gimi9 Pandas Profiling

Dataset statistics

Number of variables	19
Number of observations	2145
Missing cells	1106
Missing cells (%)	2.7%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	333.2 KiB
Average record size in memory	159.1 B

Variable types

Categorical	9
Text	3
Numeric	6
DateTime	1

Dataset

Description	한국토지주택공사에서 위탁관리중인 마이홈포털의 기존 장기전세 주택 정보로, 광역시도,단지명,세대수,주택유형,임대사업자,공급면적등의 정보를 제공합니다.
Author	한국토지주택공사
URL	https://www.data.go.kr/data/15084929/fileData.do

Alerts

`임대종류` has constant value ""	Constant
`전환보증금` has constant value ""	Constant
`시군구` is highly overall correlated with `광역시도` and 4 other fields	High correlation
`주택유형` is highly overall correlated with `주차수` and 8 other fields	High correlation
`임대사업자` is highly overall correlated with `광역시도` and 2 other fields	High correlation
`광역시도` is highly overall correlated with `공급면적(공용)` and 5 other fields	High correlation
`승강기설치여부` is highly overall correlated with `공급면적(공용)` and 3 other fields	High correlation
`세대수` is highly overall correlated with `주차수` and 4 other fields	High correlation
`주차수` is highly overall correlated with `세대수` and 5 other fields	High correlation
`공급면적(전용)` is highly overall correlated with `세대수` and 4 other fields	High correlation
`공급면적(공용)` is highly overall correlated with `세대수` and 7 other fields	High correlation
`임대보증금` is highly overall correlated with `세대수` and 6 other fields	High correlation
`월임대료` is highly overall correlated with `세대수` and 8 other fields	High correlation
`건물형태` is highly overall correlated with `월임대료`	High correlation
`난방방식` is highly overall correlated with `월임대료` and 1 other fields	High correlation
`임대사업자` is highly imbalanced (58.2%)	Imbalance
`준공일자` has 1092 (50.9%) missing values	Missing
`주차수` has 1059 (49.4%) zeros	Zeros
`임대보증금` has 32 (1.5%) zeros	Zeros
`월임대료` has 1133 (52.8%) zeros	Zeros

Reproduction

Analysis started	2024-03-14 17:11:01.918494
Analysis finished	2024-03-14 17:11:14.214786
Duration	12.3 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

임대종류
Categorical

CONSTANT

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

장기전세	2145

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	장기전세
2nd row	장기전세
3rd row	장기전세
4th row	장기전세
5th row	장기전세

Common Values

Value	Count	Frequency (%)
장기전세	2145	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
장기전세	2145	100.0%

광역시도
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

서울특별시	1081
대구광역시	1048
경기도	14
인천광역시	2

Length

Max length	5
Median length	5
Mean length	4.9869464
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	서울특별시
2nd row	서울특별시
3rd row	서울특별시
4th row	서울특별시
5th row	서울특별시

Common Values

Value	Count	Frequency (%)
서울특별시	1081	50.4%
대구광역시	1048	48.9%
경기도	14	0.7%
인천광역시	2	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
서울특별시	1081	50.4%
대구광역시	1048	48.9%
경기도	14	0.7%
인천광역시	2	0.1%

시군구
Categorical

HIGH CORRELATION

Distinct	32
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

남구	286
달서구	264
은평구	176
강동구	155
동구	133
Other values (27)	1131

Length

Max length	7
Median length	3
Mean length	2.6960373
Min length	2

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	성동구
2nd row	성동구
3rd row	성동구
4th row	성동구
5th row	성동구

Common Values

Value	Count	Frequency (%)
남구	286	13.3%
달서구	264	12.3%
은평구	176	8.2%
강동구	155	7.2%
동구	133	6.2%
북구	129	6.0%
서초구	128	6.0%
강서구	117	5.5%
서구	115	5.4%
수성구	94	4.4%
Other values (22)	548	25.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
남구	286	13.3%
달서구	264	12.3%
은평구	176	8.2%
강동구	155	7.2%
동구	133	6.2%
북구	129	6.0%
서초구	128	6.0%
강서구	117	5.4%
서구	115	5.4%
수성구	94	4.4%
Other values (23)	550	25.6%

도로명주소
Text

Distinct	379
Distinct (%)	17.7%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

Length

Max length	24
Median length	22
Mean length	18.909557
Min length	15

Characters and Unicode

Total characters	40561
Distinct characters	191
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	38 ?
Unique (%)	1.8%

Sample

1st row	서울특별시 성동구 동일로 237
2nd row	서울특별시 성동구 동일로 237
3rd row	서울특별시 성동구 동일로 237
4th row	서울특별시 성동구 동일로 237
5th row	서울특별시 성동구 자동차시장1길 14

Value	Count	Frequency (%)
서울특별시	1081	12.6%
대구광역시	1048	12.2%
남구	286	3.3%
달서구	264	3.1%
은평구	176	2.1%
강동구	155	1.8%
동구	133	1.5%
북구	129	1.5%
서초구	128	1.5%
강서구	117	1.4%
Other values (524)	5065	59.0%

Most occurring characters

Value	Count	Frequency (%)
	6437	15.9%
구	3331	8.2%
시	2164	5.3%
로	2087	5.1%
서	1846	4.6%
1	1779	4.4%
길	1391	3.4%
대	1242	3.1%
역	1096	2.7%
울	1087	2.7%
Other values (181)	18101	44.6%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	25620	63.2%
Decimal Number	7987	19.7%
Space Separator	6437	15.9%
Dash Punctuation	517	1.3%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
구	3331	13.0%
시	2164	8.4%
로	2087	8.1%
서	1846	7.2%
길	1391	5.4%
대	1242	4.8%
역	1096	4.3%
울	1087	4.2%
특	1081	4.2%
별	1081	4.2%
Other values (169)	9214	36.0%

Decimal Number

Value	Count	Frequency (%)
1	1779	22.3%
2	1053	13.2%
5	763	9.6%
3	758	9.5%
4	744	9.3%
7	729	9.1%
0	653	8.2%
6	554	6.9%
8	522	6.5%
9	432	5.4%

Space Separator

Value	Count	Frequency (%)
	6437	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	517	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	25620	63.2%
Common	14941	36.8%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
구	3331	13.0%
시	2164	8.4%
로	2087	8.1%
서	1846	7.2%
길	1391	5.4%
대	1242	4.8%
역	1096	4.3%
울	1087	4.2%
특	1081	4.2%
별	1081	4.2%
Other values (169)	9214	36.0%

Common

Value	Count	Frequency (%)
	6437	43.1%
1	1779	11.9%
2	1053	7.0%
5	763	5.1%
3	758	5.1%
4	744	5.0%
7	729	4.9%
0	653	4.4%
6	554	3.7%
8	522	3.5%
Other values (2)	949	6.4%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	25620	63.2%
ASCII	14941	36.8%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	6437	43.1%
1	1779	11.9%
2	1053	7.0%
5	763	5.1%
3	758	5.1%
4	744	5.0%
7	729	4.9%
0	653	4.4%
6	554	3.7%
8	522	3.5%
Other values (2)	949	6.4%

Hangul

Value	Count	Frequency (%)
구	3331	13.0%
시	2164	8.4%
로	2087	8.1%
서	1846	7.2%
길	1391	5.4%
대	1242	4.8%
역	1096	4.3%
울	1087	4.2%
특	1081	4.2%
별	1081	4.2%
Other values (169)	9214	36.0%

단지명
Text

Distinct	406
Distinct (%)	18.9%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

Length

Max length	21
Median length	17
Mean length	8.5407925
Min length	2

Characters and Unicode

Total characters	18320
Distinct characters	306
Distinct categories	9 ?
Distinct scripts	3 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	52 ?
Unique (%)	2.4%

Sample

1st row	서울숲아이파크(임대)
2nd row	서울숲아이파크(임대)
3rd row	서울숲아이파크(임대)
4th row	서울숲아이파크(임대)
5th row	와이엠프라젠

Value	Count	Frequency (%)
마곡지구	85	3.6%
상암월드컵파크	29	1.2%
신내3지구	24	1.0%
천왕2지구2단지(서울리츠3호	20	0.8%
2단지(임대	20	0.8%
세곡2지구3단지(레미안포레	20	0.8%
고덕리엔파크3단지	20	0.8%
고덕리엔파크1단지	19	0.8%
서초더샵포레	19	0.8%
10단지(임대	18	0.8%
Other values (414)	2081	88.4%

Most occurring characters

Value	Count	Frequency (%)
지	1174	6.4%
단	795	4.3%
)	698	3.8%
(	698	3.8%
대	563	3.1%
1	483	2.6%
임	466	2.5%
스	449	2.5%
빌	448	2.4%
2	403	2.2%
Other values (296)	12143	66.3%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	14476	79.0%
Decimal Number	1793	9.8%
Close Punctuation	698	3.8%
Open Punctuation	698	3.8%
Dash Punctuation	340	1.9%
Space Separator	210	1.1%
Uppercase Letter	80	0.4%
Connector Punctuation	19	0.1%
Lowercase Letter	6	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
지	1174	8.1%
단	795	5.5%
대	563	3.9%
임	466	3.2%
스	449	3.1%
빌	448	3.1%
이	354	2.4%
구	344	2.4%
파	320	2.2%
리	304	2.1%
Other values (268)	9259	64.0%

Uppercase Letter

Value	Count	Frequency (%)
B	16	20.0%
S	12	15.0%
K	12	15.0%
A	10	12.5%
C	10	12.5%
M	4	5.0%
D	4	5.0%
L	4	5.0%
W	2	2.5%
E	2	2.5%
Other values (2)	4	5.0%

Decimal Number

Value	Count	Frequency (%)
1	483	26.9%
2	403	22.5%
3	341	19.0%
4	140	7.8%
5	87	4.9%
7	79	4.4%
6	79	4.4%
0	72	4.0%
8	62	3.5%
9	47	2.6%

Close Punctuation

Value	Count	Frequency (%)
)	698	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	698	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	340	100.0%

Space Separator

Value	Count	Frequency (%)
	210	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	19	100.0%

Lowercase Letter

Value	Count	Frequency (%)
e	6	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	14476	79.0%
Common	3758	20.5%
Latin	86	0.5%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
지	1174	8.1%
단	795	5.5%
대	563	3.9%
임	466	3.2%
스	449	3.1%
빌	448	3.1%
이	354	2.4%
구	344	2.4%
파	320	2.2%
리	304	2.1%
Other values (268)	9259	64.0%

Common

Value	Count	Frequency (%)
)	698	18.6%
(	698	18.6%
1	483	12.9%
2	403	10.7%
3	341	9.1%
-	340	9.0%
	210	5.6%
4	140	3.7%
5	87	2.3%
7	79	2.1%
Other values (5)	279	7.4%

Latin

Value	Count	Frequency (%)
B	16	18.6%
S	12	14.0%
K	12	14.0%
A	10	11.6%
C	10	11.6%
e	6	7.0%
M	4	4.7%
D	4	4.7%
L	4	4.7%
W	2	2.3%
Other values (3)	6	7.0%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	14476	79.0%
ASCII	3844	21.0%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
지	1174	8.1%
단	795	5.5%
대	563	3.9%
임	466	3.2%
스	449	3.1%
빌	448	3.1%
이	354	2.4%
구	344	2.4%
파	320	2.2%
리	304	2.1%
Other values (268)	9259	64.0%

ASCII

Value	Count	Frequency (%)
)	698	18.2%
(	698	18.2%
1	483	12.6%
2	403	10.5%
3	341	8.9%
-	340	8.8%
	210	5.5%
4	140	3.6%
5	87	2.3%
7	79	2.1%
Other values (18)	365	9.5%

세대수
Real number (ℝ)

HIGH CORRELATION

Distinct	160
Distinct (%)	7.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	115.27133

Minimum	2
Maximum	998
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	19.0 KiB

Quantile statistics

Minimum	2
5-th percentile	7
Q1	11
median	17
Q3	162
95-th percentile	572
Maximum	998
Range	996
Interquartile range (IQR)	151

Descriptive statistics

Standard deviation	180.51659
Coefficient of variation (CV)	1.5660147
Kurtosis	6.01508
Mean	115.27133
Median Absolute Deviation (MAD)	10
Skewness	2.4013333
Sum	247257
Variance	32586.241
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8	186	8.7%
11	160	7.5%
10	147	6.9%
13	144	6.7%
12	90	4.2%
9	69	3.2%
7	59	2.8%
14	54	2.5%
16	44	2.1%
15	43	2.0%
Other values (150)	1149	53.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	2	0.1%
3	2	0.1%
5	17	0.8%
6	35	1.6%
7	59	2.8%
8	186	8.7%
9	69	3.2%
10	147	6.9%
11	160	7.5%
12	90	4.2%

Value	Count	Frequency (%)
998	9	0.4%
832	20	0.9%
831	12	0.6%
698	10	0.5%
662	20	0.9%
652	8	0.4%
628	8	0.4%
593	15	0.7%
588	4	0.2%
572	9	0.4%

주택유형
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

아파트	1095
다가구주택	1048
연립주택	2

Length

Max length	5
Median length	3
Mean length	3.9780886
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	아파트
2nd row	아파트
3rd row	아파트
4th row	아파트
5th row	아파트

Common Values

Value	Count	Frequency (%)
아파트	1095	51.0%
다가구주택	1048	48.9%
연립주택	2	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
아파트	1095	51.0%
다가구주택	1048	48.9%
연립주택	2	0.1%

임대사업자
Categorical

HIGH CORRELATION IMBALANCE

Distinct	6
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

SH공사	1078
대구도시공사	1048
LH서울	9
LH경기남부	6
인천도시공사	2

Length

Max length	6
Median length	4
Mean length	4.9864802
Min length	4

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	SH공사
2nd row	SH공사
3rd row	SH공사
4th row	SH공사
5th row	SH공사

Common Values

Value	Count	Frequency (%)
SH공사	1078	50.3%
대구도시공사	1048	48.9%
LH서울	9	0.4%
LH경기남부	6	0.3%
인천도시공사	2	0.1%
LH경기북부	2	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
sh공사	1078	50.3%
대구도시공사	1048	48.9%
lh서울	9	0.4%
lh경기남부	6	0.3%
인천도시공사	2	0.1%
lh경기북부	2	0.1%

준공일자
Date

MISSING

Distinct	159
Distinct (%)	15.1%
Missing	1092
Missing (%)	50.9%
Memory size	16.9 KiB

Minimum	1993-10-18 00:00:00
Maximum	2022-02-15 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

건물형태
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

<NA>	1052
혼합식	529
계단식	415
복도식	149

Length

Max length	4
Median length	3
Mean length	3.4904429
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	계단식
2nd row	계단식
3rd row	계단식
4th row	계단식
5th row	계단식

Common Values

Value	Count	Frequency (%)
<NA>	1052	49.0%
혼합식	529	24.7%
계단식	415	19.3%
복도식	149	6.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
na	1052	49.0%
혼합식	529	24.7%
계단식	415	19.3%
복도식	149	6.9%

난방방식
Categorical

HIGH CORRELATION

Distinct	6
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

<NA>	1048
지역가스난방	272
개별난방	251
개별가스난방	209
지역난방	200

Length

Max length	6
Median length	4
Mean length	4.602331
Min length	4

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	개별가스난방
2nd row	개별가스난방
3rd row	개별가스난방
4th row	개별가스난방
5th row	개별가스난방

Common Values

Value	Count	Frequency (%)
<NA>	1048	48.9%
지역가스난방	272	12.7%
개별난방	251	11.7%
개별가스난방	209	9.7%
지역난방	200	9.3%
지역폐열난방	165	7.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
na	1048	48.9%
지역가스난방	272	12.7%
개별난방	251	11.7%
개별가스난방	209	9.7%
지역난방	200	9.3%
지역폐열난방	165	7.7%

승강기설치여부
Categorical

HIGH CORRELATION

Distinct	4
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

전체동 설치	1064
<NA>	1052
일부동 설치	27
미설치	2

Length

Max length	6
Median length	6
Mean length	5.016317
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	전체동 설치
2nd row	전체동 설치
3rd row	전체동 설치
4th row	전체동 설치
5th row	전체동 설치

Common Values

Value	Count	Frequency (%)
전체동 설치	1064	49.6%
<NA>	1052	49.0%
일부동 설치	27	1.3%
미설치	2	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
설치	1091	33.7%
전체동	1064	32.9%
na	1052	32.5%
일부동	27	0.8%
미설치	2	0.1%

주차수
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	189
Distinct (%)	8.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	433.08718

Minimum	0
Maximum	3972
Zeros	1059
Zeros (%)	49.4%
Negative	0
Negative (%)	0.0%
Memory size	19.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	74
Q3	664
95-th percentile	1571
Maximum	3972
Range	3972
Interquartile range (IQR)	664

Descriptive statistics

Standard deviation	607.74428
Coefficient of variation (CV)	1.4032839
Kurtosis	3.6418793
Mean	433.08718
Median Absolute Deviation (MAD)	74
Skewness	1.7881443
Sum	928972
Variance	369353.11
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1059	49.4%
1364	33	1.5%
2616	27	1.3%
1311	25	1.2%
693	22	1.0%
874	20	0.9%
1767	19	0.9%
656	16	0.7%
1449	16	0.7%
2265	16	0.7%
Other values (179)	892	41.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1059	49.4%
2	1	< 0.1%
6	1	< 0.1%
15	2	0.1%
16	1	< 0.1%
23	1	< 0.1%
24	1	< 0.1%
52	3	0.1%
55	1	< 0.1%
72	1	< 0.1%

Value	Count	Frequency (%)
3972	3	0.1%
3088	2	0.1%
2616	27	1.3%
2334	9	0.4%
2265	16	0.7%
2235	5	0.2%
2189	12	0.6%
2011	1	< 0.1%
1834	8	0.4%
1767	19	0.9%

형명
Text

Distinct	277
Distinct (%)	13.0%
Missing	14
Missing (%)	0.7%
Memory size	16.9 KiB

Length

Max length	8
Median length	6
Mean length	2.2792116
Min length	1

Characters and Unicode

Total characters	4857
Distinct characters	43
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	161 ?
Unique (%)	7.6%

Sample

1st row	55
2nd row	64
3rd row	75
4th row	84
5th row	45

Value	Count	Frequency (%)
1	726	34.1%
2	169	7.9%
3	139	6.5%
59a	115	5.4%
59b	65	3.1%
84a	65	3.1%
84b	50	2.3%
59a1	39	1.8%
59c	39	1.8%
84c	33	1.5%
Other values (253)	691	32.4%

Most occurring characters

Value	Count	Frequency (%)
1	1107	22.8%
5	546	11.2%
9	537	11.1%
4	514	10.6%
8	417	8.6%
A	386	7.9%
2	237	4.9%
B	232	4.8%
3	162	3.3%
C	142	2.9%
Other values (33)	577	11.9%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3598	74.1%
Uppercase Letter	1146	23.6%
Dash Punctuation	65	1.3%
Lowercase Letter	40	0.8%
Other Punctuation	3	0.1%
Math Symbol	3	0.1%
Other Symbol	2	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	386	33.7%
B	232	20.2%
C	142	12.4%
S	79	6.9%
D	79	6.9%
E	43	3.8%
P	43	3.8%
F	39	3.4%
N	31	2.7%
T	15	1.3%
Other values (12)	57	5.0%

Decimal Number

Value	Count	Frequency (%)
1	1107	30.8%
5	546	15.2%
9	537	14.9%
4	514	14.3%
8	417	11.6%
2	237	6.6%
3	162	4.5%
7	35	1.0%
0	31	0.9%
6	12	0.3%

Lowercase Letter

Value	Count	Frequency (%)
a	12	30.0%
b	8	20.0%
c	7	17.5%
d	6	15.0%
e	4	10.0%
f	2	5.0%
n	1	2.5%

Dash Punctuation

Value	Count	Frequency (%)
-	65	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	3	100.0%

Math Symbol

Value	Count	Frequency (%)
+	3	100.0%

Other Symbol

Value	Count	Frequency (%)
㎡	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	3671	75.6%
Latin	1186	24.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	386	32.5%
B	232	19.6%
C	142	12.0%
S	79	6.7%
D	79	6.7%
E	43	3.6%
P	43	3.6%
F	39	3.3%
N	31	2.6%
T	15	1.3%
Other values (19)	97	8.2%

Common

Value	Count	Frequency (%)
1	1107	30.2%
5	546	14.9%
9	537	14.6%
4	514	14.0%
8	417	11.4%
2	237	6.5%
3	162	4.4%
-	65	1.8%
7	35	1.0%
0	31	0.8%
Other values (4)	20	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4855	> 99.9%
CJK Compat	2	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1107	22.8%
5	546	11.2%
9	537	11.1%
4	514	10.6%
8	417	8.6%
A	386	8.0%
2	237	4.9%
B	232	4.8%
3	162	3.3%
C	142	2.9%
Other values (32)	575	11.8%

CJK Compat

Value	Count	Frequency (%)
㎡	2	100.0%

공급면적(전용)
Real number (ℝ)

HIGH CORRELATION

Distinct	1104
Distinct (%)	51.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	58.96353

Minimum	15.36
Maximum	129.34
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	19.0 KiB

Quantile statistics

Minimum	15.36
5-th percentile	23.262
Q1	40.65
median	59.8
Q3	84.36
95-th percentile	89.718
Maximum	129.34
Range	113.98
Interquartile range (IQR)	43.71

Descriptive statistics

Standard deviation	23.378629
Coefficient of variation (CV)	0.39649303
Kurtosis	-0.55045248
Mean	58.96353
Median Absolute Deviation (MAD)	21.28
Skewness	0.24297571
Sum	126476.77
Variance	546.56029
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
59.95	37	1.7%
59.98	36	1.7%
59.99	35	1.6%
59.97	34	1.6%
84.97	32	1.5%
59.94	31	1.4%
84.96	27	1.3%
84.98	27	1.3%
59.87	27	1.3%
84.95	24	1.1%
Other values (1094)	1835	85.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
15.36	1	< 0.1%
16.21	1	< 0.1%
17.16	1	< 0.1%
17.28	1	< 0.1%
17.48	1	< 0.1%
17.84	1	< 0.1%
18.0	1	< 0.1%
18.25	1	< 0.1%
18.5	1	< 0.1%
18.62	2	0.1%

Value	Count	Frequency (%)
129.34	1	< 0.1%
125.46	1	< 0.1%
124.459	1	< 0.1%
118.35	1	< 0.1%
117.49	1	< 0.1%
115.99	1	< 0.1%
114.99	1	< 0.1%
114.98	9	0.4%
114.97	3	0.1%
114.95	2	0.1%

공급면적(공용)
Real number (ℝ)

HIGH CORRELATION

Distinct	1542
Distinct (%)	71.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	17.051468

Minimum	1
Maximum	58.872
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	19.0 KiB

Quantile statistics

Minimum	1
5-th percentile	3.5
Q1	5.84
median	18.4
Q3	26.04
95-th percentile	34.362
Maximum	58.872
Range	57.872
Interquartile range (IQR)	20.2

Descriptive statistics

Standard deviation	11.231358
Coefficient of variation (CV)	0.65867395
Kurtosis	-0.72081303
Mean	17.051468
Median Absolute Deviation (MAD)	10.64
Skewness	0.39781619
Sum	36575.398
Variance	126.14339
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
31.55	13	0.6%
31.94	7	0.3%
4.96	7	0.3%
5.2	7	0.3%
21.18	6	0.3%
5.41	6	0.3%
3.59	5	0.2%
32.45	5	0.2%
26.17	5	0.2%
5.4	5	0.2%
Other values (1532)	2079	96.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.0	1	< 0.1%
2.18	1	< 0.1%
2.24	1	< 0.1%
2.25	1	< 0.1%
2.2541	1	< 0.1%
2.2605	1	< 0.1%
2.2719	1	< 0.1%
2.3089	1	< 0.1%
2.31	1	< 0.1%
2.34	1	< 0.1%

Value	Count	Frequency (%)
58.872	1	< 0.1%
56.803	1	< 0.1%
56.15	1	< 0.1%
55.932	1	< 0.1%
55.138	1	< 0.1%
55.0	1	< 0.1%
54.834	2	0.1%
53.463	1	< 0.1%
50.53	1	< 0.1%
50.18	1	< 0.1%

임대보증금
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	900
Distinct (%)	42.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.6271988 × 10⁸

Minimum	0
Maximum	1.001 × 10⁹
Zeros	32
Zeros (%)	1.5%
Negative	0
Negative (%)	0.0%
Memory size	19.0 KiB

Quantile statistics

Minimum	0
5-th percentile	1896000
Q1	3460000
median	1.0176 × 10⁸
Q3	3.185 × 10⁸
95-th percentile	5.075 × 10⁸
Maximum	1.001 × 10⁹
Range	1.001 × 10⁹
Interquartile range (IQR)	3.1504 × 10⁸

Descriptive statistics

Standard deviation	1.9617717 × 10⁸
Coefficient of variation (CV)	1.2056128
Kurtosis	0.62963946
Mean	1.6271988 × 10⁸
Median Absolute Deviation (MAD)	99029000
Skewness	1.1095071
Sum	3.4903415 × 10¹¹
Variance	3.8485482 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
381500000	36	1.7%
0	32	1.5%
393750000	28	1.3%
2121000	23	1.1%
409500000	22	1.0%
102880000	22	1.0%
367500000	22	1.0%
356250000	20	0.9%
158130000	19	0.9%
3182000	19	0.9%
Other values (890)	1902	88.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	32	1.5%
1244000	1	< 0.1%
1313000	1	< 0.1%
1399000	1	< 0.1%
1478000	1	< 0.1%
1485000	1	< 0.1%
1498000	1	< 0.1%
1500000	3	0.1%
1531000	1	< 0.1%
1532000	1	< 0.1%

Value	Count	Frequency (%)
1001000000	2	0.1%
980000000	2	0.1%
945000000	3	0.1%
861250000	1	< 0.1%
837850000	2	0.1%
805000000	3	0.1%
781200000	1	< 0.1%
772500000	2	0.1%
752500000	5	0.2%
750000000	1	< 0.1%

월임대료
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	862
Distinct (%)	40.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	53496.093

Minimum	0
Maximum	422000
Zeros	1133
Zeros (%)	52.8%
Negative	0
Negative (%)	0.0%
Memory size	19.0 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	101550
95-th percentile	170496
Maximum	422000
Range	422000
Interquartile range (IQR)	101550

Descriptive statistics

Standard deviation	67124.979
Coefficient of variation (CV)	1.2547641
Kurtosis	1.6616168
Mean	53496.093
Median Absolute Deviation (MAD)	0
Skewness	1.2348291
Sum	1.1474912 × 10⁸
Variance	4.5057629 × 10⁹
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1133	52.8%
78000	5	0.2%
70000	4	0.2%
74000	4	0.2%
89000	4	0.2%
62000	4	0.2%
62030	4	0.2%
120000	4	0.2%
79000	3	0.1%
72000	3	0.1%
Other values (852)	977	45.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1133	52.8%
25960	1	< 0.1%
38520	1	< 0.1%
41510	1	< 0.1%
41780	1	< 0.1%
42230	1	< 0.1%
43150	1	< 0.1%
44390	1	< 0.1%
44450	1	< 0.1%
45210	1	< 0.1%

Value	Count	Frequency (%)
422000	1	< 0.1%
387000	1	< 0.1%
374400	1	< 0.1%
366110	1	< 0.1%
357000	1	< 0.1%
336400	1	< 0.1%
330000	1	< 0.1%
327370	1	< 0.1%
320000	1	< 0.1%
308230	1	< 0.1%

전환보증금
Categorical

CONSTANT

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	16.9 KiB

0	2145

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	2145	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	2145	100.0%

Heatmap
Table

	광역시도	시군구	세대수	주택유형	임대사업자	건물형태	난방방식	승강기설치여부	주차수	공급면적(전용)	공급면적(공용)	임대보증금	월임대료
광역시도	1.000	1.000	0.588	0.676	0.987	0.326	0.128	0.000	0.633	0.634	0.740	0.757	0.745
시군구	1.000	1.000	0.763	1.000	0.981	0.669	0.938	0.903	0.810	0.662	0.719	0.795	0.682
세대수	0.588	0.763	1.000	0.767	0.620	0.536	0.470	0.368	0.864	0.403	0.488	0.519	0.443
주택유형	0.676	1.000	0.767	1.000	0.941	0.021	0.041	1.000	0.849	0.681	0.788	0.802	0.792
임대사업자	0.987	0.981	0.620	0.941	1.000	0.229	0.266	0.000	0.610	0.561	0.659	0.678	0.663
건물형태	0.326	0.669	0.536	0.021	0.229	1.000	0.367	0.300	0.498	0.307	0.378	0.302	NaN
난방방식	0.128	0.938	0.470	0.041	0.266	0.367	1.000	0.210	0.449	0.471	0.341	0.545	NaN
승강기설치여부	0.000	0.903	0.368	1.000	0.000	0.300	0.210	1.000	0.752	0.353	0.857	0.430	NaN
주차수	0.633	0.810	0.864	0.849	0.610	0.498	0.449	0.752	1.000	0.500	0.543	0.648	0.517
공급면적(전용)	0.634	0.662	0.403	0.681	0.561	0.307	0.471	0.353	0.500	1.000	0.801	0.735	0.830
공급면적(공용)	0.740	0.719	0.488	0.788	0.659	0.378	0.341	0.857	0.543	0.801	1.000	0.775	0.789
임대보증금	0.757	0.795	0.519	0.802	0.678	0.302	0.545	0.430	0.648	0.735	0.775	1.000	0.737
월임대료	0.745	0.682	0.443	0.792	0.663	NaN	NaN	NaN	0.517	0.830	0.789	0.737	1.000

Heatmap
Table

	시군구	난방방식	주택유형	건물형태	임대사업자	광역시도	승강기설치여부
시군구	1.000	0.698	0.993	0.446	0.892	0.993	0.756
난방방식	0.698	1.000	0.050	0.298	0.102	0.097	0.161
주택유형	0.993	0.050	1.000	0.034	0.706	0.706	1.000
건물형태	0.446	0.298	0.034	1.000	0.176	0.112	0.101
임대사업자	0.892	0.102	0.706	0.176	1.000	0.925	0.000
광역시도	0.993	0.097	0.706	0.112	0.925	1.000	0.000
승강기설치여부	0.756	0.161	1.000	0.101	0.000	0.000	1.000

Heatmap
Table

	세대수	주차수	공급면적(전용)	공급면적(공용)	임대보증금	월임대료	광역시도	시군구	주택유형	임대사업자	건물형태	난방방식	승강기설치여부
세대수	1.000	0.828	0.504	0.664	0.680	-0.743	0.419	0.405	0.471	0.365	0.278	0.294	0.174
주차수	0.828	1.000	0.618	0.782	0.802	-0.827	0.463	0.462	0.564	0.357	0.253	0.278	0.456
공급면적(전용)	0.504	0.618	1.000	0.816	0.824	-0.418	0.435	0.300	0.533	0.337	0.192	0.214	0.226
공급면적(공용)	0.664	0.782	0.816	1.000	0.880	-0.685	0.547	0.347	0.672	0.422	0.179	0.204	0.574
임대보증금	0.680	0.802	0.824	0.880	1.000	-0.664	0.567	0.426	0.693	0.441	0.189	0.256	0.286
월임대료	-0.743	-0.827	-0.418	-0.685	-0.664	1.000	0.553	0.315	0.678	0.426	1.000	1.000	1.000
광역시도	0.419	0.463	0.435	0.547	0.567	0.553	1.000	0.993	0.706	0.925	0.112	0.097	0.000
시군구	0.405	0.462	0.300	0.347	0.426	0.315	0.993	1.000	0.993	0.892	0.446	0.698	0.756
주택유형	0.471	0.564	0.533	0.672	0.693	0.678	0.706	0.993	1.000	0.706	0.034	0.050	1.000
임대사업자	0.365	0.357	0.337	0.422	0.441	0.426	0.925	0.892	0.706	1.000	0.176	0.102	0.000
건물형태	0.278	0.253	0.192	0.179	0.189	1.000	0.112	0.446	0.034	0.176	1.000	0.298	0.101
난방방식	0.294	0.278	0.214	0.204	0.256	1.000	0.097	0.698	0.050	0.102	0.298	1.000	0.161
승강기설치여부	0.174	0.456	0.226	0.574	0.286	1.000	0.000	0.756	1.000	0.000	0.101	0.161	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	임대종류	광역시도	시군구	도로명주소	단지명	세대수	주택유형	임대사업자	준공일자	건물형태	난방방식	승강기설치여부	주차수	형명	공급면적(전용)	공급면적(공용)	임대보증금
0	장기전세	서울특별시	성동구	서울특별시 성동구 동일로 237	서울숲아이파크(임대)	34	아파트	SH공사	2008-12-22	계단식	개별가스난방	전체동 설치	286	55	55.88	18.05	95760000
1	장기전세	서울특별시	성동구	서울특별시 성동구 동일로 237	서울숲아이파크(임대)	34	아파트	SH공사	2008-12-22	계단식	개별가스난방	전체동 설치	286	64	64.21	20.19	303750000
2	장기전세	서울특별시	성동구	서울특별시 성동구 동일로 237	서울숲아이파크(임대)	34	아파트	SH공사	2008-12-22	계단식	개별가스난방	전체동 설치	286	75	75.51	25.35	119960000
3	장기전세	서울특별시	성동구	서울특별시 성동구 동일로 237	서울숲아이파크(임대)	34	아파트	SH공사	2008-12-22	계단식	개별가스난방	전체동 설치	286	84	84.87	27.57	402500000
4	장기전세	서울특별시	성동구	서울특별시 성동구 자동차시장1길 14	와이엠프라젠	5	아파트	SH공사	2007-10-15	계단식	개별가스난방	전체동 설치	86	45	45.33	15.124	63820000
5	장기전세	서울특별시	성동구	서울특별시 성동구 자동차시장1길 14	와이엠프라젠	5	아파트	SH공사	2007-10-15	계단식	개별가스난방	전체동 설치	86	59	59.94	19.889	89000000
6	장기전세	서울특별시	성동구	서울특별시 성동구 자동차시장1길 14	와이엠프라젠	5	아파트	SH공사	2007-10-15	계단식	개별가스난방	전체동 설치	86	84	84.95	20.934	114400000
7	장기전세	서울특별시	성동구	서울특별시 성동구 청계천로 474	왕십리주상복합(서울리츠3호)	37	아파트	SH공사	2009-11-20	복도식	개별가스난방	전체동 설치	120	124	124.459	47.52	532000000
8	장기전세	서울특별시	성동구	서울특별시 성동구 청계천로 474	왕십리 주상복합	32	아파트	SH공사	2009-11-20	복도식	개별가스난방	전체동 설치	120	38	38.982	14.884	202500000
9	장기전세	서울특별시	성동구	서울특별시 성동구 청계천로 474	왕십리 주상복합	32	아파트	SH공사	2009-11-20	복도식	개별가스난방	전체동 설치	120	47	47.822	18.259	232500000

	임대종류	광역시도	시군구	도로명주소	단지명	세대수	주택유형	임대사업자	준공일자	건물형태	난방방식	승강기설치여부	주차수	형명	공급면적(전용)	공급면적(공용)	임대보증금
2135	장기전세	경기도	의정부시	경기도 의정부시 누원로 52	수락리버시티2단지	129	아파트	SH공사	2009-08-13	복도식	지역가스난방	전체동 설치	560	59B	59.5	15.5	137810000
2136	장기전세	경기도	의정부시	경기도 의정부시 누원로 52	수락리버시티2단지	129	아파트	SH공사	2009-08-13	복도식	지역가스난방	전체동 설치	560	84B	84.81	22.54	245700000
2137	장기전세	경기도	고양시 덕양구	경기도 고양시 덕양구 도래울로 86	도래울3단지	384	아파트	LH경기북부	2015-06-30	혼합식	지역난방	전체동 설치	0	51	51.8	20.0048	91182000
2138	장기전세	경기도	고양시 덕양구	경기도 고양시 덕양구 도래울로 86	도래울3단지	384	아파트	LH경기북부	2015-06-30	혼합식	지역난방	전체동 설치	0	59	59.96	23.1562	106303000
2139	장기전세	경기도	하남시	경기도 하남시 미사강변중앙로 100	하남미사 A26BL	588	아파트	LH경기남부	2016-09-30	<NA>	지역난방	<NA>	539	51	51.37	21.5569	183228000
2140	장기전세	경기도	하남시	경기도 하남시 미사강변중앙로 100	하남미사 A26BL	588	아파트	LH경기남부	2016-09-30	<NA>	지역난방	<NA>	539	51	51.39	21.5652	183228000
2141	장기전세	경기도	하남시	경기도 하남시 미사강변중앙로 100	하남미사 A26BL	588	아파트	LH경기남부	2016-09-30	<NA>	지역난방	<NA>	539	59	59.76	25.0776	215057000
2142	장기전세	경기도	하남시	경기도 하남시 미사강변중앙로 100	하남미사 A26BL	588	아파트	LH경기남부	2016-09-30	<NA>	지역난방	<NA>	539	59	59.8	25.0944	215057000
2143	장기전세	경기도	하남시	경기도 하남시 신우실로 15	하남감일 스윗시티2단지	307	아파트	LH경기남부	2021-03-15	계단식	지역난방	전체동 설치	0	74	74.93	28.2964	319200000
2144	장기전세	경기도	하남시	경기도 하남시 신우실로 15	하남감일 스윗시티2단지	307	아파트	LH경기남부	2021-03-15	계단식	지역난방	전체동 설치	0	84	84.95	32.0804	361600000

Overview

Variables

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Uppercase Letter

Decimal Number

Close Punctuation

Open Punctuation

Dash Punctuation

Space Separator

Connector Punctuation

Lowercase Letter

Most occurring scripts

Most frequent character per script

Hangul

Common

Latin

Most occurring blocks

Most frequent character per block

Hangul

ASCII

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Lowercase Letter

Dash Punctuation

Other Punctuation

Math Symbol

Other Symbol

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

CJK Compat

Common Values