Overview

Dataset statistics

Number of variables13
Number of observations7427
Missing cells7779
Missing cells (%)8.1%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory776.2 KiB
Average record size in memory107.0 B

Variable types

Text3
DateTime5
Numeric1
Categorical3
Unsupported1

Alerts

lastupdtdt has constant value ""Constant
last_load_dttm has constant value ""Constant
Dataset has 4 (0.1%) duplicate rowsDuplicates
sttussecode is highly overall correlated with sttussecodenmHigh correlation
sttussecodenm is highly overall correlated with sttussecodeHigh correlation
ldcode is highly overall correlated with ldcodenmHigh correlation
ldcodenm is highly overall correlated with ldcodeHigh correlation
sttussecode is highly imbalanced (97.7%)Imbalance
sttussecodenm is highly imbalanced (97.7%)Imbalance
estbsbeginde has 89 (1.2%) missing valuesMissing
estbsendde has 89 (1.2%) missing valuesMissing
telnolist has 7427 (100.0%) missing valuesMissing
telnolist is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 02:16:35.575967
Analysis finished2024-04-17 02:16:36.811722
Duration1.24 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

brkrnm
Text

Distinct6138
Distinct (%)83.3%
Missing62
Missing (%)0.8%
Memory size58.2 KiB
2024-04-17T11:16:37.028498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length3
Mean length3.002444
Min length2

Characters and Unicode

Total characters22113
Distinct characters328
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5402 ?
Unique (%)73.3%

Sample

1st row정영희
2nd row이지미
3rd row김덕길
4th row천순철
5th row김정석
ValueCountFrequency (%)
김정희 16
 
0.2%
이영주 11
 
0.1%
김미경 11
 
0.1%
이정희 10
 
0.1%
김미숙 10
 
0.1%
김민정 10
 
0.1%
김영희 10
 
0.1%
이미경 10
 
0.1%
김경희 10
 
0.1%
김현정 8
 
0.1%
Other values (6136) 7268
98.6%
2024-04-17T11:16:37.659518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 1590
 
7.2%
이 1122
 
5.1%
정 1071
 
4.8%
영 769
 
3.5%
박 660
 
3.0%
희 556
 
2.5%
경 537
 
2.4%
미 469
 
2.1%
숙 442
 
2.0%
현 404
 
1.8%
Other values (318) 14493
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22060
99.8%
Lowercase Letter 15
 
0.1%
Close Punctuation 11
 
< 0.1%
Open Punctuation 11
 
< 0.1%
Space Separator 10
 
< 0.1%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 1590
 
7.2%
이 1122
 
5.1%
정 1071
 
4.9%
영 769
 
3.5%
박 660
 
3.0%
희 556
 
2.5%
경 537
 
2.4%
미 469
 
2.1%
숙 442
 
2.0%
현 404
 
1.8%
Other values (299) 14440
65.5%
Lowercase Letter
ValueCountFrequency (%)
e 4
26.7%
y 2
13.3%
a 2
13.3%
s 1
 
6.7%
u 1
 
6.7%
n 1
 
6.7%
g 1
 
6.7%
m 1
 
6.7%
k 1
 
6.7%
i 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
16.7%
C 1
16.7%
L 1
16.7%
H 1
16.7%
A 1
16.7%
B 1
16.7%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22028
99.6%
Common 32
 
0.1%
Han 32
 
0.1%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 1590
 
7.2%
이 1122
 
5.1%
정 1071
 
4.9%
영 769
 
3.5%
박 660
 
3.0%
희 556
 
2.5%
경 537
 
2.4%
미 469
 
2.1%
숙 442
 
2.0%
현 404
 
1.8%
Other values (272) 14408
65.4%
Han
ValueCountFrequency (%)
金 3
 
9.4%
美 2
 
6.2%
崔 2
 
6.2%
順 2
 
6.2%
張 1
 
3.1%
榮 1
 
3.1%
忠 1
 
3.1%
孝 1
 
3.1%
萬 1
 
3.1%
然 1
 
3.1%
Other values (17) 17
53.1%
Latin
ValueCountFrequency (%)
e 4
19.0%
y 2
 
9.5%
a 2
 
9.5%
s 1
 
4.8%
S 1
 
4.8%
C 1
 
4.8%
L 1
 
4.8%
u 1
 
4.8%
n 1
 
4.8%
H 1
 
4.8%
Other values (6) 6
28.6%
Common
ValueCountFrequency (%)
) 11
34.4%
( 11
34.4%
10
31.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22028
99.6%
ASCII 53
 
0.2%
CJK 31
 
0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 1590
 
7.2%
이 1122
 
5.1%
정 1071
 
4.9%
영 769
 
3.5%
박 660
 
3.0%
희 556
 
2.5%
경 537
 
2.4%
미 469
 
2.1%
숙 442
 
2.0%
현 404
 
1.8%
Other values (272) 14408
65.4%
ASCII
ValueCountFrequency (%)
) 11
20.8%
( 11
20.8%
10
18.9%
e 4
 
7.5%
y 2
 
3.8%
a 2
 
3.8%
s 1
 
1.9%
S 1
 
1.9%
C 1
 
1.9%
L 1
 
1.9%
Other values (9) 9
17.0%
CJK
ValueCountFrequency (%)
金 3
 
9.7%
美 2
 
6.5%
崔 2
 
6.5%
順 2
 
6.5%
張 1
 
3.2%
榮 1
 
3.2%
忠 1
 
3.2%
孝 1
 
3.2%
萬 1
 
3.2%
然 1
 
3.2%
Other values (16) 16
51.6%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%

bsnmcmpnm
Text

Distinct4811
Distinct (%)65.3%
Missing56
Missing (%)0.8%
Memory size58.2 KiB
2024-04-17T11:16:37.900229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length11.306743
Min length4

Characters and Unicode

Total characters83342
Distinct characters630
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

Unique3969 ?
Unique (%)53.8%

Sample

1st row천봉공인중개사
2nd row중앙공인중개사무소
3rd row마당발부동산중개사무소
4th row참조은공인중개사사무소
5th row가람공인중개사사무소
ValueCountFrequency (%)
사무소 83
 
1.1%
공인중개사사무소 83
 
1.1%
현대공인중개사사무소 41
 
0.5%
삼성공인중개사사무소 36
 
0.5%
행운공인중개사사무소 33
 
0.4%
미래공인중개사사무소 33
 
0.4%
태양공인중개사사무소 30
 
0.4%
탑공인중개사사무소 28
 
0.4%
우리공인중개사사무소 25
 
0.3%
신세계공인중개사사무소 25
 
0.3%
Other values (4794) 7212
94.5%
2024-04-17T11:16:38.331722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 13290
15.9%
중 7401
 
8.9%
개 7384
 
8.9%
소 6965
 
8.4%
무 6924
 
8.3%
인 6457
 
7.7%
공 6274
 
7.5%
동 2803
 
3.4%
부 2547
 
3.1%
산 2495
 
3.0%
Other values (620) 20802
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81459
97.7%
Uppercase Letter 787
 
0.9%
Space Separator 339
 
0.4%
Decimal Number 333
 
0.4%
Lowercase Letter 171
 
0.2%
Open Punctuation 110
 
0.1%
Close Punctuation 110
 
0.1%
Other Punctuation 21
 
< 0.1%
Dash Punctuation 9
 
< 0.1%
Letter Number 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 13290
16.3%
중 7401
 
9.1%
개 7384
 
9.1%
소 6965
 
8.6%
무 6924
 
8.5%
인 6457
 
7.9%
공 6274
 
7.7%
동 2803
 
3.4%
부 2547
 
3.1%
산 2495
 
3.1%
Other values (551) 18919
23.2%
Uppercase Letter
ValueCountFrequency (%)
K 146
18.6%
S 100
12.7%
T 69
 
8.8%
L 66
 
8.4%
C 52
 
6.6%
O 45
 
5.7%
W 39
 
5.0%
E 33
 
4.2%
H 30
 
3.8%
B 26
 
3.3%
Other values (16) 181
23.0%
Lowercase Letter
ValueCountFrequency (%)
e 75
43.9%
h 27
 
15.8%
t 13
 
7.6%
c 11
 
6.4%
k 8
 
4.7%
w 8
 
4.7%
s 7
 
4.1%
i 4
 
2.3%
o 4
 
2.3%
n 3
 
1.8%
Other values (9) 11
 
6.4%
Decimal Number
ValueCountFrequency (%)
1 144
43.2%
8 45
 
13.5%
4 38
 
11.4%
2 31
 
9.3%
3 24
 
7.2%
9 20
 
6.0%
5 12
 
3.6%
6 7
 
2.1%
0 6
 
1.8%
7 6
 
1.8%
Other Punctuation
ValueCountFrequency (%)
& 7
33.3%
. 6
28.6%
？ 2
 
9.5%
· 2
 
9.5%
# 2
 
9.5%
, 1
 
4.8%
! 1
 
4.8%
Space Separator
ValueCountFrequency (%)
339
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓡ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81446
97.7%
Latin 959
 
1.2%
Common 924
 
1.1%
Han 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 13290
16.3%
중 7401
 
9.1%
개 7384
 
9.1%
소 6965
 
8.6%
무 6924
 
8.5%
인 6457
 
7.9%
공 6274
 
7.7%
동 2803
 
3.4%
부 2547
 
3.1%
산 2495
 
3.1%
Other values (539) 18906
23.2%
Latin
ValueCountFrequency (%)
K 146
15.2%
S 100
 
10.4%
e 75
 
7.8%
T 69
 
7.2%
L 66
 
6.9%
C 52
 
5.4%
O 45
 
4.7%
W 39
 
4.1%
E 33
 
3.4%
H 30
 
3.1%
Other values (36) 304
31.7%
Common
ValueCountFrequency (%)
339
36.7%
1 144
15.6%
( 110
 
11.9%
) 110
 
11.9%
8 45
 
4.9%
4 38
 
4.1%
2 31
 
3.4%
3 24
 
2.6%
9 20
 
2.2%
5 12
 
1.3%
Other values (13) 51
 
5.5%
Han
ValueCountFrequency (%)
福 2
15.4%
利 1
7.7%
秀 1
7.7%
人 1
7.7%
太 1
7.7%
甲 1
7.7%
明 1
7.7%
堂 1
7.7%
該 1
7.7%
本 1
7.7%
Other values (2) 2
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81446
97.7%
ASCII 1877
 
2.3%
CJK 13
 
< 0.1%
None 4
 
< 0.1%
Number Forms 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 13290
16.3%
중 7401
 
9.1%
개 7384
 
9.1%
소 6965
 
8.6%
무 6924
 
8.5%
인 6457
 
7.9%
공 6274
 
7.7%
동 2803
 
3.4%
부 2547
 
3.1%
산 2495
 
3.1%
Other values (539) 18906
23.2%
ASCII
ValueCountFrequency (%)
339
18.1%
K 146
 
7.8%
1 144
 
7.7%
( 110
 
5.9%
) 110
 
5.9%
S 100
 
5.3%
e 75
 
4.0%
T 69
 
3.7%
L 66
 
3.5%
C 52
 
2.8%
Other values (55) 666
35.5%
CJK
ValueCountFrequency (%)
福 2
15.4%
利 1
7.7%
秀 1
7.7%
人 1
7.7%
太 1
7.7%
甲 1
7.7%
明 1
7.7%
堂 1
7.7%
該 1
7.7%
本 1
7.7%
Other values (2) 2
15.4%
None
ValueCountFrequency (%)
？ 2
50.0%
· 2
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 1
100.0%

estbsbeginde
Date

MISSING 

Distinct515
Distinct (%)7.0%
Missing89
Missing (%)1.2%
Memory size58.2 KiB
Minimum2013-03-24 00:00:00
Maximum2021-12-16 00:00:00
2024-04-17T11:16:38.490315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:38.669793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

estbsendde
Date

MISSING 

Distinct512
Distinct (%)7.0%
Missing89
Missing (%)1.2%
Memory size58.2 KiB
Minimum2014-03-23 00:00:00
Maximum2024-11-15 00:00:00
2024-04-17T11:16:38.842826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:39.031199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

jurirno
Text

Distinct7366
Distinct (%)99.9%
Missing56
Missing (%)0.8%
Memory size58.2 KiB
2024-04-17T11:16:39.328967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length13.468186
Min length6

Characters and Unicode

Total characters99274
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

Unique7361 ?
Unique (%)99.9%

Sample

1st row가-01-619
2nd row가-01-620
3rd row가-01-621
4th row가-01-624
5th row가-01-625
ValueCountFrequency (%)
가-11-2094 2
 
< 0.1%
26470-2015-00086 2
 
< 0.1%
2
 
< 0.1%
26440-2019-00095 2
 
< 0.1%
가 2
 
< 0.1%
26230-2017-00146 2
 
< 0.1%
26410-2016-00056 2
 
< 0.1%
26440-2020-00098 1
 
< 0.1%
26440-2020-00095 1
 
< 0.1%
26440-2020-00096 1
 
< 0.1%
Other values (7359) 7359
99.8%
2024-04-17T11:16:39.816436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 28009
28.2%
2 15812
15.9%
- 14672
14.8%
1 9995
 
10.1%
6 7710
 
7.8%
3 4200
 
4.2%
4 3883
 
3.9%
5 3675
 
3.7%
7 3155
 
3.2%
9 2973
 
3.0%
Other values (4) 5190
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82073
82.7%
Dash Punctuation 14672
 
14.8%
Other Letter 2524
 
2.5%
Space Separator 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 28009
34.1%
2 15812
19.3%
1 9995
 
12.2%
6 7710
 
9.4%
3 4200
 
5.1%
4 3883
 
4.7%
5 3675
 
4.5%
7 3155
 
3.8%
9 2973
 
3.6%
8 2661
 
3.2%
Other Letter
ValueCountFrequency (%)
가 2494
98.8%
나 30
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 14672
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 96750
97.5%
Hangul 2524
 
2.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 28009
28.9%
2 15812
16.3%
- 14672
15.2%
1 9995
 
10.3%
6 7710
 
8.0%
3 4200
 
4.3%
4 3883
 
4.0%
5 3675
 
3.8%
7 3155
 
3.3%
9 2973
 
3.1%
Other values (2) 2666
 
2.8%
Hangul
ValueCountFrequency (%)
가 2494
98.8%
나 30
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96750
97.5%
Hangul 2524
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 28009
28.9%
2 15812
16.3%
- 14672
15.2%
1 9995
 
10.3%
6 7710
 
8.0%
3 4200
 
4.3%
4 3883
 
4.0%
5 3675
 
3.8%
7 3155
 
3.3%
9 2973
 
3.1%
Other values (2) 2666
 
2.8%
Hangul
ValueCountFrequency (%)
가 2494
98.8%
나 30
 
1.2%

lastupdtdt
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
Minimum2021-01-31 00:00:00
Maximum2021-01-31 00:00:00
2024-04-17T11:16:39.963715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:40.063198image/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%
Mean26369.886
Minimum26110
Maximum26710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.4 KiB
2024-04-17T11:16:40.138082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum26110
5-th percentile26170
Q126260
median26350
Q326470
95-th percentile26710
Maximum26710
Range600
Interquartile range (IQR)210

Descriptive statistics

Standard deviation133.87822
Coefficient of variation (CV)0.0050769359
Kurtosis0.37403298
Mean26369.886
Median Absolute Deviation (MAD)90
Skewness0.61086186
Sum1.9584914 × 108
Variance17923.378
MonotonicityNot monotonic
2024-04-17T11:16:40.225257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
26350 930
12.5%
26230 844
11.4%
26260 669
9.0%
26470 602
8.1%
26440 588
7.9%
26500 535
7.2%
26410 534
7.2%
26290 525
7.1%
26380 469
 
6.3%
26710 434
 
5.8%
Other values (6) 1297
17.5%
ValueCountFrequency (%)
26110 123
 
1.7%
26140 155
 
2.1%
26170 161
 
2.2%
26200 130
 
1.8%
26230 844
11.4%
26260 669
9.0%
26290 525
7.1%
26320 417
5.6%
26350 930
12.5%
26380 469
6.3%
ValueCountFrequency (%)
26710 434
5.8%
26530 311
 
4.2%
26500 535
7.2%
26470 602
8.1%
26440 588
7.9%
26410 534
7.2%
26380 469
6.3%
26350 930
12.5%
26320 417
5.6%
26290 525
7.1%

ldcodenm
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
부산광역시 해운대구
930 
부산광역시 부산진구
844 
부산광역시 동래구
669 
부산광역시 연제구
602 
부산광역시 강서구
588 
Other values (11)
3794 

Length

Max length10
Median length9
Mean length9.052915
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 중구
2nd row부산광역시 중구
3rd row부산광역시 중구
4th row부산광역시 중구
5th row부산광역시 중구

Common Values

ValueCountFrequency (%)
부산광역시 해운대구 930
12.5%
부산광역시 부산진구 844
11.4%
부산광역시 동래구 669
9.0%
부산광역시 연제구 602
8.1%
부산광역시 강서구 588
7.9%
부산광역시 수영구 535
7.2%
부산광역시 금정구 534
7.2%
부산광역시 남구 525
7.1%
부산광역시 사하구 469
 
6.3%
부산광역시 기장군 434
 
5.8%
Other values (6) 1297
17.5%

Length

2024-04-17T11:16:40.331343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 7427
50.0%
해운대구 930
 
6.3%
부산진구 844
 
5.7%
동래구 669
 
4.5%
연제구 602
 
4.1%
강서구 588
 
4.0%
수영구 535
 
3.6%
금정구 534
 
3.6%
남구 525
 
3.5%
사하구 469
 
3.2%
Other values (7) 1731
 
11.7%

registde
Date

Distinct3192
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
Minimum1984-04-24 00:00:00
Maximum2021-01-28 00:00:00
2024-04-17T11:16:40.437696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:40.549060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

sttussecode
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
1
7394 
2
 
24
3
 
5
8
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 7394
99.6%
2 24
 
0.3%
3 5
 
0.1%
8 4
 
0.1%

Length

2024-04-17T11:16:40.654362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:40.757449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 7394
99.6%
2 24
 
0.3%
3 5
 
0.1%
8 4
 
0.1%

sttussecodenm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
영업중
7394 
휴업
 
24
휴업연장
 
5
업무정지
 
4

Length

Max length4
Median length3
Mean length2.9979803
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 7394
99.6%
휴업 24
 
0.3%
휴업연장 5
 
0.1%
업무정지 4
 
0.1%

Length

2024-04-17T11:16:40.853313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:40.968991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 7394
99.6%
휴업 24
 
0.3%
휴업연장 5
 
0.1%
업무정지 4
 
0.1%

telnolist
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7427
Missing (%)100.0%
Memory size65.4 KiB

last_load_dttm
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size58.2 KiB
Minimum2021-02-01 06:23:03
Maximum2021-02-01 06:23:03
2024-04-17T11:16:41.036604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:41.109875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-17T11:16:36.382287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T11:16:41.162434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodeldcodenmsttussecodesttussecodenm
ldcode1.0001.0000.0470.047
ldcodenm1.0001.0000.0620.062
sttussecode0.0470.0621.0001.000
sttussecodenm0.0470.0621.0001.000
2024-04-17T11:16:41.237890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
sttussecodeldcodenmsttussecodenm
sttussecode1.0000.0291.000
ldcodenm0.0291.0000.029
sttussecodenm1.0000.0291.000
2024-04-17T11:16:41.309860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodeldcodenmsttussecodesttussecodenm
ldcode1.0000.9990.0200.020
ldcodenm0.9991.0000.0290.029
sttussecode0.0200.0291.0001.000
sttussecodenm0.0200.0291.0001.000

Missing values

2024-04-17T11:16:36.493421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T11:16:36.639729image/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.
2024-04-17T11:16:36.749311image/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

brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmtelnolistlast_load_dttm
0정영희천봉공인중개사2021-01-042022-01-03가-01-6192021-01-3126110부산광역시 중구2011-01-041영업중<NA>2021-02-01 06:23:03
1이지미중앙공인중개사무소2021-01-132022-01-12가-01-6202021-01-3126110부산광역시 중구2011-01-131영업중<NA>2021-02-01 06:23:03
2김덕길마당발부동산중개사무소2020-04-062021-04-05가-01-6212021-01-3126110부산광역시 중구2006-04-101영업중<NA>2021-02-01 06:23:03
3천순철참조은공인중개사사무소2020-08-112021-08-10가-01-6242021-01-3126110부산광역시 중구2008-08-111영업중<NA>2021-02-01 06:23:03
4김정석가람공인중개사사무소2020-05-182021-05-17가-01-6252021-01-3126110부산광역시 중구2011-05-191영업중<NA>2021-02-01 06:23:03
5손동욱박사부동산중개사무소2020-05-232021-05-22가-01-6262021-01-3126110부산광역시 중구2011-05-201영업중<NA>2021-02-01 06:23:03
6박성순명문부동산공인중개사사무소2020-03-282021-03-27가-01-6482021-01-3126110부산광역시 중구2012-03-281영업중<NA>2021-02-01 06:23:03
7남상복남상복 부동산 공인중개사사무소2020-04-162021-04-15가-01-6502021-01-3126110부산광역시 중구2012-04-161영업중<NA>2021-02-01 06:23:03
8조 희3G 공인중개사사무소2020-04-232021-04-22가-01-6512021-01-3126110부산광역시 중구2012-04-161영업중<NA>2021-02-01 06:23:03
9윤성진뉴롯데 공인중개사사무소2020-04-252021-04-24가-01-6522021-01-3126110부산광역시 중구2012-04-251영업중<NA>2021-02-01 06:23:03
brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmtelnolistlast_load_dttm
7417이서영일광퀸부동산공인중개사사무소2020-03-272021-03-26가16-9662021-01-3126710부산광역시 기장군2012-03-271영업중<NA>2021-02-01 06:23:03
7418하화정강남공인중개사사무소2020-05-012021-04-30가16-9722021-01-3126710부산광역시 기장군2012-04-241영업중<NA>2021-02-01 06:23:03
7419서창열부자공인중개사사무소2020-06-082021-06-07가16-9842021-01-3126710부산광역시 기장군2012-06-071영업중<NA>2021-02-01 06:23:03
7420선은미롯데캐슬부동산공인중개사사무소2020-08-162021-08-15가16-9922021-01-3126710부산광역시 기장군2012-08-161영업중<NA>2021-02-01 06:23:03
7421한성희크로바공인중개사사무소2020-12-202021-12-19가16-10142021-01-3126710부산광역시 기장군2012-12-201영업중<NA>2021-02-01 06:23:03
7422김성훈여명컨설팅공인중개사사무소2020-12-232021-12-22가16-10172021-01-3126710부산광역시 기장군2012-12-211영업중<NA>2021-02-01 06:23:03
7423윤학순기장우리들공인중개사사무소2021-01-062022-01-05가-16-10272021-01-3126710부산광역시 기장군2013-01-041영업중<NA>2021-02-01 06:23:03
7424최해정제일부동산공인중개사사무소2021-01-152022-01-14가16-10302021-01-3126710부산광역시 기장군2013-01-151영업중<NA>2021-02-01 06:23:03
7425황숙이서희스타힐스부동산공인중개사사무소2021-02-042022-02-03가16-10372021-01-3126710부산광역시 기장군2013-02-041영업중<NA>2021-02-01 06:23:03
7426최권세알파부동산공인중개사사무소2020-04-082021-04-07가16-10492021-01-3126710부산광역시 기장군2013-03-081영업중<NA>2021-02-01 06:23:03

Duplicate rows

Most frequently occurring

brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmlast_load_dttm# duplicates
3<NA><NA><NA><NA><NA>2021-01-3126380부산광역시 사하구2012-10-291영업중2021-02-01 06:23:036
0<NA>삼성명가부동산중개2014-06-122015-06-11가-11-20942021-01-3126410부산광역시 금정구2013-06-121영업중2021-02-01 06:23:032
1<NA><NA><NA><NA><NA>2021-01-3126140부산광역시 서구2015-06-101영업중2021-02-01 06:23:032
2<NA><NA><NA><NA><NA>2021-01-3126170부산광역시 동구2013-08-281영업중2021-02-01 06:23:032