Overview

Dataset statistics

Number of variables9
Number of observations295
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory76.4 B

Variable types

Numeric4
Text3
DateTime1
Categorical1

Dataset

Description인천광역시 서구관내에 위치한 공동주택 현황(아파트명, 소재지, 층수, 동수, 세대수, 사용검사일 등)입니다.
Author인천광역시 서구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3078100&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
번호 is highly overall correlated with 동수 and 2 other fieldsHigh correlation
동수 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
동수(주택) is highly overall correlated with 번호 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 번호 and 2 other fieldsHigh correlation
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 02:12:04.849512
Analysis finished2024-03-18 02:12:07.295361
Duration2.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct295
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148
Minimum1
Maximum295
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T11:12:07.351709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile15.7
Q174.5
median148
Q3221.5
95-th percentile280.3
Maximum295
Range294
Interquartile range (IQR)147

Descriptive statistics

Standard deviation85.30338
Coefficient of variation (CV)0.57637419
Kurtosis-1.2
Mean148
Median Absolute Deviation (MAD)74
Skewness0
Sum43660
Variance7276.6667
MonotonicityStrictly increasing
2024-03-18T11:12:07.460502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
204 1
 
0.3%
202 1
 
0.3%
201 1
 
0.3%
200 1
 
0.3%
199 1
 
0.3%
198 1
 
0.3%
197 1
 
0.3%
196 1
 
0.3%
195 1
 
0.3%
Other values (285) 285
96.6%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
295 1
0.3%
294 1
0.3%
293 1
0.3%
292 1
0.3%
291 1
0.3%
290 1
0.3%
289 1
0.3%
288 1
0.3%
287 1
0.3%
286 1
0.3%

아파트명
Text

Distinct277
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-18T11:12:07.651812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length20
Mean length8.6745763
Min length4

Characters and Unicode

Total characters2559
Distinct characters271
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique264 ?
Unique (%)89.5%

Sample

1st row덕산아파트
2nd row진주1단지아파트
3rd row석남1차아파트
4th row석남2차아파트
5th row황해아파트
ValueCountFrequency (%)
검단신도시 6
 
1.6%
청라 6
 
1.6%
동진아파트 5
 
1.3%
아파트 4
 
1.1%
효정아파트 3
 
0.8%
진흥아파트 3
 
0.8%
2단지 3
 
0.8%
1단지 3
 
0.8%
sk 3
 
0.8%
현광아파트 3
 
0.8%
Other values (308) 333
89.5%
2024-03-18T11:12:08.015581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 236
 
9.2%
트 231
 
9.0%
파 224
 
8.8%
78
 
3.0%
차 63
 
2.5%
이 49
 
1.9%
2 43
 
1.7%
단 41
 
1.6%
대 38
 
1.5%
라 37
 
1.4%
Other values (261) 1519
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2277
89.0%
Decimal Number 105
 
4.1%
Space Separator 78
 
3.0%
Uppercase Letter 43
 
1.7%
Open Punctuation 17
 
0.7%
Close Punctuation 17
 
0.7%
Lowercase Letter 17
 
0.7%
Other Punctuation 3
 
0.1%
Final Punctuation 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 236
 
10.4%
트 231
 
10.1%
파 224
 
9.8%
차 63
 
2.8%
이 49
 
2.2%
단 41
 
1.8%
대 38
 
1.7%
라 37
 
1.6%
스 37
 
1.6%
검 35
 
1.5%
Other values (214) 1286
56.5%
Uppercase Letter
ValueCountFrequency (%)
S 6
14.0%
A 4
 
9.3%
K 4
 
9.3%
E 4
 
9.3%
I 3
 
7.0%
L 3
 
7.0%
H 3
 
7.0%
P 2
 
4.7%
W 2
 
4.7%
V 2
 
4.7%
Other values (9) 10
23.3%
Decimal Number
ValueCountFrequency (%)
2 43
41.0%
1 32
30.5%
3 14
 
13.3%
0 5
 
4.8%
4 4
 
3.8%
5 2
 
1.9%
6 2
 
1.9%
9 1
 
1.0%
8 1
 
1.0%
7 1
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
23.5%
k 2
11.8%
c 2
11.8%
a 2
11.8%
r 2
11.8%
s 1
 
5.9%
d 1
 
5.9%
w 1
 
5.9%
i 1
 
5.9%
v 1
 
5.9%
Other Punctuation
ValueCountFrequency (%)
. 1
33.3%
, 1
33.3%
' 1
33.3%
Space Separator
ValueCountFrequency (%)
78
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2277
89.0%
Common 222
 
8.7%
Latin 60
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 236
 
10.4%
트 231
 
10.1%
파 224
 
9.8%
차 63
 
2.8%
이 49
 
2.2%
단 41
 
1.8%
대 38
 
1.7%
라 37
 
1.6%
스 37
 
1.6%
검 35
 
1.5%
Other values (214) 1286
56.5%
Latin
ValueCountFrequency (%)
S 6
 
10.0%
A 4
 
6.7%
e 4
 
6.7%
K 4
 
6.7%
E 4
 
6.7%
I 3
 
5.0%
L 3
 
5.0%
H 3
 
5.0%
P 2
 
3.3%
k 2
 
3.3%
Other values (19) 25
41.7%
Common
ValueCountFrequency (%)
78
35.1%
2 43
19.4%
1 32
14.4%
( 17
 
7.7%
) 17
 
7.7%
3 14
 
6.3%
0 5
 
2.3%
4 4
 
1.8%
5 2
 
0.9%
6 2
 
0.9%
Other values (8) 8
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2277
89.0%
ASCII 281
 
11.0%
Punctuation 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 236
 
10.4%
트 231
 
10.1%
파 224
 
9.8%
차 63
 
2.8%
이 49
 
2.2%
단 41
 
1.8%
대 38
 
1.7%
라 37
 
1.6%
스 37
 
1.6%
검 35
 
1.5%
Other values (214) 1286
56.5%
ASCII
ValueCountFrequency (%)
78
27.8%
2 43
15.3%
1 32
11.4%
( 17
 
6.0%
) 17
 
6.0%
3 14
 
5.0%
S 6
 
2.1%
0 5
 
1.8%
A 4
 
1.4%
e 4
 
1.4%
Other values (36) 61
21.7%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

소재지(도로명)
Text

Distinct294
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-18T11:12:08.230730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43
Mean length33.349153
Min length13

Characters and Unicode

Total characters9838
Distinct characters258
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique293 ?
Unique (%)99.3%

Sample

1st row인천광역시 서구 건지로284번길 93 (가좌동, 덕산아파트)
2nd row인천광역시 서구 장고개로337번길 32 (가좌동, 진주아파트)
3rd row인천광역시 서구 신석로112번길 35 (석남동, 석남아파트)
4th row인천광역시 서구 길주로 104 (석남동, 석남아파트)
5th row인천광역시 서구 염곡로 318 (석남동, 황해아파트)
ValueCountFrequency (%)
인천광역시 298
 
17.0%
서구 294
 
16.8%
가좌동 43
 
2.5%
석남동 39
 
2.2%
마전동 35
 
2.0%
경서동 25
 
1.4%
가정동 21
 
1.2%
연희동 21
 
1.2%
불로동 14
 
0.8%
당하동 14
 
0.8%
Other values (548) 946
54.1%
2024-03-18T11:12:08.566878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1867
 
19.0%
서 350
 
3.6%
동 314
 
3.2%
광 313
 
3.2%
로 313
 
3.2%
인 308
 
3.1%
시 304
 
3.1%
천 303
 
3.1%
역 302
 
3.1%
구 296
 
3.0%
Other values (248) 5168
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5997
61.0%
Space Separator 1867
 
19.0%
Decimal Number 1120
 
11.4%
Open Punctuation 281
 
2.9%
Close Punctuation 280
 
2.8%
Other Punctuation 257
 
2.6%
Dash Punctuation 18
 
0.2%
Uppercase Letter 13
 
0.1%
Lowercase Letter 3
 
< 0.1%
Letter Number 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 350
 
5.8%
동 314
 
5.2%
광 313
 
5.2%
로 313
 
5.2%
인 308
 
5.1%
시 304
 
5.1%
천 303
 
5.1%
역 302
 
5.0%
구 296
 
4.9%
아 208
 
3.5%
Other values (220) 2986
49.8%
Decimal Number
ValueCountFrequency (%)
1 219
19.6%
2 165
14.7%
3 148
13.2%
4 108
9.6%
5 91
8.1%
7 88
7.9%
6 84
 
7.5%
9 75
 
6.7%
8 74
 
6.6%
0 68
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
K 3
23.1%
S 2
15.4%
C 2
15.4%
E 1
 
7.7%
V 1
 
7.7%
W 1
 
7.7%
I 1
 
7.7%
L 1
 
7.7%
H 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
, 255
99.2%
. 2
 
0.8%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%
Space Separator
ValueCountFrequency (%)
1867
100.0%
Open Punctuation
ValueCountFrequency (%)
( 281
100.0%
Close Punctuation
ValueCountFrequency (%)
) 280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5997
61.0%
Common 3823
38.9%
Latin 18
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 350
 
5.8%
동 314
 
5.2%
광 313
 
5.2%
로 313
 
5.2%
인 308
 
5.1%
시 304
 
5.1%
천 303
 
5.1%
역 302
 
5.0%
구 296
 
4.9%
아 208
 
3.5%
Other values (220) 2986
49.8%
Common
ValueCountFrequency (%)
1867
48.8%
( 281
 
7.4%
) 280
 
7.3%
, 255
 
6.7%
1 219
 
5.7%
2 165
 
4.3%
3 148
 
3.9%
4 108
 
2.8%
5 91
 
2.4%
7 88
 
2.3%
Other values (6) 321
 
8.4%
Latin
ValueCountFrequency (%)
e 3
16.7%
K 3
16.7%
S 2
11.1%
C 2
11.1%
E 1
 
5.6%
V 1
 
5.6%
W 1
 
5.6%
I 1
 
5.6%
L 1
 
5.6%
H 1
 
5.6%
Other values (2) 2
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5997
61.0%
ASCII 3839
39.0%
Number Forms 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1867
48.6%
( 281
 
7.3%
) 280
 
7.3%
, 255
 
6.6%
1 219
 
5.7%
2 165
 
4.3%
3 148
 
3.9%
4 108
 
2.8%
5 91
 
2.4%
7 88
 
2.3%
Other values (16) 337
 
8.8%
Hangul
ValueCountFrequency (%)
서 350
 
5.8%
동 314
 
5.2%
광 313
 
5.2%
로 313
 
5.2%
인 308
 
5.1%
시 304
 
5.1%
천 303
 
5.1%
역 302
 
5.0%
구 296
 
4.9%
아 208
 
3.5%
Other values (220) 2986
49.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
50.0%
Ⅱ 1
50.0%

층수
Text

Distinct92
Distinct (%)31.3%
Missing1
Missing (%)0.3%
Memory size2.4 KiB
2024-03-18T11:12:08.787688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.037415
Min length1

Characters and Unicode

Total characters893
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)19.0%

Sample

1st row5
2nd row14
3rd row5
4th row5
5th row5
ValueCountFrequency (%)
5 39
 
13.2%
6 36
 
12.2%
15 35
 
11.9%
20 12
 
4.1%
18 9
 
3.1%
10 7
 
2.4%
25 7
 
2.4%
지하2층~지상25층 7
 
2.4%
12 6
 
2.0%
14 6
 
2.0%
Other values (83) 131
44.4%
2024-03-18T11:12:09.112697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 183
20.5%
5 136
15.2%
2 124
13.9%
~ 83
9.3%
0 57
 
6.4%
6 50
 
5.6%
8 35
 
3.9%
4 35
 
3.9%
층 34
 
3.8%
3 33
 
3.7%
Other values (8) 123
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 690
77.3%
Math Symbol 103
 
11.5%
Other Letter 98
 
11.0%
Dash Punctuation 1
 
0.1%
Space Separator 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 183
26.5%
5 136
19.7%
2 124
18.0%
0 57
 
8.3%
6 50
 
7.2%
8 35
 
5.1%
4 35
 
5.1%
3 33
 
4.8%
9 24
 
3.5%
7 13
 
1.9%
Other Letter
ValueCountFrequency (%)
층 34
34.7%
지 32
32.7%
하 17
17.3%
상 15
15.3%
Math Symbol
ValueCountFrequency (%)
~ 83
80.6%
～ 20
 
19.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 795
89.0%
Hangul 98
 
11.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 183
23.0%
5 136
17.1%
2 124
15.6%
~ 83
10.4%
0 57
 
7.2%
6 50
 
6.3%
8 35
 
4.4%
4 35
 
4.4%
3 33
 
4.2%
9 24
 
3.0%
Other values (4) 35
 
4.4%
Hangul
ValueCountFrequency (%)
층 34
34.7%
지 32
32.7%
하 17
17.3%
상 15
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 775
86.8%
Hangul 98
 
11.0%
None 20
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 183
23.6%
5 136
17.5%
2 124
16.0%
~ 83
10.7%
0 57
 
7.4%
6 50
 
6.5%
8 35
 
4.5%
4 35
 
4.5%
3 33
 
4.3%
9 24
 
3.1%
Other values (3) 15
 
1.9%
Hangul
ValueCountFrequency (%)
층 34
34.7%
지 32
32.7%
하 17
17.3%
상 15
15.3%
None
ValueCountFrequency (%)
～ 20
100.0%

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.779661
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T11:12:09.218830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q39
95-th percentile18.3
Maximum39
Range38
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.7512725
Coefficient of variation (CV)0.8483127
Kurtosis6.1626936
Mean6.779661
Median Absolute Deviation (MAD)3
Skewness2.0261773
Sum2000
Variance33.077136
MonotonicityNot monotonic
2024-03-18T11:12:09.319363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
5 41
13.9%
1 40
13.6%
4 27
9.2%
3 25
8.5%
2 25
8.5%
7 24
8.1%
6 19
 
6.4%
8 18
 
6.1%
11 14
 
4.7%
9 11
 
3.7%
Other values (18) 51
17.3%
ValueCountFrequency (%)
1 40
13.6%
2 25
8.5%
3 25
8.5%
4 27
9.2%
5 41
13.9%
6 19
6.4%
7 24
8.1%
8 18
6.1%
9 11
 
3.7%
10 8
 
2.7%
ValueCountFrequency (%)
39 1
 
0.3%
37 1
 
0.3%
27 1
 
0.3%
26 1
 
0.3%
24 1
 
0.3%
23 2
0.7%
22 1
 
0.3%
21 1
 
0.3%
20 2
0.7%
19 4
1.4%

동수(주택)
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)8.2%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean5.9455782
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T11:12:09.414348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q37.75
95-th percentile16
Maximum36
Range35
Interquartile range (IQR)5.75

Descriptive statistics

Standard deviation5.1447078
Coefficient of variation (CV)0.86529982
Kurtosis7.5788818
Mean5.9455782
Median Absolute Deviation (MAD)3
Skewness2.1972236
Sum1748
Variance26.468018
MonotonicityNot monotonic
2024-03-18T11:12:09.520951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 44
14.9%
4 38
12.9%
2 37
12.5%
6 32
10.8%
5 29
9.8%
3 23
7.8%
7 17
 
5.8%
10 12
 
4.1%
8 12
 
4.1%
9 8
 
2.7%
Other values (14) 42
14.2%
ValueCountFrequency (%)
1 44
14.9%
2 37
12.5%
3 23
7.8%
4 38
12.9%
5 29
9.8%
6 32
10.8%
7 17
 
5.8%
8 12
 
4.1%
9 8
 
2.7%
10 12
 
4.1%
ValueCountFrequency (%)
36 1
 
0.3%
35 1
 
0.3%
25 1
 
0.3%
23 1
 
0.3%
22 1
 
0.3%
20 1
 
0.3%
19 3
1.0%
17 3
1.0%
16 4
1.4%
15 3
1.0%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct229
Distinct (%)77.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean474
Minimum28
Maximum3331
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-18T11:12:09.648168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28
5-th percentile47.7
Q1160
median309
Q3620.5
95-th percentile1393.2
Maximum3331
Range3303
Interquartile range (IQR)460.5

Descriptive statistics

Standard deviation462.24765
Coefficient of variation (CV)0.97520602
Kurtosis6.7311204
Mean474
Median Absolute Deviation (MAD)189
Skewness2.163046
Sum139830
Variance213672.89
MonotonicityNot monotonic
2024-03-18T11:12:09.943985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299 5
 
1.7%
192 5
 
1.7%
252 5
 
1.7%
120 4
 
1.4%
132 4
 
1.4%
30 4
 
1.4%
160 4
 
1.4%
35 3
 
1.0%
144 3
 
1.0%
174 3
 
1.0%
Other values (219) 255
86.4%
ValueCountFrequency (%)
28 2
0.7%
30 4
1.4%
32 1
 
0.3%
35 3
1.0%
40 1
 
0.3%
43 1
 
0.3%
45 1
 
0.3%
47 2
0.7%
48 2
0.7%
49 1
 
0.3%
ValueCountFrequency (%)
3331 1
0.3%
2378 1
0.3%
2276 1
0.3%
2134 1
0.3%
1942 1
0.3%
1767 1
0.3%
1757 1
0.3%
1739 1
0.3%
1699 1
0.3%
1598 1
0.3%

사용검사일
Date

Distinct268
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
Minimum1982-02-27 00:00:00
Maximum2022-08-19 00:00:00
2024-03-18T11:12:10.085763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:10.240318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2022-08-01
295 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-01
2nd row2022-08-01
3rd row2022-08-01
4th row2022-08-01
5th row2022-08-01

Common Values

ValueCountFrequency (%)
2022-08-01 295
100.0%

Length

2024-03-18T11:12:10.348067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T11:12:10.428418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-01 295
100.0%

Interactions

2024-03-18T11:12:06.768529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:05.773868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.104955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.410166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.836560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:05.855674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.180144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.489874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.910296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:05.932363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.257683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.596194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.980866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.020800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.331651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T11:12:06.682599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T11:12:10.478820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호층수동수동수(주택)세대수
번호1.0000.9030.4180.3770.394
층수0.9031.0000.9090.9110.950
동수0.4180.9091.0000.9870.791
동수(주택)0.3770.9110.9871.0000.822
세대수0.3940.9500.7910.8221.000
2024-03-18T11:12:10.562027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호동수동수(주택)세대수
번호1.0000.5160.5050.560
동수0.5161.0000.9620.876
동수(주택)0.5050.9621.0000.887
세대수0.5600.8760.8871.000

Missing values

2024-03-18T11:12:07.073370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T11:12:07.178288image/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.
2024-03-18T11:12:07.258309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

번호아파트명소재지(도로명)층수동수동수(주택)세대수사용검사일데이터기준일자
01덕산아파트인천광역시 서구 건지로284번길 93 (가좌동, 덕산아파트)5321201982-02-272022-08-01
12진주1단지아파트인천광역시 서구 장고개로337번길 32 (가좌동, 진주아파트)1411106861983-03-012022-08-01
23석남1차아파트인천광역시 서구 신석로112번길 35 (석남동, 석남아파트)511301983-04-092022-08-01
34석남2차아파트인천광역시 서구 길주로 104 (석남동, 석남아파트)511301983-04-092022-08-01
45황해아파트인천광역시 서구 염곡로 318 (석남동, 황해아파트)522901983-09-052022-08-01
56한샘아파트인천광역시 서구 원적로 31 (가좌동, 한샘아파트)5441601983-12-192022-08-01
67동진아파트인천광역시 서구 석남로109번길 18 (석남동, 동진아파트)533601983-12-202022-08-01
78금성아파트인천광역시 서구 가정로261번길 11 (석남동, 금성아파트)511301984-05-092022-08-01
89아주아파트인천광역시 서구 건지로318번길 4 (가좌동, 아주아파트)622961984-05-192022-08-01
910세우아파트인천광역시 서구 건지로318번길 26 (가좌동, 세우아파트)5551801984-06-272022-08-01
번호아파트명소재지(도로명)층수동수동수(주택)세대수사용검사일데이터기준일자
285286검단신도시 디에트르 더 펠리체인천광역시 서구 이음2로 30지하2층~지상25층21512792022-01-282022-08-01
286287북청라하우스토리인천광역시 서구 경서로31번길 15지하2층~지상20층764302022-02-252022-08-01
287288검단대광로제비앙센트럴포레인천광역시 서구 검단로768번길 46지하2층~지상27층765562022-02-222022-08-01
288289호반써밋 프라임뷰인천광역시 서구 이음2로 70지하2층~지상25층887192022-05-022022-08-01
289290파라곤 보타닉파크인천광역시 서구 서로3로 225지하2층~지상25층12108872022-05-272022-08-01
290291검단신도시 대광로제비앙라포레인천광역시 서구 원당동 37-7지하2층~지상20층997352022-05-302022-08-01
291292검단신도시 파라곤센트럴파크인천광역시 서구 당하동 산 12-1지하2층~지상25층161211222022-06-292022-08-01
292293검단신도시 예미지 트리플에듀인천광역시 서구 원당동 286지하2층~지상25층141412492022-06-302022-08-01
293294검단신안인스빌 어반퍼스트인천광역시 서구 이음1로 173지하2층~지상25층121210732022-07-282022-08-01
294295검단신도시 모아미래도 엘리트파크인천광역시 서로3로 50지하2층~지상25층776582022-08-192022-08-01