Overview

Dataset statistics

Number of variables9
Number of observations8560
Missing cells10237
Missing cells (%)13.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory643.8 KiB
Average record size in memory77.0 B

Variable types

Numeric5
Text2
Categorical2

Dataset

Description인천광역시 남동구 집합건물현황에 대한 데이터로 소재지주소, 건물명, 연면적, 주용도, 세대수, 가구수, 호수 데이터기준일 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://www.data.go.kr/data/15099824/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연면적 is highly overall correlated with 호수High correlation
호수 is highly overall correlated with 연면적High correlation
주용도 is highly imbalanced (79.8%)Imbalance
건물명 has 2952 (34.5%) missing valuesMissing
호수 has 7192 (84.0%) missing valuesMissing
가구수 is highly skewed (γ1 = 29.40509917)Skewed
순번 has unique valuesUnique
세대수 has 1638 (19.1%) zerosZeros
가구수 has 8414 (98.3%) zerosZeros

Reproduction

Analysis started2024-03-23 06:22:41.130668
Analysis finished2024-03-23 06:22:55.605419
Duration14.47 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct8560
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4280.5
Minimum1
Maximum8560
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-03-23T06:22:56.054376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile428.95
Q12140.75
median4280.5
Q36420.25
95-th percentile8132.05
Maximum8560
Range8559
Interquartile range (IQR)4279.5

Descriptive statistics

Standard deviation2471.2035
Coefficient of variation (CV)0.57731655
Kurtosis-1.2
Mean4280.5
Median Absolute Deviation (MAD)2140
Skewness0
Sum36641080
Variance6106846.7
MonotonicityStrictly increasing
2024-03-23T06:22:56.842202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5704 1
 
< 0.1%
5718 1
 
< 0.1%
5717 1
 
< 0.1%
5716 1
 
< 0.1%
5715 1
 
< 0.1%
5714 1
 
< 0.1%
5713 1
 
< 0.1%
5712 1
 
< 0.1%
5711 1
 
< 0.1%
Other values (8550) 8550
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8560 1
< 0.1%
8559 1
< 0.1%
8558 1
< 0.1%
8557 1
< 0.1%
8556 1
< 0.1%
8555 1
< 0.1%
8554 1
< 0.1%
8553 1
< 0.1%
8552 1
< 0.1%
8551 1
< 0.1%

소재지주소
Text

Distinct5948
Distinct (%)69.5%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
2024-03-23T06:22:57.960133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length19.226869
Min length15

Characters and Unicode

Total characters164582
Distinct characters38
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

Unique5369 ?
Unique (%)62.7%

Sample

1st row인천광역시 남동구 간석동 388-43
2nd row인천광역시 남동구 구월동 1236-5
3rd row인천광역시 남동구 구월동 1143-24
4th row인천광역시 남동구 간석동 268-21
5th row인천광역시 남동구 간석동 391
ValueCountFrequency (%)
인천광역시 8560
25.0%
남동구 8560
25.0%
구월동 2179
 
6.4%
만수동 2153
 
6.3%
간석동 1986
 
5.8%
논현동 920
 
2.7%
서창동 567
 
1.7%
남촌동 366
 
1.1%
도림동 171
 
0.5%
장수동 164
 
0.5%
Other values (5809) 8614
25.2%
2024-03-23T06:22:59.562236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25680
15.6%
동 17120
 
10.4%
구 10739
 
6.5%
남 8926
 
5.4%
1 8580
 
5.2%
인 8560
 
5.2%
광 8560
 
5.2%
역 8560
 
5.2%
시 8560
 
5.2%
천 8560
 
5.2%
Other values (28) 50737
30.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 94160
57.2%
Decimal Number 37622
 
22.9%
Space Separator 25680
 
15.6%
Dash Punctuation 7120
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 17120
18.2%
구 10739
11.4%
남 8926
9.5%
인 8560
9.1%
광 8560
9.1%
역 8560
9.1%
시 8560
9.1%
천 8560
9.1%
수 2319
 
2.5%
월 2179
 
2.3%
Other values (16) 10077
10.7%
Decimal Number
ValueCountFrequency (%)
1 8580
22.8%
2 4156
11.0%
3 3906
10.4%
5 3241
 
8.6%
6 3195
 
8.5%
4 3149
 
8.4%
9 3149
 
8.4%
7 3080
 
8.2%
8 2599
 
6.9%
0 2567
 
6.8%
Space Separator
ValueCountFrequency (%)
25680
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 94160
57.2%
Common 70422
42.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 17120
18.2%
구 10739
11.4%
남 8926
9.5%
인 8560
9.1%
광 8560
9.1%
역 8560
9.1%
시 8560
9.1%
천 8560
9.1%
수 2319
 
2.5%
월 2179
 
2.3%
Other values (16) 10077
10.7%
Common
ValueCountFrequency (%)
25680
36.5%
1 8580
 
12.2%
- 7120
 
10.1%
2 4156
 
5.9%
3 3906
 
5.5%
5 3241
 
4.6%
6 3195
 
4.5%
4 3149
 
4.5%
9 3149
 
4.5%
7 3080
 
4.4%
Other values (2) 5166
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 94160
57.2%
ASCII 70422
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25680
36.5%
1 8580
 
12.2%
- 7120
 
10.1%
2 4156
 
5.9%
3 3906
 
5.5%
5 3241
 
4.6%
6 3195
 
4.5%
4 3149
 
4.5%
9 3149
 
4.5%
7 3080
 
4.4%
Other values (2) 5166
 
7.3%
Hangul
ValueCountFrequency (%)
동 17120
18.2%
구 10739
11.4%
남 8926
9.5%
인 8560
9.1%
광 8560
9.1%
역 8560
9.1%
시 8560
9.1%
천 8560
9.1%
수 2319
 
2.5%
월 2179
 
2.3%
Other values (16) 10077
10.7%

건물명
Text

MISSING 

Distinct2260
Distinct (%)40.3%
Missing2952
Missing (%)34.5%
Memory size67.0 KiB
2024-03-23T06:23:00.417401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length31
Mean length7.0900499
Min length1

Characters and Unicode

Total characters39761
Distinct characters488
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1577 ?
Unique (%)28.1%

Sample

1st row호진주택
2nd row구월 해드림11차
3rd row카르페디엠
4th row삼정주택
5th row간석호방사랑채
ValueCountFrequency (%)
구월 131
 
1.8%
논현휴먼시아 112
 
1.5%
만수주공아파트 104
 
1.4%
한화 90
 
1.2%
주공아파트 81
 
1.1%
힐스테이트 73
 
1.0%
에코메트로 73
 
1.0%
소래휴먼시아 72
 
1.0%
꿈에그린아파트 68
 
0.9%
포레시안(foresian 67
 
0.9%
Other values (2327) 6376
88.0%
2024-03-23T06:23:01.514259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
아 1907
 
4.8%
트 1737
 
4.4%
1697
 
4.3%
빌 1631
 
4.1%
파 1247
 
3.1%
라 1214
 
3.1%
지 800
 
2.0%
이 756
 
1.9%
스 694
 
1.7%
에 642
 
1.6%
Other values (478) 27436
69.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 35436
89.1%
Space Separator 1697
 
4.3%
Decimal Number 1429
 
3.6%
Lowercase Letter 487
 
1.2%
Uppercase Letter 342
 
0.9%
Close Punctuation 142
 
0.4%
Open Punctuation 142
 
0.4%
Dash Punctuation 50
 
0.1%
Other Punctuation 25
 
0.1%
Letter Number 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 1907
 
5.4%
트 1737
 
4.9%
빌 1631
 
4.6%
파 1247
 
3.5%
라 1214
 
3.4%
지 800
 
2.3%
이 756
 
2.1%
스 694
 
2.0%
에 642
 
1.8%
동 613
 
1.7%
Other values (425) 24195
68.3%
Uppercase Letter
ValueCountFrequency (%)
F 67
19.6%
A 54
15.8%
B 40
11.7%
C 24
 
7.0%
L 22
 
6.4%
T 16
 
4.7%
S 15
 
4.4%
G 13
 
3.8%
P 13
 
3.8%
I 11
 
3.2%
Other values (13) 67
19.6%
Decimal Number
ValueCountFrequency (%)
1 528
36.9%
2 286
20.0%
3 117
 
8.2%
5 102
 
7.1%
0 99
 
6.9%
4 79
 
5.5%
6 76
 
5.3%
7 71
 
5.0%
8 38
 
2.7%
9 33
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
s 73
15.0%
a 70
14.4%
o 68
14.0%
e 68
14.0%
r 68
14.0%
n 67
13.8%
i 67
13.8%
l 3
 
0.6%
c 2
 
0.4%
w 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 16
64.0%
, 5
 
20.0%
# 3
 
12.0%
. 1
 
4.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 10
90.9%
Ⅲ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
1697
100.0%
Close Punctuation
ValueCountFrequency (%)
) 142
100.0%
Open Punctuation
ValueCountFrequency (%)
( 142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 35432
89.1%
Common 3485
 
8.8%
Latin 840
 
2.1%
Han 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 1907
 
5.4%
트 1737
 
4.9%
빌 1631
 
4.6%
파 1247
 
3.5%
라 1214
 
3.4%
지 800
 
2.3%
이 756
 
2.1%
스 694
 
2.0%
에 642
 
1.8%
동 613
 
1.7%
Other values (421) 24191
68.3%
Latin
ValueCountFrequency (%)
s 73
 
8.7%
a 70
 
8.3%
o 68
 
8.1%
e 68
 
8.1%
r 68
 
8.1%
n 67
 
8.0%
i 67
 
8.0%
F 67
 
8.0%
A 54
 
6.4%
B 40
 
4.8%
Other values (25) 198
23.6%
Common
ValueCountFrequency (%)
1697
48.7%
1 528
 
15.2%
2 286
 
8.2%
) 142
 
4.1%
( 142
 
4.1%
3 117
 
3.4%
5 102
 
2.9%
0 99
 
2.8%
4 79
 
2.3%
6 76
 
2.2%
Other values (8) 217
 
6.2%
Han
ValueCountFrequency (%)
品 1
25.0%
名 1
25.0%
眞 1
25.0%
希 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 35432
89.1%
ASCII 4314
 
10.8%
Number Forms 11
 
< 0.1%
CJK 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
아 1907
 
5.4%
트 1737
 
4.9%
빌 1631
 
4.6%
파 1247
 
3.5%
라 1214
 
3.4%
지 800
 
2.3%
이 756
 
2.1%
스 694
 
2.0%
에 642
 
1.8%
동 613
 
1.7%
Other values (421) 24191
68.3%
ASCII
ValueCountFrequency (%)
1697
39.3%
1 528
 
12.2%
2 286
 
6.6%
) 142
 
3.3%
( 142
 
3.3%
3 117
 
2.7%
5 102
 
2.4%
0 99
 
2.3%
4 79
 
1.8%
6 76
 
1.8%
Other values (41) 1046
24.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 10
90.9%
Ⅲ 1
 
9.1%
CJK
ValueCountFrequency (%)
品 1
25.0%
名 1
25.0%
眞 1
25.0%
希 1
25.0%

연면적
Real number (ℝ)

HIGH CORRELATION 

Distinct6382
Distinct (%)74.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2758.3973
Minimum0
Maximum119755.93
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-03-23T06:23:02.173142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile166.4595
Q1329.28
median595.55
Q31995.745
95-th percentile12365.01
Maximum119755.93
Range119755.93
Interquartile range (IQR)1666.465

Descriptive statistics

Standard deviation5865.8215
Coefficient of variation (CV)2.1265325
Kurtosis57.418246
Mean2758.3973
Median Absolute Deviation (MAD)269.025
Skewness5.8155613
Sum23611881
Variance34407862
MonotonicityNot monotonic
2024-03-23T06:23:02.793936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
329.28 32
 
0.4%
328.32 30
 
0.4%
329.4 24
 
0.3%
329.76 23
 
0.3%
329.52 23
 
0.3%
9.0 22
 
0.3%
329.6 20
 
0.2%
329.04 20
 
0.2%
328.8 18
 
0.2%
327.36 17
 
0.2%
Other values (6372) 8331
97.3%
ValueCountFrequency (%)
0.0 1
< 0.1%
2.02 1
< 0.1%
3.64 1
< 0.1%
3.75 1
< 0.1%
5.58 1
< 0.1%
6.0 1
< 0.1%
6.46 1
< 0.1%
6.5 2
< 0.1%
6.75 1
< 0.1%
6.76 1
< 0.1%
ValueCountFrequency (%)
119755.93 1
< 0.1%
87747.62 1
< 0.1%
82294.563 1
< 0.1%
80432.52 1
< 0.1%
69914.08 1
< 0.1%
69179.49 1
< 0.1%
66698.53 1
< 0.1%
63867.087 1
< 0.1%
62738.897 1
< 0.1%
62086.348 1
< 0.1%

주용도
Categorical

IMBALANCE 

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
공동주택
7474 
제1종근린생활시설
 
310
업무시설
 
290
제2종근린생활시설
 
274
공장
 
73
Other values (15)
 
139

Length

Max length10
Median length4
Mean length4.3434579
Min length2

Unique

Unique5 ?
Unique (%)0.1%

Sample

1st row공동주택
2nd row공동주택
3rd row업무시설
4th row공동주택
5th row공동주택

Common Values

ValueCountFrequency (%)
공동주택 7474
87.3%
제1종근린생활시설 310
 
3.6%
업무시설 290
 
3.4%
제2종근린생활시설 274
 
3.2%
공장 73
 
0.9%
판매시설 35
 
0.4%
자동차관련시설 30
 
0.4%
노유자시설 17
 
0.2%
교육연구시설 17
 
0.2%
숙박시설 14
 
0.2%
Other values (10) 26
 
0.3%

Length

2024-03-23T06:23:03.291697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공동주택 7474
87.3%
제1종근린생활시설 310
 
3.6%
업무시설 290
 
3.4%
제2종근린생활시설 274
 
3.2%
공장 73
 
0.9%
판매시설 35
 
0.4%
자동차관련시설 30
 
0.4%
노유자시설 17
 
0.2%
교육연구시설 17
 
0.2%
숙박시설 14
 
0.2%
Other values (10) 26
 
0.3%

세대수
Real number (ℝ)

ZEROS 

Distinct193
Distinct (%)2.3%
Missing25
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean21.23843
Minimum0
Maximum356
Zeros1638
Zeros (%)19.1%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-03-23T06:23:03.922163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median8
Q314
95-th percentile108
Maximum356
Range356
Interquartile range (IQR)8

Descriptive statistics

Standard deviation36.258126
Coefficient of variation (CV)1.7071943
Kurtosis9.7814701
Mean21.23843
Median Absolute Deviation (MAD)4
Skewness2.8835014
Sum181270
Variance1314.6517
MonotonicityNot monotonic
2024-03-23T06:23:04.655299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 2304
26.9%
0 1638
19.1%
10 836
 
9.8%
6 365
 
4.3%
12 295
 
3.4%
15 281
 
3.3%
9 273
 
3.2%
14 154
 
1.8%
7 121
 
1.4%
16 114
 
1.3%
Other values (183) 2154
25.2%
ValueCountFrequency (%)
0 1638
19.1%
1 56
 
0.7%
2 51
 
0.6%
3 55
 
0.6%
4 110
 
1.3%
5 74
 
0.9%
6 365
 
4.3%
7 121
 
1.4%
8 2304
26.9%
9 273
 
3.2%
ValueCountFrequency (%)
356 1
< 0.1%
354 1
< 0.1%
340 1
< 0.1%
294 2
< 0.1%
288 1
< 0.1%
270 1
< 0.1%
254 1
< 0.1%
246 1
< 0.1%
244 1
< 0.1%
241 1
< 0.1%

가구수
Real number (ℝ)

SKEWED  ZEROS 

Distinct20
Distinct (%)0.2%
Missing68
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.061469618
Minimum0
Maximum54
Zeros8414
Zeros (%)98.3%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-03-23T06:23:05.057617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum54
Range54
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2124425
Coefficient of variation (CV)19.724256
Kurtosis999.28862
Mean0.061469618
Median Absolute Deviation (MAD)0
Skewness29.405099
Sum522
Variance1.4700168
MonotonicityNot monotonic
2024-03-23T06:23:05.542637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 8414
98.3%
1 28
 
0.3%
2 25
 
0.3%
8 3
 
< 0.1%
19 3
 
< 0.1%
20 2
 
< 0.1%
9 2
 
< 0.1%
6 2
 
< 0.1%
4 2
 
< 0.1%
36 1
 
< 0.1%
Other values (10) 10
 
0.1%
(Missing) 68
 
0.8%
ValueCountFrequency (%)
0 8414
98.3%
1 28
 
0.3%
2 25
 
0.3%
3 1
 
< 0.1%
4 2
 
< 0.1%
6 2
 
< 0.1%
8 3
 
< 0.1%
9 2
 
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
ValueCountFrequency (%)
54 1
 
< 0.1%
42 1
 
< 0.1%
41 1
 
< 0.1%
36 1
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
20 2
< 0.1%
19 3
< 0.1%
15 1
 
< 0.1%
13 1
 
< 0.1%

호수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct165
Distinct (%)12.1%
Missing7192
Missing (%)84.0%
Infinite0
Infinite (%)0.0%
Mean31.059211
Minimum0
Maximum832
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size75.4 KiB
2024-03-23T06:23:05.917933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median10
Q328
95-th percentile139.9
Maximum832
Range832
Interquartile range (IQR)25

Descriptive statistics

Standard deviation67.187801
Coefficient of variation (CV)2.1632166
Kurtosis39.91763
Mean31.059211
Median Absolute Deviation (MAD)8
Skewness5.3994778
Sum42489
Variance4514.2006
MonotonicityNot monotonic
2024-03-23T06:23:06.227839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 152
 
1.8%
2 125
 
1.5%
4 78
 
0.9%
3 68
 
0.8%
6 59
 
0.7%
5 51
 
0.6%
8 45
 
0.5%
7 41
 
0.5%
9 36
 
0.4%
11 35
 
0.4%
Other values (155) 678
 
7.9%
(Missing) 7192
84.0%
ValueCountFrequency (%)
0 2
 
< 0.1%
1 152
1.8%
2 125
1.5%
3 68
0.8%
4 78
0.9%
5 51
 
0.6%
6 59
 
0.7%
7 41
 
0.5%
8 45
 
0.5%
9 36
 
0.4%
ValueCountFrequency (%)
832 1
< 0.1%
691 1
< 0.1%
654 1
< 0.1%
605 1
< 0.1%
524 1
< 0.1%
516 1
< 0.1%
480 1
< 0.1%
381 1
< 0.1%
367 1
< 0.1%
349 1
< 0.1%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.0 KiB
2024-02-22
8560 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-02-22
2nd row2024-02-22
3rd row2024-02-22
4th row2024-02-22
5th row2024-02-22

Common Values

ValueCountFrequency (%)
2024-02-22 8560
100.0%

Length

2024-03-23T06:23:06.656287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:23:06.953068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-02-22 8560
100.0%

Interactions

2024-03-23T06:22:49.749670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:43.706504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:45.117845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:46.828427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:48.469713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:49.999799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:43.953600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:45.453968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:47.095165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:48.724872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:50.436316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:44.237404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:45.820891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:47.571238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:48.944764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:50.919183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:44.552708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:46.154890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:47.860456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:49.216688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:51.478502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:44.826164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:46.496219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:48.216738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T06:22:49.491771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T06:23:07.154911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연면적주용도세대수가구수호수
순번1.0000.1490.3170.3410.0260.062
연면적0.1491.0000.2140.3830.0000.800
주용도0.3170.2141.0000.0600.1690.342
세대수0.3410.3830.0601.0000.0530.000
가구수0.0260.0000.1690.0531.0000.000
호수0.0620.8000.3420.0000.0001.000
2024-03-23T06:23:07.460910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연면적세대수가구수호수주용도
순번1.000-0.367-0.0230.023-0.2370.124
연면적-0.3671.0000.4800.0340.8160.085
세대수-0.0230.4801.000-0.043-0.3510.023
가구수0.0230.034-0.0431.000-0.1090.071
호수-0.2370.816-0.351-0.1091.0000.145
주용도0.1240.0850.0230.0710.1451.000

Missing values

2024-03-23T06:22:52.696373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:22:53.733103image/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.
2024-03-23T06:22:55.225132image/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

순번소재지주소건물명연면적주용도세대수가구수호수데이터기준일
01인천광역시 남동구 간석동 388-43호진주택659.06공동주택120<NA>2024-02-22
12인천광역시 남동구 구월동 1236-5구월 해드림11차1304.58공동주택220<NA>2024-02-22
23인천광역시 남동구 구월동 1143-24카르페디엠20778.36업무시설001712024-02-22
34인천광역시 남동구 간석동 268-21삼정주택657.83공동주택80<NA>2024-02-22
45인천광역시 남동구 간석동 391간석호방사랑채1243.77공동주택160<NA>2024-02-22
56인천광역시 남동구 구월동 1243-3팔라스빌839.98공동주택80<NA>2024-02-22
67인천광역시 남동구 구월동 1172-6명성다온채2316.73공동주택320<NA>2024-02-22
78인천광역시 남동구 만수동 907-9드림타워11차659.69공동주택100<NA>2024-02-22
89인천광역시 남동구 간석동 390-27간석엔씨파크658.91공동주택100<NA>2024-02-22
910인천광역시 남동구 구월동 1277-33대문주택613.35공동주택80<NA>2024-02-22
순번소재지주소건물명연면적주용도세대수가구수호수데이터기준일
85508551인천광역시 남동구 구월동 1551구월 아시아드선수촌 7단지532.3158공동주택0<NA><NA>2024-02-22
85518552인천광역시 남동구 구월동 1551구월 아시아드선수촌 7단지25178.8675공동주택0<NA><NA>2024-02-22
85528553인천광역시 남동구 구월동 1551구월 아시아드선수촌 7단지10573.3825공동주택219<NA><NA>2024-02-22
85538554인천광역시 남동구 구월동 1551구월 아시아드선수촌 7단지5393.1129공동주택130<NA><NA>2024-02-22
85548555인천광역시 남동구 구월동 1551구월 아시아드선수촌 7단지13555.4818공동주택232<NA><NA>2024-02-22
85558556인천광역시 남동구 간석동 280-11하누리프라자8257.88업무시설<NA><NA>672024-02-22
85568557인천광역시 남동구 만수동 918-25힘찬659.91공동주택10<NA><NA>2024-02-22
85578558인천광역시 남동구 논현동 764-1인천논현 에코파크 아리스타24467.1885업무시설<NA><NA>1972024-02-22
85588559인천광역시 남동구 장수동 792-3라온하제B659.72공동주택8<NA><NA>2024-02-22
85598560인천광역시 남동구 장수동 792-2라온하제A659.48공동주택8<NA><NA>2024-02-22