Overview

Dataset statistics

Number of variables29
Number of observations10000
Missing cells115240
Missing cells (%)39.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 MiB
Average record size in memory250.0 B

Variable types

Numeric6
Text8
DateTime6
Categorical6
Unsupported3

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),자산규모,부채총액,자본금,판매방식명
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16098/S/1/datasetView.do

Alerts

인허가취소일자 is highly imbalanced (93.9%)Imbalance
폐업일자 has 5979 (59.8%) missing valuesMissing
휴업시작일자 has 9961 (99.6%) missing valuesMissing
휴업종료일자 has 9961 (99.6%) missing valuesMissing
재개업일자 has 9879 (98.8%) missing valuesMissing
전화번호 has 1620 (16.2%) missing valuesMissing
소재지면적 has 10000 (100.0%) missing valuesMissing
소재지우편번호 has 6744 (67.4%) missing valuesMissing
지번주소 has 1019 (10.2%) missing valuesMissing
도로명주소 has 4057 (40.6%) missing valuesMissing
도로명우편번호 has 6413 (64.1%) missing valuesMissing
업태구분명 has 10000 (100.0%) missing valuesMissing
좌표정보(X) has 3808 (38.1%) missing valuesMissing
좌표정보(Y) has 3808 (38.1%) missing valuesMissing
자산규모 has 7330 (73.3%) missing valuesMissing
부채총액 has 7343 (73.4%) missing valuesMissing
자본금 has 7318 (73.2%) missing valuesMissing
판매방식명 has 10000 (100.0%) missing valuesMissing
부채총액 is highly skewed (γ1 = 21.41362853)Skewed
자본금 is highly skewed (γ1 = 40.81562564)Skewed
관리번호 has unique valuesUnique
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
판매방식명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자산규모 has 804 (8.0%) zerosZeros
부채총액 has 1646 (16.5%) zerosZeros
자본금 has 572 (5.7%) zerosZeros

Reproduction

Analysis started2024-05-11 00:38:14.707243
Analysis finished2024-05-11 00:38:21.154476
Duration6.45 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3153806
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T00:38:21.300075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13100000
median3180000
Q33220000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)120000

Descriptive statistics

Standard deviation72626.179
Coefficient of variation (CV)0.023028106
Kurtosis-0.77632737
Mean3153806
Median Absolute Deviation (MAD)40000
Skewness-0.74150031
Sum3.153806 × 1010
Variance5.2745618 × 109
MonotonicityNot monotonic
2024-05-11T00:38:21.743329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3220000 1763
17.6%
3210000 1085
 
10.8%
3230000 610
 
6.1%
3180000 552
 
5.5%
3160000 482
 
4.8%
3150000 450
 
4.5%
3130000 440
 
4.4%
3200000 435
 
4.3%
3170000 377
 
3.8%
3240000 363
 
3.6%
Other values (15) 3443
34.4%
ValueCountFrequency (%)
3000000 227
2.3%
3010000 357
3.6%
3020000 205
2.1%
3030000 308
3.1%
3040000 305
3.0%
3050000 204
2.0%
3060000 262
2.6%
3070000 159
1.6%
3080000 159
1.6%
3090000 125
 
1.2%
ValueCountFrequency (%)
3240000 363
 
3.6%
3230000 610
 
6.1%
3220000 1763
17.6%
3210000 1085
10.8%
3200000 435
 
4.3%
3190000 240
 
2.4%
3180000 552
 
5.5%
3170000 377
 
3.8%
3160000 482
 
4.8%
3150000 450
 
4.5%

관리번호
Text

UNIQUE 

Distinct10000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T00:38:22.241652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters190000
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

Unique10000 ?
Unique (%)100.0%

Sample

1st row2000323013123200045
2nd row1996301010023200006
3rd row2009309010523200003
4th row2001301010023200051
5th row2006318011723201330
ValueCountFrequency (%)
2000323013123200045 1
 
< 0.1%
2011322016223200158 1
 
< 0.1%
2017313020123200013 1
 
< 0.1%
2011303010323200021 1
 
< 0.1%
2016322016223200135 1
 
< 0.1%
2011322016223200153 1
 
< 0.1%
2000322008323200025 1
 
< 0.1%
2006300010123200876 1
 
< 0.1%
2011322016223200043 1
 
< 0.1%
2006317010523200389 1
 
< 0.1%
Other values (9990) 9990
99.9%
2024-05-11T00:38:23.213127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 62670
33.0%
2 42814
22.5%
3 27993
14.7%
1 24542
 
12.9%
9 6456
 
3.4%
6 5652
 
3.0%
8 5040
 
2.7%
5 4969
 
2.6%
7 4940
 
2.6%
4 4919
 
2.6%
Other values (2) 5
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 189995
> 99.9%
Dash Punctuation 3
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 62670
33.0%
2 42814
22.5%
3 27993
14.7%
1 24542
 
12.9%
9 6456
 
3.4%
6 5652
 
3.0%
8 5040
 
2.7%
5 4969
 
2.6%
7 4940
 
2.6%
4 4919
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 190000
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 62670
33.0%
2 42814
22.5%
3 27993
14.7%
1 24542
 
12.9%
9 6456
 
3.4%
6 5652
 
3.0%
8 5040
 
2.7%
5 4969
 
2.6%
7 4940
 
2.6%
4 4919
 
2.6%
Other values (2) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 190000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 62670
33.0%
2 42814
22.5%
3 27993
14.7%
1 24542
 
12.9%
9 6456
 
3.4%
6 5652
 
3.0%
8 5040
 
2.7%
5 4969
 
2.6%
7 4940
 
2.6%
4 4919
 
2.6%
Other values (2) 5
 
< 0.1%
Distinct4878
Distinct (%)48.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum1900-01-01 00:00:00
Maximum2024-04-29 00:00:00
2024-05-11T00:38:23.789482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:24.304865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct48
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9687 
20071022
 
56
20100416
 
26
20190418
 
24
20080826
 
24
Other values (43)
 
183

Length

Max length8
Median length4
Mean length4.1252
Min length4

Unique

Unique19 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9687
96.9%
20071022 56
 
0.6%
20100416 26
 
0.3%
20190418 24
 
0.2%
20080826 24
 
0.2%
20080923 20
 
0.2%
20080811 13
 
0.1%
20030923 13
 
0.1%
20081009 12
 
0.1%
20100414 12
 
0.1%
Other values (38) 113
 
1.1%

Length

2024-05-11T00:38:24.833246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 9687
96.9%
20071022 56
 
0.6%
20100416 26
 
0.3%
20190418 24
 
0.2%
20080826 24
 
0.2%
20080923 20
 
0.2%
20080811 13
 
0.1%
20030923 13
 
0.1%
20081009 12
 
0.1%
20100414 12
 
0.1%
Other values (38) 113
 
1.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
4516 
4
4031 
1
1352 
5
 
74
2
 
27

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row3
3rd row3
4th row3
5th row4

Common Values

ValueCountFrequency (%)
3 4516
45.2%
4 4031
40.3%
1 1352
 
13.5%
5 74
 
0.7%
2 27
 
0.3%

Length

2024-05-11T00:38:25.382743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:25.796605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 4516
45.2%
4 4031
40.3%
1 1352
 
13.5%
5 74
 
0.7%
2 27
 
0.3%

영업상태명
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업
4516 
취소/말소/만료/정지/중지
4031 
영업/정상
1352 
제외/삭제/전출
 
74
휴업
 
27

Length

Max length14
Median length8
Mean length7.2872
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row취소/말소/만료/정지/중지
2nd row폐업
3rd row폐업
4th row폐업
5th row취소/말소/만료/정지/중지

Common Values

ValueCountFrequency (%)
폐업 4516
45.2%
취소/말소/만료/정지/중지 4031
40.3%
영업/정상 1352
 
13.5%
제외/삭제/전출 74
 
0.7%
휴업 27
 
0.3%

Length

2024-05-11T00:38:26.223524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:26.429508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 4516
45.2%
취소/말소/만료/정지/중지 4031
40.3%
영업/정상 1352
 
13.5%
제외/삭제/전출 74
 
0.7%
휴업 27
 
0.3%
Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
03
4516 
07
3652 
01
1343 
04
 
379
05
 
74
Other values (4)
 
36

Length

Max length4
Median length2
Mean length2.0012
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row07
2nd row03
3rd row03
4th row03
5th row07

Common Values

ValueCountFrequency (%)
03 4516
45.2%
07 3652
36.5%
01 1343
 
13.4%
04 379
 
3.8%
05 74
 
0.7%
02 27
 
0.3%
BBBB 6
 
0.1%
06 2
 
< 0.1%
- 1
 
< 0.1%

Length

2024-05-11T00:38:26.668443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:26.905391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
03 4516
45.2%
07 3652
36.5%
01 1343
 
13.4%
04 379
 
3.8%
05 74
 
0.7%
02 27
 
0.3%
bbbb 6
 
0.1%
06 2
 
< 0.1%
1
 
< 0.1%
Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
폐업처리
4516 
직권말소
3652 
정상영업
1343 
직권취소
 
379
타시군구이관
 
74
Other values (3)
 
36

Length

Max length6
Median length4
Mean length4.0152
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row직권말소
2nd row폐업처리
3rd row폐업처리
4th row폐업처리
5th row직권말소

Common Values

ValueCountFrequency (%)
폐업처리 4516
45.2%
직권말소 3652
36.5%
정상영업 1343
 
13.4%
직권취소 379
 
3.8%
타시군구이관 74
 
0.7%
휴업처리 27
 
0.3%
<NA> 7
 
0.1%
타시군구전입 2
 
< 0.1%

Length

2024-05-11T00:38:27.281651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:27.655283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 4516
45.2%
직권말소 3652
36.5%
정상영업 1343
 
13.4%
직권취소 379
 
3.8%
타시군구이관 74
 
0.7%
휴업처리 27
 
0.3%
na 7
 
0.1%
타시군구전입 2
 
< 0.1%

폐업일자
Text

MISSING 

Distinct2532
Distinct (%)63.0%
Missing5979
Missing (%)59.8%
Memory size156.2 KiB
2024-05-11T00:38:28.269052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0696344
Min length8

Characters and Unicode

Total characters32448
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

Unique1643 ?
Unique (%)40.9%

Sample

1st row20040830
2nd row20090612
3rd row20020318
4th row20020902
5th row20061221
ValueCountFrequency (%)
20080624 22
 
0.5%
20080814 13
 
0.3%
20130827 11
 
0.3%
20200609 10
 
0.2%
20200707 10
 
0.2%
20130821 9
 
0.2%
20200708 8
 
0.2%
20200320 8
 
0.2%
20100913 8
 
0.2%
20200611 8
 
0.2%
Other values (2522) 3914
97.3%
2024-05-11T00:38:29.526050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10628
32.8%
2 7563
23.3%
1 5698
17.6%
3 1572
 
4.8%
8 1289
 
4.0%
9 1218
 
3.8%
7 1065
 
3.3%
4 983
 
3.0%
6 956
 
2.9%
5 806
 
2.5%
Other values (2) 670
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31778
97.9%
Other Punctuation 390
 
1.2%
Dash Punctuation 280
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10628
33.4%
2 7563
23.8%
1 5698
17.9%
3 1572
 
4.9%
8 1289
 
4.1%
9 1218
 
3.8%
7 1065
 
3.4%
4 983
 
3.1%
6 956
 
3.0%
5 806
 
2.5%
Other Punctuation
ValueCountFrequency (%)
/ 390
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 280
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32448
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10628
32.8%
2 7563
23.3%
1 5698
17.6%
3 1572
 
4.8%
8 1289
 
4.0%
9 1218
 
3.8%
7 1065
 
3.3%
4 983
 
3.0%
6 956
 
2.9%
5 806
 
2.5%
Other values (2) 670
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10628
32.8%
2 7563
23.3%
1 5698
17.6%
3 1572
 
4.8%
8 1289
 
4.0%
9 1218
 
3.8%
7 1065
 
3.3%
4 983
 
3.0%
6 956
 
2.9%
5 806
 
2.5%
Other values (2) 670
 
2.1%

휴업시작일자
Date

MISSING 

Distinct39
Distinct (%)100.0%
Missing9961
Missing (%)99.6%
Memory size156.2 KiB
Minimum2004-12-01 00:00:00
Maximum2023-12-05 00:00:00
2024-05-11T00:38:29.904010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:30.296923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

휴업종료일자
Date

MISSING 

Distinct34
Distinct (%)87.2%
Missing9961
Missing (%)99.6%
Memory size156.2 KiB
Minimum2004-12-31 00:00:00
Maximum2030-07-27 00:00:00
2024-05-11T00:38:30.675925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:31.108011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

재개업일자
Date

MISSING 

Distinct116
Distinct (%)95.9%
Missing9879
Missing (%)98.8%
Memory size156.2 KiB
Minimum1996-11-04 00:00:00
Maximum2023-12-15 00:00:00
2024-05-11T00:38:31.554326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:31.967245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct7598
Distinct (%)90.7%
Missing1620
Missing (%)16.2%
Memory size156.2 KiB
2024-05-11T00:38:32.791108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length10.526969
Min length1

Characters and Unicode

Total characters88216
Distinct characters19
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7397 ?
Unique (%)88.3%

Sample

1st row449-9938
2nd row02 774 0680
3rd row999-0983
4th row02 773 8595
5th row02 782 0638
ValueCountFrequency (%)
02 3757
 
24.7%
151
 
1.0%
501 35
 
0.2%
508 34
 
0.2%
539 34
 
0.2%
562 32
 
0.2%
558 31
 
0.2%
552 30
 
0.2%
538 29
 
0.2%
566 28
 
0.2%
Other values (7673) 11078
72.7%
2024-05-11T00:38:33.868320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12645
14.3%
2 12375
14.0%
10891
12.3%
5 6917
7.8%
- 6381
7.2%
3 6005
6.8%
8 5772
6.5%
4 5762
6.5%
1 5705
6.5%
6 5605
6.4%
Other values (9) 10158
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70570
80.0%
Space Separator 10891
 
12.3%
Dash Punctuation 6381
 
7.2%
Other Punctuation 223
 
0.3%
Close Punctuation 127
 
0.1%
Math Symbol 23
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12645
17.9%
2 12375
17.5%
5 6917
9.8%
3 6005
8.5%
8 5772
8.2%
4 5762
8.2%
1 5705
8.1%
6 5605
7.9%
7 5408
7.7%
9 4376
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 216
96.9%
/ 5
 
2.2%
, 2
 
0.9%
Math Symbol
ValueCountFrequency (%)
~ 22
95.7%
+ 1
 
4.3%
Space Separator
ValueCountFrequency (%)
10891
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6381
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 88216
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12645
14.3%
2 12375
14.0%
10891
12.3%
5 6917
7.8%
- 6381
7.2%
3 6005
6.8%
8 5772
6.5%
4 5762
6.5%
1 5705
6.5%
6 5605
6.4%
Other values (9) 10158
11.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12645
14.3%
2 12375
14.0%
10891
12.3%
5 6917
7.8%
- 6381
7.2%
3 6005
6.8%
8 5772
6.5%
4 5762
6.5%
1 5705
6.5%
6 5605
6.4%
Other values (9) 10158
11.5%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

소재지우편번호
Text

MISSING 

Distinct968
Distinct (%)29.7%
Missing6744
Missing (%)67.4%
Memory size156.2 KiB
2024-05-11T00:38:34.506176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0052211
Min length6

Characters and Unicode

Total characters19553
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique611 ?
Unique (%)18.8%

Sample

1st row138200
2nd row132040
3rd row135962
4th row134843
5th row140210
ValueCountFrequency (%)
135080 113
 
3.5%
137070 100
 
3.1%
151050 87
 
2.7%
153023 73
 
2.2%
158070 72
 
2.2%
152050 69
 
2.1%
138160 61
 
1.9%
137060 60
 
1.8%
138220 56
 
1.7%
158050 47
 
1.4%
Other values (958) 2518
77.3%
2024-05-11T00:38:35.394680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4959
25.4%
0 4517
23.1%
3 2340
12.0%
5 2063
10.6%
2 1537
 
7.9%
8 1500
 
7.7%
7 897
 
4.6%
4 813
 
4.2%
9 471
 
2.4%
6 439
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19536
99.9%
Dash Punctuation 17
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4959
25.4%
0 4517
23.1%
3 2340
12.0%
5 2063
10.6%
2 1537
 
7.9%
8 1500
 
7.7%
7 897
 
4.6%
4 813
 
4.2%
9 471
 
2.4%
6 439
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19553
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4959
25.4%
0 4517
23.1%
3 2340
12.0%
5 2063
10.6%
2 1537
 
7.9%
8 1500
 
7.7%
7 897
 
4.6%
4 813
 
4.2%
9 471
 
2.4%
6 439
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19553
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4959
25.4%
0 4517
23.1%
3 2340
12.0%
5 2063
10.6%
2 1537
 
7.9%
8 1500
 
7.7%
7 897
 
4.6%
4 813
 
4.2%
9 471
 
2.4%
6 439
 
2.2%

지번주소
Text

MISSING 

Distinct6880
Distinct (%)76.6%
Missing1019
Missing (%)10.2%
Memory size156.2 KiB
2024-05-11T00:38:36.069588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length102
Median length93
Mean length32.184723
Min length2

Characters and Unicode

Total characters289051
Distinct characters612
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6002 ?
Unique (%)66.8%

Sample

1st row서울특별시 송파구 문정동 **번지 대명빌딩*층
2nd row서울특별시 중구 서소문동 **-*
3rd row서울특별시 도봉구 창동 ***번지 *호 미화빌딩 지층
4th row서울특별시 중구 서소문동 **-**
5th row서울특별시 영등포구 여의도동**-* 맨하탄빌딩-****
ValueCountFrequency (%)
서울특별시 8530
17.6%
5484
 
11.3%
번지 4414
 
9.1%
4255
 
8.8%
2057
 
4.2%
강남구 1646
 
3.4%
서초구 967
 
2.0%
역삼동 719
 
1.5%
송파구 552
 
1.1%
서초동 463
 
1.0%
Other values (4087) 19408
40.0%
2024-05-11T00:38:37.257286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89020
30.8%
* 52817
18.3%
10948
 
3.8%
10314
 
3.6%
9632
 
3.3%
8869
 
3.1%
8734
 
3.0%
8549
 
3.0%
8532
 
3.0%
6041
 
2.1%
Other values (602) 75595
26.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 141192
48.8%
Space Separator 89020
30.8%
Other Punctuation 53062
 
18.4%
Dash Punctuation 4656
 
1.6%
Uppercase Letter 663
 
0.2%
Decimal Number 138
 
< 0.1%
Open Punctuation 104
 
< 0.1%
Close Punctuation 103
 
< 0.1%
Lowercase Letter 81
 
< 0.1%
Math Symbol 16
 
< 0.1%
Other values (2) 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
10948
 
7.8%
10314
 
7.3%
9632
 
6.8%
8869
 
6.3%
8734
 
6.2%
8549
 
6.1%
8532
 
6.0%
6041
 
4.3%
5107
 
3.6%
4489
 
3.2%
Other values (535) 59977
42.5%
Uppercase Letter
ValueCountFrequency (%)
B 169
25.5%
A 66
 
10.0%
T 50
 
7.5%
D 48
 
7.2%
K 47
 
7.1%
I 43
 
6.5%
S 34
 
5.1%
C 28
 
4.2%
E 22
 
3.3%
G 21
 
3.2%
Other values (15) 135
20.4%
Lowercase Letter
ValueCountFrequency (%)
e 18
22.2%
t 9
11.1%
b 9
11.1%
k 8
9.9%
r 6
 
7.4%
s 6
 
7.4%
c 5
 
6.2%
n 5
 
6.2%
a 4
 
4.9%
i 4
 
4.9%
Other values (5) 7
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 28
20.3%
4 21
15.2%
2 18
13.0%
0 13
9.4%
5 12
8.7%
3 12
8.7%
6 11
 
8.0%
7 10
 
7.2%
9 8
 
5.8%
8 5
 
3.6%
Other Punctuation
ValueCountFrequency (%)
* 52817
99.5%
, 150
 
0.3%
/ 47
 
0.1%
. 23
 
< 0.1%
@ 20
 
< 0.1%
& 3
 
< 0.1%
; 1
 
< 0.1%
? 1
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
~ 15
93.8%
1
 
6.2%
Letter Number
ValueCountFrequency (%)
11
78.6%
3
 
21.4%
Space Separator
ValueCountFrequency (%)
89020
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4656
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 103
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 147099
50.9%
Hangul 141194
48.8%
Latin 758
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
10948
 
7.8%
10314
 
7.3%
9632
 
6.8%
8869
 
6.3%
8734
 
6.2%
8549
 
6.1%
8532
 
6.0%
6041
 
4.3%
5107
 
3.6%
4489
 
3.2%
Other values (536) 59979
42.5%
Latin
ValueCountFrequency (%)
B 169
22.3%
A 66
 
8.7%
T 50
 
6.6%
D 48
 
6.3%
K 47
 
6.2%
I 43
 
5.7%
S 34
 
4.5%
C 28
 
3.7%
E 22
 
2.9%
G 21
 
2.8%
Other values (32) 230
30.3%
Common
ValueCountFrequency (%)
89020
60.5%
* 52817
35.9%
- 4656
 
3.2%
, 150
 
0.1%
( 104
 
0.1%
) 103
 
0.1%
/ 47
 
< 0.1%
1 28
 
< 0.1%
. 23
 
< 0.1%
4 21
 
< 0.1%
Other values (14) 130
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147842
51.1%
Hangul 141191
48.8%
Number Forms 14
 
< 0.1%
None 2
 
< 0.1%
Compat Jamo 1
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89020
60.2%
* 52817
35.7%
- 4656
 
3.1%
B 169
 
0.1%
, 150
 
0.1%
( 104
 
0.1%
) 103
 
0.1%
A 66
 
< 0.1%
T 50
 
< 0.1%
D 48
 
< 0.1%
Other values (53) 659
 
0.4%
Hangul
ValueCountFrequency (%)
10948
 
7.8%
10314
 
7.3%
9632
 
6.8%
8869
 
6.3%
8734
 
6.2%
8549
 
6.1%
8532
 
6.0%
6041
 
4.3%
5107
 
3.6%
4489
 
3.2%
Other values (534) 59976
42.5%
Number Forms
ValueCountFrequency (%)
11
78.6%
3
 
21.4%
None
ValueCountFrequency (%)
2
100.0%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
Math Operators
ValueCountFrequency (%)
1
100.0%

도로명주소
Text

MISSING 

Distinct5439
Distinct (%)91.5%
Missing4057
Missing (%)40.6%
Memory size156.2 KiB
2024-05-11T00:38:37.818413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length57
Mean length34.417634
Min length15

Characters and Unicode

Total characters204544
Distinct characters610
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5088 ?
Unique (%)85.6%

Sample

1st row서울특별시 송파구 새말로 *** (문정동,대명빌딩*층)
2nd row서울특별시 도봉구 도봉로 *** (창동,미화빌딩 지층)
3rd row서울특별시 서초구 서초대로 ***, *층 (방배동, 양지빌딩*)
4th row서울특별시 강남구 논현로**길 ** (개포동, 친환경식품유통센터*층)
5th row서울특별시 송파구 백제고분로**길 **, ***호 (송파동, 선경빌딩*층)
ValueCountFrequency (%)
6162
 
16.4%
서울특별시 5938
 
15.8%
2390
 
6.4%
1833
 
4.9%
강남구 794
 
2.1%
송파구 585
 
1.6%
서초구 445
 
1.2%
영등포구 384
 
1.0%
구로구 369
 
1.0%
관악구 368
 
1.0%
Other values (4780) 18317
48.7%
2024-05-11T00:38:38.901894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 34672
17.0%
31773
 
15.5%
7636
 
3.7%
7341
 
3.6%
, 6959
 
3.4%
6754
 
3.3%
6726
 
3.3%
6139
 
3.0%
5986
 
2.9%
) 5980
 
2.9%
Other values (600) 84578
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117273
57.3%
Other Punctuation 41667
 
20.4%
Space Separator 31773
 
15.5%
Close Punctuation 5980
 
2.9%
Open Punctuation 5979
 
2.9%
Dash Punctuation 923
 
0.5%
Uppercase Letter 649
 
0.3%
Decimal Number 171
 
0.1%
Lowercase Letter 88
 
< 0.1%
Math Symbol 25
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7636
 
6.5%
7341
 
6.3%
6754
 
5.8%
6726
 
5.7%
6139
 
5.2%
5986
 
5.1%
5950
 
5.1%
5939
 
5.1%
3010
 
2.6%
2965
 
2.5%
Other values (537) 58827
50.2%
Uppercase Letter
ValueCountFrequency (%)
B 144
22.2%
A 64
9.9%
T 64
9.9%
K 52
 
8.0%
I 41
 
6.3%
S 38
 
5.9%
C 36
 
5.5%
E 31
 
4.8%
D 22
 
3.4%
R 17
 
2.6%
Other values (15) 140
21.6%
Lowercase Letter
ValueCountFrequency (%)
e 20
22.7%
n 11
12.5%
t 10
11.4%
r 8
 
9.1%
b 7
 
8.0%
c 5
 
5.7%
k 5
 
5.7%
a 4
 
4.5%
s 4
 
4.5%
o 4
 
4.5%
Other values (5) 10
11.4%
Decimal Number
ValueCountFrequency (%)
1 34
19.9%
4 24
14.0%
2 19
11.1%
3 18
10.5%
0 17
9.9%
5 14
8.2%
9 12
 
7.0%
6 12
 
7.0%
8 11
 
6.4%
7 10
 
5.8%
Other Punctuation
ValueCountFrequency (%)
* 34672
83.2%
, 6959
 
16.7%
/ 15
 
< 0.1%
. 12
 
< 0.1%
& 5
 
< 0.1%
@ 4
 
< 0.1%
Letter Number
ValueCountFrequency (%)
12
75.0%
4
 
25.0%
Space Separator
ValueCountFrequency (%)
31773
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5980
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5979
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 923
100.0%
Math Symbol
ValueCountFrequency (%)
~ 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117273
57.3%
Common 86518
42.3%
Latin 753
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7636
 
6.5%
7341
 
6.3%
6754
 
5.8%
6726
 
5.7%
6139
 
5.2%
5986
 
5.1%
5950
 
5.1%
5939
 
5.1%
3010
 
2.6%
2965
 
2.5%
Other values (537) 58827
50.2%
Latin
ValueCountFrequency (%)
B 144
19.1%
A 64
 
8.5%
T 64
 
8.5%
K 52
 
6.9%
I 41
 
5.4%
S 38
 
5.0%
C 36
 
4.8%
E 31
 
4.1%
D 22
 
2.9%
e 20
 
2.7%
Other values (32) 241
32.0%
Common
ValueCountFrequency (%)
* 34672
40.1%
31773
36.7%
, 6959
 
8.0%
) 5980
 
6.9%
( 5979
 
6.9%
- 923
 
1.1%
1 34
 
< 0.1%
~ 25
 
< 0.1%
4 24
 
< 0.1%
2 19
 
< 0.1%
Other values (11) 130
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117273
57.3%
ASCII 87255
42.7%
Number Forms 16
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 34672
39.7%
31773
36.4%
, 6959
 
8.0%
) 5980
 
6.9%
( 5979
 
6.9%
- 923
 
1.1%
B 144
 
0.2%
A 64
 
0.1%
T 64
 
0.1%
K 52
 
0.1%
Other values (51) 645
 
0.7%
Hangul
ValueCountFrequency (%)
7636
 
6.5%
7341
 
6.3%
6754
 
5.8%
6726
 
5.7%
6139
 
5.2%
5986
 
5.1%
5950
 
5.1%
5939
 
5.1%
3010
 
2.6%
2965
 
2.5%
Other values (537) 58827
50.2%
Number Forms
ValueCountFrequency (%)
12
75.0%
4
 
25.0%

도로명우편번호
Text

MISSING 

Distinct2130
Distinct (%)59.4%
Missing6413
Missing (%)64.1%
Memory size156.2 KiB
2024-05-11T00:38:39.621615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.37385
Min length5

Characters and Unicode

Total characters19276
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1449 ?
Unique (%)40.4%

Sample

1st row137061
2nd row135962
3rd row05667
4th row06224
5th row06744
ValueCountFrequency (%)
151050 36
 
1.0%
135081 30
 
0.8%
153023 26
 
0.7%
08378 19
 
0.5%
06132 17
 
0.5%
151015 16
 
0.4%
08390 16
 
0.4%
06150 13
 
0.4%
08506 12
 
0.3%
08381 12
 
0.3%
Other values (2120) 3390
94.5%
2024-05-11T00:38:40.572528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4008
20.8%
1 3041
15.8%
8 1914
9.9%
5 1909
9.9%
3 1909
9.9%
7 1561
 
8.1%
2 1455
 
7.5%
6 1329
 
6.9%
4 1199
 
6.2%
9 934
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19259
99.9%
Dash Punctuation 17
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4008
20.8%
1 3041
15.8%
8 1914
9.9%
5 1909
9.9%
3 1909
9.9%
7 1561
 
8.1%
2 1455
 
7.6%
6 1329
 
6.9%
4 1199
 
6.2%
9 934
 
4.8%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19276
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4008
20.8%
1 3041
15.8%
8 1914
9.9%
5 1909
9.9%
3 1909
9.9%
7 1561
 
8.1%
2 1455
 
7.5%
6 1329
 
6.9%
4 1199
 
6.2%
9 934
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19276
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4008
20.8%
1 3041
15.8%
8 1914
9.9%
5 1909
9.9%
3 1909
9.9%
7 1561
 
8.1%
2 1455
 
7.5%
6 1329
 
6.9%
4 1199
 
6.2%
9 934
 
4.8%
Distinct9381
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T00:38:41.302475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length7.5672
Min length1

Characters and Unicode

Total characters75672
Distinct characters913
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

Unique8967 ?
Unique (%)89.7%

Sample

1st row주)잠자리
2nd row장데스떼화장품
3rd rowL.S코리아
4th row종근당동교100
5th row예원환경개발
ValueCountFrequency (%)
주식회사 1015
 
7.9%
245
 
1.9%
인셀덤 84
 
0.7%
마임 45
 
0.4%
대리점 28
 
0.2%
코리아 27
 
0.2%
유니베라 25
 
0.2%
윤선생영어교실 22
 
0.2%
에치와이 20
 
0.2%
알로에마임 19
 
0.1%
Other values (9896) 11323
88.1%
2024-05-11T00:38:42.444476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3947
 
5.2%
) 3056
 
4.0%
( 3007
 
4.0%
2864
 
3.8%
2492
 
3.3%
2060
 
2.7%
2008
 
2.7%
1469
 
1.9%
1299
 
1.7%
1166
 
1.5%
Other values (903) 52304
69.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63348
83.7%
Close Punctuation 3057
 
4.0%
Open Punctuation 3008
 
4.0%
Space Separator 2864
 
3.8%
Uppercase Letter 1603
 
2.1%
Lowercase Letter 1023
 
1.4%
Other Punctuation 291
 
0.4%
Decimal Number 277
 
0.4%
Other Symbol 138
 
0.2%
Dash Punctuation 61
 
0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3947
 
6.2%
2492
 
3.9%
2060
 
3.3%
2008
 
3.2%
1469
 
2.3%
1299
 
2.1%
1166
 
1.8%
1162
 
1.8%
1032
 
1.6%
900
 
1.4%
Other values (826) 45813
72.3%
Uppercase Letter
ValueCountFrequency (%)
S 173
 
10.8%
C 134
 
8.4%
L 105
 
6.6%
E 103
 
6.4%
K 89
 
5.6%
M 85
 
5.3%
N 84
 
5.2%
T 81
 
5.1%
I 79
 
4.9%
G 74
 
4.6%
Other values (15) 596
37.2%
Lowercase Letter
ValueCountFrequency (%)
o 131
12.8%
e 99
 
9.7%
n 92
 
9.0%
a 90
 
8.8%
t 80
 
7.8%
i 73
 
7.1%
r 59
 
5.8%
l 46
 
4.5%
s 44
 
4.3%
d 43
 
4.2%
Other values (15) 266
26.0%
Decimal Number
ValueCountFrequency (%)
1 60
21.7%
2 49
17.7%
0 47
17.0%
3 35
12.6%
5 30
10.8%
8 16
 
5.8%
7 13
 
4.7%
4 11
 
4.0%
6 11
 
4.0%
9 5
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 194
66.7%
& 53
 
18.2%
, 30
 
10.3%
? 6
 
2.1%
/ 5
 
1.7%
1
 
0.3%
' 1
 
0.3%
; 1
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 3056
> 99.9%
] 1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3007
> 99.9%
[ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
2864
100.0%
Other Symbol
ValueCountFrequency (%)
138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Letter Number
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63459
83.9%
Common 9559
 
12.6%
Latin 2627
 
3.5%
Han 27
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3947
 
6.2%
2492
 
3.9%
2060
 
3.2%
2008
 
3.2%
1469
 
2.3%
1299
 
2.0%
1166
 
1.8%
1162
 
1.8%
1032
 
1.6%
900
 
1.4%
Other values (803) 45924
72.4%
Latin
ValueCountFrequency (%)
S 173
 
6.6%
C 134
 
5.1%
o 131
 
5.0%
L 105
 
4.0%
E 103
 
3.9%
e 99
 
3.8%
n 92
 
3.5%
a 90
 
3.4%
K 89
 
3.4%
M 85
 
3.2%
Other values (41) 1526
58.1%
Common
ValueCountFrequency (%)
) 3056
32.0%
( 3007
31.5%
2864
30.0%
. 194
 
2.0%
- 61
 
0.6%
1 60
 
0.6%
& 53
 
0.6%
2 49
 
0.5%
0 47
 
0.5%
3 35
 
0.4%
Other values (15) 133
 
1.4%
Han
ValueCountFrequency (%)
3
 
11.1%
2
 
7.4%
1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
貿 1
 
3.7%
1
 
3.7%
1
 
3.7%
1
 
3.7%
Other values (14) 14
51.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63321
83.7%
ASCII 12184
 
16.1%
None 139
 
0.2%
CJK 26
 
< 0.1%
Number Forms 1
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
3947
 
6.2%
2492
 
3.9%
2060
 
3.3%
2008
 
3.2%
1469
 
2.3%
1299
 
2.1%
1166
 
1.8%
1162
 
1.8%
1032
 
1.6%
900
 
1.4%
Other values (802) 45786
72.3%
ASCII
ValueCountFrequency (%)
) 3056
25.1%
( 3007
24.7%
2864
23.5%
. 194
 
1.6%
S 173
 
1.4%
C 134
 
1.1%
o 131
 
1.1%
L 105
 
0.9%
E 103
 
0.8%
e 99
 
0.8%
Other values (64) 2318
19.0%
None
ValueCountFrequency (%)
138
99.3%
1
 
0.7%
CJK
ValueCountFrequency (%)
3
 
11.5%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
貿 1
 
3.8%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (13) 13
50.0%
Number Forms
ValueCountFrequency (%)
1
100.0%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%
Distinct8462
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2007-06-28 19:44:09
Maximum2024-05-09 13:25:34
2024-05-11T00:38:42.884044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:43.352035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
I
7874 
U
2126 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 7874
78.7%
U 2126
 
21.3%

Length

2024-05-11T00:38:43.776441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T00:38:44.149874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 7874
78.7%
u 2126
 
21.3%
Distinct1066
Distinct (%)10.7%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:05:00
2024-05-11T00:38:44.491569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T00:38:45.050429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct4803
Distinct (%)77.6%
Missing3808
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean199320.95
Minimum167789.6
Maximum410956.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T00:38:45.509585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum167789.6
5-th percentile186820.54
Q1191787.61
median201277.45
Q3205249.98
95-th percentile211149.34
Maximum410956.06
Range243166.46
Interquartile range (IQR)13462.369

Descriptive statistics

Standard deviation8237.9893
Coefficient of variation (CV)0.041330273
Kurtosis68.957404
Mean199320.95
Median Absolute Deviation (MAD)6335.6458
Skewness2.6049641
Sum1.2341953 × 109
Variance67864468
MonotonicityNot monotonic
2024-05-11T00:38:46.145222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190923.551317757 34
 
0.3%
205787.106208763 28
 
0.3%
189538.020935968 20
 
0.2%
204069.137085371 16
 
0.2%
203081.161708641 13
 
0.1%
190776.468544178 12
 
0.1%
187734.804380866 10
 
0.1%
190680.536850936 10
 
0.1%
204536.822020513 10
 
0.1%
195588.796492288 10
 
0.1%
Other values (4793) 6029
60.3%
(Missing) 3808
38.1%
ValueCountFrequency (%)
167789.600877091 1
< 0.1%
175131.079643805 1
< 0.1%
180226.735 1
< 0.1%
182268.752831116 1
< 0.1%
182524.823835629 1
< 0.1%
182865.612372488 1
< 0.1%
182872.579435573 1
< 0.1%
182874.245118806 1
< 0.1%
182908.612304722 1
< 0.1%
182914.770762913 1
< 0.1%
ValueCountFrequency (%)
410956.055910194 1
< 0.1%
226417.645595042 1
< 0.1%
215659.154061 1
< 0.1%
215212.94326834 1
< 0.1%
215195.884311721 1
< 0.1%
215033.880778399 1
< 0.1%
214958.713997465 1
< 0.1%
214888.465504117 1
< 0.1%
214731.479362033 1
< 0.1%
214330.033963773 1
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct4805
Distinct (%)77.6%
Missing3808
Missing (%)38.1%
Infinite0
Infinite (%)0.0%
Mean447560.9
Minimum229315.44
Maximum464814.72
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T00:38:46.555372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum229315.44
5-th percentile441694.92
Q1443522.66
median446183.37
Q3450698.58
95-th percentile458789.02
Maximum464814.72
Range235499.27
Interquartile range (IQR)7175.9178

Descriptive statistics

Standard deviation5993.5824
Coefficient of variation (CV)0.013391658
Kurtosis283.41772
Mean447560.9
Median Absolute Deviation (MAD)3427.8003
Skewness-7.1387885
Sum2.7712971 × 109
Variance35923030
MonotonicityNot monotonic
2024-05-11T00:38:47.142244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
446575.396546634 34
 
0.3%
451191.34653897 28
 
0.3%
441982.427934953 20
 
0.2%
444786.116475712 16
 
0.2%
444381.101104143 13
 
0.1%
442370.143700207 12
 
0.1%
442098.372819317 10
 
0.1%
447125.503353306 10
 
0.1%
444660.784269339 10
 
0.1%
442392.645303533 10
 
0.1%
Other values (4795) 6029
60.3%
(Missing) 3808
38.1%
ValueCountFrequency (%)
229315.443803811 1
 
< 0.1%
420821.921380891 1
 
< 0.1%
424231.6000988 1
 
< 0.1%
437488.324221587 1
 
< 0.1%
437585.386881809 1
 
< 0.1%
437675.777761649 1
 
< 0.1%
437914.06299827 5
0.1%
437974.032482417 1
 
< 0.1%
438247.940519369 1
 
< 0.1%
438442.592445398 1
 
< 0.1%
ValueCountFrequency (%)
464814.717432497 1
< 0.1%
464508.952781941 1
< 0.1%
464448.684446374 1
< 0.1%
464356.527197506 1
< 0.1%
464321.382754776 1
< 0.1%
464315.286672957 1
< 0.1%
464295.628375287 1
< 0.1%
464199.048415229 1
< 0.1%
464106.730290644 1
< 0.1%
464092.187505065 1
< 0.1%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct917
Distinct (%)34.3%
Missing7330
Missing (%)73.3%
Infinite0
Infinite (%)0.0%
Mean1.4851605 × 1010
Minimum0
Maximum4.6039035 × 1012
Zeros804
Zeros (%)8.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T00:38:47.713026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median50000000
Q32 × 108
95-th percentile4.9297403 × 109
Maximum4.6039035 × 1012
Range4.6039035 × 1012
Interquartile range (IQR)2 × 108

Descriptive statistics

Standard deviation1.92091 × 1011
Coefficient of variation (CV)12.934023
Kurtosis365.5459
Mean1.4851605 × 1010
Median Absolute Deviation (MAD)50000000
Skewness18.204107
Sum3.9653785 × 1013
Variance3.6898953 × 1022
MonotonicityNot monotonic
2024-05-11T00:38:48.389525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 804
 
8.0%
50000000 248
 
2.5%
100000000 127
 
1.3%
10000000 121
 
1.2%
30000000 46
 
0.5%
300000000 45
 
0.4%
20000000 43
 
0.4%
200000000 41
 
0.4%
1 34
 
0.3%
9 31
 
0.3%
Other values (907) 1130
 
11.3%
(Missing) 7330
73.3%
ValueCountFrequency (%)
0 804
8.0%
1 34
 
0.3%
3 1
 
< 0.1%
6 1
 
< 0.1%
9 31
 
0.3%
282 1
 
< 0.1%
1000 2
 
< 0.1%
5000 1
 
< 0.1%
50000 1
 
< 0.1%
100000 1
 
< 0.1%
ValueCountFrequency (%)
4603903488718 1
< 0.1%
4136312863585 1
< 0.1%
4111211369976 1
< 0.1%
3825200434847 1
< 0.1%
2704529366060 1
< 0.1%
2131049471426 1
< 0.1%
1986833637298 1
< 0.1%
1815771000000 1
< 0.1%
1535979241671 1
< 0.1%
1421582000000 1
< 0.1%

부채총액
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct826
Distinct (%)31.1%
Missing7343
Missing (%)73.4%
Infinite0
Infinite (%)0.0%
Mean9.3510627 × 109
Minimum-40000000
Maximum3.9418009 × 1012
Zeros1646
Zeros (%)16.5%
Negative1
Negative (%)< 0.1%
Memory size166.0 KiB
2024-05-11T00:38:49.126512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-40000000
5-th percentile0
Q10
median0
Q362350094
95-th percentile3.7718627 × 109
Maximum3.9418009 × 1012
Range3.9418409 × 1012
Interquartile range (IQR)62350094

Descriptive statistics

Standard deviation1.3403522 × 1011
Coefficient of variation (CV)14.333689
Kurtosis523.78406
Mean9.3510627 × 109
Median Absolute Deviation (MAD)0
Skewness21.413629
Sum2.4845774 × 1013
Variance1.796544 × 1022
MonotonicityNot monotonic
2024-05-11T00:38:49.792071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1646
 
16.5%
1 34
 
0.3%
9 31
 
0.3%
20000000 18
 
0.2%
50000000 17
 
0.2%
30000000 16
 
0.2%
10000000 12
 
0.1%
100000000 10
 
0.1%
5000000 9
 
0.1%
200000000 8
 
0.1%
Other values (816) 856
 
8.6%
(Missing) 7343
73.4%
ValueCountFrequency (%)
-40000000 1
 
< 0.1%
0 1646
16.5%
1 34
 
0.3%
2 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
9 31
 
0.3%
1000 2
 
< 0.1%
4000 1
 
< 0.1%
5000 1
 
< 0.1%
ValueCountFrequency (%)
3941800875811 1
< 0.1%
3496058346300 1
< 0.1%
2353781354122 1
< 0.1%
1996733817795 1
< 0.1%
1688331000000 1
< 0.1%
1452220106803 1
< 0.1%
1341131000000 1
< 0.1%
1060250012236 1
< 0.1%
826988458311 1
< 0.1%
792291956975 1
< 0.1%

자본금
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct472
Distinct (%)17.6%
Missing7318
Missing (%)73.2%
Infinite0
Infinite (%)0.0%
Mean3.818569 × 109
Minimum-4.9435732 × 1010
Maximum3.6740713 × 1012
Zeros572
Zeros (%)5.7%
Negative32
Negative (%)0.3%
Memory size166.0 KiB
2024-05-11T00:38:50.514192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-4.9435732 × 1010
5-th percentile0
Q11250
median50000000
Q31 × 108
95-th percentile1.226921 × 109
Maximum3.6740713 × 1012
Range3.723507 × 1012
Interquartile range (IQR)99998750

Descriptive statistics

Standard deviation7.773976 × 1010
Coefficient of variation (CV)20.358349
Kurtosis1870.3461
Mean3.818569 × 109
Median Absolute Deviation (MAD)50000000
Skewness40.815626
Sum1.0241402 × 1013
Variance6.0434704 × 1021
MonotonicityNot monotonic
2024-05-11T00:38:51.207037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 572
 
5.7%
50000000 503
 
5.0%
100000000 238
 
2.4%
10000000 195
 
1.9%
300000000 85
 
0.9%
20000000 76
 
0.8%
200000000 72
 
0.7%
30000000 66
 
0.7%
5000000 52
 
0.5%
150000000 46
 
0.5%
Other values (462) 777
 
7.8%
(Missing) 7318
73.2%
ValueCountFrequency (%)
-49435732223 1
< 0.1%
-13849612934 1
< 0.1%
-7290247478 1
< 0.1%
-7075069195 1
< 0.1%
-5543521800 1
< 0.1%
-3296920906 1
< 0.1%
-1807203631 1
< 0.1%
-1444996935 1
< 0.1%
-1208795643 1
< 0.1%
-1046895018 1
< 0.1%
ValueCountFrequency (%)
3674071270014 1
< 0.1%
926583625062 1
< 0.1%
881276552656 1
< 0.1%
640254517285 1
< 0.1%
500000000000 1
< 0.1%
350748011938 1
< 0.1%
266900616671 1
< 0.1%
200000000000 1
< 0.1%
169410494165 1
< 0.1%
160100000000 1
< 0.1%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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78743090000200930901052320000320090205<NA>3폐업03폐업처리20090612<NA><NA><NA>999-0983<NA>132040서울특별시 도봉구 창동 ***번지 *호 미화빌딩 지층서울특별시 도봉구 도봉로 *** (창동,미화빌딩 지층)<NA>L.S코리아2009-06-12 17:10:01I2018-08-31 23:59:59.0<NA>203439.447502461539.552727<NA><NA><NA><NA>
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165123180000200631801172320133020061213<NA>4취소/말소/만료/정지/중지07직권말소<NA><NA><NA><NA>02 782 0638<NA><NA>서울특별시 영등포구 여의도동**-* 맨하탄빌딩-****<NA><NA>예원환경개발2012-02-29 13:41:39I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
122993150000200231501002321626920020330<NA>3폐업03폐업처리20020902<NA><NA><NA>02 659 3225<NA><NA>서울특별시 강서구등촌제*동***-* *층<NA><NA>주식회사 하이스닥2008-06-03 17:00:21I2018-08-31 23:59:59.0<NA><NA><NA>000<NA>
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개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
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188233200000201632002112320004720160928<NA>4취소/말소/만료/정지/중지07직권말소<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 ***번지 **호서울특별시 관악구 봉천로**길 *-*, B**호 (봉천동)08749원스톱백(one stop back)2019-12-30 20:52:13U2020-01-01 02:40:00.0<NA>194469.456208442566.906679<NA><NA><NA><NA>
178743200000200532001062320077720051027<NA>3폐업03폐업처리20080627<NA><NA><NA>02 855 2775<NA><NA>서울시 관악구 신원동****-** ***호<NA><NA>중부2008-06-27 17:24:56I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA><NA><NA>
76823080000200330800922320012820030513<NA>4취소/말소/만료/정지/중지07직권말소<NA><NA><NA><NA>02 985 5612<NA><NA>서울특별시 강북구 미아동 ***-****서울특별시 강북구 삼양로**길 ** (미아동)01185효진2020-11-27 10:50:50U2020-11-29 02:40:00.0<NA>201311.378787457716.127222<NA><NA><NA><NA>
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