.7730.9051.000
2024-04-06T18:37:48.732898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도면적 (제곱미터)수용 (명)임시 주거시설 용도
위도1.0000.2910.0250.0920.000
경도0.2911.0000.120-0.0900.000
면적 (제곱미터)0.0250.1201.0000.8450.634
수용 (명)0.092-0.0900.8451.0000.556
임시 주거시설 용도0.0000.0000.6340.5561.000

Missing values

2024-04-06T18:37:45.179904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T18:37:45.306890image/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

시설명장소위도경도임시 주거시설 용도면적 (제곱미터)수용 (명)
0능허대초교옥련1동 442-137.424084126.648761강당612185
1송도초교비류대로214번길 2137.4266126.65848강당537163
2옥련2동 행정복지센터연수구 옥련로 8237.426146126.648286교육장소14444
3옥련초교한진로3037.425555126.649156강당495150
4선학동 행정복지센터선학로5437.422355126.701314공공청사1039315
5선학초교선학동 35837.423993126.700182강당628190
6선학체육관경원대로52637.418265126.690184선수대기실1668505
7선학중학교선학로1937.420776126.698289강당859260
8문남초교연수1동541-137.42098126.679399강당612185
9생활과학고등학교함박뫼로10337.423678126.67823교사동155804721
시설명장소위도경도임시 주거시설 용도면적 (제곱미터)수용 (명)
36예송초교컨벤시아대로252번길7537.392921126.646044교사동649197
37옥련중학교청량로 22237.42609126.65439강당612505
38해양과학고등학교능허대로 7137.42524126.64073체육관38513177
39연화초등학교원인재로 15037.41108126.68104강당522431
40대건고등학교능허대로 43737.40203126.6652급식동17751464
41인천여자중학교먼우금로 13837.60396126.67374강당1081892
42연송초등학교해돋이로 24837.39979126.63902강당693572
43미송초등학교아카데미로 66737.4147126.61341강당646533
44미송중학교아카데미로 67937.41598126.61317강당592488
45은송초등학교센트럴로 46037.4137126.62964강당588486