Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells13696
Missing cells (%)10.5%
Duplicate rows5
Duplicate rows (%)0.1%
Total size in memory1.1 MiB
Average record size in memory115.0 B

Variable types

Categorical5
Text5
DateTime2
Numeric1

Alerts

lastupdtdt has constant value ""Constant
Dataset has 5 (0.1%) duplicate rowsDuplicates
ofcpssecodenm is highly overall correlated with brkrasortcode and 2 other fieldsHigh correlation
brkrasortcode is highly overall correlated with brkrasortcodenm and 2 other fieldsHigh correlation
ofcpssecode is highly overall correlated with brkrasortcode and 2 other fieldsHigh correlation
brkrasortcodenm is highly overall correlated with brkrasortcode and 2 other fieldsHigh correlation
ldcode is highly overall correlated with ldcodenmHigh correlation
ldcodenm is highly overall correlated with ldcodeHigh correlation
bsnmcmpnm has 2705 (27.1%) missing valuesMissing
crqfcacqdt has 4204 (42.0%) missing valuesMissing
crqfcno has 4082 (40.8%) missing valuesMissing
jurirno has 2705 (27.1%) missing valuesMissing

Reproduction

Analysis started2024-04-16 10:26:03.845030
Analysis finished2024-04-16 10:26:05.588745
Duration1.74 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

brkrasortcode
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2
6541 
4
3256 
1
 
201
3
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row2
3rd row2
4th row4
5th row2

Common Values

ValueCountFrequency (%)
2 6541
65.4%
4 3256
32.6%
1 201
 
2.0%
3 2
 
< 0.1%

Length

2024-04-16T19:26:05.645946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:26:05.731835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 6541
65.4%
4 3256
32.6%
1 201
 
2.0%
3 2
 
< 0.1%

brkrasortcodenm
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
공인중개사
6541 
중개보조원
3256 
중개인
 
201
법인
 
2

Length

Max length5
Median length5
Mean length4.9592
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row중개보조원
2nd row공인중개사
3rd row공인중개사
4th row중개보조원
5th row공인중개사

Common Values

ValueCountFrequency (%)
공인중개사 6541
65.4%
중개보조원 3256
32.6%
중개인 201
 
2.0%
법인 2
 
< 0.1%

Length

2024-04-16T19:26:05.822069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:26:05.913362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공인중개사 6541
65.4%
중개보조원 3256
32.6%
중개인 201
 
2.0%
법인 2
 
< 0.1%

brkrnm
Text

Distinct7919
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-04-16T19:26:06.191652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length3
Mean length3.0137
Min length2

Characters and Unicode

Total characters30137
Distinct characters385
Distinct categories5 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6670 ?
Unique (%)66.7%

Sample

1st row김영홍
2nd row최미숙
3rd row강수영
4th row김석제
5th row김우용
ValueCountFrequency (%)
김영희 19
 
0.2%
김정숙 14
 
0.1%
김민정 11
 
0.1%
김경희 11
 
0.1%
이영주 11
 
0.1%
김인숙 10
 
0.1%
이정희 10
 
0.1%
정영희 9
 
0.1%
이정훈 9
 
0.1%
김정희 9
 
0.1%
Other values (7914) 9894
98.9%
2024-04-16T19:26:06.655646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 2264
 
7.5%
이 1412
 
4.7%
정 1349
 
4.5%
영 1001
 
3.3%
박 904
 
3.0%
희 702
 
2.3%
경 614
 
2.0%
미 560
 
1.9%
성 551
 
1.8%
숙 549
 
1.8%
Other values (375) 20231
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30038
99.7%
Open Punctuation 41
 
0.1%
Close Punctuation 41
 
0.1%
Uppercase Letter 9
 
< 0.1%
Space Separator 8
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 2264
 
7.5%
이 1412
 
4.7%
정 1349
 
4.5%
영 1001
 
3.3%
박 904
 
3.0%
희 702
 
2.3%
경 614
 
2.0%
미 560
 
1.9%
성 551
 
1.8%
숙 549
 
1.8%
Other values (366) 20132
67.0%
Uppercase Letter
ValueCountFrequency (%)
I 3
33.3%
N 2
22.2%
Y 1
 
11.1%
A 1
 
11.1%
T 1
 
11.1%
J 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 41
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 29920
99.3%
Han 118
 
0.4%
Common 90
 
0.3%
Latin 9
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 2264
 
7.6%
이 1412
 
4.7%
정 1349
 
4.5%
영 1001
 
3.3%
박 904
 
3.0%
희 702
 
2.3%
경 614
 
2.1%
미 560
 
1.9%
성 551
 
1.8%
숙 549
 
1.8%
Other values (284) 20014
66.9%
Han
ValueCountFrequency (%)
金 8
 
6.8%
李 6
 
5.1%
鄭 5
 
4.2%
崔 5
 
4.2%
子 4
 
3.4%
朴 3
 
2.5%
順 3
 
2.5%
基 3
 
2.5%
根 2
 
1.7%
成 2
 
1.7%
Other values (72) 77
65.3%
Latin
ValueCountFrequency (%)
I 3
33.3%
N 2
22.2%
Y 1
 
11.1%
A 1
 
11.1%
T 1
 
11.1%
J 1
 
11.1%
Common
ValueCountFrequency (%)
( 41
45.6%
) 41
45.6%
8
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 29919
99.3%
CJK 111
 
0.4%
ASCII 99
 
0.3%
CJK Compat Ideographs 7
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 2264
 
7.6%
이 1412
 
4.7%
정 1349
 
4.5%
영 1001
 
3.3%
박 904
 
3.0%
희 702
 
2.3%
경 614
 
2.1%
미 560
 
1.9%
성 551
 
1.8%
숙 549
 
1.8%
Other values (283) 20013
66.9%
ASCII
ValueCountFrequency (%)
( 41
41.4%
) 41
41.4%
8
 
8.1%
I 3
 
3.0%
N 2
 
2.0%
Y 1
 
1.0%
A 1
 
1.0%
T 1
 
1.0%
J 1
 
1.0%
CJK
ValueCountFrequency (%)
金 8
 
7.2%
鄭 5
 
4.5%
崔 5
 
4.5%
子 4
 
3.6%
朴 3
 
2.7%
順 3
 
2.7%
基 3
 
2.7%
根 2
 
1.8%
成 2
 
1.8%
永 2
 
1.8%
Other values (70) 74
66.7%
CJK Compat Ideographs
ValueCountFrequency (%)
李 6
85.7%
林 1
 
14.3%
Compat Jamo
ValueCountFrequency (%)
ㅂ 1
100.0%

bsnmcmpnm
Text

MISSING 

Distinct3317
Distinct (%)45.5%
Missing2705
Missing (%)27.1%
Memory size156.2 KiB
2024-04-16T19:26:06.883616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length11.267992
Min length4

Characters and Unicode

Total characters82200
Distinct characters574
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1988 ?
Unique (%)27.3%

Sample

1st row왕우공인중개사사무소
2nd rowThe파크공인중개사사무소
3rd row소정공인중개사사무소
4th row명품공인중개사사무소
5th row토박이공인중개사사무소
ValueCountFrequency (%)
주식회사 103
 
1.4%
공인중개사사무소 79
 
1.0%
사무소 64
 
0.8%
조은공인중개사사무소 46
 
0.6%
주)부동산중개법인개벽 40
 
0.5%
현대공인중개사사무소 37
 
0.5%
주)온나라부동산중개법인 36
 
0.5%
삼성공인중개사사무소 34
 
0.4%
삼오부동산중개법인 33
 
0.4%
미래공인중개사사무소 32
 
0.4%
Other values (3310) 7102
93.4%
2024-04-16T19:26:07.186501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 12696
15.4%
개 7339
 
8.9%
중 7314
 
8.9%
소 6601
 
8.0%
무 6560
 
8.0%
인 6323
 
7.7%
공 5913
 
7.2%
동 3001
 
3.7%
부 2751
 
3.3%
산 2719
 
3.3%
Other values (564) 20983
25.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80171
97.5%
Uppercase Letter 753
 
0.9%
Space Separator 383
 
0.5%
Decimal Number 319
 
0.4%
Close Punctuation 208
 
0.3%
Open Punctuation 208
 
0.3%
Lowercase Letter 131
 
0.2%
Other Punctuation 19
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Letter Number 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 12696
15.8%
개 7339
 
9.2%
중 7314
 
9.1%
소 6601
 
8.2%
무 6560
 
8.2%
인 6323
 
7.9%
공 5913
 
7.4%
동 3001
 
3.7%
부 2751
 
3.4%
산 2719
 
3.4%
Other values (502) 18954
23.6%
Uppercase Letter
ValueCountFrequency (%)
K 138
18.3%
S 91
12.1%
T 59
 
7.8%
L 59
 
7.8%
W 43
 
5.7%
C 43
 
5.7%
H 38
 
5.0%
O 35
 
4.6%
B 32
 
4.2%
E 29
 
3.9%
Other values (14) 186
24.7%
Lowercase Letter
ValueCountFrequency (%)
e 58
44.3%
h 20
 
15.3%
w 10
 
7.6%
t 9
 
6.9%
s 7
 
5.3%
c 6
 
4.6%
k 5
 
3.8%
b 4
 
3.1%
i 3
 
2.3%
o 3
 
2.3%
Other values (5) 6
 
4.6%
Decimal Number
ValueCountFrequency (%)
1 134
42.0%
8 42
 
13.2%
2 39
 
12.2%
4 38
 
11.9%
3 23
 
7.2%
9 19
 
6.0%
5 9
 
2.8%
0 6
 
1.9%
7 5
 
1.6%
6 4
 
1.3%
Other Punctuation
ValueCountFrequency (%)
. 7
36.8%
& 6
31.6%
？ 2
 
10.5%
· 2
 
10.5%
! 1
 
5.3%
# 1
 
5.3%
Space Separator
ValueCountFrequency (%)
383
100.0%
Close Punctuation
ValueCountFrequency (%)
) 208
100.0%
Open Punctuation
ValueCountFrequency (%)
( 208
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80159
97.5%
Common 1144
 
1.4%
Latin 885
 
1.1%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 12696
15.8%
개 7339
 
9.2%
중 7314
 
9.1%
소 6601
 
8.2%
무 6560
 
8.2%
인 6323
 
7.9%
공 5913
 
7.4%
동 3001
 
3.7%
부 2751
 
3.4%
산 2719
 
3.4%
Other values (492) 18942
23.6%
Latin
ValueCountFrequency (%)
K 138
15.6%
S 91
 
10.3%
T 59
 
6.7%
L 59
 
6.7%
e 58
 
6.6%
W 43
 
4.9%
C 43
 
4.9%
H 38
 
4.3%
O 35
 
4.0%
B 32
 
3.6%
Other values (30) 289
32.7%
Common
ValueCountFrequency (%)
383
33.5%
) 208
18.2%
( 208
18.2%
1 134
 
11.7%
8 42
 
3.7%
2 39
 
3.4%
4 38
 
3.3%
3 23
 
2.0%
9 19
 
1.7%
5 9
 
0.8%
Other values (12) 41
 
3.6%
Han
ValueCountFrequency (%)
福 3
25.0%
甲 1
 
8.3%
秀 1
 
8.3%
該 1
 
8.3%
氷 1
 
8.3%
人 1
 
8.3%
本 1
 
8.3%
炫 1
 
8.3%
明 1
 
8.3%
堂 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80159
97.5%
ASCII 2023
 
2.5%
CJK 12
 
< 0.1%
None 4
 
< 0.1%
Number Forms 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 12696
15.8%
개 7339
 
9.2%
중 7314
 
9.1%
소 6601
 
8.2%
무 6560
 
8.2%
인 6323
 
7.9%
공 5913
 
7.4%
동 3001
 
3.7%
부 2751
 
3.4%
산 2719
 
3.4%
Other values (492) 18942
23.6%
ASCII
ValueCountFrequency (%)
383
18.9%
) 208
 
10.3%
( 208
 
10.3%
K 138
 
6.8%
1 134
 
6.6%
S 91
 
4.5%
T 59
 
2.9%
L 59
 
2.9%
e 58
 
2.9%
W 43
 
2.1%
Other values (48) 642
31.7%
CJK
ValueCountFrequency (%)
福 3
25.0%
甲 1
 
8.3%
秀 1
 
8.3%
該 1
 
8.3%
氷 1
 
8.3%
人 1
 
8.3%
本 1
 
8.3%
炫 1
 
8.3%
明 1
 
8.3%
堂 1
 
8.3%
None
ValueCountFrequency (%)
？ 2
50.0%
· 2
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 1
100.0%

crqfcacqdt
Text

MISSING 

Distinct641
Distinct (%)11.1%
Missing4204
Missing (%)42.0%
Memory size156.2 KiB
2024-04-16T19:26:07.449245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9993099
Min length8

Characters and Unicode

Total characters57956
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)6.9%

Sample

1st row2014-10-02
2nd row2012-12-10
3rd row1985-11-18
4th row2007-12-17
5th row2016-12-12
ValueCountFrequency (%)
2005-07-20 382
 
6.6%
2017-12-11 350
 
6.0%
2016-12-12 288
 
5.0%
2019-12-09 247
 
4.3%
2018-12-10 205
 
3.5%
2003-11-07 197
 
3.4%
2015-12-09 195
 
3.4%
2005-12-12 170
 
2.9%
2001-12-10 156
 
2.7%
2011-12-19 153
 
2.6%
Other values (631) 3453
59.6%
2024-04-16T19:26:07.843379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13299
22.9%
0 12139
20.9%
- 11588
20.0%
2 10884
18.8%
9 2745
 
4.7%
5 1701
 
2.9%
7 1572
 
2.7%
8 1449
 
2.5%
3 1086
 
1.9%
6 944
 
1.6%
Other values (2) 549
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46364
80.0%
Dash Punctuation 11588
 
20.0%
Space Separator 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13299
28.7%
0 12139
26.2%
2 10884
23.5%
9 2745
 
5.9%
5 1701
 
3.7%
7 1572
 
3.4%
8 1449
 
3.1%
3 1086
 
2.3%
6 944
 
2.0%
4 545
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 11588
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57956
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13299
22.9%
0 12139
20.9%
- 11588
20.0%
2 10884
18.8%
9 2745
 
4.7%
5 1701
 
2.9%
7 1572
 
2.7%
8 1449
 
2.5%
3 1086
 
1.9%
6 944
 
1.6%
Other values (2) 549
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57956
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13299
22.9%
0 12139
20.9%
- 11588
20.0%
2 10884
18.8%
9 2745
 
4.7%
5 1701
 
2.9%
7 1572
 
2.7%
8 1449
 
2.5%
3 1086
 
1.9%
6 944
 
1.6%
Other values (2) 549
 
0.9%

crqfcno
Text

MISSING 

Distinct5693
Distinct (%)96.2%
Missing4082
Missing (%)40.8%
Memory size156.2 KiB
2024-04-16T19:26:08.131030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length9.1809733
Min length1

Characters and Unicode

Total characters54333
Distinct characters62
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5485 ?
Unique (%)92.7%

Sample

1st row10-00771
2nd row23-00361
3rd row5119
4th row18-170
5th row26-2016-02198
ValueCountFrequency (%)
부산 376
 
5.8%
부산시 46
 
0.7%
부산광역시 22
 
0.3%
경남 19
 
0.3%
부산광역시장 17
 
0.3%
경상남도 6
 
0.1%
1154 5
 
0.1%
경기도 5
 
0.1%
제 5
 
0.1%
716 4
 
0.1%
Other values (5655) 5942
92.2%
2024-04-16T19:26:08.546380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8643
15.9%
2 6809
12.5%
1 6575
12.1%
- 6056
11.1%
6 3784
 
7.0%
4 2507
 
4.6%
3 2441
 
4.5%
8 2248
 
4.1%
7 2241
 
4.1%
5 2241
 
4.1%
Other values (52) 10788
19.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39691
73.1%
Other Letter 6660
 
12.3%
Dash Punctuation 6056
 
11.1%
Open Punctuation 692
 
1.3%
Close Punctuation 691
 
1.3%
Space Separator 532
 
1.0%
Other Punctuation 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 1969
29.6%
부 1949
29.3%
호 525
 
7.9%
제 471
 
7.1%
시 380
 
5.7%
광 288
 
4.3%
역 287
 
4.3%
장 161
 
2.4%
경 138
 
2.1%
남 112
 
1.7%
Other values (33) 380
 
5.7%
Decimal Number
ValueCountFrequency (%)
0 8643
21.8%
2 6809
17.2%
1 6575
16.6%
6 3784
9.5%
4 2507
 
6.3%
3 2441
 
6.2%
8 2248
 
5.7%
7 2241
 
5.6%
5 2241
 
5.6%
9 2202
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 5
45.5%
, 4
36.4%
: 2
 
18.2%
Open Punctuation
ValueCountFrequency (%)
( 633
91.5%
[ 59
 
8.5%
Close Punctuation
ValueCountFrequency (%)
) 632
91.5%
] 59
 
8.5%
Dash Punctuation
ValueCountFrequency (%)
- 6056
100.0%
Space Separator
ValueCountFrequency (%)
532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47673
87.7%
Hangul 6660
 
12.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 1969
29.6%
부 1949
29.3%
호 525
 
7.9%
제 471
 
7.1%
시 380
 
5.7%
광 288
 
4.3%
역 287
 
4.3%
장 161
 
2.4%
경 138
 
2.1%
남 112
 
1.7%
Other values (33) 380
 
5.7%
Common
ValueCountFrequency (%)
0 8643
18.1%
2 6809
14.3%
1 6575
13.8%
- 6056
12.7%
6 3784
7.9%
4 2507
 
5.3%
3 2441
 
5.1%
8 2248
 
4.7%
7 2241
 
4.7%
5 2241
 
4.7%
Other values (9) 4128
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47673
87.7%
Hangul 6660
 
12.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8643
18.1%
2 6809
14.3%
1 6575
13.8%
- 6056
12.7%
6 3784
7.9%
4 2507
 
5.3%
3 2441
 
5.1%
8 2248
 
4.7%
7 2241
 
4.7%
5 2241
 
4.7%
Other values (9) 4128
8.7%
Hangul
ValueCountFrequency (%)
산 1969
29.6%
부 1949
29.3%
호 525
 
7.9%
제 471
 
7.1%
시 380
 
5.7%
광 288
 
4.3%
역 287
 
4.3%
장 161
 
2.4%
경 138
 
2.1%
남 112
 
1.7%
Other values (33) 380
 
5.7%

jurirno
Text

MISSING 

Distinct4730
Distinct (%)64.8%
Missing2705
Missing (%)27.1%
Memory size156.2 KiB
2024-04-16T19:26:08.747093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length13.727759
Min length6

Characters and Unicode

Total characters100144
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3393 ?
Unique (%)46.5%

Sample

1st row26470-2020-00141
2nd row가-10-3423
3rd row가-11-1977
4th row26320-2019-00052
5th row26440-2020-00094
ValueCountFrequency (%)
26470-2018-00085 40
 
0.5%
26470-2016-00066 36
 
0.5%
26230-2016-00137 33
 
0.5%
26470-2015-00027 32
 
0.4%
가-13-1490 27
 
0.4%
26470-2018-00103 24
 
0.3%
26530-2017-00027 23
 
0.3%
가-05-3566 20
 
0.3%
26230-2020-00110 17
 
0.2%
26230-2016-00096 17
 
0.2%
Other values (4723) 7030
96.3%
2024-04-16T19:26:09.047476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28632
28.6%
2 16146
16.1%
- 14532
14.5%
1 10058
 
10.0%
6 7886
 
7.9%
3 4269
 
4.3%
4 3783
 
3.8%
5 3601
 
3.6%
7 3336
 
3.3%
9 3006
 
3.0%
Other values (4) 4895
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 83347
83.2%
Dash Punctuation 14532
 
14.5%
Other Letter 2261
 
2.3%
Space Separator 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28632
34.4%
2 16146
19.4%
1 10058
 
12.1%
6 7886
 
9.5%
3 4269
 
5.1%
4 3783
 
4.5%
5 3601
 
4.3%
7 3336
 
4.0%
9 3006
 
3.6%
8 2630
 
3.2%
Other Letter
ValueCountFrequency (%)
가 2244
99.2%
나 17
 
0.8%
Dash Punctuation
ValueCountFrequency (%)
- 14532
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 97883
97.7%
Hangul 2261
 
2.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28632
29.3%
2 16146
16.5%
- 14532
14.8%
1 10058
 
10.3%
6 7886
 
8.1%
3 4269
 
4.4%
4 3783
 
3.9%
5 3601
 
3.7%
7 3336
 
3.4%
9 3006
 
3.1%
Other values (2) 2634
 
2.7%
Hangul
ValueCountFrequency (%)
가 2244
99.2%
나 17
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97883
97.7%
Hangul 2261
 
2.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28632
29.3%
2 16146
16.5%
- 14532
14.8%
1 10058
 
10.3%
6 7886
 
8.1%
3 4269
 
4.4%
4 3783
 
3.9%
5 3601
 
3.7%
7 3336
 
3.4%
9 3006
 
3.1%
Other values (2) 2634
 
2.7%
Hangul
ValueCountFrequency (%)
가 2244
99.2%
나 17
 
0.8%

lastupdtdt
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-12-22 00:00:00
Maximum2020-12-22 00:00:00
2024-04-16T19:26:09.142321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T19:26:09.217470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

ldcode
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26363.647
Minimum26110
Maximum26710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-04-16T19:26:09.297276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26110
5-th percentile26170
Q126260
median26350
Q326440
95-th percentile26530
Maximum26710
Range600
Interquartile range (IQR)180

Descriptive statistics

Standard deviation128.77309
Coefficient of variation (CV)0.0048844944
Kurtosis0.5607224
Mean26363.647
Median Absolute Deviation (MAD)90
Skewness0.63410638
Sum2.6363647 × 108
Variance16582.508
MonotonicityNot monotonic
2024-04-16T19:26:09.383852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
26230 1398
14.0%
26350 1395
14.0%
26260 1063
10.6%
26470 901
9.0%
26410 860
8.6%
26440 763
7.6%
26380 684
6.8%
26500 642
6.4%
26290 544
 
5.4%
26710 495
 
5.0%
Other values (6) 1255
12.6%
ValueCountFrequency (%)
26110 185
 
1.8%
26140 155
 
1.6%
26170 173
 
1.7%
26200 147
 
1.5%
26230 1398
14.0%
26260 1063
10.6%
26290 544
 
5.4%
26320 323
 
3.2%
26350 1395
14.0%
26380 684
6.8%
ValueCountFrequency (%)
26710 495
 
5.0%
26530 272
 
2.7%
26500 642
6.4%
26470 901
9.0%
26440 763
7.6%
26410 860
8.6%
26380 684
6.8%
26350 1395
14.0%
26320 323
 
3.2%
26290 544
 
5.4%

ldcodenm
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
부산광역시 부산진구
1398 
부산광역시 해운대구
1395 
부산광역시 동래구
1063 
부산광역시 연제구
901 
부산광역시 금정구
860 
Other values (11)
4383 

Length

Max length10
Median length9
Mean length9.1413
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 연제구
2nd row부산광역시 해운대구
3rd row부산광역시 금정구
4th row부산광역시 부산진구
5th row부산광역시 금정구

Common Values

ValueCountFrequency (%)
부산광역시 부산진구 1398
14.0%
부산광역시 해운대구 1395
14.0%
부산광역시 동래구 1063
10.6%
부산광역시 연제구 901
9.0%
부산광역시 금정구 860
8.6%
부산광역시 강서구 763
7.6%
부산광역시 사하구 684
6.8%
부산광역시 수영구 642
6.4%
부산광역시 남구 544
 
5.4%
부산광역시 기장군 495
 
5.0%
Other values (6) 1255
12.6%

Length

2024-04-16T19:26:09.497026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 10000
50.0%
부산진구 1398
 
7.0%
해운대구 1395
 
7.0%
동래구 1063
 
5.3%
연제구 901
 
4.5%
금정구 860
 
4.3%
강서구 763
 
3.8%
사하구 684
 
3.4%
수영구 642
 
3.2%
남구 544
 
2.7%
Other values (7) 1750
 
8.8%

ofcpssecode
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
3687 
4
3592 
<NA>
2699 
3
 
16
2
 
6

Length

Max length4
Median length1
Mean length1.8097
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row1
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
1 3687
36.9%
4 3592
35.9%
<NA> 2699
27.0%
3 16
 
0.2%
2 6
 
0.1%

Length

2024-04-16T19:26:09.614934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:26:09.719171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 3687
36.9%
4 3592
35.9%
na 2699
27.0%
3 16
 
0.2%
2 6
 
0.1%

ofcpssecodenm
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
대표
3687 
일반
3592 
<NA>
2699 
이사
 
16
감사
 
6

Length

Max length4
Median length2
Mean length2.5398
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대표 3687
36.9%
일반 3592
35.9%
<NA> 2699
27.0%
이사 16
 
0.2%
감사 6
 
0.1%

Length

2024-04-16T19:26:09.853354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:26:09.949474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대표 3687
36.9%
일반 3592
35.9%
na 2699
27.0%
이사 16
 
0.2%
감사 6
 
0.1%

last_load_dttm
Date

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2020-12-23 12:10:31
Maximum2020-12-23 12:10:32
2024-04-16T19:26:10.033908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T19:26:10.112708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

Interactions

2024-04-16T19:26:04.884654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-16T19:26:10.176579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
brkrasortcodebrkrasortcodenmldcodeldcodenmofcpssecodeofcpssecodenmlast_load_dttm
brkrasortcode1.0001.0000.2430.3110.5770.5770.043
brkrasortcodenm1.0001.0000.2430.3110.5770.5770.043
ldcode0.2430.2431.0001.0000.2160.2160.996
ldcodenm0.3110.3111.0001.0000.2540.2540.996
ofcpssecode0.5770.5770.2160.2541.0001.0000.022
ofcpssecodenm0.5770.5770.2160.2541.0001.0000.022
last_load_dttm0.0430.0430.9960.9960.0220.0221.000
2024-04-16T19:26:10.270678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ofcpssecodenmldcodenmbrkrasortcodeofcpssecodebrkrasortcodenm
ofcpssecodenm1.0000.1220.5871.0000.587
ldcodenm0.1221.0000.1500.1220.150
brkrasortcode0.5870.1501.0000.5871.000
ofcpssecode1.0000.1220.5871.0000.587
brkrasortcodenm0.5870.1501.0000.5871.000
2024-04-16T19:26:10.355309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodebrkrasortcodebrkrasortcodenmldcodenmofcpssecodeofcpssecodenm
ldcode1.0000.1100.1101.0000.0970.097
brkrasortcode0.1101.0001.0000.1500.5870.587
brkrasortcodenm0.1101.0001.0000.1500.5870.587
ldcodenm1.0000.1500.1501.0000.1220.122
ofcpssecode0.0970.5870.5870.1221.0001.000
ofcpssecodenm0.0970.5870.5870.1221.0001.000

Missing values

2024-04-16T19:26:05.005849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-16T19:26:05.371180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-04-16T19:26:05.501806image/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

brkrasortcodebrkrasortcodenmbrkrnmbsnmcmpnmcrqfcacqdtcrqfcnojurirnolastupdtdtldcodeldcodenmofcpssecodeofcpssecodenmlast_load_dttm
166744중개보조원김영홍왕우공인중개사사무소<NA><NA>26470-2020-001412020-12-2226470부산광역시 연제구4일반2020-12-23 12:10:32
82212공인중개사최미숙The파크공인중개사사무소2014-10-0210-00771가-10-34232020-12-2226350부산광역시 해운대구4일반2020-12-23 12:10:31
136142공인중개사강수영소정공인중개사사무소2012-12-1023-00361가-11-19772020-12-2226410부산광역시 금정구1대표2020-12-23 12:10:32
37494중개보조원김석제<NA><NA><NA><NA>2020-12-2226230부산광역시 부산진구<NA><NA>2020-12-23 12:10:31
132912공인중개사김우용<NA>1985-11-185119<NA>2020-12-2226410부산광역시 금정구<NA><NA>2020-12-23 12:10:32
77392공인중개사김성찬명품공인중개사사무소2007-12-1718-17026320-2019-000522020-12-2226320부산광역시 북구1대표2020-12-23 12:10:31
59722공인중개사김명숙<NA><NA><NA><NA>2020-12-2226260부산광역시 동래구<NA><NA>2020-12-23 12:10:31
148582공인중개사김재순토박이공인중개사사무소2016-12-1226-2016-0219826440-2020-000942020-12-2226440부산광역시 강서구1대표2020-12-23 12:10:32
187902공인중개사최정아해뜨는 공인중개사사무소2008-12-15제19-342호가-16-12362020-12-2226710부산광역시 기장군1대표2020-12-23 12:10:32
134624중개보조원김동은금정더샵공인중개사사무소<NA><NA>26410-2019-000762020-12-2226410부산광역시 금정구4일반2020-12-23 12:10:32
brkrasortcodebrkrasortcodenmbrkrnmbsnmcmpnmcrqfcacqdtcrqfcnojurirnolastupdtdtldcodeldcodenmofcpssecodeofcpssecodenmlast_load_dttm
168404중개보조원공용진(주)온나라부동산중개법인<NA><NA>26470-2016-000662020-12-2226470부산광역시 연제구4일반2020-12-23 12:10:32
109482공인중개사이혜정<NA>2008-10-2619-434<NA>2020-12-2226380부산광역시 사하구<NA><NA>2020-12-23 12:10:32
1021중개인이상화<NA><NA><NA><NA>2020-12-2226110부산광역시 중구<NA><NA>2020-12-23 12:10:31
88982공인중개사이수연앳홈공인중개사사무소2015-12-0731-2015-0033726350-2020-001482020-12-2226350부산광역시 해운대구1대표2020-12-23 12:10:31
31862공인중개사박성진서면1번지부동산공인중개사사무소2017-12-1126-2017-0121926230-2018-000832020-12-2226230부산광역시 부산진구1대표2020-12-23 12:10:31
48442공인중개사이병동장군공인중개사사무소1985-11-08부산광역시 - 317526260-2015-000842020-12-2226260부산광역시 동래구1대표2020-12-23 12:10:31
17822공인중개사조영옥빛나라공인중개사사무소2017-12-1126-2017-00867(부산)26230-2018-000912020-12-2226230부산광역시 부산진구4일반2020-12-23 12:10:31
81052공인중개사최용희<NA>2000-11-20부산 12<NA>2020-12-2226350부산광역시 해운대구<NA><NA>2020-12-23 12:10:31
154154중개보조원정회연세종공인중개사사무소<NA><NA>가-13-21042020-12-2226470부산광역시 연제구4일반2020-12-23 12:10:32
30274중개보조원박한수해피공인중개사사무소<NA><NA>26230-2017-001032020-12-2226230부산광역시 부산진구4일반2020-12-23 12:10:31

Duplicate rows

Most frequently occurring

brkrasortcodebrkrasortcodenmbrkrnmbsnmcmpnmcrqfcacqdtcrqfcnojurirnolastupdtdtldcodeldcodenmofcpssecodeofcpssecodenmlast_load_dttm# duplicates
02공인중개사권의현<NA><NA><NA><NA>2020-12-2226410부산광역시 금정구<NA><NA>2020-12-23 12:10:322
12공인중개사박성진법무공인중개사사무소2011-12-19부산22-00193가-14-11962020-12-2226500부산광역시 수영구1대표2020-12-23 12:10:322
22공인중개사박창호<NA><NA><NA><NA>2020-12-2226260부산광역시 동래구<NA><NA>2020-12-23 12:10:312
32공인중개사한영수<NA><NA><NA><NA>2020-12-2226260부산광역시 동래구<NA><NA>2020-12-23 12:10:312
44중개보조원이기옥<NA><NA><NA><NA>2020-12-2226410부산광역시 금정구<NA><NA>2020-12-23 12:10:322