Overview

Dataset statistics

Number of variables13
Number of observations7603
Missing cells7963
Missing cells (%)8.1%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory794.6 KiB
Average record size in memory107.0 B

Variable types

Text3
DateTime3
Categorical5
Numeric1
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 (97.9%)Imbalance
sttussecodenm is highly imbalanced (97.9%)Imbalance
estbsbeginde has 91 (1.2%) missing valuesMissing
estbsendde has 91 (1.2%) missing valuesMissing
telnolist has 7603 (100.0%) missing valuesMissing
telnolist is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 02:16:16.448310
Analysis finished2024-04-17 02:16:17.595441
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

brkrnm
Text

Distinct6266
Distinct (%)83.2%
Missing68
Missing (%)0.9%
Memory size59.5 KiB
2024-04-17T11:16:17.806824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length3
Mean length3.0039814
Min length2

Characters and Unicode

Total characters22635
Distinct characters339
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

Unique5522 ?
Unique (%)73.3%

Sample

1st row배상수
2nd row송창선
3rd row박상희
4th row이혜정
5th row문준기
ValueCountFrequency (%)
김정희 17
 
0.2%
이영주 11
 
0.1%
김미경 11
 
0.1%
김미숙 10
 
0.1%
김경희 10
 
0.1%
김영희 10
 
0.1%
이정희 10
 
0.1%
이미경 9
 
0.1%
김민정 9
 
0.1%
이정미 8
 
0.1%
Other values (6266) 7441
98.6%
2024-04-17T11:16:18.180747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 1625
 
7.2%
이 1149
 
5.1%
정 1094
 
4.8%
영 790
 
3.5%
박 684
 
3.0%
희 564
 
2.5%
경 542
 
2.4%
미 487
 
2.2%
숙 452
 
2.0%
현 416
 
1.8%
Other values (329) 14832
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22566
99.7%
Uppercase Letter 20
 
0.1%
Lowercase Letter 15
 
0.1%
Space Separator 12
 
0.1%
Open Punctuation 11
 
< 0.1%
Close Punctuation 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 1625
 
7.2%
이 1149
 
5.1%
정 1094
 
4.8%
영 790
 
3.5%
박 684
 
3.0%
희 564
 
2.5%
경 542
 
2.4%
미 487
 
2.2%
숙 452
 
2.0%
현 416
 
1.8%
Other values (301) 14763
65.4%
Uppercase Letter
ValueCountFrequency (%)
L 3
15.0%
K 2
 
10.0%
N 2
 
10.0%
A 2
 
10.0%
B 1
 
5.0%
H 1
 
5.0%
C 1
 
5.0%
S 1
 
5.0%
R 1
 
5.0%
I 1
 
5.0%
Other values (5) 5
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
26.7%
y 2
13.3%
a 2
13.3%
u 1
 
6.7%
n 1
 
6.7%
s 1
 
6.7%
g 1
 
6.7%
i 1
 
6.7%
k 1
 
6.7%
m 1
 
6.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22534
99.6%
Latin 35
 
0.2%
Common 34
 
0.2%
Han 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 1625
 
7.2%
이 1149
 
5.1%
정 1094
 
4.9%
영 790
 
3.5%
박 684
 
3.0%
희 564
 
2.5%
경 542
 
2.4%
미 487
 
2.2%
숙 452
 
2.0%
현 416
 
1.8%
Other values (274) 14731
65.4%
Han
ValueCountFrequency (%)
金 3
 
9.4%
美 2
 
6.2%
崔 2
 
6.2%
順 2
 
6.2%
榮 1
 
3.1%
姜 1
 
3.1%
忠 1
 
3.1%
棲 1
 
3.1%
然 1
 
3.1%
愛 1
 
3.1%
Other values (17) 17
53.1%
Latin
ValueCountFrequency (%)
e 4
 
11.4%
L 3
 
8.6%
K 2
 
5.7%
N 2
 
5.7%
A 2
 
5.7%
y 2
 
5.7%
a 2
 
5.7%
u 1
 
2.9%
B 1
 
2.9%
H 1
 
2.9%
Other values (15) 15
42.9%
Common
ValueCountFrequency (%)
12
35.3%
( 11
32.4%
) 11
32.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22534
99.6%
ASCII 69
 
0.3%
CJK 31
 
0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 1625
 
7.2%
이 1149
 
5.1%
정 1094
 
4.9%
영 790
 
3.5%
박 684
 
3.0%
희 564
 
2.5%
경 542
 
2.4%
미 487
 
2.2%
숙 452
 
2.0%
현 416
 
1.8%
Other values (274) 14731
65.4%
ASCII
ValueCountFrequency (%)
12
17.4%
( 11
15.9%
) 11
15.9%
e 4
 
5.8%
L 3
 
4.3%
K 2
 
2.9%
N 2
 
2.9%
A 2
 
2.9%
y 2
 
2.9%
a 2
 
2.9%
Other values (18) 18
26.1%
CJK
ValueCountFrequency (%)
金 3
 
9.7%
美 2
 
6.5%
崔 2
 
6.5%
順 2
 
6.5%
榮 1
 
3.2%
姜 1
 
3.2%
忠 1
 
3.2%
棲 1
 
3.2%
然 1
 
3.2%
愛 1
 
3.2%
Other values (16) 16
51.6%
CJK Compat Ideographs
ValueCountFrequency (%)
李 1
100.0%

bsnmcmpnm
Text

Distinct4943
Distinct (%)65.5%
Missing55
Missing (%)0.7%
Memory size59.5 KiB
2024-04-17T11:16:18.355574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length11.318362
Min length4

Characters and Unicode

Total characters85431
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

Unique4086 ?
Unique (%)54.1%

Sample

1st row경동공인중개사사무소
2nd row(주)해강부동산중개법인
3rd row신원플러스공인중개사사무소
4th row해솔공인중개사사무소
5th row예가공인중개사사무소
ValueCountFrequency (%)
사무소 82
 
1.1%
공인중개사사무소 76
 
1.0%
현대공인중개사사무소 40
 
0.5%
삼성공인중개사사무소 36
 
0.5%
미래공인중개사사무소 35
 
0.4%
행운공인중개사사무소 33
 
0.4%
태양공인중개사사무소 33
 
0.4%
탑공인중개사사무소 28
 
0.4%
하나공인중개사사무소 27
 
0.3%
주식회사 24
 
0.3%
Other values (4914) 7390
94.7%
2024-04-17T11:16:18.641346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 13591
15.9%
중 7581
 
8.9%
개 7565
 
8.9%
소 7125
 
8.3%
무 7082
 
8.3%
인 6602
 
7.7%
공 6402
 
7.5%
동 2883
 
3.4%
부 2643
 
3.1%
산 2585
 
3.0%
Other values (620) 21372
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 83545
97.8%
Uppercase Letter 795
 
0.9%
Space Separator 347
 
0.4%
Decimal Number 316
 
0.4%
Lowercase Letter 176
 
0.2%
Open Punctuation 110
 
0.1%
Close Punctuation 110
 
0.1%
Other Punctuation 20
 
< 0.1%
Dash Punctuation 9
 
< 0.1%
Modifier Symbol 1
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 13591
16.3%
중 7581
 
9.1%
개 7565
 
9.1%
소 7125
 
8.5%
무 7082
 
8.5%
인 6602
 
7.9%
공 6402
 
7.7%
동 2883
 
3.5%
부 2643
 
3.2%
산 2585
 
3.1%
Other values (554) 19486
23.3%
Uppercase Letter
ValueCountFrequency (%)
K 149
18.7%
S 104
13.1%
L 71
 
8.9%
T 70
 
8.8%
C 51
 
6.4%
O 44
 
5.5%
W 38
 
4.8%
E 31
 
3.9%
G 29
 
3.6%
H 27
 
3.4%
Other values (16) 181
22.8%
Lowercase Letter
ValueCountFrequency (%)
e 78
44.3%
h 27
 
15.3%
t 15
 
8.5%
c 14
 
8.0%
w 10
 
5.7%
k 8
 
4.5%
s 6
 
3.4%
o 4
 
2.3%
n 3
 
1.7%
i 2
 
1.1%
Other values (7) 9
 
5.1%
Decimal Number
ValueCountFrequency (%)
1 137
43.4%
8 44
 
13.9%
4 36
 
11.4%
2 26
 
8.2%
3 23
 
7.3%
9 19
 
6.0%
5 12
 
3.8%
6 7
 
2.2%
7 7
 
2.2%
0 5
 
1.6%
Other Punctuation
ValueCountFrequency (%)
& 7
35.0%
. 7
35.0%
· 3
15.0%
! 1
 
5.0%
# 1
 
5.0%
, 1
 
5.0%
Space Separator
ValueCountFrequency (%)
347
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 83533
97.8%
Latin 972
 
1.1%
Common 914
 
1.1%
Han 12
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 13591
16.3%
중 7581
 
9.1%
개 7565
 
9.1%
소 7125
 
8.5%
무 7082
 
8.5%
인 6602
 
7.9%
공 6402
 
7.7%
동 2883
 
3.5%
부 2643
 
3.2%
산 2585
 
3.1%
Other values (543) 19474
23.3%
Latin
ValueCountFrequency (%)
K 149
15.3%
S 104
 
10.7%
e 78
 
8.0%
L 71
 
7.3%
T 70
 
7.2%
C 51
 
5.2%
O 44
 
4.5%
W 38
 
3.9%
E 31
 
3.2%
G 29
 
3.0%
Other values (34) 307
31.6%
Common
ValueCountFrequency (%)
347
38.0%
1 137
 
15.0%
( 110
 
12.0%
) 110
 
12.0%
8 44
 
4.8%
4 36
 
3.9%
2 26
 
2.8%
3 23
 
2.5%
9 19
 
2.1%
5 12
 
1.3%
Other values (12) 50
 
5.5%
Han
ValueCountFrequency (%)
福 2
16.7%
炫 1
8.3%
秀 1
8.3%
利 1
8.3%
太 1
8.3%
甲 1
8.3%
明 1
8.3%
堂 1
8.3%
本 1
8.3%
該 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 83533
97.8%
ASCII 1881
 
2.2%
CJK 12
 
< 0.1%
None 3
 
< 0.1%
Number Forms 1
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 13591
16.3%
중 7581
 
9.1%
개 7565
 
9.1%
소 7125
 
8.5%
무 7082
 
8.5%
인 6602
 
7.9%
공 6402
 
7.7%
동 2883
 
3.5%
부 2643
 
3.2%
산 2585
 
3.1%
Other values (543) 19474
23.3%
ASCII
ValueCountFrequency (%)
347
18.4%
K 149
 
7.9%
1 137
 
7.3%
( 110
 
5.8%
) 110
 
5.8%
S 104
 
5.5%
e 78
 
4.1%
L 71
 
3.8%
T 70
 
3.7%
C 51
 
2.7%
Other values (53) 654
34.8%
None
ValueCountFrequency (%)
· 3
100.0%
CJK
ValueCountFrequency (%)
福 2
16.7%
炫 1
8.3%
秀 1
8.3%
利 1
8.3%
太 1
8.3%
甲 1
8.3%
明 1
8.3%
堂 1
8.3%
本 1
8.3%
該 1
8.3%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 1
100.0%

estbsbeginde
Date

MISSING 

Distinct490
Distinct (%)6.5%
Missing91
Missing (%)1.2%
Memory size59.5 KiB
Minimum2013-03-24 00:00:00
Maximum2021-12-16 00:00:00
2024-04-17T11:16:18.743273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:18.853895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

estbsendde
Date

MISSING 

Distinct482
Distinct (%)6.4%
Missing91
Missing (%)1.2%
Memory size59.5 KiB
Minimum2014-03-23 00:00:00
Maximum2024-11-15 00:00:00
2024-04-17T11:16:18.959473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:19.059089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

jurirno
Text

Distinct7540
Distinct (%)99.9%
Missing55
Missing (%)0.7%
Memory size59.5 KiB
2024-04-17T11:16:19.248477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length13.568495
Min length6

Characters and Unicode

Total characters102415
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

Unique7532 ?
Unique (%)99.8%

Sample

1st row26140-2020-00031
2nd row26140-2020-00032
3rd row26140-2020-00034
4th row26140-2020-00036
5th row26140-2020-00037
ValueCountFrequency (%)
가-11-2094 2
 
< 0.1%
26470-2015-00086 2
 
< 0.1%
2
 
< 0.1%
26260-2021-00066 2
 
< 0.1%
26230-2017-00146 2
 
< 0.1%
가 2
 
< 0.1%
26440-2019-00095 2
 
< 0.1%
26410-2021-00043 2
 
< 0.1%
26260-2021-00055 2
 
< 0.1%
26410-2016-00056 2
 
< 0.1%
Other values (7533) 7533
99.7%
2024-04-17T11:16:19.530106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 29047
28.4%
2 16717
16.3%
- 15028
14.7%
1 10312
 
10.1%
6 7972
 
7.8%
3 4334
 
4.2%
4 4021
 
3.9%
5 3738
 
3.6%
7 3196
 
3.1%
9 2922
 
2.9%
Other values (4) 5128
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84899
82.9%
Dash Punctuation 15028
 
14.7%
Other Letter 2483
 
2.4%
Space Separator 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 29047
34.2%
2 16717
19.7%
1 10312
 
12.1%
6 7972
 
9.4%
3 4334
 
5.1%
4 4021
 
4.7%
5 3738
 
4.4%
7 3196
 
3.8%
9 2922
 
3.4%
8 2640
 
3.1%
Other Letter
ValueCountFrequency (%)
가 2453
98.8%
나 30
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 15028
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99932
97.6%
Hangul 2483
 
2.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 29047
29.1%
2 16717
16.7%
- 15028
15.0%
1 10312
 
10.3%
6 7972
 
8.0%
3 4334
 
4.3%
4 4021
 
4.0%
5 3738
 
3.7%
7 3196
 
3.2%
9 2922
 
2.9%
Other values (2) 2645
 
2.6%
Hangul
ValueCountFrequency (%)
가 2453
98.8%
나 30
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99932
97.6%
Hangul 2483
 
2.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 29047
29.1%
2 16717
16.7%
- 15028
15.0%
1 10312
 
10.3%
6 7972
 
8.0%
3 4334
 
4.3%
4 4021
 
4.0%
5 3738
 
3.7%
7 3196
 
3.2%
9 2922
 
2.9%
Other values (2) 2645
 
2.6%
Hangul
ValueCountFrequency (%)
가 2453
98.8%
나 30
 
1.2%

lastupdtdt
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size59.5 KiB
2021-04-29
7603 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-04-29
2nd row2021-04-29
3rd row2021-04-29
4th row2021-04-29
5th row2021-04-29

Common Values

ValueCountFrequency (%)
2021-04-29 7603
100.0%

Length

2024-04-17T11:16:19.643183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:19.715024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-29 7603
100.0%

ldcode
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26369.867
Minimum26110
Maximum26710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.0 KiB
2024-04-17T11:16:19.775975image/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 deviation133.84277
Coefficient of variation (CV)0.0050755951
Kurtosis0.37941146
Mean26369.867
Median Absolute Deviation (MAD)90
Skewness0.61796166
Sum2.004901 × 108
Variance17913.887
MonotonicityNot monotonic
2024-04-17T11:16:20.085938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
26350 948
12.5%
26230 866
11.4%
26260 701
9.2%
26470 626
8.2%
26440 599
7.9%
26410 546
7.2%
26500 539
7.1%
26290 533
7.0%
26380 477
 
6.3%
26710 446
 
5.9%
Other values (6) 1322
17.4%
ValueCountFrequency (%)
26110 125
 
1.6%
26140 155
 
2.0%
26170 161
 
2.1%
26200 134
 
1.8%
26230 866
11.4%
26260 701
9.2%
26290 533
7.0%
26320 430
5.7%
26350 948
12.5%
26380 477
6.3%
ValueCountFrequency (%)
26710 446
5.9%
26530 317
 
4.2%
26500 539
7.1%
26470 626
8.2%
26440 599
7.9%
26410 546
7.2%
26380 477
6.3%
26350 948
12.5%
26320 430
5.7%
26290 533
7.0%

ldcodenm
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size59.5 KiB
부산광역시 해운대구
948 
부산광역시 부산진구
866 
부산광역시 동래구
701 
부산광역시 연제구
626 
부산광역시 강서구
599 
Other values (11)
3863 

Length

Max length10
Median length9
Mean length9.0539261
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부산광역시 해운대구 948
12.5%
부산광역시 부산진구 866
11.4%
부산광역시 동래구 701
9.2%
부산광역시 연제구 626
8.2%
부산광역시 강서구 599
7.9%
부산광역시 금정구 546
7.2%
부산광역시 수영구 539
7.1%
부산광역시 남구 533
7.0%
부산광역시 사하구 477
 
6.3%
부산광역시 기장군 446
 
5.9%
Other values (6) 1322
17.4%

Length

2024-04-17T11:16:20.187878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 7603
50.0%
해운대구 948
 
6.2%
부산진구 866
 
5.7%
동래구 701
 
4.6%
연제구 626
 
4.1%
강서구 599
 
3.9%
금정구 546
 
3.6%
수영구 539
 
3.5%
남구 533
 
3.5%
사하구 477
 
3.1%
Other values (7) 1768
 
11.6%

registde
Date

Distinct3223
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Memory size59.5 KiB
Minimum1984-04-24 00:00:00
Maximum2021-04-28 00:00:00
2024-04-17T11:16:20.311776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:20.455035image/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 size59.5 KiB
1
7573 
2
 
23
8
 
5
3
 
2

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 7573
99.6%
2 23
 
0.3%
8 5
 
0.1%
3 2
 
< 0.1%

Length

2024-04-17T11:16:20.559105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:20.637878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 7573
99.6%
2 23
 
0.3%
8 5
 
0.1%
3 2
 
< 0.1%

sttussecodenm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size59.5 KiB
영업중
7573 
휴업
 
23
업무정지
 
5
휴업연장
 
2

Length

Max length4
Median length3
Mean length2.9978956
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 7573
99.6%
휴업 23
 
0.3%
업무정지 5
 
0.1%
휴업연장 2
 
< 0.1%

Length

2024-04-17T11:16:20.731242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:20.819529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 7573
99.6%
휴업 23
 
0.3%
업무정지 5
 
0.1%
휴업연장 2
 
< 0.1%

telnolist
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7603
Missing (%)100.0%
Memory size67.0 KiB

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size59.5 KiB
2021-05-01 06:23:03
7603 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-05-01 06:23:03
2nd row2021-05-01 06:23:03
3rd row2021-05-01 06:23:03
4th row2021-05-01 06:23:03
5th row2021-05-01 06:23:03

Common Values

ValueCountFrequency (%)
2021-05-01 06:23:03 7603
100.0%

Length

2024-04-17T11:16:20.907893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:20.983135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-05-01 7603
50.0%
06:23:03 7603
50.0%

Interactions

2024-04-17T11:16:17.175259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T11:16:21.033181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodeldcodenmsttussecodesttussecodenm
ldcode1.0001.0000.0290.029
ldcodenm1.0001.0000.0650.065
sttussecode0.0290.0651.0001.000
sttussecodenm0.0290.0651.0001.000
2024-04-17T11:16:21.103556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
sttussecodeldcodenmsttussecodenm
sttussecode1.0000.0311.000
ldcodenm0.0311.0000.031
sttussecodenm1.0000.0311.000
2024-04-17T11:16:21.174349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodeldcodenmsttussecodesttussecodenm
ldcode1.0000.9990.0190.019
ldcodenm0.9991.0000.0310.031
sttussecode0.0190.0311.0001.000
sttussecodenm0.0190.0311.0001.000

Missing values

2024-04-17T11:16:17.281605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T11:16:17.423558image/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.
2024-04-17T11:16:17.531685image/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
0배상수경동공인중개사사무소2020-11-062021-11-0526140-2020-000312021-04-2926140부산광역시 서구2020-11-061영업중<NA>2021-05-01 06:23:03
1송창선(주)해강부동산중개법인2020-11-252021-11-2426140-2020-000322021-04-2926140부산광역시 서구2020-11-181영업중<NA>2021-05-01 06:23:03
2박상희신원플러스공인중개사사무소2020-12-012021-11-3026140-2020-000342021-04-2926140부산광역시 서구2020-11-301영업중<NA>2021-05-01 06:23:03
3이혜정해솔공인중개사사무소2020-12-172021-12-1626140-2020-000362021-04-2926140부산광역시 서구2020-12-171영업중<NA>2021-05-01 06:23:03
4문준기예가공인중개사사무소2020-12-182021-12-1726140-2020-000372021-04-2926140부산광역시 서구2020-12-171영업중<NA>2021-05-01 06:23:03
5이미선구덕공인중개사사무소2020-12-212021-12-2026140-2020-000382021-04-2926140부산광역시 서구2020-12-181영업중<NA>2021-05-01 06:23:03
6홍순현해솔부동산중개사무소2020-05-212021-05-2026140-2020-000392021-04-2926140부산광역시 서구2020-05-201영업중<NA>2021-05-01 06:23:03
7서소정골든공인중개사사무소2021-01-062022-01-0526140-2021-000012021-04-2926140부산광역시 서구2021-01-051영업중<NA>2021-05-01 06:23:03
8하태성한진부동산중개사무소2021-01-062022-01-0526140-2021-000022021-04-2926140부산광역시 서구2021-01-061영업중<NA>2021-05-01 06:23:03
9박영수새현대공인중개사사무소2021-01-062022-01-0526140-2021-000032021-04-2926140부산광역시 서구2021-01-061영업중<NA>2021-05-01 06:23:03
brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmtelnolistlast_load_dttm
7593이서영일광퀸부동산공인중개사사무소2021-03-272022-03-26가16-9662021-04-2926710부산광역시 기장군2012-03-271영업중<NA>2021-05-01 06:23:03
7594하화정강남공인중개사사무소2021-05-012022-04-30가16-9722021-04-2926710부산광역시 기장군2012-04-241영업중<NA>2021-05-01 06:23:03
7595서창열부자공인중개사사무소2020-06-082021-06-07가16-9842021-04-2926710부산광역시 기장군2012-06-071영업중<NA>2021-05-01 06:23:03
7596한성희크로바공인중개사사무소2020-12-202021-12-19가16-10142021-04-2926710부산광역시 기장군2012-12-201영업중<NA>2021-05-01 06:23:03
7597김성훈여명컨설팅공인중개사사무소2020-12-232021-12-22가16-10172021-04-2926710부산광역시 기장군2012-12-211영업중<NA>2021-05-01 06:23:03
7598윤학순기장우리들공인중개사사무소2021-01-062022-01-05가-16-10272021-04-2926710부산광역시 기장군2013-01-041영업중<NA>2021-05-01 06:23:03
7599최해정제일부동산공인중개사사무소2021-01-152022-01-14가16-10302021-04-2926710부산광역시 기장군2013-01-151영업중<NA>2021-05-01 06:23:03
7600황숙이서희스타힐스부동산공인중개사사무소2021-02-042022-02-03가16-10372021-04-2926710부산광역시 기장군2013-02-041영업중<NA>2021-05-01 06:23:03
7601최권세정관일등부동산공인중개사사무소2021-04-082022-04-07가16-10492021-04-2926710부산광역시 기장군2013-03-081영업중<NA>2021-05-01 06:23:03
7602한충기대동부동산공인중개사사무소2021-03-202022-03-19가16-10532021-04-2926710부산광역시 기장군2013-03-251영업중<NA>2021-05-01 06:23:03

Duplicate rows

Most frequently occurring

brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmlast_load_dttm# duplicates
3<NA><NA><NA><NA><NA>2021-04-2926380부산광역시 사하구2012-10-291영업중2021-05-01 06:23:036
0<NA>삼성명가부동산중개2014-06-122015-06-11가-11-20942021-04-2926410부산광역시 금정구2013-06-121영업중2021-05-01 06:23:032
1<NA><NA><NA><NA><NA>2021-04-2926140부산광역시 서구2015-06-101영업중2021-05-01 06:23:032
2<NA><NA><NA><NA><NA>2021-04-2926170부산광역시 동구2013-08-281영업중2021-05-01 06:23:032