Overview

Dataset statistics

Number of variables14
Number of observations10000
Missing cells28522
Missing cells (%)20.4%
Duplicate rows5
Duplicate rows (%)0.1%
Total size in memory1.2 MiB
Average record size in memory121.0 B

Variable types

Categorical5
Text8
Numeric1

Dataset

Description송파구 내 주택관리업자 상호, 주소, 대표번호 등 제공
Author서울특별시 송파구
URLhttps://www.data.go.kr/data/15044852/fileData.do

Alerts

Dataset has 5 (0.1%) duplicate rowsDuplicates
사업자구분 is highly overall correlated with 임대주택구분 and 1 other fieldsHigh correlation
임대주택구분 is highly overall correlated with 사업자구분 and 1 other fieldsHigh correlation
종류 is highly overall correlated with 사업자구분 and 1 other fieldsHigh correlation
임시주소 has 9235 (92.3%) missing valuesMissing
동명 has 7525 (75.2%) missing valuesMissing
호명 has 2961 (29.6%) missing valuesMissing
실명 has 8415 (84.2%) missing valuesMissing
면적 has 340 (3.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 03:03:57.823818
Analysis finished2023-12-12 03:04:01.484917
Duration3.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

영업구분
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
등록영업중
7457 
전입영업중
2543 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전입영업중
2nd row전입영업중
3rd row등록영업중
4th row등록영업중
5th row전입영업중

Common Values

ValueCountFrequency (%)
등록영업중 7457
74.6%
전입영업중 2543
 
25.4%

Length

2023-12-12T12:04:01.573874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:01.714580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록영업중 7457
74.6%
전입영업중 2543
 
25.4%

등록번호
Text

Distinct5683
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:04:02.100092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length19.2083
Min length16

Characters and Unicode

Total characters192083
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3747 ?
Unique (%)37.5%

Sample

1st row2020-송파구-임대사업자-3076
2nd row2019-송파구-임대사업자-426
3rd row2004-송파구-임대사업자-1694
4th row2019-송파구-임대사업자-4676
5th row2018-송파구-임대사업자-17499
ValueCountFrequency (%)
2018-송파구-임대사업자-18524 89
 
0.9%
2019-송파구-임대사업자-2094 59
 
0.6%
2020-송파구-임대사업자-1159 50
 
0.5%
2005-송파구-임대사업자-2229 40
 
0.4%
2020-송파구-임대사업자-1873 31
 
0.3%
2005-송파구-임대사업자-2288 27
 
0.3%
2018-송파구-임대사업자-17971 18
 
0.2%
2018-송파구-임대사업자-20941 16
 
0.2%
2017-송파구-임대사업자-13551 15
 
0.1%
2020-송파구-임대사업자-1641 13
 
0.1%
Other values (5673) 9642
96.4%
2023-12-12T12:04:02.672050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 30000
15.6%
2 17705
 
9.2%
0 17154
 
8.9%
1 14304
 
7.4%
임 10000
 
5.2%
자 10000
 
5.2%
업 10000
 
5.2%
사 10000
 
5.2%
대 10000
 
5.2%
구 10000
 
5.2%
Other values (9) 52920
27.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82083
42.7%
Other Letter 80000
41.6%
Dash Punctuation 30000
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 17705
21.6%
0 17154
20.9%
1 14304
17.4%
8 6776
 
8.3%
9 5781
 
7.0%
4 4279
 
5.2%
3 4193
 
5.1%
7 4163
 
5.1%
6 3887
 
4.7%
5 3841
 
4.7%
Other Letter
ValueCountFrequency (%)
임 10000
12.5%
자 10000
12.5%
업 10000
12.5%
사 10000
12.5%
대 10000
12.5%
구 10000
12.5%
파 10000
12.5%
송 10000
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 30000
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 112083
58.4%
Hangul 80000
41.6%

Most frequent character per script

Common
ValueCountFrequency (%)
- 30000
26.8%
2 17705
15.8%
0 17154
15.3%
1 14304
12.8%
8 6776
 
6.0%
9 5781
 
5.2%
4 4279
 
3.8%
3 4193
 
3.7%
7 4163
 
3.7%
6 3887
 
3.5%
Hangul
ValueCountFrequency (%)
임 10000
12.5%
자 10000
12.5%
업 10000
12.5%
사 10000
12.5%
대 10000
12.5%
구 10000
12.5%
파 10000
12.5%
송 10000
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 112083
58.4%
Hangul 80000
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 30000
26.8%
2 17705
15.8%
0 17154
15.3%
1 14304
12.8%
8 6776
 
6.0%
9 5781
 
5.2%
4 4279
 
3.8%
3 4193
 
3.7%
7 4163
 
3.7%
6 3887
 
3.5%
Hangul
ValueCountFrequency (%)
임 10000
12.5%
자 10000
12.5%
업 10000
12.5%
사 10000
12.5%
대 10000
12.5%
구 10000
12.5%
파 10000
12.5%
송 10000
12.5%

사업자구분
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
임대사업자
3915 
일반형임대사업자
3287 
매입임대사업자
1662 
허가건설임대사업자
1025 
기업형임대사업자
 
96
Other values (2)
 
15

Length

Max length9
Median length8
Mean length6.7574
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row임대사업자
2nd row일반형임대사업자
3rd row허가건설임대사업자
4th row임대사업자
5th row매입임대사업자

Common Values

ValueCountFrequency (%)
임대사업자 3915
39.1%
일반형임대사업자 3287
32.9%
매입임대사업자 1662
16.6%
허가건설임대사업자 1025
 
10.2%
기업형임대사업자 96
 
1.0%
주택건설업자 8
 
0.1%
<NA> 7
 
0.1%

Length

2023-12-12T12:04:02.896381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:03.058996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대사업자 3915
39.1%
일반형임대사업자 3287
32.9%
매입임대사업자 1662
16.6%
허가건설임대사업자 1025
 
10.2%
기업형임대사업자 96
 
1.0%
주택건설업자 8
 
0.1%
na 7
 
0.1%

도로명주소
Text

Distinct5357
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T12:04:03.462721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length34.1747
Min length10

Characters and Unicode

Total characters341747
Distinct characters339
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3366 ?
Unique (%)33.7%

Sample

1st row서울특별시 송파구 올림픽로 135 252동 1004호 (잠실동, 리센츠)
2nd row서울특별시 송파구 올림픽로35길 104 12동 401호 (신천동, 장미아파트)
3rd row서울특별시 송파구 가락로13길 17 401
4th row서울특별시 송파구 가락로 192 22동 506호 (송파동, 한양아파트)
5th row서울특별시 송파구 올림픽로 99 136동 301호 (잠실동, 잠실엘스)
ValueCountFrequency (%)
서울특별시 9971
 
15.4%
송파구 9949
 
15.4%
잠실동 1500
 
2.3%
올림픽로 1078
 
1.7%
가락동 1029
 
1.6%
송파대로 929
 
1.4%
문정동 832
 
1.3%
신천동 689
 
1.1%
방이동 558
 
0.9%
헬리오시티 520
 
0.8%
Other values (2794) 37694
58.2%
2023-12-12T12:04:04.070112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
54912
 
16.1%
1 16854
 
4.9%
파 15388
 
4.5%
송 12489
 
3.7%
동 12311
 
3.6%
2 11482
 
3.4%
0 10739
 
3.1%
시 10714
 
3.1%
구 9999
 
2.9%
울 9995
 
2.9%
Other values (329) 176864
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 191609
56.1%
Decimal Number 72768
 
21.3%
Space Separator 54912
 
16.1%
Open Punctuation 6685
 
2.0%
Close Punctuation 6684
 
2.0%
Other Punctuation 5847
 
1.7%
Dash Punctuation 2919
 
0.9%
Uppercase Letter 275
 
0.1%
Lowercase Letter 36
 
< 0.1%
Control 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 15388
 
8.0%
송 12489
 
6.5%
동 12311
 
6.4%
시 10714
 
5.6%
구 9999
 
5.2%
울 9995
 
5.2%
서 9979
 
5.2%
별 9973
 
5.2%
특 9972
 
5.2%
로 9894
 
5.2%
Other values (292) 80895
42.2%
Uppercase Letter
ValueCountFrequency (%)
A 96
34.9%
C 64
23.3%
B 31
 
11.3%
T 17
 
6.2%
P 13
 
4.7%
D 11
 
4.0%
E 9
 
3.3%
I 7
 
2.5%
S 6
 
2.2%
J 6
 
2.2%
Other values (4) 15
 
5.5%
Decimal Number
ValueCountFrequency (%)
1 16854
23.2%
2 11482
15.8%
0 10739
14.8%
3 8626
11.9%
4 6610
 
9.1%
5 5732
 
7.9%
6 3589
 
4.9%
8 3417
 
4.7%
9 2923
 
4.0%
7 2796
 
3.8%
Lowercase Letter
ValueCountFrequency (%)
e 27
75.0%
u 3
 
8.3%
i 3
 
8.3%
t 3
 
8.3%
Control
ValueCountFrequency (%)
10
83.3%
1
 
8.3%
1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 5844
99.9%
. 3
 
0.1%
Space Separator
ValueCountFrequency (%)
54912
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6685
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2919
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 191609
56.1%
Common 149827
43.8%
Latin 311
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 15388
 
8.0%
송 12489
 
6.5%
동 12311
 
6.4%
시 10714
 
5.6%
구 9999
 
5.2%
울 9995
 
5.2%
서 9979
 
5.2%
별 9973
 
5.2%
특 9972
 
5.2%
로 9894
 
5.2%
Other values (292) 80895
42.2%
Common
ValueCountFrequency (%)
54912
36.7%
1 16854
 
11.2%
2 11482
 
7.7%
0 10739
 
7.2%
3 8626
 
5.8%
( 6685
 
4.5%
) 6684
 
4.5%
4 6610
 
4.4%
, 5844
 
3.9%
5 5732
 
3.8%
Other values (9) 15659
 
10.5%
Latin
ValueCountFrequency (%)
A 96
30.9%
C 64
20.6%
B 31
 
10.0%
e 27
 
8.7%
T 17
 
5.5%
P 13
 
4.2%
D 11
 
3.5%
E 9
 
2.9%
I 7
 
2.3%
S 6
 
1.9%
Other values (8) 30
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 191609
56.1%
ASCII 150138
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54912
36.6%
1 16854
 
11.2%
2 11482
 
7.6%
0 10739
 
7.2%
3 8626
 
5.7%
( 6685
 
4.5%
) 6684
 
4.5%
4 6610
 
4.4%
, 5844
 
3.9%
5 5732
 
3.8%
Other values (27) 15970
 
10.6%
Hangul
ValueCountFrequency (%)
파 15388
 
8.0%
송 12489
 
6.5%
동 12311
 
6.4%
시 10714
 
5.6%
구 9999
 
5.2%
울 9995
 
5.2%
서 9979
 
5.2%
별 9973
 
5.2%
특 9972
 
5.2%
로 9894
 
5.2%
Other values (292) 80895
42.2%

임대주택구분
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
민간매입임대주택
7684 
민간건설임대주택
2293 
<NA>
 
23

Length

Max length8
Median length8
Mean length7.9908
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row민간건설임대주택
2nd row민간매입임대주택
3rd row민간건설임대주택
4th row민간매입임대주택
5th row민간매입임대주택

Common Values

ValueCountFrequency (%)
민간매입임대주택 7684
76.8%
민간건설임대주택 2293
 
22.9%
<NA> 23
 
0.2%

Length

2023-12-12T12:04:04.301151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:04.469724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
민간매입임대주택 7684
76.8%
민간건설임대주택 2293
 
22.9%
na 23
 
0.2%

지번주소
Text

Distinct5123
Distinct (%)51.3%
Missing23
Missing (%)0.2%
Memory size156.2 KiB
2023-12-12T12:04:04.899133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length62
Mean length25.555377
Min length2

Characters and Unicode

Total characters254966
Distinct characters601
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3343 ?
Unique (%)33.5%

Sample

1st row경기도 시흥시 정왕동 2748-3 (정왕동)
2nd row서울특별시 강동구 명일동 257 (명일동, 고덕주공아파트)
3rd row서울특별시 송파구 석촌동 268-21 (석촌동)
4th row경기도 용인시 기흥구 영덕동 1315 (영덕동, 힉스유타워)
5th row충청남도 계룡시 엄사면 엄사리 282 성원아파트 9-108,9-203,9-209,
ValueCountFrequency (%)
서울특별시 6893
 
13.7%
송파구 4396
 
8.7%
경기도 1748
 
3.5%
석촌동 1119
 
2.2%
삼전동 1073
 
2.1%
잠실동 1052
 
2.1%
방이동 874
 
1.7%
송파동 871
 
1.7%
문정동 716
 
1.4%
강남구 470
 
0.9%
Other values (7200) 31246
61.9%
2023-12-12T12:04:05.873324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45808
 
18.0%
동 15535
 
6.1%
시 9836
 
3.9%
1 8970
 
3.5%
구 8620
 
3.4%
서 7746
 
3.0%
별 6969
 
2.7%
특 6946
 
2.7%
울 6911
 
2.7%
- 6836
 
2.7%
Other values (591) 130789
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 148876
58.4%
Space Separator 45808
 
18.0%
Decimal Number 38228
 
15.0%
Dash Punctuation 6836
 
2.7%
Open Punctuation 5793
 
2.3%
Close Punctuation 5793
 
2.3%
Other Punctuation 2874
 
1.1%
Uppercase Letter 475
 
0.2%
Lowercase Letter 198
 
0.1%
Letter Number 38
 
< 0.1%
Other values (3) 47
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 15535
 
10.4%
시 9836
 
6.6%
구 8620
 
5.8%
서 7746
 
5.2%
별 6969
 
4.7%
특 6946
 
4.7%
울 6911
 
4.6%
파 6673
 
4.5%
송 5570
 
3.7%
도 2502
 
1.7%
Other values (520) 71568
48.1%
Uppercase Letter
ValueCountFrequency (%)
A 64
13.5%
C 48
 
10.1%
S 37
 
7.8%
B 35
 
7.4%
L 32
 
6.7%
M 32
 
6.7%
K 27
 
5.7%
I 26
 
5.5%
T 24
 
5.1%
E 24
 
5.1%
Other values (14) 126
26.5%
Lowercase Letter
ValueCountFrequency (%)
e 49
24.7%
l 21
10.6%
s 16
 
8.1%
u 15
 
7.6%
i 15
 
7.6%
o 13
 
6.6%
a 10
 
5.1%
h 9
 
4.5%
r 9
 
4.5%
n 8
 
4.0%
Other values (10) 33
16.7%
Decimal Number
ValueCountFrequency (%)
1 8970
23.5%
2 5246
13.7%
3 3748
9.8%
4 3413
 
8.9%
5 3394
 
8.9%
0 3038
 
7.9%
6 3024
 
7.9%
7 2690
 
7.0%
9 2383
 
6.2%
8 2322
 
6.1%
Other Punctuation
ValueCountFrequency (%)
, 2750
95.7%
. 109
 
3.8%
@ 5
 
0.2%
/ 3
 
0.1%
' 3
 
0.1%
: 2
 
0.1%
& 2
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 21
55.3%
Ⅰ 13
34.2%
Ⅲ 4
 
10.5%
Space Separator
ValueCountFrequency (%)
45808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6836
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5793
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5793
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 34
100.0%
Control
ValueCountFrequency (%)
10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 148869
58.4%
Common 105379
41.3%
Latin 711
 
0.3%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 15535
 
10.4%
시 9836
 
6.6%
구 8620
 
5.8%
서 7746
 
5.2%
별 6969
 
4.7%
특 6946
 
4.7%
울 6911
 
4.6%
파 6673
 
4.5%
송 5570
 
3.7%
도 2502
 
1.7%
Other values (516) 71561
48.1%
Latin
ValueCountFrequency (%)
A 64
 
9.0%
e 49
 
6.9%
C 48
 
6.8%
S 37
 
5.2%
B 35
 
4.9%
L 32
 
4.5%
M 32
 
4.5%
K 27
 
3.8%
I 26
 
3.7%
T 24
 
3.4%
Other values (37) 337
47.4%
Common
ValueCountFrequency (%)
45808
43.5%
1 8970
 
8.5%
- 6836
 
6.5%
( 5793
 
5.5%
) 5793
 
5.5%
2 5246
 
5.0%
3 3748
 
3.6%
4 3413
 
3.2%
5 3394
 
3.2%
0 3038
 
2.9%
Other values (14) 13340
 
12.7%
Han
ValueCountFrequency (%)
院 2
28.6%
利 2
28.6%
諸 2
28.6%
外 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 148869
58.4%
ASCII 106018
41.6%
Number Forms 38
 
< 0.1%
CJK Compat 34
 
< 0.1%
CJK 5
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45808
43.2%
1 8970
 
8.5%
- 6836
 
6.4%
( 5793
 
5.5%
) 5793
 
5.5%
2 5246
 
4.9%
3 3748
 
3.5%
4 3413
 
3.2%
5 3394
 
3.2%
0 3038
 
2.9%
Other values (57) 13979
 
13.2%
Hangul
ValueCountFrequency (%)
동 15535
 
10.4%
시 9836
 
6.6%
구 8620
 
5.8%
서 7746
 
5.2%
별 6969
 
4.7%
특 6946
 
4.7%
울 6911
 
4.6%
파 6673
 
4.5%
송 5570
 
3.7%
도 2502
 
1.7%
Other values (516) 71561
48.1%
CJK Compat
ValueCountFrequency (%)
㎡ 34
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 21
55.3%
Ⅰ 13
34.2%
Ⅲ 4
 
10.5%
CJK
ValueCountFrequency (%)
院 2
40.0%
諸 2
40.0%
外 1
20.0%
CJK Compat Ideographs
ValueCountFrequency (%)
利 2
100.0%

도로명주소.1
Text

Distinct5639
Distinct (%)56.5%
Missing23
Missing (%)0.2%
Memory size156.2 KiB
2023-12-12T12:04:06.374921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length91
Median length61
Mean length27.137516
Min length1

Characters and Unicode

Total characters270751
Distinct characters636
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4333 ?
Unique (%)43.4%

Sample

1st row경기도 시흥시 시화호수전원2길 10-6 (정왕동)
2nd row서울특별시 강동구 상암로 251 (명일동, 고덕주공아파트)
3rd row서울특별시 송파구 가락로13길 17 (석촌동)
4th row경기도 용인시 기흥구 중부대로 184 (영덕동, 힉스유타워)
5th row 충청남도 논산시 두마면 엄사리 282 성원아파트 9-108,9-203,9-209,
ValueCountFrequency (%)
서울특별시 6232
 
12.4%
송파구 3924
 
7.8%
경기도 1605
 
3.2%
삼전동 609
 
1.2%
석촌동 601
 
1.2%
잠실동 559
 
1.1%
송파동 453
 
0.9%
방이동 446
 
0.9%
강남구 433
 
0.9%
문정동 310
 
0.6%
Other values (8388) 35056
69.8%
2023-12-12T12:04:07.062860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45714
 
16.9%
1 10231
 
3.8%
동 9985
 
3.7%
시 9004
 
3.3%
구 7798
 
2.9%
2 7252
 
2.7%
서 7060
 
2.6%
로 7043
 
2.6%
( 6979
 
2.6%
) 6978
 
2.6%
Other values (626) 152707
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 157739
58.3%
Space Separator 45714
 
16.9%
Decimal Number 44846
 
16.6%
Open Punctuation 6979
 
2.6%
Close Punctuation 6978
 
2.6%
Dash Punctuation 4198
 
1.6%
Other Punctuation 3445
 
1.3%
Uppercase Letter 503
 
0.2%
Lowercase Letter 180
 
0.1%
Control 85
 
< 0.1%
Other values (3) 84
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 9985
 
6.3%
시 9004
 
5.7%
구 7798
 
4.9%
서 7060
 
4.5%
로 7043
 
4.5%
별 6304
 
4.0%
특 6282
 
4.0%
울 6281
 
4.0%
파 6052
 
3.8%
길 5342
 
3.4%
Other values (555) 86588
54.9%
Uppercase Letter
ValueCountFrequency (%)
A 94
18.7%
C 43
 
8.5%
B 41
 
8.2%
S 36
 
7.2%
M 31
 
6.2%
L 28
 
5.6%
I 28
 
5.6%
K 24
 
4.8%
E 24
 
4.8%
T 22
 
4.4%
Other values (15) 132
26.2%
Lowercase Letter
ValueCountFrequency (%)
e 42
23.3%
l 18
10.0%
s 16
 
8.9%
i 14
 
7.8%
u 14
 
7.8%
o 12
 
6.7%
a 10
 
5.6%
r 9
 
5.0%
h 9
 
5.0%
n 8
 
4.4%
Other values (9) 28
15.6%
Decimal Number
ValueCountFrequency (%)
1 10231
22.8%
2 7252
16.2%
3 5393
12.0%
0 4794
10.7%
4 4108
9.2%
5 3310
 
7.4%
6 2876
 
6.4%
8 2382
 
5.3%
7 2331
 
5.2%
9 2169
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 3312
96.1%
. 120
 
3.5%
' 4
 
0.1%
/ 3
 
0.1%
: 2
 
0.1%
& 2
 
0.1%
@ 2
 
0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 19
55.9%
Ⅰ 11
32.4%
Ⅲ 4
 
11.8%
Space Separator
ValueCountFrequency (%)
45714
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6979
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6978
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4198
100.0%
Control
ValueCountFrequency (%)
85
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 47
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 157733
58.3%
Common 112295
41.5%
Latin 717
 
0.3%
Han 6
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 9985
 
6.3%
시 9004
 
5.7%
구 7798
 
4.9%
서 7060
 
4.5%
로 7043
 
4.5%
별 6304
 
4.0%
특 6282
 
4.0%
울 6281
 
4.0%
파 6052
 
3.8%
길 5342
 
3.4%
Other values (552) 86582
54.9%
Latin
ValueCountFrequency (%)
A 94
 
13.1%
C 43
 
6.0%
e 42
 
5.9%
B 41
 
5.7%
S 36
 
5.0%
M 31
 
4.3%
L 28
 
3.9%
I 28
 
3.9%
K 24
 
3.3%
E 24
 
3.3%
Other values (37) 326
45.5%
Common
ValueCountFrequency (%)
45714
40.7%
1 10231
 
9.1%
2 7252
 
6.5%
( 6979
 
6.2%
) 6978
 
6.2%
3 5393
 
4.8%
0 4794
 
4.3%
- 4198
 
3.7%
4 4108
 
3.7%
, 3312
 
2.9%
Other values (14) 13336
 
11.9%
Han
ValueCountFrequency (%)
諸 2
33.3%
利 2
33.3%
院 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 157733
58.3%
ASCII 112931
41.7%
CJK Compat 47
 
< 0.1%
Number Forms 34
 
< 0.1%
CJK 4
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
45714
40.5%
1 10231
 
9.1%
2 7252
 
6.4%
( 6979
 
6.2%
) 6978
 
6.2%
3 5393
 
4.8%
0 4794
 
4.2%
- 4198
 
3.7%
4 4108
 
3.6%
, 3312
 
2.9%
Other values (57) 13972
 
12.4%
Hangul
ValueCountFrequency (%)
동 9985
 
6.3%
시 9004
 
5.7%
구 7798
 
4.9%
서 7060
 
4.5%
로 7043
 
4.5%
별 6304
 
4.0%
특 6282
 
4.0%
울 6281
 
4.0%
파 6052
 
3.8%
길 5342
 
3.4%
Other values (552) 86582
54.9%
CJK Compat
ValueCountFrequency (%)
㎡ 47
100.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 19
55.9%
Ⅰ 11
32.4%
Ⅲ 4
 
11.8%
CJK
ValueCountFrequency (%)
諸 2
50.0%
院 2
50.0%
CJK Compat Ideographs
ValueCountFrequency (%)
利 2
100.0%

임시주소
Text

MISSING 

Distinct763
Distinct (%)99.7%
Missing9235
Missing (%)92.3%
Memory size156.2 KiB
2023-12-12T12:04:07.524982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length61
Mean length34.162092
Min length20

Characters and Unicode

Total characters26134
Distinct characters366
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique761 ?
Unique (%)99.5%

Sample

1st row경기도 하남시 하남미사지구 업무 1-2,3블럭 하남미사 우성르보아파크Ⅱ 1241호
2nd row경기도 고양시 일산서구 탄현동 1559-1번지 신한 헤스티아 오피스텔 1018호
3rd row경기도 하남시 하남미사(09, 보금3)지구 2308-1(업무 8-1블럭)외 미사 인스타 시티 937호
4th row경기도 남양주시 진건읍 다산진건 공공주택지구 상업용지1 블럭 1-2,3 로트 다산 헤리움 그랑비스타 1차 519호
5th row서울특별시 강동구 명일동 188, 203호
ValueCountFrequency (%)
서울특별시 508
 
9.6%
송파구 221
 
4.2%
경기도 209
 
4.0%
외 127
 
2.4%
하남시 105
 
2.0%
강남구 88
 
1.7%
2필지 72
 
1.4%
삼성동 71
 
1.3%
140-32 59
 
1.1%
강서구 58
 
1.1%
Other values (1318) 3747
71.2%
2023-12-12T12:04:08.237687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4517
 
17.3%
1 1580
 
6.0%
2 1045
 
4.0%
0 958
 
3.7%
시 932
 
3.6%
동 854
 
3.3%
호 750
 
2.9%
- 705
 
2.7%
구 702
 
2.7%
3 636
 
2.4%
Other values (356) 13455
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14018
53.6%
Decimal Number 6229
23.8%
Space Separator 4517
 
17.3%
Dash Punctuation 705
 
2.7%
Other Punctuation 281
 
1.1%
Uppercase Letter 160
 
0.6%
Close Punctuation 84
 
0.3%
Open Punctuation 84
 
0.3%
Lowercase Letter 29
 
0.1%
Letter Number 24
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 932
 
6.6%
동 854
 
6.1%
호 750
 
5.4%
구 702
 
5.0%
서 612
 
4.4%
울 524
 
3.7%
별 514
 
3.7%
특 511
 
3.6%
지 405
 
2.9%
도 313
 
2.2%
Other values (306) 7901
56.4%
Uppercase Letter
ValueCountFrequency (%)
B 55
34.4%
L 48
30.0%
A 14
 
8.8%
C 11
 
6.9%
T 9
 
5.6%
S 5
 
3.1%
R 3
 
1.9%
N 3
 
1.9%
P 2
 
1.2%
K 2
 
1.2%
Other values (7) 8
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
e 11
37.9%
h 6
20.7%
o 3
 
10.3%
s 2
 
6.9%
t 1
 
3.4%
a 1
 
3.4%
n 1
 
3.4%
i 1
 
3.4%
l 1
 
3.4%
m 1
 
3.4%
Decimal Number
ValueCountFrequency (%)
1 1580
25.4%
2 1045
16.8%
0 958
15.4%
3 636
10.2%
4 520
 
8.3%
5 383
 
6.1%
8 315
 
5.1%
6 288
 
4.6%
7 285
 
4.6%
9 219
 
3.5%
Other Punctuation
ValueCountFrequency (%)
, 267
95.0%
. 10
 
3.6%
/ 4
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 83
98.8%
] 1
 
1.2%
Open Punctuation
ValueCountFrequency (%)
( 83
98.8%
[ 1
 
1.2%
Letter Number
ValueCountFrequency (%)
Ⅱ 23
95.8%
Ⅰ 1
 
4.2%
Space Separator
ValueCountFrequency (%)
4517
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 705
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14018
53.6%
Common 11903
45.5%
Latin 213
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 932
 
6.6%
동 854
 
6.1%
호 750
 
5.4%
구 702
 
5.0%
서 612
 
4.4%
울 524
 
3.7%
별 514
 
3.7%
특 511
 
3.6%
지 405
 
2.9%
도 313
 
2.2%
Other values (306) 7901
56.4%
Latin
ValueCountFrequency (%)
B 55
25.8%
L 48
22.5%
Ⅱ 23
10.8%
A 14
 
6.6%
C 11
 
5.2%
e 11
 
5.2%
T 9
 
4.2%
h 6
 
2.8%
S 5
 
2.3%
R 3
 
1.4%
Other values (20) 28
13.1%
Common
ValueCountFrequency (%)
4517
37.9%
1 1580
 
13.3%
2 1045
 
8.8%
0 958
 
8.0%
- 705
 
5.9%
3 636
 
5.3%
4 520
 
4.4%
5 383
 
3.2%
8 315
 
2.6%
6 288
 
2.4%
Other values (10) 956
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14018
53.6%
ASCII 12092
46.3%
Number Forms 24
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4517
37.4%
1 1580
 
13.1%
2 1045
 
8.6%
0 958
 
7.9%
- 705
 
5.8%
3 636
 
5.3%
4 520
 
4.3%
5 383
 
3.2%
8 315
 
2.6%
6 288
 
2.4%
Other values (38) 1145
 
9.5%
Hangul
ValueCountFrequency (%)
시 932
 
6.6%
동 854
 
6.1%
호 750
 
5.4%
구 702
 
5.0%
서 612
 
4.4%
울 524
 
3.7%
별 514
 
3.7%
특 511
 
3.6%
지 405
 
2.9%
도 313
 
2.2%
Other values (306) 7901
56.4%
Number Forms
ValueCountFrequency (%)
Ⅱ 23
95.8%
Ⅰ 1
 
4.2%

동명
Text

MISSING 

Distinct733
Distinct (%)29.6%
Missing7525
Missing (%)75.2%
Memory size156.2 KiB
2023-12-12T12:04:08.613200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length19
Mean length4.5753535
Min length1

Characters and Unicode

Total characters11324
Distinct characters319
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique397 ?
Unique (%)16.0%

Sample

1st row주건축물제1동
2nd row908동
3rd rowB동
4th row주건축물제1동
5th row102
ValueCountFrequency (%)
101동 100
 
3.4%
주건축물제1동 84
 
2.9%
102동 73
 
2.5%
103동 58
 
2.0%
1동 52
 
1.8%
101 51
 
1.7%
b동 41
 
1.4%
롯데캐슬 37
 
1.3%
105동 37
 
1.3%
104동 36
 
1.2%
Other values (808) 2367
80.6%
2023-12-12T12:04:09.160029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1572
 
13.9%
동 1237
 
10.9%
0 1146
 
10.1%
2 595
 
5.3%
461
 
4.1%
3 317
 
2.8%
4 248
 
2.2%
5 230
 
2.0%
스 206
 
1.8%
6 192
 
1.7%
Other values (309) 5120
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5816
51.4%
Decimal Number 4667
41.2%
Space Separator 461
 
4.1%
Uppercase Letter 291
 
2.6%
Letter Number 29
 
0.3%
Lowercase Letter 20
 
0.2%
Open Punctuation 11
 
0.1%
Close Punctuation 11
 
0.1%
Other Punctuation 11
 
0.1%
Dash Punctuation 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1237
 
21.3%
스 206
 
3.5%
주 134
 
2.3%
빌 130
 
2.2%
파 120
 
2.1%
시 109
 
1.9%
사 109
 
1.9%
미 106
 
1.8%
제 105
 
1.8%
크 104
 
1.8%
Other values (264) 3456
59.4%
Uppercase Letter
ValueCountFrequency (%)
A 68
23.4%
B 68
23.4%
C 22
 
7.6%
S 15
 
5.2%
E 14
 
4.8%
T 12
 
4.1%
M 12
 
4.1%
I 11
 
3.8%
U 10
 
3.4%
P 9
 
3.1%
Other values (10) 50
17.2%
Decimal Number
ValueCountFrequency (%)
1 1572
33.7%
0 1146
24.6%
2 595
 
12.7%
3 317
 
6.8%
4 248
 
5.3%
5 230
 
4.9%
6 192
 
4.1%
7 143
 
3.1%
8 120
 
2.6%
9 104
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
e 10
50.0%
s 3
 
15.0%
n 3
 
15.0%
t 3
 
15.0%
c 1
 
5.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 14
48.3%
Ⅱ 14
48.3%
Ⅲ 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 8
72.7%
, 2
 
18.2%
/ 1
 
9.1%
Space Separator
ValueCountFrequency (%)
461
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5815
51.4%
Common 5168
45.6%
Latin 340
 
3.0%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1237
 
21.3%
스 206
 
3.5%
주 134
 
2.3%
빌 130
 
2.2%
파 120
 
2.1%
시 109
 
1.9%
사 109
 
1.9%
미 106
 
1.8%
제 105
 
1.8%
크 104
 
1.8%
Other values (263) 3455
59.4%
Latin
ValueCountFrequency (%)
A 68
20.0%
B 68
20.0%
C 22
 
6.5%
S 15
 
4.4%
E 14
 
4.1%
Ⅰ 14
 
4.1%
Ⅱ 14
 
4.1%
T 12
 
3.5%
M 12
 
3.5%
I 11
 
3.2%
Other values (18) 90
26.5%
Common
ValueCountFrequency (%)
1 1572
30.4%
0 1146
22.2%
2 595
 
11.5%
461
 
8.9%
3 317
 
6.1%
4 248
 
4.8%
5 230
 
4.5%
6 192
 
3.7%
7 143
 
2.8%
8 120
 
2.3%
Other values (7) 144
 
2.8%
Han
ValueCountFrequency (%)
家 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5815
51.4%
ASCII 5479
48.4%
Number Forms 29
 
0.3%
CJK 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1572
28.7%
0 1146
20.9%
2 595
 
10.9%
461
 
8.4%
3 317
 
5.8%
4 248
 
4.5%
5 230
 
4.2%
6 192
 
3.5%
7 143
 
2.6%
8 120
 
2.2%
Other values (32) 455
 
8.3%
Hangul
ValueCountFrequency (%)
동 1237
 
21.3%
스 206
 
3.5%
주 134
 
2.3%
빌 130
 
2.2%
파 120
 
2.1%
시 109
 
1.9%
사 109
 
1.9%
미 106
 
1.8%
제 105
 
1.8%
크 104
 
1.8%
Other values (263) 3455
59.4%
Number Forms
ValueCountFrequency (%)
Ⅰ 14
48.3%
Ⅱ 14
48.3%
Ⅲ 1
 
3.4%
CJK
ValueCountFrequency (%)
家 1
100.0%

호명
Text

MISSING 

Distinct1182
Distinct (%)16.8%
Missing2961
Missing (%)29.6%
Memory size156.2 KiB
2023-12-12T12:04:09.575267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length3
Mean length3.5171189
Min length1

Characters and Unicode

Total characters24757
Distinct characters50
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique656 ?
Unique (%)9.3%

Sample

1st row205
2nd row901호
3rd row202
4th row219
5th row302
ValueCountFrequency (%)
301 343
 
4.9%
201 341
 
4.8%
302 339
 
4.8%
202 301
 
4.3%
401 272
 
3.8%
402 264
 
3.7%
203 196
 
2.8%
501 188
 
2.7%
303 172
 
2.4%
502 136
 
1.9%
Other values (1166) 4518
63.9%
2023-12-12T12:04:10.173744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6427
26.0%
1 4341
17.5%
2 3777
15.3%
3 2783
11.2%
4 1944
 
7.9%
호 1631
 
6.6%
5 1098
 
4.4%
6 722
 
2.9%
7 535
 
2.2%
8 490
 
2.0%
Other values (40) 1009
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22577
91.2%
Other Letter 1889
 
7.6%
Uppercase Letter 142
 
0.6%
Dash Punctuation 111
 
0.4%
Space Separator 32
 
0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 1631
86.3%
층 105
 
5.6%
지 33
 
1.7%
동 30
 
1.6%
이 16
 
0.8%
에 10
 
0.5%
씨 10
 
0.5%
비 9
 
0.5%
오 6
 
0.3%
피 5
 
0.3%
Other values (17) 34
 
1.8%
Decimal Number
ValueCountFrequency (%)
0 6427
28.5%
1 4341
19.2%
2 3777
16.7%
3 2783
12.3%
4 1944
 
8.6%
5 1098
 
4.9%
6 722
 
3.2%
7 535
 
2.4%
8 490
 
2.2%
9 460
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
B 57
40.1%
A 52
36.6%
C 19
 
13.4%
F 5
 
3.5%
D 5
 
3.5%
O 1
 
0.7%
S 1
 
0.7%
I 1
 
0.7%
T 1
 
0.7%
Dash Punctuation
ValueCountFrequency (%)
- 111
100.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22726
91.8%
Hangul 1889
 
7.6%
Latin 142
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 1631
86.3%
층 105
 
5.6%
지 33
 
1.7%
동 30
 
1.6%
이 16
 
0.8%
에 10
 
0.5%
씨 10
 
0.5%
비 9
 
0.5%
오 6
 
0.3%
피 5
 
0.3%
Other values (17) 34
 
1.8%
Common
ValueCountFrequency (%)
0 6427
28.3%
1 4341
19.1%
2 3777
16.6%
3 2783
12.2%
4 1944
 
8.6%
5 1098
 
4.8%
6 722
 
3.2%
7 535
 
2.4%
8 490
 
2.2%
9 460
 
2.0%
Other values (4) 149
 
0.7%
Latin
ValueCountFrequency (%)
B 57
40.1%
A 52
36.6%
C 19
 
13.4%
F 5
 
3.5%
D 5
 
3.5%
O 1
 
0.7%
S 1
 
0.7%
I 1
 
0.7%
T 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22868
92.4%
Hangul 1889
 
7.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6427
28.1%
1 4341
19.0%
2 3777
16.5%
3 2783
12.2%
4 1944
 
8.5%
5 1098
 
4.8%
6 722
 
3.2%
7 535
 
2.3%
8 490
 
2.1%
9 460
 
2.0%
Other values (13) 291
 
1.3%
Hangul
ValueCountFrequency (%)
호 1631
86.3%
층 105
 
5.6%
지 33
 
1.7%
동 30
 
1.6%
이 16
 
0.8%
에 10
 
0.5%
씨 10
 
0.5%
비 9
 
0.5%
오 6
 
0.3%
피 5
 
0.3%
Other values (17) 34
 
1.8%

실명
Text

MISSING 

Distinct158
Distinct (%)10.0%
Missing8415
Missing (%)84.2%
Memory size156.2 KiB
2023-12-12T12:04:10.506037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.0574132
Min length1

Characters and Unicode

Total characters4846
Distinct characters29
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)4.9%

Sample

1st row301
2nd row403
3rd row305
4th row5층
5th row1층
ValueCountFrequency (%)
201 123
 
7.7%
301 121
 
7.6%
202 111
 
7.0%
302 100
 
6.3%
401 78
 
4.9%
101 75
 
4.7%
102 73
 
4.6%
203 66
 
4.1%
402 57
 
3.6%
303 55
 
3.4%
Other values (143) 736
46.1%
2023-12-12T12:04:11.011490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1446
29.8%
2 888
18.3%
1 816
16.8%
3 656
13.5%
4 373
 
7.7%
층 142
 
2.9%
B 132
 
2.7%
5 132
 
2.7%
호 96
 
2.0%
6 47
 
1.0%
Other values (19) 118
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4378
90.3%
Other Letter 320
 
6.6%
Uppercase Letter 132
 
2.7%
Space Separator 11
 
0.2%
Dash Punctuation 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
층 142
44.4%
호 96
30.0%
지 47
 
14.7%
하 12
 
3.8%
실 8
 
2.5%
좌 3
 
0.9%
측 3
 
0.9%
상 2
 
0.6%
월 1
 
0.3%
일 1
 
0.3%
Other values (5) 5
 
1.6%
Decimal Number
ValueCountFrequency (%)
0 1446
33.0%
2 888
20.3%
1 816
18.6%
3 656
15.0%
4 373
 
8.5%
5 132
 
3.0%
6 47
 
1.1%
7 16
 
0.4%
8 4
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
B 132
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4392
90.6%
Hangul 320
 
6.6%
Latin 134
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
층 142
44.4%
호 96
30.0%
지 47
 
14.7%
하 12
 
3.8%
실 8
 
2.5%
좌 3
 
0.9%
측 3
 
0.9%
상 2
 
0.6%
월 1
 
0.3%
일 1
 
0.3%
Other values (5) 5
 
1.6%
Common
ValueCountFrequency (%)
0 1446
32.9%
2 888
20.2%
1 816
18.6%
3 656
14.9%
4 373
 
8.5%
5 132
 
3.0%
6 47
 
1.1%
7 16
 
0.4%
11
 
0.3%
8 4
 
0.1%
Other values (2) 3
 
0.1%
Latin
ValueCountFrequency (%)
B 132
98.5%
b 2
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4526
93.4%
Hangul 320
 
6.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1446
31.9%
2 888
19.6%
1 816
18.0%
3 656
14.5%
4 373
 
8.2%
B 132
 
2.9%
5 132
 
2.9%
6 47
 
1.0%
7 16
 
0.4%
11
 
0.2%
Other values (4) 9
 
0.2%
Hangul
ValueCountFrequency (%)
층 142
44.4%
호 96
30.0%
지 47
 
14.7%
하 12
 
3.8%
실 8
 
2.5%
좌 3
 
0.9%
측 3
 
0.9%
상 2
 
0.6%
월 1
 
0.3%
일 1
 
0.3%
Other values (5) 5
 
1.6%

종류
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
장기일반민간임대주택(8년)
3741 
준공공임대
1413 
단기임대
1313 
매입임대주택
1064 
단기민간임대주택
968 
Other values (10)
1501 

Length

Max length15
Median length14
Mean length9.1273
Min length2

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row장기일반민간임대주택(8년)
2nd row준공공임대
3rd row<NA>
4th row단기민간임대주택
5th row<NA>

Common Values

ValueCountFrequency (%)
장기일반민간임대주택(8년) 3741
37.4%
준공공임대 1413
 
14.1%
단기임대 1313
 
13.1%
매입임대주택 1064
 
10.6%
단기민간임대주택 968
 
9.7%
5년임대주택(민간) 741
 
7.4%
<NA> 446
 
4.5%
공공지원민간임대주택(8년) 118
 
1.2%
기업형임대 89
 
0.9%
장기일반민간임대주택(10년) 67
 
0.7%
Other values (5) 40
 
0.4%

Length

2023-12-12T12:04:11.212721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
장기일반민간임대주택(8년 3741
37.4%
준공공임대 1413
 
14.1%
단기임대 1313
 
13.1%
매입임대주택 1064
 
10.6%
단기민간임대주택 968
 
9.7%
5년임대주택(민간 741
 
7.4%
na 446
 
4.5%
공공지원민간임대주택(8년 118
 
1.2%
기업형임대 89
 
0.9%
장기일반민간임대주택(10년 67
 
0.7%
Other values (5) 40
 
0.4%

유형
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
다세대주택
3755 
준주택(오피스텔)
1867 
아파트
1771 
다가구주택
1311 
도시형생활주택
414 
Other values (3)
882 

Length

Max length9
Median length5
Mean length5.3872
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row다세대주택
2nd row아파트
3rd row다세대주택
4th row준주택(오피스텔)
5th row<NA>

Common Values

ValueCountFrequency (%)
다세대주택 3755
37.5%
준주택(오피스텔) 1867
18.7%
아파트 1771
17.7%
다가구주택 1311
 
13.1%
도시형생활주택 414
 
4.1%
<NA> 410
 
4.1%
단독주택 392
 
3.9%
연립주택 80
 
0.8%

Length

2023-12-12T12:04:11.380271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:04:11.555426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
다세대주택 3755
37.5%
준주택(오피스텔 1867
18.7%
아파트 1771
17.7%
다가구주택 1311
 
13.1%
도시형생활주택 414
 
4.1%
na 410
 
4.1%
단독주택 392
 
3.9%
연립주택 80
 
0.8%

면적
Real number (ℝ)

MISSING 

Distinct4364
Distinct (%)45.2%
Missing340
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean41.158872
Minimum0
Maximum658.44
Zeros16
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T12:04:11.740758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16.58
Q123.09
median34.29125
Q351.03
95-th percentile84.9184
Maximum658.44
Range658.44
Interquartile range (IQR)27.94

Descriptive statistics

Standard deviation29.374744
Coefficient of variation (CV)0.71369168
Kurtosis81.574185
Mean41.158872
Median Absolute Deviation (MAD)12.97125
Skewness6.0876143
Sum397594.7
Variance862.87561
MonotonicityNot monotonic
2023-12-12T12:04:11.925487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.95 70
 
0.7%
20.0 54
 
0.5%
1.0 50
 
0.5%
30.0 29
 
0.3%
22.0 27
 
0.3%
22.05 27
 
0.3%
20.79 25
 
0.2%
17.17 24
 
0.2%
27.68 24
 
0.2%
21.02 24
 
0.2%
Other values (4354) 9306
93.1%
(Missing) 340
 
3.4%
ValueCountFrequency (%)
0.0 16
 
0.2%
1.0 50
0.5%
4.18 1
 
< 0.1%
7.38 1
 
< 0.1%
8.25 1
 
< 0.1%
9.23 1
 
< 0.1%
9.4 2
 
< 0.1%
9.56 1
 
< 0.1%
10.0 1
 
< 0.1%
10.08 1
 
< 0.1%
ValueCountFrequency (%)
658.44 1
< 0.1%
549.45 1
< 0.1%
523.26 1
< 0.1%
520.3 1
< 0.1%
519.58 1
< 0.1%
469.95 1
< 0.1%
461.28 1
< 0.1%
446.08 1
< 0.1%
433.63 1
< 0.1%
426.63 1
< 0.1%

Interactions

2023-12-12T12:04:00.500308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:04:12.054985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업구분사업자구분임대주택구분종류유형면적
영업구분1.0000.4290.1030.3460.1980.063
사업자구분0.4291.0000.8140.9030.3980.059
임대주택구분0.1030.8141.0000.6740.4110.182
종류0.3460.9030.6741.0000.6000.087
유형0.1980.3980.4110.6001.0000.356
면적0.0630.0590.1820.0870.3561.000
2023-12-12T12:04:12.178859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
임대주택구분사업자구분유형영업구분종류
임대주택구분1.0000.6180.4400.0660.536
사업자구분0.6181.0000.2500.3090.735
유형0.4400.2501.0000.2120.265
영업구분0.0660.3090.2121.0000.270
종류0.5360.7350.2650.2701.000
2023-12-12T12:04:12.313369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적영업구분사업자구분임대주택구분종류유형
면적1.0000.0490.0310.1400.0350.189
영업구분0.0491.0000.3090.0660.2700.212
사업자구분0.0310.3091.0000.6180.7350.250
임대주택구분0.1400.0660.6181.0000.5360.440
종류0.0350.2700.7350.5361.0000.265
유형0.1890.2120.2500.4400.2651.000

Missing values

2023-12-12T12:04:00.724573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:04:01.020104image/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.
2023-12-12T12:04:01.311540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

영업구분등록번호사업자구분도로명주소임대주택구분지번주소도로명주소.1임시주소동명호명실명종류유형면적
251전입영업중2020-송파구-임대사업자-3076임대사업자서울특별시 송파구 올림픽로 135 252동 1004호 (잠실동, 리센츠)민간건설임대주택경기도 시흥시 정왕동 2748-3 (정왕동)경기도 시흥시 시화호수전원2길 10-6 (정왕동)<NA>주건축물제1동205<NA>장기일반민간임대주택(8년)다세대주택19.555
14856전입영업중2019-송파구-임대사업자-426일반형임대사업자서울특별시 송파구 올림픽로35길 104 12동 401호 (신천동, 장미아파트)민간매입임대주택서울특별시 강동구 명일동 257 (명일동, 고덕주공아파트)서울특별시 강동구 상암로 251 (명일동, 고덕주공아파트)<NA>908동901호<NA>준공공임대아파트83.34
29033등록영업중2004-송파구-임대사업자-1694허가건설임대사업자서울특별시 송파구 가락로13길 17 401민간건설임대주택서울특별시 송파구 석촌동 268-21 (석촌동)서울특별시 송파구 가락로13길 17 (석촌동)<NA><NA>202<NA><NA>다세대주택40.55
7052등록영업중2019-송파구-임대사업자-4676임대사업자서울특별시 송파구 가락로 192 22동 506호 (송파동, 한양아파트)민간매입임대주택경기도 용인시 기흥구 영덕동 1315 (영덕동, 힉스유타워)경기도 용인시 기흥구 중부대로 184 (영덕동, 힉스유타워)<NA>B동219<NA>단기민간임대주택준주택(오피스텔)23.15
22353전입영업중2018-송파구-임대사업자-17499매입임대사업자서울특별시 송파구 올림픽로 99 136동 301호 (잠실동, 잠실엘스)민간매입임대주택충청남도 계룡시 엄사면 엄사리 282 성원아파트 9-108,9-203,9-209,충청남도 논산시 두마면 엄사리 282 성원아파트 9-108,9-203,9-209,<NA><NA><NA><NA><NA><NA><NA>
26707등록영업중2006-송파구-임대사업자-2366매입임대사업자서울특별시 송파구 백제고분로32길 12-16민간매입임대주택서울특별시 송파구 삼전동 163-5서울특별시 송파구 삼전동 163-5 302호<NA><NA>302<NA>매입임대주택다세대주택39.41
6294등록영업중2020-송파구-임대사업자-263임대사업자서울특별시 송파구 송파대로 345 109동 602호 (가락동, 헬리오시티)민간매입임대주택서울특별시 중랑구 면목동 576-5 (면목동)서울특별시 중랑구 면목동 사가정로41길 52-8 (면목동)<NA><NA><NA>301장기일반민간임대주택(8년)단독주택58.32
14808전입영업중2019-송파구-임대사업자-455임대사업자서울특별시 송파구 잠실로 62 335동 1702호 (잠실동, 트리지움)민간매입임대주택서울특별시 강남구 역삼동 691-5 (역삼동)서울특별시 강남구 봉은사로48길 44-13 (역삼동)<NA><NA>102<NA>장기일반민간임대주택(8년)다세대주택26.78
9842등록영업중2019-송파구-임대사업자-3162임대사업자서울특별시 송파구 올림픽로 99 104동 1602호 (잠실동, 잠실엘스)민간매입임대주택경기도 하남시 하남미사지구 업무 1-2,3블럭 하남미사 우성르보아파크Ⅱ 1241호<NA><NA><NA>단기민간임대주택준주택(오피스텔)17.95
8463전입영업중2019-송파구-임대사업자-3918매입임대사업자서울특별시 송파구 새말로 62 1471호 (문정동, 송파푸르지오시티)민간매입임대주택경기도 고양시 일산서구 탄현동 1559-1번지 신한 헤스티아 오피스텔 1018호<NA>1018<NA>단기민간임대주택준주택(오피스텔)21.81
영업구분등록번호사업자구분도로명주소임대주택구분지번주소도로명주소.1임시주소동명호명실명종류유형면적
27116등록영업중2005-송파구-임대사업자-2248허가건설임대사업자서울특별시 송파구 백제고분로11길 8-23민간건설임대주택서울특별시 송파구 잠실동 224-5서울특별시 송파구 잠실동 224-5 402호<NA><NA>402<NA>5년임대주택(민간)다세대주택32.12
19836전입영업중2018-송파구-임대사업자-18768일반형임대사업자서울특별시 송파구 잠실로 62 322동 602호 (잠실동, 트리지움)민간매입임대주택서울특별시 은평구 응암동 419번지 일원 백련산 SK VIEW IPARK 107동 803호<NA><NA><NA>장기일반민간임대주택(8년)아파트84.9039
8648등록영업중2019-송파구-임대사업자-3825임대사업자서울특별시 송파구 중대로 24 227동 601호 (문정동, 올림픽훼밀리타운아파트)민간매입임대주택경기도 용인시 수지구 죽전동 875 (죽전동, 서영선씨 주택)경기도 용인시 수지구 용구대로2787번길 9-12 (죽전동, 서영선씨 주택)<NA><NA><NA>B103장기일반민간임대주택(8년)다가구주택32.42
8814등록영업중2019-송파구-임대사업자-3697임대사업자서울특별시 송파구 백제고분로41길 36-12민간매입임대주택서울특별시 송파구 송파동 28-8 (송파동)서울특별시 송파구 백제고분로41길 36-12 (송파동)<NA><NA><NA>102장기일반민간임대주택(8년)다가구주택32.76
18128등록영업중2018-송파구-임대사업자-19991임대사업자서울특별시 송파구 올림픽로 135 216동 2201호 (잠실동, 리센츠)민간매입임대주택경기도 성남시 수정구 신흥동 6491 (신흥동)경기도 성남시 수정구 탄리로 40-4 (신흥동)<NA><NA><NA>1장기일반민간임대주택(8년)다가구주택144.33
1147전입영업중2020-송파구-임대사업자-2613일반형임대사업자서울특별시 송파구 위례성대로8길 16 403호 (방이동, 다온빌)민간매입임대주택서울특별시 중랑구 면목동 381-2 (면목동)서울특별시 중랑구 면목동 면목로27다길 6 (면목동)<NA><NA>602호<NA>단기임대다세대주택24.57
35492전입영업중2018-송파구-임대사업자-14817일반형임대사업자서울특별시 송파구 송이로30길 11 (문정동)민간매입임대주택서울특별시 송파구 문정동 652-1 (문정동, 프라비다옥토 오피스텔)<NA><NA>706<NA>단기임대준주택(오피스텔)18.75
17939등록영업중2018-송파구-임대사업자-20100임대사업자서울특별시 송파구 석촌호수로 210 706호 (석촌동, 효성해링턴타워)민간매입임대주택서울특별시 강남구 청담동 40-18 (청담동)서울특별시 강남구 선릉로132길 3-8 (청담동)<NA><NA><NA>303장기일반민간임대주택(8년)다가구주택44.38
12059등록영업중2019-송파구-임대사업자-2073임대사업자서울특별시 송파구 백제고분로50길 15-21민간매입임대주택서울특별시 송파구 방이동 49-4 (방이동, 아주리센 센트럴파크)서울특별시 송파구 오금로11길 55-8 (방이동, 아주리센 센트럴파크)<NA><NA>803<NA>단기민간임대주택준주택(오피스텔)28.88
4010등록영업중2020-송파구-임대사업자-1383임대사업자서울특별시 송파구 송파대로 345 108동 2003호 (가락동, 헬리오시티)민간매입임대주택경기도 성남시 분당구 운중동 918 (운중동, 산운마을)경기도 성남시 분당구 판교원로82번길 30 (운중동, 산운마을)<NA>1307동2903<NA>장기일반민간임대주택(8년)아파트84.92

Duplicate rows

Most frequently occurring

영업구분등록번호사업자구분도로명주소임대주택구분지번주소도로명주소.1임시주소동명호명실명종류유형면적# duplicates
0등록영업중2003-송파구-임대사업자-1566허가건설임대사업자서울특별시 송파구 백제고분로19길 4-12민간건설임대주택서울특별시 송파구 잠실동 250-18 (잠실동)서울특별시 송파구 백제고분로19길 4-12 (잠실동)<NA><NA>403호<NA><NA><NA><NA>2
1등록영업중2004-송파구-임대사업자-1602허가건설임대사업자서울특별시 송파구 삼전로6길 25 501호 (삼전동, 전원빌라)민간건설임대주택서울특별시 송파구 삼전동 46-5 (삼전동)서울특별시 송파구 삼전로6길 25 (삼전동)<NA><NA>402<NA>5년임대주택(민간)다세대주택58.842
2등록영업중2004-송파구-임대사업자-1681허가건설임대사업자서울특별시 송파구 송파대로48길 6 (송파동)민간건설임대주택서울특별시 송파구 송파동 9-4서울특별시 송파구 송파동 9-4 402호<NA><NA>402<NA><NA><NA><NA>2
3등록영업중2004-송파구-임대사업자-1766허가건설임대사업자서울특별시 송파구 올림픽로32길 42-10민간건설임대주택서울특별시 송파구 방이동 93-8 (방이동)서울특별시 송파구 올림픽로32길 42-10 (방이동)<NA><NA>303<NA>5년임대주택(민간)다세대주택47.732
4전입영업중2018-송파구-임대사업자-18001허가건설임대사업자서울특별시 송파구 잠실로 88 130동 1102호 (잠실동, 레이크팰리스)민간건설임대주택서울특별시 강남구 논현동 173-7서울특별시 강남구 논현동 173-7<NA><NA><NA><NA>5년임대주택(민간)다세대주택46.012