gimi9 Pandas Profiling

Dataset statistics

Number of variables	18
Number of observations	1000
Missing cells	1607
Missing cells (%)	8.9%
Duplicate rows	33
Duplicate rows (%)	3.3%
Total size in memory	145.6 KiB
Average record size in memory	149.1 B

Variable types

Categorical	7
Text	7
Numeric	3
DateTime	1

Dataset

Description	한국주택금융공사 주택연금부 업무 관련 공개 공공데이터 (해당 부서의 업무와 관련된 데이터베이스에서 공개 가능한 원천 데이터)
Author	한국주택금융공사
URL	https://www.data.go.kr/data/15072786/fileData.do

Alerts

`REG_DY` has constant value ""	Constant
`REG_TS` has constant value ""	Constant
Dataset has 33 (3.3%) duplicate rows	Duplicates
`DEUNGGI_MOK_CD` is highly overall correlated with `DEUNGGI_GUBUN` and 1 other fields	High correlation
`DEUNGGI_CAUSE_CONT` is highly overall correlated with `DEUNGGI_GUBUN` and 1 other fields	High correlation
`DEUNGGI_GUBUN` is highly overall correlated with `DEUNGGI_MOK_CD` and 3 other fields	High correlation
`BIGO` is highly overall correlated with `CUST_NO` and 5 other fields	High correlation
`CTRL_BRCD` is highly overall correlated with `REG_IDENTI_NO` and 2 other fields	High correlation
`CUST_NO` is highly overall correlated with `JEOPSU_DY` and 1 other fields	High correlation
`REG_IDENTI_NO` is highly overall correlated with `BIGO` and 1 other fields	High correlation
`JEOPSU_DY` is highly overall correlated with `CUST_NO` and 1 other fields	High correlation
`GUBUN` is highly overall correlated with `BIGO`	High correlation
`DEUNGGI_GUBUN` is highly imbalanced (63.8%)	Imbalance
`DEUNGGI_MOK_CD` is highly imbalanced (80.7%)	Imbalance
`DEUNGGI_CAUSE_CONT` is highly imbalanced (57.6%)	Imbalance
`BIGO` is highly imbalanced (86.4%)	Imbalance
`BUILDING_NM` has 728 (72.8%) missing values	Missing
`DONG` has 443 (44.3%) missing values	Missing
`HO` has 364 (36.4%) missing values	Missing
`DEUNGGI_MOK` has 72 (7.2%) missing values	Missing

Reproduction

Analysis started	2023-12-12 02:16:19.713196
Analysis finished	2023-12-12 02:16:23.032634
Duration	3.32 seconds
Software version	ydata-profiling vv4.5.1
Download configuration	config.json

REG_DY
Categorical

CONSTANT

Distinct	1
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

20191216	1000

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	20191216
2nd row	20191216
3rd row	20191216
4th row	20191216
5th row	20191216

Common Values

Value	Count	Frequency (%)
20191216	1000	100.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
20191216	1000	100.0%

GUARNT_NO
Text

Distinct	719
Distinct (%)	71.9%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	14
Median length	14
Mean length	14
Min length	14

Characters and Unicode

Total characters	14000
Distinct characters	24
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

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

Unique

Unique	609 ?
Unique (%)	60.9%

Sample

1st row	RTLA2015000154
2nd row	RTLA2015000145
3rd row	RTLA2015000144
4th row	RTLA2015000133
5th row	RTLA2015000133

Value	Count	Frequency (%)
rtac2012000415	44	4.4%
rtba2013000285	30	3.0%
rtab2014000535	26	2.6%
rqad2014000571	24	2.4%
rqad2013000754	12	1.2%
rtba2014000315	10	1.0%
rtab2016000862	8	0.8%
rtac2014000407	8	0.8%
rtac2013000552	8	0.8%
rtaa2017000818	4	0.4%
Other values (709)	826	82.6%

Most occurring characters

Value	Count	Frequency (%)
0	4427	31.6%
2	1446	10.3%
1	1357	9.7%
A	1062	7.6%
R	1002	7.2%
T	823	5.9%
5	562	4.0%
4	504	3.6%
3	436	3.1%
7	376	2.7%
Other values (14)	2005	14.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	10000	71.4%
Uppercase Letter	4000	28.6%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	1062	26.6%
R	1002	25.1%
T	823	20.6%
B	255	6.4%
Q	198	5.0%
D	196	4.9%
H	143	3.6%
C	133	3.3%
O	56	1.4%
M	37	0.9%
Other values (4)	95	2.4%

Decimal Number

Value	Count	Frequency (%)
0	4427	44.3%
2	1446	14.5%
1	1357	13.6%
5	562	5.6%
4	504	5.0%
3	436	4.4%
7	376	3.8%
6	348	3.5%
8	332	3.3%
9	212	2.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	10000	71.4%
Latin	4000	28.6%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	1062	26.6%
R	1002	25.1%
T	823	20.6%
B	255	6.4%
Q	198	5.0%
D	196	4.9%
H	143	3.6%
C	133	3.3%
O	56	1.4%
M	37	0.9%
Other values (4)	95	2.4%

Common

Value	Count	Frequency (%)
0	4427	44.3%
2	1446	14.5%
1	1357	13.6%
5	562	5.6%
4	504	5.0%
3	436	4.4%
7	376	3.8%
6	348	3.5%
8	332	3.3%
9	212	2.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	14000	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	4427	31.6%
2	1446	10.3%
1	1357	9.7%
A	1062	7.6%
R	1002	7.2%
T	823	5.9%
5	562	4.0%
4	504	3.6%
3	436	3.1%
7	376	2.7%
Other values (14)	2005	14.3%

CUST_NO
Real number (ℝ)

HIGH CORRELATION

Distinct	719
Distinct (%)	71.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	95039416

Minimum	8831828
Maximum	1.2570211 × 10⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	8831828
5-th percentile	66285412
Q1	84999370
median	95182429
Q3	1.0828157 × 10⁸
95-th percentile	1.187346 × 10⁸
Maximum	1.2570211 × 10⁸
Range	1.1687029 × 10⁸
Interquartile range (IQR)	23282196

Descriptive statistics

Standard deviation	16342816
Coefficient of variation (CV)	0.1719583
Kurtosis	2.137478
Mean	95039416
Median Absolute Deviation (MAD)	11057794
Skewness	-0.73852974
Sum	9.5039416 × 10¹⁰
Variance	2.6708765 × 10¹⁴
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
89209889	44	4.4%
94805126	30	3.0%
99857768	26	2.6%
99026133	24	2.4%
94763527	12	1.2%
99092798	10	1.0%
112541320	8	0.8%
95448074	8	0.8%
98914987	8	0.8%
80648122	4	0.4%
Other values (709)	826	82.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
8831828	1	0.1%
9336885	1	0.1%
9354621	1	0.1%
28716334	1	0.1%
31834232	1	0.1%
34209275	1	0.1%
38546031	1	0.1%
41363269	1	0.1%
42004446	1	0.1%
45750153	1	0.1%

Value	Count	Frequency (%)
125702114	1	0.1%
125472444	1	0.1%
125253579	1	0.1%
125248500	2	0.2%
125237566	1	0.1%
125189957	2	0.2%
125171305	1	0.1%
125049631	2	0.2%
124824433	1	0.1%
124802170	2	0.2%

DEUNGGI_GUBUN
Categorical

HIGH CORRELATION IMBALANCE

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

2	931
1	69

Length

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

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
2	931	93.1%
1	69	6.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2	931	93.1%
1	69	6.9%

GUBUN
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

전유	630
토지	276
건물	94

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	전유
2nd row	전유
3rd row	전유
4th row	토지
5th row	건물

Common Values

Value	Count	Frequency (%)
전유	630	63.0%
토지	276	27.6%
건물	94	9.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
전유	630	63.0%
토지	276	27.6%
건물	94	9.4%

REG_IDENTI_NO
Real number (ℝ)

HIGH CORRELATION

Distinct	142
Distinct (%)	14.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.491125 × 10¹³

Minimum	1.1012 × 10¹³
Maximum	2.8502 × 10¹³
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	1.1012 × 10¹³
5-th percentile	1.1132 × 10¹³
Q1	1.1512 × 10¹³
median	1.3122 × 10¹³
Q3	1.8012 × 10¹³
95-th percentile	2.6432 × 10¹³
Maximum	2.8502 × 10¹³
Range	1.749 × 10¹³
Interquartile range (IQR)	6.5 × 10¹²

Descriptive statistics

Standard deviation	4.5706674 × 10¹²
Coefficient of variation (CV)	0.30652476
Kurtosis	1.2535644
Mean	1.491125 × 10¹³
Median Absolute Deviation (MAD)	1.64 × 10¹²
Skewness	1.4412123
Sum	1.491125 × 10¹⁶
Variance	2.0891 × 10²⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11492000000000	56	5.6%
11602000000000	54	5.4%
13452000000000	43	4.3%
18112000000000	40	4.0%
12462000000000	34	3.4%
11132000000000	33	3.3%
13562000000000	31	3.1%
11502000000000	30	3.0%
11642000000000	25	2.5%
27432000000000	24	2.4%
Other values (132)	630	63.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
11012000000000	5	0.5%
11022000000000	4	0.4%
11032000000000	2	0.2%
11112000000000	13	1.3%
11122000000000	6	0.6%
11132000000000	33	3.3%
11142000000000	4	0.4%
11152000000000	10	1.0%
11162000000000	1	0.1%
11412000000000	6	0.6%

Value	Count	Frequency (%)
28502000000000	4	0.4%
28492000000000	3	0.3%
28482000000000	1	0.1%
28412000000000	4	0.4%
28112000000000	2	0.2%
28012000000000	1	0.1%
27432000000000	24	2.4%
27422000000000	5	0.5%
27412000000000	1	0.1%
27012000000000	3	0.3%

BUDONGSAN_PYOSI
Text

Distinct	695
Distinct (%)	69.5%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	34
Median length	27
Mean length	19.069
Min length	14

Characters and Unicode

Total characters	19069
Distinct characters	245
Distinct categories	5 ?
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	551 ?
Unique (%)	55.1%

Sample

1st row	충청북도 충주시 지현동 1088
2nd row	충청북도 청주시 서원구 수곡동 314
3rd row	충청북도 청주시 흥덕구 복대동 3034
4th row	충청북도 제천시 신월동 512-19
5th row	충청북도 제천시 신월동 512-19

Value	Count	Frequency (%)
서울특별시	405	9.5%
경기도	273	6.4%
부산광역시	106	2.5%
강서구	59	1.4%
화곡동	45	1.1%
354-54	44	1.0%
고양시	44	1.0%
용인시	43	1.0%
도봉구	42	1.0%
용산구	40	0.9%
Other values (1246)	3169	74.2%

Most occurring characters

Value	Count	Frequency (%)
	3274	17.2%
동	1024	5.4%
시	994	5.2%
구	870	4.6%
1	797	4.2%
서	575	3.0%
-	571	3.0%
도	463	2.4%
3	456	2.4%
2	455	2.4%
Other values (235)	9590	50.3%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	11328	59.4%
Decimal Number	3895	20.4%
Space Separator	3274	17.2%
Dash Punctuation	571	3.0%
Other Punctuation	1	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
동	1024	9.0%
시	994	8.8%
구	870	7.7%
서	575	5.1%
도	463	4.1%
울	411	3.6%
별	411	3.6%
특	410	3.6%
경	309	2.7%
기	297	2.6%
Other values (222)	5564	49.1%

Decimal Number

Value	Count	Frequency (%)
1	797	20.5%
3	456	11.7%
2	455	11.7%
4	448	11.5%
5	377	9.7%
7	289	7.4%
6	287	7.4%
9	270	6.9%
8	269	6.9%
0	247	6.3%

Space Separator

Value	Count	Frequency (%)
	3274	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	571	100.0%

Other Punctuation

Value	Count	Frequency (%)
,	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	11328	59.4%
Common	7741	40.6%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
동	1024	9.0%
시	994	8.8%
구	870	7.7%
서	575	5.1%
도	463	4.1%
울	411	3.6%
별	411	3.6%
특	410	3.6%
경	309	2.7%
기	297	2.6%
Other values (222)	5564	49.1%

Common

Value	Count	Frequency (%)
	3274	42.3%
1	797	10.3%
-	571	7.4%
3	456	5.9%
2	455	5.9%
4	448	5.8%
5	377	4.9%
7	289	3.7%
6	287	3.7%
9	270	3.5%
Other values (3)	517	6.7%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	11328	59.4%
ASCII	7741	40.6%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	3274	42.3%
1	797	10.3%
-	571	7.4%
3	456	5.9%
2	455	5.9%
4	448	5.8%
5	377	4.9%
7	289	3.7%
6	287	3.7%
9	270	3.5%
Other values (3)	517	6.7%

Hangul

Value	Count	Frequency (%)
동	1024	9.0%
시	994	8.8%
구	870	7.7%
서	575	5.1%
도	463	4.1%
울	411	3.6%
별	411	3.6%
특	410	3.6%
경	309	2.7%
기	297	2.6%
Other values (222)	5564	49.1%

JIBUN
Text

Distinct	669
Distinct (%)	66.9%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Length

Max length	21
Median length	20
Mean length	5.129
Min length	1

Characters and Unicode

Total characters	5129
Distinct characters	57
Distinct categories	7 ?
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	508 ?
Unique (%)	50.8%

Sample

1st row	1088
2nd row	314외 1필지
3rd row	3034
4th row	512-19
5th row	512-19

Value	Count	Frequency (%)
1필지	57	5.0%
354-54	44	3.9%
1396-1	30	2.7%
494-22	26	2.3%
2필지	19	1.7%
3필지	15	1.3%
110-1	12	1.1%
235-86	12	1.1%
235-81	12	1.1%
471	10	0.9%
Other values (675)	893	79.0%

Most occurring characters

Value	Count	Frequency (%)
1	833	16.2%
-	553	10.8%
2	461	9.0%
3	457	8.9%
4	439	8.6%
5	378	7.4%
6	290	5.7%
7	289	5.6%
8	269	5.2%
9	269	5.2%
Other values (47)	891	17.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3952	77.1%
Dash Punctuation	553	10.8%
Other Letter	406	7.9%
Space Separator	130	2.5%
Lowercase Letter	58	1.1%
Uppercase Letter	29	0.6%
Other Punctuation	1	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
지	115	28.3%
외	112	27.6%
필	112	27.6%
월	18	4.4%
일	18	4.4%
구	3	0.7%
산	2	0.5%
트	2	0.5%
로	2	0.5%
블	2	0.5%
Other values (18)	20	4.9%

Decimal Number

Value	Count	Frequency (%)
1	833	21.1%
2	461	11.7%
3	457	11.6%
4	439	11.1%
5	378	9.6%
6	290	7.3%
7	289	7.3%
8	269	6.8%
9	269	6.8%
0	267	6.8%

Lowercase Letter

Value	Count	Frequency (%)
a	18	31.0%
n	12	20.7%
r	8	13.8%
e	7	12.1%
b	5	8.6%
p	3	5.2%
u	2	3.4%
g	1	1.7%
c	1	1.7%
t	1	1.7%

Uppercase Letter

Value	Count	Frequency (%)
J	12	41.4%
M	7	24.1%
F	5	17.2%
A	2	6.9%
S	2	6.9%
O	1	3.4%

Dash Punctuation

Value	Count	Frequency (%)
-	553	100.0%

Space Separator

Value	Count	Frequency (%)
	130	100.0%

Other Punctuation

Value	Count	Frequency (%)
,	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	4636	90.4%
Hangul	406	7.9%
Latin	87	1.7%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
지	115	28.3%
외	112	27.6%
필	112	27.6%
월	18	4.4%
일	18	4.4%
구	3	0.7%
산	2	0.5%
트	2	0.5%
로	2	0.5%
블	2	0.5%
Other values (18)	20	4.9%

Latin

Value	Count	Frequency (%)
a	18	20.7%
J	12	13.8%
n	12	13.8%
r	8	9.2%
e	7	8.0%
M	7	8.0%
b	5	5.7%
F	5	5.7%
p	3	3.4%
u	2	2.3%
Other values (6)	8	9.2%

Common

Value	Count	Frequency (%)
1	833	18.0%
-	553	11.9%
2	461	9.9%
3	457	9.9%
4	439	9.5%
5	378	8.2%
6	290	6.3%
7	289	6.2%
8	269	5.8%
9	269	5.8%
Other values (3)	398	8.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4723	92.1%
Hangul	406	7.9%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	833	17.6%
-	553	11.7%
2	461	9.8%
3	457	9.7%
4	439	9.3%
5	378	8.0%
6	290	6.1%
7	289	6.1%
8	269	5.7%
9	269	5.7%
Other values (19)	485	10.3%

Hangul

Value	Count	Frequency (%)
지	115	28.3%
외	112	27.6%
필	112	27.6%
월	18	4.4%
일	18	4.4%
구	3	0.7%
산	2	0.5%
트	2	0.5%
로	2	0.5%
블	2	0.5%
Other values (18)	20	4.9%

BUILDING_NM
Text

MISSING

Distinct	247
Distinct (%)	90.8%
Missing	728
Missing (%)	72.8%
Memory size	7.9 KiB

Length

Max length	16
Median length	13
Mean length	7.5294118
Min length	2

Characters and Unicode

Total characters	2048
Distinct characters	297
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	223 ?
Unique (%)	82.0%

Sample

1st row	삼일아파트
2nd row	고운여의주아파트
3rd row	가동
4th row	전원주택
5th row	신천지

Value	Count	Frequency (%)
신트리4단지아파트	3	1.1%
해솔마을3단지	2	0.7%
문정래미안아파트	2	0.7%
행당동대림아파트	2	0.7%
숲속마을	2	0.7%
세원수아파트	2	0.7%
개봉동아이파크	2	0.7%
유원강변아파트	2	0.7%
대방2차현대아파트	2	0.7%
에스케이뷰아파트	2	0.7%
Other values (247)	264	92.6%

Most occurring characters

Value	Count	Frequency (%)
트	154	7.5%
아	147	7.2%
파	145	7.1%
마	51	2.5%
을	49	2.4%
스	43	2.1%
지	42	2.1%
동	41	2.0%
이	38	1.9%
대	34	1.7%
Other values (287)	1304	63.7%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	1984	96.9%
Decimal Number	49	2.4%
Space Separator	13	0.6%
Dash Punctuation	2	0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
트	154	7.8%
아	147	7.4%
파	145	7.3%
마	51	2.6%
을	49	2.5%
스	43	2.2%
지	42	2.1%
동	41	2.1%
이	38	1.9%
대	34	1.7%
Other values (280)	1240	62.5%

Decimal Number

Value	Count	Frequency (%)
1	19	38.8%
2	15	30.6%
3	9	18.4%
4	5	10.2%
8	1	2.0%

Space Separator

Value	Count	Frequency (%)
	13	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	1984	96.9%
Common	64	3.1%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
트	154	7.8%
아	147	7.4%
파	145	7.3%
마	51	2.6%
을	49	2.5%
스	43	2.2%
지	42	2.1%
동	41	2.1%
이	38	1.9%
대	34	1.7%
Other values (280)	1240	62.5%

Common

Value	Count	Frequency (%)
1	19	29.7%
2	15	23.4%
	13	20.3%
3	9	14.1%
4	5	7.8%
-	2	3.1%
8	1	1.6%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	1984	96.9%
ASCII	64	3.1%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
트	154	7.8%
아	147	7.4%
파	145	7.3%
마	51	2.6%
을	49	2.5%
스	43	2.2%
지	42	2.1%
동	41	2.1%
이	38	1.9%
대	34	1.7%
Other values (280)	1240	62.5%

ASCII

Value	Count	Frequency (%)
1	19	29.7%
2	15	23.4%
	13	20.3%
3	9	14.1%
4	5	7.8%
-	2	3.1%
8	1	1.6%

DONG
Text

MISSING

Distinct	157
Distinct (%)	28.2%
Missing	443
Missing (%)	44.3%
Memory size	7.9 KiB

Length

Max length	6
Median length	3
Mean length	2.8599641
Min length	1

Characters and Unicode

Total characters	1593
Distinct characters	19
Distinct categories	3 ?
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	85 ?
Unique (%)	15.3%

Sample

1st row	103
2nd row	409
3rd row	103
4th row	나
5th row	101

Value	Count	Frequency (%)
101	68	12.2%
102	36	6.5%
103	31	5.6%
105	26	4.7%
201	20	3.6%
106	18	3.2%
107	15	2.7%
104	14	2.5%
111	11	2.0%
2	9	1.6%
Other values (147)	309	55.5%

Most occurring characters

Value	Count	Frequency (%)
1	500	31.4%
0	429	26.9%
2	189	11.9%
3	114	7.2%
4	90	5.6%
6	68	4.3%
5	63	4.0%
7	55	3.5%
8	35	2.2%
9	31	1.9%
Other values (9)	19	1.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1574	98.8%
Other Letter	18	1.1%
Other Punctuation	1	0.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	500	31.8%
0	429	27.3%
2	189	12.0%
3	114	7.2%
4	90	5.7%
6	68	4.3%
5	63	4.0%
7	55	3.5%
8	35	2.2%
9	31	2.0%

Other Letter

Value	Count	Frequency (%)
나	5	27.8%
가	5	27.8%
에	2	11.1%
이	2	11.1%
상	1	5.6%
디	1	5.6%
씨	1	5.6%
비	1	5.6%

Other Punctuation

Value	Count	Frequency (%)
,	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1575	98.9%
Hangul	18	1.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	500	31.7%
0	429	27.2%
2	189	12.0%
3	114	7.2%
4	90	5.7%
6	68	4.3%
5	63	4.0%
7	55	3.5%
8	35	2.2%
9	31	2.0%

Hangul

Value	Count	Frequency (%)
나	5	27.8%
가	5	27.8%
에	2	11.1%
이	2	11.1%
상	1	5.6%
디	1	5.6%
씨	1	5.6%
비	1	5.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1575	98.9%
Hangul	18	1.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	500	31.7%
0	429	27.2%
2	189	12.0%
3	114	7.2%
4	90	5.7%
6	68	4.3%
5	63	4.0%
7	55	3.5%
8	35	2.2%
9	31	2.0%

Hangul

Value	Count	Frequency (%)
나	5	27.8%
가	5	27.8%
에	2	11.1%
이	2	11.1%
상	1	5.6%
디	1	5.6%
씨	1	5.6%
비	1	5.6%

HO
Text

MISSING

Distinct	173
Distinct (%)	27.2%
Missing	364
Missing (%)	36.4%
Memory size	7.9 KiB

Length

Max length	4
Median length	3
Mean length	3.2955975
Min length	1

Characters and Unicode

Total characters	2096
Distinct characters	12
Distinct categories	2 ?
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	67 ?
Unique (%)	10.5%

Sample

1st row	1003
2nd row	1406
3rd row	901
4th row	1002
5th row	303

Value	Count	Frequency (%)
202	20	3.1%
302	19	3.0%
201	14	2.2%
301	11	1.7%
403	11	1.7%
702	11	1.7%
501	11	1.7%
101	11	1.7%
402	11	1.7%
1301	10	1.6%
Other values (163)	507	79.7%

Most occurring characters

Value	Count	Frequency (%)
0	651	31.1%
1	427	20.4%
2	248	11.8%
3	199	9.5%
4	153	7.3%
5	124	5.9%
6	101	4.8%
7	83	4.0%
9	55	2.6%
8	53	2.5%
Other values (2)	2	0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2094	99.9%
Other Letter	2	0.1%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	651	31.1%
1	427	20.4%
2	248	11.8%
3	199	9.5%
4	153	7.3%
5	124	5.9%
6	101	4.8%
7	83	4.0%
9	55	2.6%
8	53	2.5%

Other Letter

Value	Count	Frequency (%)
에	1	50.0%
이	1	50.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2094	99.9%
Hangul	2	0.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	651	31.1%
1	427	20.4%
2	248	11.8%
3	199	9.5%
4	153	7.3%
5	124	5.9%
6	101	4.8%
7	83	4.0%
9	55	2.6%
8	53	2.5%

Hangul

Value	Count	Frequency (%)
에	1	50.0%
이	1	50.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2094	99.9%
Hangul	2	0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	651	31.1%
1	427	20.4%
2	248	11.8%
3	199	9.5%
4	153	7.3%
5	124	5.9%
6	101	4.8%
7	83	4.0%
9	55	2.6%
8	53	2.5%

Hangul

Value	Count	Frequency (%)
에	1	50.0%
이	1	50.0%

JEOPSU_DY
Real number (ℝ)

HIGH CORRELATION

Distinct	644
Distinct (%)	64.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	20166389

Minimum	20080402
Maximum	20191106
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	20080402
5-th percentile	20120507
Q1	20151110
median	20170904
Q3	20181025
95-th percentile	20190823
Maximum	20191106
Range	110704
Interquartile range (IQR)	29915.5

Descriptive statistics

Standard deviation	22762.559
Coefficient of variation (CV)	0.0011287375
Kurtosis	0.7960534
Mean	20166389
Median Absolute Deviation (MAD)	10689.5
Skewness	-1.0952858
Sum	2.0166389 × 10¹⁰
Variance	5.1813411 × 10⁸
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
20180709	22	2.2%
20180711	10	1.0%
20171127	6	0.6%
20190412	6	0.6%
20160704	6	0.6%
20181213	5	0.5%
20170714	5	0.5%
20180806	5	0.5%
20170626	5	0.5%
20190820	5	0.5%
Other values (634)	925	92.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
20080402	1	0.1%
20080507	1	0.1%
20090501	1	0.1%
20090703	1	0.1%
20090923	1	0.1%
20090924	1	0.1%
20100319	1	0.1%
20100419	2	0.2%
20100422	2	0.2%
20100701	2	0.2%

Value	Count	Frequency (%)
20191106	1	0.1%
20191105	2	0.2%
20191104	1	0.1%
20191101	1	0.1%
20191031	3	0.3%
20191030	1	0.1%
20191025	2	0.2%
20191023	3	0.3%
20191022	1	0.1%
20191018	1	0.1%

DEUNGGI_MOK
Text

MISSING

Distinct	269
Distinct (%)	29.0%
Missing	72
Missing (%)	7.2%
Memory size	7.9 KiB

Length

Max length	86
Median length	5
Mean length	7.78125
Min length	5

Characters and Unicode

Total characters	7221
Distinct characters	171
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	236 ?
Unique (%)	25.4%

Sample

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

Value	Count	Frequency (%)
소유권이전	610	63.4%
공유자전원지분전부이전	9	0.9%
소유권일부이전	5	0.5%
15번임임환지분전부이전	4	0.4%
41번최영숙지분전부이전	4	0.4%
20번박삼례지분전부이전	4	0.4%
중	4	0.4%
24번제연주지분전부이전	4	0.4%
1번정진식지분전부이전	2	0.2%
44번조충희지분전부이전	2	0.2%
Other values (289)	314	32.6%

Most occurring characters

Value	Count	Frequency (%)
전	1256	17.4%
이	977	13.5%
유	643	8.9%
소	626	8.7%
권	624	8.6%
분	339	4.7%
지	335	4.6%
부	334	4.6%
번	330	4.6%
2	143	2.0%
Other values (161)	1614	22.4%

Most occurring categories

Value	Count	Frequency (%)
Other Letter	6425	89.0%
Decimal Number	718	9.9%
Space Separator	34	0.5%
Other Punctuation	32	0.4%
Open Punctuation	4	0.1%
Close Punctuation	4	0.1%
Dash Punctuation	4	0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
전	1256	19.5%
이	977	15.2%
유	643	10.0%
소	626	9.7%
권	624	9.7%
분	339	5.3%
지	335	5.2%
부	334	5.2%
번	330	5.1%
김	49	0.8%
Other values (145)	912	14.2%

Decimal Number

Value	Count	Frequency (%)
2	143	19.9%
1	131	18.2%
3	93	13.0%
4	85	11.8%
5	57	7.9%
7	48	6.7%
6	47	6.5%
0	46	6.4%
9	39	5.4%
8	29	4.0%

Other Punctuation

Value	Count	Frequency (%)
,	26	81.2%
.	6	18.8%

Space Separator

Value	Count	Frequency (%)
	34	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	4	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	4	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	4	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Hangul	6425	89.0%
Common	796	11.0%

Most frequent character per script

Hangul

Value	Count	Frequency (%)
전	1256	19.5%
이	977	15.2%
유	643	10.0%
소	626	9.7%
권	624	9.7%
분	339	5.3%
지	335	5.2%
부	334	5.2%
번	330	5.1%
김	49	0.8%
Other values (145)	912	14.2%

Common

Value	Count	Frequency (%)
2	143	18.0%
1	131	16.5%
3	93	11.7%
4	85	10.7%
5	57	7.2%
7	48	6.0%
6	47	5.9%
0	46	5.8%
9	39	4.9%
	34	4.3%
Other values (6)	73	9.2%

Most occurring blocks

Value	Count	Frequency (%)
Hangul	6425	89.0%
ASCII	796	11.0%

Most frequent character per block

Hangul

Value	Count	Frequency (%)
전	1256	19.5%
이	977	15.2%
유	643	10.0%
소	626	9.7%
권	624	9.7%
분	339	5.3%
지	335	5.2%
부	334	5.2%
번	330	5.1%
김	49	0.8%
Other values (145)	912	14.2%

ASCII

Value	Count	Frequency (%)
2	143	18.0%
1	131	16.5%
3	93	11.7%
4	85	10.7%
5	57	7.2%
7	48	6.0%
6	47	5.9%
0	46	5.8%
9	39	4.9%
	34	4.3%
Other values (6)	73	9.2%

DEUNGGI_MOK_CD
Categorical

HIGH CORRELATION IMBALANCE

Distinct	6
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

A1ZZCZ	916
<NA>	69
A1ZZEZ	7
ZZU2EZ	4
11ZZBZ	3

Length

Max length	6
Median length	6
Mean length	5.862
Min length	4

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	A1ZZCZ
2nd row	A1ZZCZ
3rd row	A1ZZCZ
4th row	A1ZZCZ
5th row	A1ZZCZ

Common Values

Value	Count	Frequency (%)
A1ZZCZ	916	91.6%
<NA>	69	6.9%
A1ZZEZ	7	0.7%
ZZU2EZ	4	0.4%
11ZZBZ	3	0.3%
A1ZZFZ	1	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
a1zzcz	916	91.6%
na	69	6.9%
a1zzez	7	0.7%
zzu2ez	4	0.4%
11zzbz	3	0.3%
a1zzfz	1	0.1%

DEUNGGI_CAUSE_CONT
Categorical

HIGH CORRELATION IMBALANCE

Distinct	20
Distinct (%)	2.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

협의분할에 의한 상속	597
매매	218
<NA>	72
증여	63
상속	15
Other values (15)	35

Length

Max length	27
Median length	11
Mean length	7.67
Min length	2

Unique

Unique	7 ?
Unique (%)	0.7%

Sample

1st row	협의분할에 의한 상속
2nd row	협의분할에 의한 상속
3rd row	협의분할에 의한 상속
4th row	협의분할에 의한 상속
5th row	협의분할에 의한 상속

Common Values

Value	Count	Frequency (%)
협의분할에 의한 상속	597	59.7%
매매	218	21.8%
<NA>	72	7.2%
증여	63	6.3%
상속	15	1.5%
유증	7	0.7%
협의분할로 인한 재산상속	4	0.4%
재산분할	4	0.4%
합유자 전종한 사망	4	0.4%
신청착오	3	0.3%
Other values (10)	13	1.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
상속	614	27.7%
협의분할에	597	26.9%
의한	597	26.9%
매매	218	9.8%
na	72	3.2%
증여	63	2.8%
유증	7	0.3%
인한	7	0.3%
협의분할로	6	0.3%
사망	5	0.2%
Other values (16)	32	1.4%

BIGO
Categorical

HIGH CORRELATION IMBALANCE

Distinct	22
Distinct (%)	2.2%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

<NA>	931
2018년6월4일 행정구역명칭변경으로 인하여	21
2018년7월1일 행정구역명칭변경으로 인하여	11
2016년7월4일 행정구역명칭변경으로 인하여	6
2014년7월1일 행정구역명칭변경으로 인하여	6
Other values (17)	25

Length

Max length	38
Median length	4
Mean length	5.315
Min length	4

Unique

Unique	9 ?
Unique (%)	0.9%

Sample

1st row	<NA>
2nd row	<NA>
3rd row	<NA>
4th row	<NA>
5th row	<NA>

Common Values

Value	Count	Frequency (%)
<NA>	931	93.1%
2018년6월4일 행정구역명칭변경으로 인하여	21	2.1%
2018년7월1일 행정구역명칭변경으로 인하여	11	1.1%
2016년7월4일 행정구역명칭변경으로 인하여	6	0.6%
2014년7월1일 행정구역명칭변경으로 인하여	6	0.6%
2013년9월23일 행정구역명칭변경으로 인하여	2	0.2%
행정구역 명칭 변경	2	0.2%
2011년7월25일 행정구역명칭변경으로 인하여	2	0.2%
2019년10월24일 행정구역명칭변경으로 인하여	2	0.2%
2010년7월1일 행정구역명칭변경으로 인하여	2	0.2%
Other values (12)	15	1.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
na	931	81.5%
인하여	63	5.5%
행정구역명칭변경으로	60	5.3%
2018년6월4일	21	1.8%
2018년7월1일	11	1.0%
2016년7월4일	6	0.5%
2014년7월1일	6	0.5%
2010년7월1일	2	0.2%
이기	2	0.2%
대	2	0.2%
Other values (28)	38	3.3%

CTRL_BRCD
Categorical

HIGH CORRELATION

Distinct	24
Distinct (%)	2.4%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

TAC	170
TAB	124
QAD	124
TAA	88
TBA	84
Other values (19)	410

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

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

Common Values

Value	Count	Frequency (%)
TAC	170	17.0%
TAB	124	12.4%
QAD	124	12.4%
TAA	88	8.8%
TBA	84	8.4%
TAD	74	7.4%
THA	72	7.2%
THO	38	3.8%
TMA	32	3.2%
TPA	31	3.1%
Other values (14)	163	16.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
tac	170	17.0%
tab	124	12.4%
qad	124	12.4%
taa	88	8.8%
tba	84	8.4%
tad	74	7.4%
tha	72	7.2%
tho	38	3.8%
tma	32	3.2%
tpa	31	3.1%
Other values (14)	163	16.3%

REG_TS
Date

CONSTANT

Distinct	1
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Minimum	2019-12-24 14:30:00
Maximum	2019-12-24 14:30:00

Histogram

Histogram with fixed size bins (bins=1)

Heatmap
Table

	CUST_NO	DEUNGGI_GUBUN	GUBUN	REG_IDENTI_NO	JEOPSU_DY	DEUNGGI_MOK_CD	DEUNGGI_CAUSE_CONT	BIGO	CTRL_BRCD
CUST_NO	1.000	0.097	0.345	0.351	0.638	0.690	0.488	0.895	0.362
DEUNGGI_GUBUN	0.097	1.000	0.253	0.130	0.172	NaN	NaN	NaN	0.811
GUBUN	0.345	0.253	1.000	0.359	0.173	0.041	0.620	0.878	0.615
REG_IDENTI_NO	0.351	0.130	0.359	1.000	0.191	0.368	0.310	0.998	0.952
JEOPSU_DY	0.638	0.172	0.173	0.191	1.000	0.189	0.339	1.000	0.385
DEUNGGI_MOK_CD	0.690	NaN	0.041	0.368	0.189	1.000	0.931	NaN	0.294
DEUNGGI_CAUSE_CONT	0.488	NaN	0.620	0.310	0.339	0.931	1.000	NaN	0.309
BIGO	0.895	NaN	0.878	0.998	1.000	NaN	NaN	1.000	1.000
CTRL_BRCD	0.362	0.811	0.615	0.952	0.385	0.294	0.309	1.000	1.000

Heatmap
Table

	GUBUN	DEUNGGI_MOK_CD	DEUNGGI_CAUSE_CONT	DEUNGGI_GUBUN	BIGO	CTRL_BRCD
GUBUN	1.000	0.030	0.411	0.412	0.546	0.353
DEUNGGI_MOK_CD	0.030	1.000	0.800	1.000	NaN	0.145
DEUNGGI_CAUSE_CONT	0.411	0.800	1.000	1.000	NaN	0.091
DEUNGGI_GUBUN	0.412	1.000	1.000	1.000	1.000	0.663
BIGO	0.546	NaN	NaN	1.000	1.000	0.943
CTRL_BRCD	0.353	0.145	0.091	0.663	0.943	1.000

Heatmap
Table

	CUST_NO	REG_IDENTI_NO	JEOPSU_DY	DEUNGGI_GUBUN	GUBUN	DEUNGGI_MOK_CD	DEUNGGI_CAUSE_CONT	BIGO	CTRL_BRCD
CUST_NO	1.000	0.188	0.514	0.075	0.221	0.290	0.189	0.605	0.138
REG_IDENTI_NO	0.188	1.000	0.038	0.098	0.230	0.161	0.122	0.825	0.757
JEOPSU_DY	0.514	0.038	1.000	0.130	0.105	0.079	0.128	0.894	0.145
DEUNGGI_GUBUN	0.075	0.098	0.130	1.000	0.412	1.000	1.000	1.000	0.663
GUBUN	0.221	0.230	0.105	0.412	1.000	0.030	0.411	0.546	0.353
DEUNGGI_MOK_CD	0.290	0.161	0.079	1.000	0.030	1.000	0.800	0.000	0.145
DEUNGGI_CAUSE_CONT	0.189	0.122	0.128	1.000	0.411	0.800	1.000	0.000	0.091
BIGO	0.605	0.825	0.894	1.000	0.546	0.000	0.000	1.000	0.943
CTRL_BRCD	0.138	0.757	0.145	0.663	0.353	0.145	0.091	0.943	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

	REG_DY	GUARNT_NO	CUST_NO	DEUNGGI_GUBUN	GUBUN	REG_IDENTI_NO	BUDONGSAN_PYOSI	JIBUN	BUILDING_NM	DONG	HO	JEOPSU_DY	DEUNGGI_MOK	DEUNGGI_MOK_CD	DEUNGGI_CAUSE_CONT	BIGO	CTRL_BRCD	REG_TS
0	20191216	RTLA2015000154	108509567	2	전유	15112000000000	충청북도 충주시 지현동 1088	1088	<NA>	103	1003	20190327	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
1	20191216	RTLA2015000145	108202068	2	전유	15012000000000	충청북도 청주시 서원구 수곡동 314	314외 1필지	<NA>	409	1406	20160315	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
2	20191216	RTLA2015000144	100600053	2	전유	15012000000000	충청북도 청주시 흥덕구 복대동 3034	3034	삼일아파트	103	901	20170124	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
3	20191216	RTLA2015000133	106357229	2	토지	15122000000000	충청북도 제천시 신월동 512-19	512-19	<NA>	<NA>	<NA>	20191001	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
4	20191216	RTLA2015000133	106357229	2	건물	15122000000000	충청북도 제천시 신월동 512-19	512-19	<NA>	<NA>	<NA>	20191001	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
5	20191216	RTLA2011000059	85478465	2	전유	15112000000000	충청북도 충주시 연수동 465-5	465-5	<NA>	나	1002	20180919	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
6	20191216	RTLA2010000039	80745313	2	토지	15112000000000	충청북도 충주시 목행동 615-5	615-5	<NA>	<NA>	<NA>	20160317	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
7	20191216	RTLA2010000039	80745313	2	건물	15112000000000	충청북도 충주시 목행동 615-5	615-5	<NA>	<NA>	<NA>	20160317	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TLA	2019-12-24 14:30
8	20191216	RTHA2009000191	76342319	2	전유	16152000000000	충청남도 천안시 동남구 안서동 223-3	223-3	고운여의주아파트	101	303	20140912	소유권이전	A1ZZCZ	매매	<NA>	TLB	2019-12-24 14:30
9	20191216	RTHO2017000584	118585403	1	건물	12462000000000	인천광역시 미추홀구 주안동 452-21	452-21외 1필지	<NA>	<NA>	<NA>	20180711	<NA>	<NA>	<NA>	2018년7월1일 행정구역명칭변경으로 인하여	THO	2019-12-24 14:30

	REG_DY	GUARNT_NO	CUST_NO	DEUNGGI_GUBUN	GUBUN	REG_IDENTI_NO	BUDONGSAN_PYOSI	JIBUN	BUILDING_NM	DONG	HO	JEOPSU_DY	DEUNGGI_MOK	DEUNGGI_MOK_CD	DEUNGGI_CAUSE_CONT	BIGO	CTRL_BRCD	REG_TS
990	20191216	RTHA2012000507	89692344	2	건물	13452000000000	경기도 용인시 기흥구 동백동 73-98	73-98	<NA>	<NA>	<NA>	20180709	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THA	2019-12-24 14:30
991	20191216	RTHA2012000506	66191318	2	전유	13482000000000	경기도 오산시 누읍동 438	438	<NA>	101	802	20190326	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THA	2019-12-24 14:30
992	20191216	RTHB2014000392	99320622	2	전유	13492000000000	경기도 광명시 소하동 889-1	889-1	<NA>	<NA>	909	20190321	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
993	20191216	RTHB2014000368	99086526	2	전유	13412000000000	경기도 안양시 만안구 안양동 90-1	Jan-90	삼성래미안아파트	111	302	20190821	3번유덕삼지분전부이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
994	20191216	RTHB2013000426	95840876	2	전유	13142000000000	경기도 안산시 단원구 원곡동 828-5	828-5	벽산블루밍아파트	113	304	20151020	2번김병구지분전부이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
995	20191216	RTHB2013000416	95765401	2	전유	13532000000000	경기도 과천시 부림동 41	41	주공아파트	802	106	20170519	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
996	20191216	RTHB2013000404	95608885	2	전유	13552000000000	경기도 시흥시 정왕동 1866-6	1866-6	<NA>	509	202	20140616	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
997	20191216	RTHB2013000400	95579671	2	전유	13412000000000	경기도 안양시 동안구 비산동 354-10	354-10외 1필지	뉴타운아파트	3	702	20141119	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
998	20191216	RTHB2013000385	95415780	2	전유	13412000000000	경기도 안양시 만안구 석수동 805	805	주공그린빌	105	1201	20160316	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	THB	2019-12-24 14:30
999	20191216	RTHB2013000369	95214855	2	토지	13492000000000	경기도 광명시 광명동 7-89	7-89	<NA>	<NA>	<NA>	20190304	34번이주희지분전부이전	A1ZZCZ	매매	<NA>	THB	2019-12-24 14:30

Most frequently occurring

	REG_DY	GUARNT_NO	CUST_NO	DEUNGGI_GUBUN	GUBUN	REG_IDENTI_NO	BUDONGSAN_PYOSI	JIBUN	BUILDING_NM	DONG	HO	JEOPSU_DY	DEUNGGI_MOK	DEUNGGI_MOK_CD	DEUNGGI_CAUSE_CONT	BIGO	CTRL_BRCD	REG_TS	# duplicates
10	20191216	RTAA2008000143	71620120	2	전유	13562000000000	경기도 성남시 분당구 이매동 123	123	<NA>	609	1103	20141204	소유권이전	A1ZZCZ	매매	<NA>	TAA	2019-12-24 14:30	4
14	20191216	RTAA2017000818	118668634	2	전유	13562000000000	경기도 성남시 분당구 서현동 308	308	<NA>	623	202	20190313	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TAA	2019-12-24 14:30	4
32	20191216	RTOA2016000216	112778287	2	건물	20112000000000	전라남도 목포시 행복동1가 10-1	10월 01일	<NA>	<NA>	1	20170626	소유권이전	A1ZZCZ	협의분할에 의한 상속	<NA>	TOA	2019-12-24 14:30	4
0	20191216	RQAD2013000754	94763527	2	토지	11422000000000	서울특별시 용산구 원효로4가 110-1	110-1	<NA>	<NA>	<NA>	20170620	60번정우지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2
1	20191216	RQAD2013000754	94763527	2	토지	11422000000000	서울특별시 용산구 원효로4가 110-1	110-1	<NA>	<NA>	<NA>	20181030	66번이혜숙지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2
2	20191216	RQAD2014000571	99026133	2	토지	27432000000000	서울특별시 용산구 서빙고동 235-81	235-81	<NA>	<NA>	<NA>	20150204	20번박삼례지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2
3	20191216	RQAD2014000571	99026133	2	토지	27432000000000	서울특별시 용산구 서빙고동 235-81	235-81	<NA>	<NA>	<NA>	20160215	24번제연주지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2
4	20191216	RQAD2014000571	99026133	2	토지	27432000000000	서울특별시 용산구 서빙고동 235-81	235-81	<NA>	<NA>	<NA>	20180806	41번최영숙지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2
5	20191216	RQAD2014000571	99026133	2	토지	27432000000000	서울특별시 용산구 서빙고동 235-81	235-81	<NA>	<NA>	<NA>	20190820	15번임임환지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2
6	20191216	RQAD2014000571	99026133	2	토지	27432000000000	서울특별시 용산구 서빙고동 235-86	235-86	<NA>	<NA>	<NA>	20150204	20번박삼례지분전부이전	A1ZZCZ	매매	<NA>	QAD	2019-12-24 14:30	2

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Decimal Number

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Common Values (Plot)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Decimal Number

Space Separator

Dash Punctuation

Other 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

Decimal Number

Lowercase Letter

Uppercase Letter

Dash Punctuation

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Hangul

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Hangul

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

Hangul

ASCII

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Other Letter

Other Punctuation

Most occurring scripts