Overview

Dataset statistics

Number of variables12
Number of observations3656
Missing cells3517
Missing cells (%)8.0%
Duplicate rows9
Duplicate rows (%)0.2%
Total size in memory360.7 KiB
Average record size in memory101.0 B

Variable types

Categorical3
Text2
Numeric5
DateTime2

Dataset

Description인천광역시 남동구 최근 1년간 공동주택(아파트, 다세대/연립주택)별 실거래가 합계에 대한 데이터로 행정구역, 단지명, 합계동호수(건), 합계면적(제곱미터), 금액(백만원), 산출기간, 기준일자 항목을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=3077626&srcSe=7661IVAWM27C61E190

Alerts

Dataset has 9 (0.2%) duplicate rowsDuplicates
거래유형 is highly overall correlated with 중개사소재지High correlation
중개사소재지 is highly overall correlated with 거래유형High correlation
전용면적(제곱미터) is highly overall correlated with 거래금액(만원)High correlation
거래금액(만원) is highly overall correlated with 전용면적(제곱미터) and 1 other fieldsHigh correlation
건축년도 is highly overall correlated with 거래금액(만원)High correlation
거래유형 is highly imbalanced (64.3%)Imbalance
중개사소재지 is highly imbalanced (80.3%)Imbalance
해제사유발생일 has 3517 (96.2%) missing valuesMissing

Reproduction

Analysis started2024-01-28 15:37:03.185751
Analysis finished2024-01-28 15:37:05.928503
Duration2.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정구역
Categorical

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
인천광역시 남동구 만수동
917 
인천광역시 남동구 논현동
879 
인천광역시 남동구 구월동
821 
인천광역시 남동구 간석동
554 
인천광역시 남동구 서창동
430 
Other values (3)
 
55

Length

Max length13
Median length13
Mean length13
Min length13

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row인천광역시 남동구 간석동
2nd row인천광역시 남동구 간석동
3rd row인천광역시 남동구 간석동
4th row인천광역시 남동구 간석동
5th row인천광역시 남동구 간석동

Common Values

ValueCountFrequency (%)
인천광역시 남동구 만수동 917
25.1%
인천광역시 남동구 논현동 879
24.0%
인천광역시 남동구 구월동 821
22.5%
인천광역시 남동구 간석동 554
15.2%
인천광역시 남동구 서창동 430
11.8%
인천광역시 남동구 남촌동 32
 
0.9%
인천광역시 남동구 도림동 22
 
0.6%
인천광역시 남동구 장수동 1
 
< 0.1%

Length

2024-01-29T00:37:05.982419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:37:06.070403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 3656
33.3%
남동구 3656
33.3%
만수동 917
 
8.4%
논현동 879
 
8.0%
구월동 821
 
7.5%
간석동 554
 
5.1%
서창동 430
 
3.9%
남촌동 32
 
0.3%
도림동 22
 
0.2%
장수동 1
 
< 0.1%

단지명
Text

Distinct240
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
2024-01-29T00:37:06.273135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length15
Mean length7.3413567
Min length2

Characters and Unicode

Total characters26840
Distinct characters255
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

Unique54 ?
Unique (%)1.5%

Sample

1st rowTK리즈빌
2nd rowThe레지던스아파트
3rd row가영
4th row가영
5th row간석동행복누리움
ValueCountFrequency (%)
구월힐스테이트1단지 237
 
6.0%
롯데캐슬골드 151
 
3.8%
벽산 116
 
2.9%
포레시안 110
 
2.8%
간석래미안자이 83
 
2.1%
만수뉴서울아파트 79
 
2.0%
에코메트로11 76
 
1.9%
서창센트럴푸르지오 65
 
1.6%
어울림마을 64
 
1.6%
풍림 61
 
1.5%
Other values (239) 2916
73.7%
2024-01-29T00:37:06.582735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 1305
 
4.9%
트 1120
 
4.2%
단 1106
 
4.1%
1 1100
 
4.1%
아 842
 
3.1%
구 568
 
2.1%
스 568
 
2.1%
이 538
 
2.0%
월 535
 
2.0%
에 470
 
1.8%
Other values (245) 18688
69.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23028
85.8%
Decimal Number 2549
 
9.5%
Open Punctuation 370
 
1.4%
Close Punctuation 370
 
1.4%
Space Separator 302
 
1.1%
Dash Punctuation 99
 
0.4%
Uppercase Letter 57
 
0.2%
Other Punctuation 52
 
0.2%
Lowercase Letter 10
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1305
 
5.7%
트 1120
 
4.9%
단 1106
 
4.8%
아 842
 
3.7%
구 568
 
2.5%
스 568
 
2.5%
이 538
 
2.3%
월 535
 
2.3%
에 470
 
2.0%
수 459
 
2.0%
Other values (212) 15517
67.4%
Uppercase Letter
ValueCountFrequency (%)
C 32
56.1%
M 4
 
7.0%
T 4
 
7.0%
B 3
 
5.3%
K 3
 
5.3%
I 2
 
3.5%
H 2
 
3.5%
O 2
 
3.5%
P 2
 
3.5%
S 1
 
1.8%
Other values (2) 2
 
3.5%
Decimal Number
ValueCountFrequency (%)
1 1100
43.2%
2 322
 
12.6%
0 220
 
8.6%
3 210
 
8.2%
5 177
 
6.9%
6 143
 
5.6%
8 124
 
4.9%
7 102
 
4.0%
9 82
 
3.2%
4 69
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
s 4
40.0%
a 2
20.0%
l 2
20.0%
e 1
 
10.0%
h 1
 
10.0%
Open Punctuation
ValueCountFrequency (%)
( 370
100.0%
Close Punctuation
ValueCountFrequency (%)
) 370
100.0%
Space Separator
ValueCountFrequency (%)
302
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 99
100.0%
Other Punctuation
ValueCountFrequency (%)
, 52
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23028
85.8%
Common 3742
 
13.9%
Latin 70
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1305
 
5.7%
트 1120
 
4.9%
단 1106
 
4.8%
아 842
 
3.7%
구 568
 
2.5%
스 568
 
2.5%
이 538
 
2.3%
월 535
 
2.3%
에 470
 
2.0%
수 459
 
2.0%
Other values (212) 15517
67.4%
Latin
ValueCountFrequency (%)
C 32
45.7%
M 4
 
5.7%
T 4
 
5.7%
s 4
 
5.7%
B 3
 
4.3%
Ⅱ 3
 
4.3%
K 3
 
4.3%
I 2
 
2.9%
a 2
 
2.9%
l 2
 
2.9%
Other values (8) 11
 
15.7%
Common
ValueCountFrequency (%)
1 1100
29.4%
( 370
 
9.9%
) 370
 
9.9%
2 322
 
8.6%
302
 
8.1%
0 220
 
5.9%
3 210
 
5.6%
5 177
 
4.7%
6 143
 
3.8%
8 124
 
3.3%
Other values (5) 404
 
10.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23028
85.8%
ASCII 3809
 
14.2%
Number Forms 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 1305
 
5.7%
트 1120
 
4.9%
단 1106
 
4.8%
아 842
 
3.7%
구 568
 
2.5%
스 568
 
2.5%
이 538
 
2.3%
월 535
 
2.3%
에 470
 
2.0%
수 459
 
2.0%
Other values (212) 15517
67.4%
ASCII
ValueCountFrequency (%)
1 1100
28.9%
( 370
 
9.7%
) 370
 
9.7%
2 322
 
8.5%
302
 
7.9%
0 220
 
5.8%
3 210
 
5.5%
5 177
 
4.6%
6 143
 
3.8%
8 124
 
3.3%
Other values (22) 471
12.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 3
100.0%

전용면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct508
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean74.274095
Minimum12.03
Maximum199.069
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.3 KiB
2024-01-29T00:37:06.699486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.03
5-th percentile34.65
Q159.57
median83.84
Q384.947
95-th percentile119.877
Maximum199.069
Range187.039
Interquartile range (IQR)25.377

Descriptive statistics

Standard deviation25.311686
Coefficient of variation (CV)0.34078754
Kurtosis1.4681106
Mean74.274095
Median Absolute Deviation (MAD)18.117
Skewness0.43946051
Sum271546.09
Variance640.68147
MonotonicityNot monotonic
2024-01-29T00:37:06.807223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
84.93 109
 
3.0%
34.65 79
 
2.2%
84.92 72
 
2.0%
83.9829 68
 
1.9%
115.6671 60
 
1.6%
84.98 59
 
1.6%
83.8726 58
 
1.6%
59.9 56
 
1.5%
84.96 54
 
1.5%
59.57 53
 
1.4%
Other values (498) 2988
81.7%
ValueCountFrequency (%)
12.03 5
0.1%
12.173 1
 
< 0.1%
12.26 4
0.1%
12.373 8
0.2%
12.94 1
 
< 0.1%
13.23 1
 
< 0.1%
13.48 4
0.1%
13.65 1
 
< 0.1%
13.68 1
 
< 0.1%
14.12 3
 
0.1%
ValueCountFrequency (%)
199.069 4
 
0.1%
191.4 1
 
< 0.1%
169.668 4
 
0.1%
165.76 1
 
< 0.1%
163.71 3
 
0.1%
162.68 1
 
< 0.1%
156.168 1
 
< 0.1%
154.104 3
 
0.1%
153.08 1
 
< 0.1%
150.777 16
0.4%

계약년월
Date

Distinct12
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
Minimum2022-09-01 00:00:00
Maximum2023-08-01 00:00:00
2024-01-29T00:37:06.893140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:06.963102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)

계약일
Real number (ℝ)

Distinct31
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.56756
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.3 KiB
2024-01-29T00:37:07.045727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median15.5
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.8802539
Coefficient of variation (CV)0.57043325
Kurtosis-1.1816345
Mean15.56756
Median Absolute Deviation (MAD)7.5
Skewness0.013473863
Sum56915
Variance78.858909
MonotonicityNot monotonic
2024-01-29T00:37:07.138992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 170
 
4.6%
17 148
 
4.0%
3 144
 
3.9%
10 142
 
3.9%
19 142
 
3.9%
25 136
 
3.7%
15 135
 
3.7%
27 131
 
3.6%
8 131
 
3.6%
24 129
 
3.5%
Other values (21) 2248
61.5%
ValueCountFrequency (%)
1 170
4.6%
2 98
2.7%
3 144
3.9%
4 127
3.5%
5 97
2.7%
6 100
2.7%
7 109
3.0%
8 131
3.6%
9 108
3.0%
10 142
3.9%
ValueCountFrequency (%)
31 71
1.9%
30 106
2.9%
29 114
3.1%
28 120
3.3%
27 131
3.6%
26 103
2.8%
25 136
3.7%
24 129
3.5%
23 89
2.4%
22 109
3.0%

거래금액(만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct602
Distinct (%)16.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34756.63
Minimum3900
Maximum116000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.3 KiB
2024-01-29T00:37:07.241096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3900
5-th percentile11000
Q124300
median35500
Q344000
95-th percentile58000
Maximum116000
Range112100
Interquartile range (IQR)19700

Descriptive statistics

Standard deviation14662.693
Coefficient of variation (CV)0.4218675
Kurtosis0.59574752
Mean34756.63
Median Absolute Deviation (MAD)9700
Skewness0.29215097
Sum1.2707024 × 108
Variance2.1499455 × 108
MonotonicityNot monotonic
2024-01-29T00:37:07.351154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40000 74
 
2.0%
30000 72
 
2.0%
35000 60
 
1.6%
39000 55
 
1.5%
50000 52
 
1.4%
38000 51
 
1.4%
41000 48
 
1.3%
43000 46
 
1.3%
45000 46
 
1.3%
29000 45
 
1.2%
Other values (592) 3107
85.0%
ValueCountFrequency (%)
3900 1
 
< 0.1%
4000 4
0.1%
4200 2
 
0.1%
4400 1
 
< 0.1%
4450 1
 
< 0.1%
4500 2
 
0.1%
4600 1
 
< 0.1%
4900 2
 
0.1%
5000 6
0.2%
5100 1
 
< 0.1%
ValueCountFrequency (%)
116000 1
 
< 0.1%
115000 1
 
< 0.1%
110000 1
 
< 0.1%
100000 2
0.1%
89300 1
 
< 0.1%
89000 1
 
< 0.1%
88000 3
0.1%
86000 2
0.1%
83000 1
 
< 0.1%
82000 1
 
< 0.1%

층
Real number (ℝ)

Distinct42
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.383479
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.3 KiB
2024-01-29T00:37:07.747405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median10
Q316
95-th percentile25
Maximum46
Range45
Interquartile range (IQR)11

Descriptive statistics

Standard deviation7.3797957
Coefficient of variation (CV)0.64829
Kurtosis0.45982127
Mean11.383479
Median Absolute Deviation (MAD)5
Skewness0.77515076
Sum41618
Variance54.461385
MonotonicityNot monotonic
2024-01-29T00:37:07.844651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
5 244
 
6.7%
12 206
 
5.6%
4 199
 
5.4%
10 186
 
5.1%
3 184
 
5.0%
13 180
 
4.9%
2 176
 
4.8%
9 175
 
4.8%
6 172
 
4.7%
1 169
 
4.6%
Other values (32) 1765
48.3%
ValueCountFrequency (%)
1 169
4.6%
2 176
4.8%
3 184
5.0%
4 199
5.4%
5 244
6.7%
6 172
4.7%
7 166
4.5%
8 159
4.3%
9 175
4.8%
10 186
5.1%
ValueCountFrequency (%)
46 1
 
< 0.1%
45 1
 
< 0.1%
40 3
 
0.1%
39 3
 
0.1%
38 3
 
0.1%
37 4
0.1%
36 5
0.1%
35 2
 
0.1%
34 8
0.2%
33 9
0.2%

건축년도
Real number (ℝ)

HIGH CORRELATION 

Distinct40
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2004.9926
Minimum1980
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size32.3 KiB
2024-01-29T00:37:07.941391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1980
5-th percentile1987
Q11998
median2007
Q32013
95-th percentile2018
Maximum2022
Range42
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.9103064
Coefficient of variation (CV)0.0049428144
Kurtosis-0.74511678
Mean2004.9926
Median Absolute Deviation (MAD)7
Skewness-0.58703089
Sum7330253
Variance98.214173
MonotonicityNot monotonic
2024-01-29T00:37:08.036222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
2007 507
 
13.9%
2015 209
 
5.7%
2000 193
 
5.3%
2014 187
 
5.1%
2009 167
 
4.6%
1992 165
 
4.5%
2010 161
 
4.4%
2011 152
 
4.2%
2017 152
 
4.2%
2008 145
 
4.0%
Other values (30) 1618
44.3%
ValueCountFrequency (%)
1980 21
 
0.6%
1981 2
 
0.1%
1983 11
 
0.3%
1984 15
 
0.4%
1985 23
 
0.6%
1986 28
 
0.8%
1987 143
3.9%
1988 65
1.8%
1989 117
3.2%
1990 65
1.8%
ValueCountFrequency (%)
2022 1
 
< 0.1%
2021 7
 
0.2%
2020 59
 
1.6%
2019 65
 
1.8%
2018 101
2.8%
2017 152
4.2%
2016 77
 
2.1%
2015 209
5.7%
2014 187
5.1%
2013 57
 
1.6%

도로명
Text

Distinct255
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
2024-01-29T00:37:08.284525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length8.8460066
Min length5

Characters and Unicode

Total characters32341
Distinct characters88
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

Unique60 ?
Unique (%)1.6%

Sample

1st row경인로 649
2nd row용천로153번길 59
3rd row간석로56번길 9
4th row간석로56번길 9
5th row석정로 540-6
ValueCountFrequency (%)
호구포로 316
 
4.3%
서창남순환로 309
 
4.2%
구월로 271
 
3.7%
192 237
 
3.2%
55 201
 
2.7%
선수촌로 156
 
2.1%
803 151
 
2.1%
만수서로 134
 
1.8%
논고개로 127
 
1.7%
백범로124번길 121
 
1.7%
Other values (287) 5289
72.3%
2024-01-29T00:37:08.636881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 3656
 
11.3%
3656
 
11.3%
1 2108
 
6.5%
2 1573
 
4.9%
9 1273
 
3.9%
0 1219
 
3.8%
번 1189
 
3.7%
길 1189
 
3.7%
3 1166
 
3.6%
5 1151
 
3.6%
Other values (78) 14161
43.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16497
51.0%
Decimal Number 12031
37.2%
Space Separator 3656
 
11.3%
Dash Punctuation 157
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 3656
22.2%
번 1189
 
7.2%
길 1189
 
7.2%
구 824
 
5.0%
남 713
 
4.3%
서 524
 
3.2%
수 483
 
2.9%
포 461
 
2.8%
월 363
 
2.2%
대 352
 
2.1%
Other values (66) 6743
40.9%
Decimal Number
ValueCountFrequency (%)
1 2108
17.5%
2 1573
13.1%
9 1273
10.6%
0 1219
10.1%
3 1166
9.7%
5 1151
9.6%
4 966
8.0%
8 959
8.0%
6 933
7.8%
7 683
 
5.7%
Space Separator
ValueCountFrequency (%)
3656
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 157
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16497
51.0%
Common 15844
49.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 3656
22.2%
번 1189
 
7.2%
길 1189
 
7.2%
구 824
 
5.0%
남 713
 
4.3%
서 524
 
3.2%
수 483
 
2.9%
포 461
 
2.8%
월 363
 
2.2%
대 352
 
2.1%
Other values (66) 6743
40.9%
Common
ValueCountFrequency (%)
3656
23.1%
1 2108
13.3%
2 1573
9.9%
9 1273
 
8.0%
0 1219
 
7.7%
3 1166
 
7.4%
5 1151
 
7.3%
4 966
 
6.1%
8 959
 
6.1%
6 933
 
5.9%
Other values (2) 840
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16497
51.0%
ASCII 15844
49.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 3656
22.2%
번 1189
 
7.2%
길 1189
 
7.2%
구 824
 
5.0%
남 713
 
4.3%
서 524
 
3.2%
수 483
 
2.9%
포 461
 
2.8%
월 363
 
2.2%
대 352
 
2.1%
Other values (66) 6743
40.9%
ASCII
ValueCountFrequency (%)
3656
23.1%
1 2108
13.3%
2 1573
9.9%
9 1273
 
8.0%
0 1219
 
7.7%
3 1166
 
7.4%
5 1151
 
7.3%
4 966
 
6.1%
8 959
 
6.1%
6 933
 
5.9%
Other values (2) 840
 
5.3%

해제사유발생일
Date

MISSING 

Distinct95
Distinct (%)68.3%
Missing3517
Missing (%)96.2%
Memory size28.7 KiB
Minimum2022-09-22 00:00:00
Maximum2023-09-13 00:00:00
2024-01-29T00:37:08.749223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:08.846280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

거래유형
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
중개거래
3409 
직거래
 
247

Length

Max length4
Median length4
Mean length3.9324398
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중개거래
2nd row직거래
3rd row중개거래
4th row중개거래
5th row중개거래

Common Values

ValueCountFrequency (%)
중개거래 3409
93.2%
직거래 247
 
6.8%

Length

2024-01-29T00:37:08.951170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T00:37:09.026791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중개거래 3409
93.2%
직거래 247
 
6.8%

중개사소재지
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct45
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size28.7 KiB
인천 남동구
3121 
<NA>
 
249
인천 남동구+인천 미추홀구
 
41
인천 남동구+인천 연수구
 
32
인천 미추홀구
 
30
Other values (40)
 
183

Length

Max length15
Median length6
Mean length6.2404267
Min length4

Unique

Unique19 ?
Unique (%)0.5%

Sample

1st row인천 남동구
2nd row<NA>
3rd row인천 남동구
4th row인천 남동구
5th row경기 부천시

Common Values

ValueCountFrequency (%)
인천 남동구 3121
85.4%
<NA> 249
 
6.8%
인천 남동구+인천 미추홀구 41
 
1.1%
인천 남동구+인천 연수구 32
 
0.9%
인천 미추홀구 30
 
0.8%
인천 부평구 27
 
0.7%
인천 남동구+인천 부평구 21
 
0.6%
경기 부천시+인천 남동구 21
 
0.6%
인천 남동구+인천 서구 14
 
0.4%
인천 연수구 13
 
0.4%
Other values (35) 87
 
2.4%

Length

2024-01-29T00:37:09.112245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
인천 3311
45.7%
남동구 3197
44.1%
na 249
 
3.4%
남동구+인천 108
 
1.5%
미추홀구 72
 
1.0%
경기 63
 
0.9%
부평구 48
 
0.7%
연수구 45
 
0.6%
서울 30
 
0.4%
부천시+인천 21
 
0.3%
Other values (37) 105
 
1.4%

Interactions

2024-01-29T00:37:05.370148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:03.900015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.265211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.625392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.002516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.441628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:03.974859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.340096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.699484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.089895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.513175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.051150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.409084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.779984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.162499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.593144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.126487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.479580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.856873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.235350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.659487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.195313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.544628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:04.926862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T00:37:05.305447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T00:37:09.177193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정구역전용면적(제곱미터)계약년월계약일거래금액(만원)층건축년도해제사유발생일거래유형중개사소재지
행정구역1.0000.4790.1190.0230.4380.2320.6440.0000.1010.182
전용면적(제곱미터)0.4791.0000.1550.0000.9130.3500.6290.0000.1640.112
계약년월0.1190.1551.0000.1710.1140.0680.1140.9140.1390.174
계약일0.0230.0000.1711.0000.0000.0280.0000.0000.0000.111
거래금액(만원)0.4380.9130.1140.0001.0000.4910.6840.5790.1710.194
층0.2320.3500.0680.0280.4911.0000.4410.0000.0980.389
건축년도0.6440.6290.1140.0000.6840.4411.0000.6530.0830.230
해제사유발생일0.0000.0000.9140.0000.5790.0000.6531.0000.3000.733
거래유형0.1010.1640.1390.0000.1710.0980.0830.3001.000NaN
중개사소재지0.1820.1120.1740.1110.1940.3890.2300.733NaN1.000
2024-01-29T00:37:09.275537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거래유형중개사소재지행정구역
거래유형1.0001.0000.076
중개사소재지1.0001.0000.069
행정구역0.0760.0691.000
2024-01-29T00:37:09.348040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전용면적(제곱미터)계약일거래금액(만원)층건축년도행정구역거래유형중개사소재지
전용면적(제곱미터)1.0000.0030.8190.2220.2430.2520.1250.038
계약일0.0031.0000.001-0.017-0.0040.0130.0000.049
거래금액(만원)0.8190.0011.0000.3630.5090.2260.1310.067
층0.222-0.0170.3631.0000.3210.1130.0720.143
건축년도0.243-0.0040.5090.3211.0000.3780.0640.080
행정구역0.2520.0130.2260.1130.3781.0000.0760.069
거래유형0.1250.0000.1310.0720.0640.0761.0001.000
중개사소재지0.0380.0490.0670.1430.0800.0691.0001.000

Missing values

2024-01-29T00:37:05.747609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T00:37:05.872354image/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

행정구역단지명전용면적(제곱미터)계약년월계약일거래금액(만원)층건축년도도로명해제사유발생일거래유형중개사소재지
0인천광역시 남동구 간석동TK리즈빌42.22022-09-012515000122016경인로 649<NA>중개거래인천 남동구
1인천광역시 남동구 간석동The레지던스아파트58.8962022-09-013029800122017용천로153번길 59<NA>직거래<NA>
2인천광역시 남동구 간석동가영83.542022-09-01262100042002간석로56번길 9<NA>중개거래인천 남동구
3인천광역시 남동구 간석동가영83.542022-11-0112100032002간석로56번길 9<NA>중개거래인천 남동구
4인천광역시 남동구 간석동간석동행복누리움84.922023-05-013022000112006석정로 540-6<NA>중개거래경기 부천시
5인천광역시 남동구 간석동간석래미안자이84.982022-09-01175500072008남동대로 860<NA>중개거래인천 남동구
6인천광역시 남동구 간석동간석래미안자이143.222022-09-012765000102008남동대로 860<NA>중개거래인천 남동구
7인천광역시 남동구 간석동간석래미안자이119.522022-10-0126250082008남동대로 860<NA>중개거래인천 남동구
8인천광역시 남동구 간석동간석래미안자이84.982022-12-013056000222008남동대로 860<NA>중개거래인천 남동구
9인천광역시 남동구 간석동간석래미안자이143.222023-01-011058000212008남동대로 860<NA>중개거래인천 남동구
행정구역단지명전용면적(제곱미터)계약년월계약일거래금액(만원)층건축년도도로명해제사유발생일거래유형중개사소재지
3646인천광역시 남동구 서창동호반베르디움84.74032023-08-011754000202017서창남순환로 200<NA>중개거래인천 남동구
3647인천광역시 남동구 서창동호반베르디움84.74032023-08-011855800102017서창남순환로 200<NA>중개거래인천 남동구
3648인천광역시 남동구 서창동호반베르디움84.74032023-08-01194900022017서창남순환로 200<NA>중개거래인천 남동구
3649인천광역시 남동구 서창동호반베르디움84.74032023-08-012155000152017서창남순환로 200<NA>중개거래인천 남동구
3650인천광역시 남동구 서창동호반베르디움84.74032023-08-012455000242017서창남순환로 200<NA>중개거래인천 남동구
3651인천광역시 남동구 서창동호반베르디움84.74032023-08-012653300152017서창남순환로 200<NA>중개거래인천 남동구
3652인천광역시 남동구 서창동호반베르디움84.74032023-08-012655000182017서창남순환로 200<NA>중개거래인천 남동구
3653인천광역시 남동구 서창동호반베르디움84.74032023-08-01265220042017서창남순환로 2002023-09-12중개거래인천 남동구
3654인천광역시 남동구 서창동호반베르디움84.74032023-08-012652200142017서창남순환로 200<NA>중개거래인천 남동구
3655인천광역시 남동구 장수동장자마을한별렉스힐165.762023-03-01247000022007장자북로 47<NA>중개거래인천 남동구

Duplicate rows

Most frequently occurring

행정구역단지명전용면적(제곱미터)계약년월계약일거래금액(만원)층건축년도도로명해제사유발생일거래유형중개사소재지# duplicates
5인천광역시 남동구 논현동에코메트로1184.9972023-02-011039000132009논고개로 17<NA>중개거래인천 남동구3
0인천광역시 남동구 구월동구월힐스테이트1단지83.77692023-05-011946500252007구월로 1922023-06-23중개거래경기 부천시+인천 남동구2
1인천광역시 남동구 구월동아트뷰14.4482022-11-0130765052012예술로192번길 32<NA>직거래<NA>2
2인천광역시 남동구 구월동중앙헤리티지12.262022-10-0131500052012예술로204번길 39<NA>중개거래인천 남동구2
3인천광역시 남동구 논현동논현센트럴뷰59.582023-04-01439000122014논고개로68번길 34<NA>중개거래인천 남동구2
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