Overview

Dataset statistics

Number of variables13
Number of observations7371
Missing cells7729
Missing cells (%)8.1%
Duplicate rows5
Duplicate rows (%)0.1%
Total size in memory770.3 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 5 (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 (97.6%)Imbalance
sttussecodenm is highly imbalanced (97.6%)Imbalance
estbsbeginde has 91 (1.2%) missing valuesMissing
estbsendde has 91 (1.2%) missing valuesMissing
telnolist has 7371 (100.0%) missing valuesMissing
telnolist is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 02:16:49.239504
Analysis finished2024-04-17 02:16:50.772548
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

brkrnm
Text

Distinct6091
Distinct (%)83.4%
Missing64
Missing (%)0.9%
Memory size57.7 KiB
2024-04-17T11:16:50.987372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length3
Mean length3.0032845
Min length2

Characters and Unicode

Total characters21945
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

Unique5362 ?
Unique (%)73.4%

Sample

1st row강호근
2nd row백수현
3rd row김홍숙
4th row강영지
5th row정인수
ValueCountFrequency (%)
김정희 17
 
0.2%
김미경 11
 
0.2%
김영희 11
 
0.2%
김미숙 10
 
0.1%
이미경 10
 
0.1%
이정희 10
 
0.1%
이영주 10
 
0.1%
김경희 10
 
0.1%
김민정 9
 
0.1%
김민주 8
 
0.1%
Other values (6089) 7210
98.6%
2024-04-17T11:16:51.385007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 1594
 
7.3%
이 1117
 
5.1%
정 1064
 
4.8%
영 757
 
3.4%
박 649
 
3.0%
희 555
 
2.5%
경 537
 
2.4%
미 464
 
2.1%
숙 443
 
2.0%
현 399
 
1.8%
Other values (318) 14366
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21890
99.7%
Lowercase Letter 15
 
0.1%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%
Space Separator 10
 
< 0.1%
Uppercase Letter 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 1594
 
7.3%
이 1117
 
5.1%
정 1064
 
4.9%
영 757
 
3.5%
박 649
 
3.0%
희 555
 
2.5%
경 537
 
2.5%
미 464
 
2.1%
숙 443
 
2.0%
현 399
 
1.8%
Other values (299) 14311
65.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
26.7%
y 2
13.3%
a 2
13.3%
m 1
 
6.7%
k 1
 
6.7%
i 1
 
6.7%
g 1
 
6.7%
n 1
 
6.7%
u 1
 
6.7%
s 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
A 1
16.7%
B 1
16.7%
L 1
16.7%
H 1
16.7%
S 1
16.7%
C 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21855
99.6%
Han 35
 
0.2%
Common 34
 
0.2%
Latin 21
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 1594
 
7.3%
이 1117
 
5.1%
정 1064
 
4.9%
영 757
 
3.5%
박 649
 
3.0%
희 555
 
2.5%
경 537
 
2.5%
미 464
 
2.1%
숙 443
 
2.0%
현 399
 
1.8%
Other values (271) 14276
65.3%
Han
ValueCountFrequency (%)
金 3
 
8.6%
美 2
 
5.7%
李 2
 
5.7%
慶 2
 
5.7%
崔 2
 
5.7%
順 2
 
5.7%
忠 1
 
2.9%
喜 1
 
2.9%
曺 1
 
2.9%
然 1
 
2.9%
Other values (18) 18
51.4%
Latin
ValueCountFrequency (%)
e 4
19.0%
y 2
 
9.5%
a 2
 
9.5%
m 1
 
4.8%
A 1
 
4.8%
k 1
 
4.8%
i 1
 
4.8%
B 1
 
4.8%
L 1
 
4.8%
H 1
 
4.8%
Other values (6) 6
28.6%
Common
ValueCountFrequency (%)
( 12
35.3%
) 12
35.3%
10
29.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21855
99.6%
ASCII 55
 
0.3%
CJK 33
 
0.2%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 1594
 
7.3%
이 1117
 
5.1%
정 1064
 
4.9%
영 757
 
3.5%
박 649
 
3.0%
희 555
 
2.5%
경 537
 
2.5%
미 464
 
2.1%
숙 443
 
2.0%
현 399
 
1.8%
Other values (271) 14276
65.3%
ASCII
ValueCountFrequency (%)
( 12
21.8%
) 12
21.8%
10
18.2%
e 4
 
7.3%
y 2
 
3.6%
a 2
 
3.6%
m 1
 
1.8%
A 1
 
1.8%
k 1
 
1.8%
i 1
 
1.8%
Other values (9) 9
16.4%
CJK
ValueCountFrequency (%)
金 3
 
9.1%
美 2
 
6.1%
慶 2
 
6.1%
崔 2
 
6.1%
順 2
 
6.1%
忠 1
 
3.0%
喜 1
 
3.0%
曺 1
 
3.0%
然 1
 
3.0%
棲 1
 
3.0%
Other values (17) 17
51.5%
CJK Compat Ideographs
ValueCountFrequency (%)
李 2
100.0%

bsnmcmpnm
Text

Distinct4758
Distinct (%)65.0%
Missing56
Missing (%)0.8%
Memory size57.7 KiB
2024-04-17T11:16:51.578614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length11.286261
Min length4

Characters and Unicode

Total characters82559
Distinct characters624
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

Unique3920 ?
Unique (%)53.6%

Sample

1st rowOK공인중개사사무소
2nd row굿모닝 공인중개사
3rd row부원공인중개사
4th row신창부동산
5th row금터공인중개사
ValueCountFrequency (%)
사무소 85
 
1.1%
공인중개사사무소 85
 
1.1%
현대공인중개사사무소 42
 
0.6%
미래공인중개사사무소 36
 
0.5%
삼성공인중개사사무소 35
 
0.5%
행운공인중개사사무소 33
 
0.4%
태양공인중개사사무소 30
 
0.4%
탑공인중개사사무소 27
 
0.4%
행복공인중개사사무소 26
 
0.3%
신세계공인중개사사무소 25
 
0.3%
Other values (4742) 7152
94.4%
2024-04-17T11:16:51.887005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 13190
16.0%
중 7343
 
8.9%
개 7328
 
8.9%
소 6909
 
8.4%
무 6870
 
8.3%
인 6414
 
7.8%
공 6230
 
7.5%
동 2757
 
3.3%
부 2504
 
3.0%
산 2455
 
3.0%
Other values (614) 20559
24.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 80707
97.8%
Uppercase Letter 778
 
0.9%
Space Separator 334
 
0.4%
Decimal Number 325
 
0.4%
Lowercase Letter 165
 
0.2%
Close Punctuation 109
 
0.1%
Open Punctuation 109
 
0.1%
Other Punctuation 21
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Letter Number 2
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 13190
16.3%
중 7343
 
9.1%
개 7328
 
9.1%
소 6909
 
8.6%
무 6870
 
8.5%
인 6414
 
7.9%
공 6230
 
7.7%
동 2757
 
3.4%
부 2504
 
3.1%
산 2455
 
3.0%
Other values (548) 18707
23.2%
Uppercase Letter
ValueCountFrequency (%)
K 147
18.9%
S 98
12.6%
L 65
 
8.4%
T 65
 
8.4%
C 50
 
6.4%
O 48
 
6.2%
W 38
 
4.9%
E 33
 
4.2%
B 27
 
3.5%
G 27
 
3.5%
Other values (15) 180
23.1%
Lowercase Letter
ValueCountFrequency (%)
e 71
43.0%
h 26
 
15.8%
t 14
 
8.5%
c 11
 
6.7%
k 8
 
4.8%
w 8
 
4.8%
s 7
 
4.2%
o 4
 
2.4%
i 4
 
2.4%
n 2
 
1.2%
Other values (8) 10
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 143
44.0%
8 43
 
13.2%
4 39
 
12.0%
2 27
 
8.3%
3 24
 
7.4%
9 21
 
6.5%
5 12
 
3.7%
6 6
 
1.8%
0 5
 
1.5%
7 5
 
1.5%
Other Punctuation
ValueCountFrequency (%)
& 8
38.1%
. 7
33.3%
？ 2
 
9.5%
· 2
 
9.5%
# 1
 
4.8%
! 1
 
4.8%
Space Separator
ValueCountFrequency (%)
334
100.0%
Close Punctuation
ValueCountFrequency (%)
) 109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%
Other Symbol
ValueCountFrequency (%)
ⓡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 80694
97.7%
Latin 945
 
1.1%
Common 907
 
1.1%
Han 13
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 13190
16.3%
중 7343
 
9.1%
개 7328
 
9.1%
소 6909
 
8.6%
무 6870
 
8.5%
인 6414
 
7.9%
공 6230
 
7.7%
동 2757
 
3.4%
부 2504
 
3.1%
산 2455
 
3.0%
Other values (536) 18694
23.2%
Latin
ValueCountFrequency (%)
K 147
15.6%
S 98
 
10.4%
e 71
 
7.5%
L 65
 
6.9%
T 65
 
6.9%
C 50
 
5.3%
O 48
 
5.1%
W 38
 
4.0%
E 33
 
3.5%
B 27
 
2.9%
Other values (34) 303
32.1%
Common
ValueCountFrequency (%)
334
36.8%
1 143
15.8%
) 109
 
12.0%
( 109
 
12.0%
8 43
 
4.7%
4 39
 
4.3%
2 27
 
3.0%
3 24
 
2.6%
9 21
 
2.3%
5 12
 
1.3%
Other values (12) 46
 
5.1%
Han
ValueCountFrequency (%)
福 2
15.4%
人 1
7.7%
秀 1
7.7%
利 1
7.7%
太 1
7.7%
炫 1
7.7%
本 1
7.7%
氷 1
7.7%
甲 1
7.7%
該 1
7.7%
Other values (2) 2
15.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 80694
97.7%
ASCII 1845
 
2.2%
CJK 13
 
< 0.1%
None 4
 
< 0.1%
Number Forms 2
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 13190
16.3%
중 7343
 
9.1%
개 7328
 
9.1%
소 6909
 
8.6%
무 6870
 
8.5%
인 6414
 
7.9%
공 6230
 
7.7%
동 2757
 
3.4%
부 2504
 
3.1%
산 2455
 
3.0%
Other values (536) 18694
23.2%
ASCII
ValueCountFrequency (%)
334
18.1%
K 147
 
8.0%
1 143
 
7.8%
) 109
 
5.9%
( 109
 
5.9%
S 98
 
5.3%
e 71
 
3.8%
L 65
 
3.5%
T 65
 
3.5%
C 50
 
2.7%
Other values (52) 654
35.4%
None
ValueCountFrequency (%)
？ 2
50.0%
· 2
50.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
100.0%
CJK
ValueCountFrequency (%)
福 2
15.4%
人 1
7.7%
秀 1
7.7%
利 1
7.7%
太 1
7.7%
炫 1
7.7%
本 1
7.7%
氷 1
7.7%
甲 1
7.7%
該 1
7.7%
Other values (2) 2
15.4%
Enclosed Alphanum
ValueCountFrequency (%)
ⓡ 1
100.0%

estbsbeginde
Date

MISSING 

Distinct533
Distinct (%)7.3%
Missing91
Missing (%)1.2%
Memory size57.7 KiB
Minimum2010-05-03 00:00:00
Maximum2021-01-28 00:00:00
2024-04-17T11:16:52.004586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:52.121320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

estbsendde
Date

MISSING 

Distinct533
Distinct (%)7.3%
Missing91
Missing (%)1.2%
Memory size57.7 KiB
Minimum2011-05-02 00:00:00
Maximum2024-11-15 00:00:00
2024-04-17T11:16:52.240816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:52.385334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

jurirno
Text

Distinct7308
Distinct (%)99.9%
Missing56
Missing (%)0.8%
Memory size57.7 KiB
2024-04-17T11:16:52.590318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length13.420506
Min length6

Characters and Unicode

Total characters98171
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

Unique7301 ?
Unique (%)99.8%

Sample

1st row가-01-601
2nd row가-01-544
3rd row가-01-595
4th row가-01-573
5th row가-01-606
ValueCountFrequency (%)
가-14-1196 2
 
< 0.1%
26410-2016-00056 2
 
< 0.1%
26470-2015-00086 2
 
< 0.1%
26230-2017-00146 2
 
< 0.1%
26440-2019-00095 2
 
< 0.1%
26410-2020-00089 2
 
< 0.1%
가-11-2094 2
 
< 0.1%
가 2
 
< 0.1%
2
 
< 0.1%
가-11-956 1
 
< 0.1%
Other values (7301) 7301
99.7%
2024-04-17T11:16:52.906015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27509
28.0%
2 15437
15.7%
- 14560
14.8%
1 9899
 
10.1%
6 7622
 
7.8%
3 4175
 
4.3%
4 3859
 
3.9%
5 3678
 
3.7%
7 3172
 
3.2%
9 3011
 
3.1%
Other values (4) 5249
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81054
82.6%
Dash Punctuation 14560
 
14.8%
Other Letter 2552
 
2.6%
Space Separator 5
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27509
33.9%
2 15437
19.0%
1 9899
 
12.2%
6 7622
 
9.4%
3 4175
 
5.2%
4 3859
 
4.8%
5 3678
 
4.5%
7 3172
 
3.9%
9 3011
 
3.7%
8 2692
 
3.3%
Other Letter
ValueCountFrequency (%)
가 2522
98.8%
나 30
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 14560
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 95619
97.4%
Hangul 2552
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27509
28.8%
2 15437
16.1%
- 14560
15.2%
1 9899
 
10.4%
6 7622
 
8.0%
3 4175
 
4.4%
4 3859
 
4.0%
5 3678
 
3.8%
7 3172
 
3.3%
9 3011
 
3.1%
Other values (2) 2697
 
2.8%
Hangul
ValueCountFrequency (%)
가 2522
98.8%
나 30
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95619
97.4%
Hangul 2552
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27509
28.8%
2 15437
16.1%
- 14560
15.2%
1 9899
 
10.4%
6 7622
 
8.0%
3 4175
 
4.4%
4 3859
 
4.0%
5 3678
 
3.8%
7 3172
 
3.3%
9 3011
 
3.1%
Other values (2) 2697
 
2.8%
Hangul
ValueCountFrequency (%)
가 2522
98.8%
나 30
 
1.2%

lastupdtdt
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2020-12-22
7371 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-22
2nd row2020-12-22
3rd row2020-12-22
4th row2020-12-22
5th row2020-12-22

Common Values

ValueCountFrequency (%)
2020-12-22 7371
100.0%

Length

2024-04-17T11:16:53.015027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:53.091631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-22 7371
100.0%

ldcode
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26369.536
Minimum26110
Maximum26710
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size64.9 KiB
2024-04-17T11:16:53.160332image/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 deviation133.69004
Coefficient of variation (CV)0.0050698671
Kurtosis0.37523981
Mean26369.536
Median Absolute Deviation (MAD)90
Skewness0.60457771
Sum1.9436985 × 108
Variance17873.028
MonotonicityNot monotonic
2024-04-17T11:16:53.246428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
26350 923
12.5%
26230 836
11.3%
26260 664
9.0%
26470 602
8.2%
26440 581
7.9%
26500 534
7.2%
26410 526
7.1%
26290 522
7.1%
26380 468
 
6.3%
26710 425
 
5.8%
Other values (6) 1290
17.5%
ValueCountFrequency (%)
26110 126
 
1.7%
26140 156
 
2.1%
26170 158
 
2.1%
26200 128
 
1.7%
26230 836
11.3%
26260 664
9.0%
26290 522
7.1%
26320 415
5.6%
26350 923
12.5%
26380 468
6.3%
ValueCountFrequency (%)
26710 425
5.8%
26530 307
 
4.2%
26500 534
7.2%
26470 602
8.2%
26440 581
7.9%
26410 526
7.1%
26380 468
6.3%
26350 923
12.5%
26320 415
5.6%
26290 522
7.1%

ldcodenm
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
부산광역시 해운대구
923 
부산광역시 부산진구
836 
부산광역시 동래구
664 
부산광역시 연제구
602 
부산광역시 강서구
581 
Other values (11)
3765 

Length

Max length10
Median length9
Mean length9.0518247
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 923
12.5%
부산광역시 부산진구 836
11.3%
부산광역시 동래구 664
9.0%
부산광역시 연제구 602
8.2%
부산광역시 강서구 581
7.9%
부산광역시 수영구 534
7.2%
부산광역시 금정구 526
7.1%
부산광역시 남구 522
7.1%
부산광역시 사하구 468
 
6.3%
부산광역시 기장군 425
 
5.8%
Other values (6) 1290
17.5%

Length

2024-04-17T11:16:53.363678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부산광역시 7371
50.0%
해운대구 923
 
6.3%
부산진구 836
 
5.7%
동래구 664
 
4.5%
연제구 602
 
4.1%
강서구 581
 
3.9%
수영구 534
 
3.6%
금정구 526
 
3.6%
남구 522
 
3.5%
사하구 468
 
3.2%
Other values (7) 1715
 
11.6%

registde
Date

Distinct3179
Distinct (%)43.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
Minimum1984-04-24 00:00:00
Maximum2020-12-18 00:00:00
2024-04-17T11:16:53.462690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T11:16:53.568712image/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 size57.7 KiB
1
7337 
2
 
26
8
 
4
3
 
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 7337
99.5%
2 26
 
0.4%
8 4
 
0.1%
3 4
 
0.1%

Length

2024-04-17T11:16:53.669884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:53.747231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 7337
99.5%
2 26
 
0.4%
8 4
 
0.1%
3 4
 
0.1%

sttussecodenm
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
영업중
7337 
휴업
 
26
업무정지
 
4
휴업연장
 
4

Length

Max length4
Median length3
Mean length2.997558
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 7337
99.5%
휴업 26
 
0.4%
업무정지 4
 
0.1%
휴업연장 4
 
0.1%

Length

2024-04-17T11:16:53.856152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:53.943890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 7337
99.5%
휴업 26
 
0.4%
업무정지 4
 
0.1%
휴업연장 4
 
0.1%

telnolist
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7371
Missing (%)100.0%
Memory size64.9 KiB

last_load_dttm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.7 KiB
2020-12-23 12:24:22
7371 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-12-23 12:24:22
2nd row2020-12-23 12:24:22
3rd row2020-12-23 12:24:22
4th row2020-12-23 12:24:22
5th row2020-12-23 12:24:22

Common Values

ValueCountFrequency (%)
2020-12-23 12:24:22 7371
100.0%

Length

2024-04-17T11:16:54.028379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T11:16:54.330245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-12-23 7371
50.0%
12:24:22 7371
50.0%

Interactions

2024-04-17T11:16:50.273387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T11:16:54.375362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodeldcodenmsttussecodesttussecodenm
ldcode1.0001.0000.0580.058
ldcodenm1.0001.0000.0790.079
sttussecode0.0580.0791.0001.000
sttussecodenm0.0580.0791.0001.000
2024-04-17T11:16:54.447790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
sttussecodeldcodenmsttussecodenm
sttussecode1.0000.0371.000
ldcodenm0.0371.0000.037
sttussecodenm1.0000.0371.000
2024-04-17T11:16:54.546946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ldcodeldcodenmsttussecodesttussecodenm
ldcode1.0000.9990.0260.026
ldcodenm0.9991.0000.0370.037
sttussecode0.0260.0371.0001.000
sttussecodenm0.0260.0371.0001.000

Missing values

2024-04-17T11:16:50.397455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T11:16:50.562038image/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.
2024-04-17T11:16:50.701116image/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
0강호근OK공인중개사사무소2020-06-092021-06-08가-01-6012020-12-2226110부산광역시 중구2009-06-261영업중<NA>2020-12-23 12:24:22
1백수현굿모닝 공인중개사2020-03-092021-03-08가-01-5442020-12-2226110부산광역시 중구2004-03-221영업중<NA>2020-12-23 12:24:22
2김홍숙부원공인중개사2020-12-182021-12-17가-01-5952020-12-2226110부산광역시 중구2009-07-201영업중<NA>2020-12-23 12:24:22
3강영지신창부동산2020-09-042021-09-03가-01-5732020-12-2226110부산광역시 중구2006-09-061영업중<NA>2020-12-23 12:24:22
4정인수금터공인중개사2020-11-232021-11-22가-01-6062020-12-2226110부산광역시 중구2009-11-131영업중<NA>2020-12-23 12:24:22
5박은미천진공인중개사 사무소2020-02-172021-02-16가-01-6122020-12-2226110부산광역시 중구2010-02-171영업중<NA>2020-12-23 12:24:22
6주광형재덕공인중개사 사무소2020-03-082021-03-07가-01-6132020-12-2226110부산광역시 중구2010-03-041영업중<NA>2020-12-23 12:24:22
7최난영탑공인중개사사무소2020-09-092021-09-08가-01-6172020-12-2226110부산광역시 중구2010-09-091영업중<NA>2020-12-23 12:24:22
8정영희천봉공인중개사2020-01-042021-01-03가-01-6192020-12-2226110부산광역시 중구2011-01-048업무정지<NA>2020-12-23 12:24:22
9이지미중앙공인중개사무소2020-01-132021-01-12가-01-6202020-12-2226110부산광역시 중구2011-01-131영업중<NA>2020-12-23 12:24:22
brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmtelnolistlast_load_dttm
7361이서영일광퀸부동산공인중개사사무소2020-03-272021-03-26가16-9662020-12-2226710부산광역시 기장군2012-03-271영업중<NA>2020-12-23 12:24:22
7362하화정강남공인중개사사무소2020-05-012021-04-30가16-9722020-12-2226710부산광역시 기장군2012-04-241영업중<NA>2020-12-23 12:24:22
7363서창열부자공인중개사사무소2020-06-082021-06-07가16-9842020-12-2226710부산광역시 기장군2012-06-071영업중<NA>2020-12-23 12:24:22
7364선은미롯데캐슬부동산공인중개사사무소2020-08-162021-08-15가16-9922020-12-2226710부산광역시 기장군2012-08-161영업중<NA>2020-12-23 12:24:22
7365한성희크로바공인중개사사무소2020-12-202021-12-19가16-10142020-12-2226710부산광역시 기장군2012-12-201영업중<NA>2020-12-23 12:24:22
7366김성훈여명컨설팅공인중개사사무소2020-12-232021-12-22가16-10172020-12-2226710부산광역시 기장군2012-12-211영업중<NA>2020-12-23 12:24:22
7367윤학순기장우리들공인중개사사무소2020-01-062021-01-05가-16-10272020-12-2226710부산광역시 기장군2013-01-041영업중<NA>2020-12-23 12:24:22
7368최해정제일부동산공인중개사사무소2020-01-152021-01-14가16-10302020-12-2226710부산광역시 기장군2013-01-151영업중<NA>2020-12-23 12:24:22
7369황숙이서희스타힐스부동산공인중개사사무소2020-02-042021-02-03가16-10372020-12-2226710부산광역시 기장군2013-02-041영업중<NA>2020-12-23 12:24:22
7370최권세알파부동산공인중개사사무소2020-04-082021-04-07가16-10492020-12-2226710부산광역시 기장군2013-03-081영업중<NA>2020-12-23 12:24:22

Duplicate rows

Most frequently occurring

brkrnmbsnmcmpnmestbsbegindeestbsenddejurirnolastupdtdtldcodeldcodenmregistdesttussecodesttussecodenmlast_load_dttm# duplicates
4<NA><NA><NA><NA><NA>2020-12-2226380부산광역시 사하구2012-10-291영업중2020-12-23 12:24:226
0박성진법무공인중개사사무소2020-02-162021-02-15가-14-11962020-12-2226500부산광역시 수영구2012-01-271영업중2020-12-23 12:24:222
1<NA>삼성명가부동산중개2014-06-122015-06-11가-11-20942020-12-2226410부산광역시 금정구2013-06-121영업중2020-12-23 12:24:222
2<NA><NA><NA><NA><NA>2020-12-2226140부산광역시 서구2015-06-101영업중2020-12-23 12:24:222
3<NA><NA><NA><NA><NA>2020-12-2226170부산광역시 동구2013-08-281영업중2020-12-23 12:24:222