Overview

Dataset statistics

Number of variables29
Number of observations410
Missing cells2777
Missing cells (%)23.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory99.8 KiB
Average record size in memory249.3 B

Variable types

Categorical9
Numeric9
DateTime4
Text4
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
Author송파구
URLhttps://data.seoul.go.kr/dataList/OA-18800/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 is highly imbalanced (97.5%)Imbalance
휴업시작일자 is highly imbalanced (96.9%)Imbalance
휴업종료일자 is highly imbalanced (96.9%)Imbalance
폐업일자 has 142 (34.6%) missing valuesMissing
재개업일자 has 274 (66.8%) missing valuesMissing
전화번호 has 40 (9.8%) missing valuesMissing
소재지면적 has 410 (100.0%) missing valuesMissing
지번주소 has 49 (12.0%) missing valuesMissing
도로명주소 has 51 (12.4%) missing valuesMissing
도로명우편번호 has 235 (57.3%) missing valuesMissing
업태구분명 has 410 (100.0%) missing valuesMissing
좌표정보(X) has 53 (12.9%) missing valuesMissing
좌표정보(Y) has 53 (12.9%) missing valuesMissing
자산규모 has 217 (52.9%) missing valuesMissing
부채총액 has 217 (52.9%) missing valuesMissing
자본금 has 216 (52.7%) missing valuesMissing
판매방식명 has 410 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
최종수정일자 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 23 (5.6%) zerosZeros
부채총액 has 123 (30.0%) zerosZeros
자본금 has 12 (2.9%) zerosZeros

Reproduction

Analysis started2024-05-11 02:26:27.525848
Analysis finished2024-05-11 02:26:29.075737
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
3230000
410 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3230000
2nd row3230000
3rd row3230000
4th row3230000
5th row3230000

Common Values

ValueCountFrequency (%)
3230000 410
100.0%

Length

2024-05-11T02:26:29.318892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:29.713544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3230000 410
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0112913 × 1018
Minimum2.002323 × 1018
Maximum2.024323 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:30.127349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.002323 × 1018
5-th percentile2.003773 × 1018
Q12.006323 × 1018
median2.009323 × 1018
Q32.015323 × 1018
95-th percentile2.022323 × 1018
Maximum2.024323 × 1018
Range2.2000016 × 1016
Interquartile range (IQR)9.00001 × 1015

Descriptive statistics

Standard deviation5.9555432 × 1015
Coefficient of variation (CV)0.0029610545
Kurtosis-0.89229844
Mean2.0112913 × 1018
Median Absolute Deviation (MAD)4 × 1015
Skewness0.5564872
Sum-5.474046 × 1018
Variance3.5468494 × 1031
MonotonicityStrictly increasing
2024-05-11T02:26:30.772108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2002323013124200731 1
 
0.2%
2014323019824200007 1
 
0.2%
2014323019824200018 1
 
0.2%
2014323019824200017 1
 
0.2%
2014323019824200016 1
 
0.2%
2014323019824200015 1
 
0.2%
2014323019824200014 1
 
0.2%
2014323019824200013 1
 
0.2%
2014323019824200012 1
 
0.2%
2014323019824200011 1
 
0.2%
Other values (400) 400
97.6%
ValueCountFrequency (%)
2002323013124200731 1
0.2%
2002323013124200822 1
0.2%
2002323013124200826 1
0.2%
2002323013124200828 1
0.2%
2002323013124200903 1
0.2%
2002323013124200916 1
0.2%
2002323013124200917 1
0.2%
2002323013124201014 1
0.2%
2002323013124201022 1
0.2%
2002323013124201102 1
0.2%
ValueCountFrequency (%)
2024323029124200006 1
0.2%
2024323029124200005 1
0.2%
2024323029124200004 1
0.2%
2024323029124200003 1
0.2%
2024323029124200002 1
0.2%
2024323029124200001 1
0.2%
2023323029124200011 1
0.2%
2023323029124200010 1
0.2%
2023323029124200009 1
0.2%
2023323029124200008 1
0.2%

인허가일자
Date

Distinct377
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2002-07-31 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T02:26:31.078438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:31.409841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
409 
20130514
 
1

Length

Max length8
Median length4
Mean length4.0097561
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 409
99.8%
20130514 1
 
0.2%

Length

2024-05-11T02:26:31.826013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:32.196355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 409
99.8%
20130514 1
 
0.2%

영업상태코드
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
3
165 
4
142 
1
100 
5
 
2
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
3 165
40.2%
4 142
34.6%
1 100
24.4%
5 2
 
0.5%
2 1
 
0.2%

Length

2024-05-11T02:26:32.552890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:32.900150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 165
40.2%
4 142
34.6%
1 100
24.4%
5 2
 
0.5%
2 1
 
0.2%

영업상태명
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
폐업
165 
취소/말소/만료/정지/중지
142 
영업/정상
100 
제외/삭제/전출
 
2
휴업
 
1

Length

Max length14
Median length8
Mean length6.9170732
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 165
40.2%
취소/말소/만료/정지/중지 142
34.6%
영업/정상 100
24.4%
제외/삭제/전출 2
 
0.5%
휴업 1
 
0.2%

Length

2024-05-11T02:26:33.338473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:33.679663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 165
40.2%
취소/말소/만료/정지/중지 142
34.6%
영업/정상 100
24.4%
제외/삭제/전출 2
 
0.5%
휴업 1
 
0.2%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.897561
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:34.005006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.389718
Coefficient of variation (CV)0.61313164
Kurtosis-1.4827059
Mean3.897561
Median Absolute Deviation (MAD)2
Skewness0.29782358
Sum1598
Variance5.710752
MonotonicityNot monotonic
2024-05-11T02:26:34.492130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 165
40.2%
7 141
34.4%
1 100
24.4%
5 2
 
0.5%
4 1
 
0.2%
2 1
 
0.2%
ValueCountFrequency (%)
1 100
24.4%
2 1
 
0.2%
3 165
40.2%
4 1
 
0.2%
5 2
 
0.5%
7 141
34.4%
ValueCountFrequency (%)
7 141
34.4%
5 2
 
0.5%
4 1
 
0.2%
3 165
40.2%
2 1
 
0.2%
1 100
24.4%

상세영업상태명
Categorical

Distinct6
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
폐업처리
165 
직권말소
141 
정상영업
100 
타시군구이관
 
2
직권취소
 
1

Length

Max length6
Median length4
Mean length4.0097561
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 165
40.2%
직권말소 141
34.4%
정상영업 100
24.4%
타시군구이관 2
 
0.5%
직권취소 1
 
0.2%
휴업처리 1
 
0.2%

Length

2024-05-11T02:26:34.954087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:35.377784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 165
40.2%
직권말소 141
34.4%
정상영업 100
24.4%
타시군구이관 2
 
0.5%
직권취소 1
 
0.2%
휴업처리 1
 
0.2%

폐업일자
Date

MISSING 

Distinct164
Distinct (%)61.2%
Missing142
Missing (%)34.6%
Memory size3.3 KiB
Minimum2002-10-21 00:00:00
Maximum2024-03-01 00:00:00
2024-05-11T02:26:35.825944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:36.373908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
408 
20080218
 
1
20190719
 
1

Length

Max length8
Median length4
Mean length4.0195122
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 408
99.5%
20080218 1
 
0.2%
20190719 1
 
0.2%

Length

2024-05-11T02:26:36.946470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:37.404679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 408
99.5%
20080218 1
 
0.2%
20190719 1
 
0.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
408 
20081231
 
1
20200130
 
1

Length

Max length8
Median length4
Mean length4.0195122
Min length4

Unique

Unique2 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 408
99.5%
20081231 1
 
0.2%
20200130 1
 
0.2%

Length

2024-05-11T02:26:38.134097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:38.676730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 408
99.5%
20081231 1
 
0.2%
20200130 1
 
0.2%

재개업일자
Real number (ℝ)

MISSING 

Distinct129
Distinct (%)94.9%
Missing274
Missing (%)66.8%
Infinite0
Infinite (%)0.0%
Mean20051757
Minimum20020822
Maximum20091215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:39.406692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020822
5-th percentile20020990
Q120050327
median20050926
Q320060548
95-th percentile20070646
Maximum20091215
Range70393
Interquartile range (IQR)10221.25

Descriptive statistics

Standard deviation14723.259
Coefficient of variation (CV)0.00073426283
Kurtosis0.26463223
Mean20051757
Median Absolute Deviation (MAD)9590.5
Skewness-0.413998
Sum2.7270389 × 109
Variance2.1677437 × 108
MonotonicityNot monotonic
2024-05-11T02:26:40.044785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20050404 2
 
0.5%
20050414 2
 
0.5%
20050419 2
 
0.5%
20061108 2
 
0.5%
20050427 2
 
0.5%
20050402 2
 
0.5%
20020903 2
 
0.5%
20051205 1
 
0.2%
20051207 1
 
0.2%
20051110 1
 
0.2%
Other values (119) 119
29.0%
(Missing) 274
66.8%
ValueCountFrequency (%)
20020822 1
0.2%
20020826 1
0.2%
20020828 1
0.2%
20020903 2
0.5%
20020916 1
0.2%
20020917 1
0.2%
20021014 1
0.2%
20021022 1
0.2%
20021102 1
0.2%
20021114 1
0.2%
ValueCountFrequency (%)
20091215 1
0.2%
20090917 1
0.2%
20071004 1
0.2%
20070828 1
0.2%
20070814 1
0.2%
20070730 1
0.2%
20070718 1
0.2%
20070622 1
0.2%
20070615 1
0.2%
20070613 1
0.2%

전화번호
Text

MISSING 

Distinct354
Distinct (%)95.7%
Missing40
Missing (%)9.8%
Memory size3.3 KiB
2024-05-11T02:26:41.047256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.3972973
Min length1

Characters and Unicode

Total characters3477
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique341 ?
Unique (%)92.2%

Sample

1st row3431-4543
2nd row2202-7174
3rd row412-0048
4th row2202-5146
5th row2105-5622
ValueCountFrequency (%)
11111111 4
 
1.1%
4
 
1.1%
070-8146-7500 2
 
0.5%
02-3452-7222 2
 
0.5%
406-3600 2
 
0.5%
02-430-7557 2
 
0.5%
1 2
 
0.5%
02-423-8005 2
 
0.5%
424-0955 2
 
0.5%
1577-8318 2
 
0.5%
Other values (343) 346
93.5%
2024-05-11T02:26:42.550708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 539
15.5%
- 482
13.9%
2 458
13.2%
1 401
11.5%
4 386
11.1%
3 238
6.8%
5 208
 
6.0%
6 207
 
6.0%
7 205
 
5.9%
9 181
 
5.2%
Other values (5) 172
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2986
85.9%
Dash Punctuation 482
 
13.9%
Other Punctuation 6
 
0.2%
Math Symbol 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 539
18.1%
2 458
15.3%
1 401
13.4%
4 386
12.9%
3 238
8.0%
5 208
 
7.0%
6 207
 
6.9%
7 205
 
6.9%
9 181
 
6.1%
8 163
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 482
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3477
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 539
15.5%
- 482
13.9%
2 458
13.2%
1 401
11.5%
4 386
11.1%
3 238
6.8%
5 208
 
6.0%
6 207
 
6.0%
7 205
 
5.9%
9 181
 
5.2%
Other values (5) 172
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 539
15.5%
- 482
13.9%
2 458
13.2%
1 401
11.5%
4 386
11.1%
3 238
6.8%
5 208
 
6.0%
6 207
 
6.0%
7 205
 
5.9%
9 181
 
5.2%
Other values (5) 172
 
4.9%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing410
Missing (%)100.0%
Memory size3.7 KiB

소재지우편번호
Categorical

Distinct32
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
<NA>
195 
138160
48 
138050
31 
138220
25 
138190
21 
Other values (27)
90 

Length

Max length7
Median length6
Mean length5.0512195
Min length4

Unique

Unique17 ?
Unique (%)4.1%

Sample

1st row138050
2nd row138050
3rd row<NA>
4th row138180
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 195
47.6%
138160 48
 
11.7%
138050 31
 
7.6%
138220 25
 
6.1%
138190 21
 
5.1%
138240 19
 
4.6%
138170 15
 
3.7%
138200 14
 
3.4%
138130 8
 
2.0%
138040 4
 
1.0%
Other values (22) 30
 
7.3%

Length

2024-05-11T02:26:43.135532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 195
47.6%
138160 48
 
11.7%
138050 31
 
7.6%
138220 25
 
6.1%
138190 21
 
5.1%
138240 19
 
4.6%
138170 15
 
3.7%
138200 14
 
3.4%
138130 8
 
2.0%
138040 4
 
1.0%
Other values (22) 30
 
7.3%

지번주소
Text

MISSING 

Distinct292
Distinct (%)80.9%
Missing49
Missing (%)12.0%
Memory size3.3 KiB
2024-05-11T02:26:43.712427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length77
Median length38
Mean length26.614958
Min length13

Characters and Unicode

Total characters9608
Distinct characters239
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique250 ?
Unique (%)69.3%

Sample

1st row서울특별시 송파구 방이동 **번지 대우유토피아*층
2nd row서울특별시 송파구 방이동 ***번지 *호
3rd row서울특별시 송파구 잠실동 ***-** *층
4th row서울특별시 송파구 삼전동 ***번지 **호 삼전빌딩*층***호
5th row서울특별시 송파구 잠실동 ***-** 두성빌딩 *,*층
ValueCountFrequency (%)
서울특별시 361
18.0%
송파구 360
17.9%
번지 272
13.5%
호 255
12.7%
109
 
5.4%
가락동 74
 
3.7%
잠실동 65
 
3.2%
층 61
 
3.0%
문정동 55
 
2.7%
방이동 45
 
2.2%
Other values (204) 353
17.6%
2024-05-11T02:26:44.967486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1790
18.6%
* 1670
17.4%
파 416
 
4.3%
송 399
 
4.2%
동 380
 
4.0%
시 371
 
3.9%
서 370
 
3.9%
울 362
 
3.8%
구 361
 
3.8%
별 361
 
3.8%
Other values (229) 3128
32.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6032
62.8%
Space Separator 1790
 
18.6%
Other Punctuation 1673
 
17.4%
Dash Punctuation 75
 
0.8%
Uppercase Letter 24
 
0.2%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Decimal Number 4
 
< 0.1%
Other Symbol 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 416
 
6.9%
송 399
 
6.6%
동 380
 
6.3%
시 371
 
6.2%
서 370
 
6.1%
울 362
 
6.0%
구 361
 
6.0%
별 361
 
6.0%
특 361
 
6.0%
지 291
 
4.8%
Other values (204) 2360
39.1%
Uppercase Letter
ValueCountFrequency (%)
T 5
20.8%
A 3
12.5%
E 2
 
8.3%
R 2
 
8.3%
S 2
 
8.3%
K 2
 
8.3%
Q 1
 
4.2%
G 1
 
4.2%
O 1
 
4.2%
L 1
 
4.2%
Other values (4) 4
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
7 1
25.0%
Other Punctuation
ValueCountFrequency (%)
* 1670
99.8%
, 3
 
0.2%
Space Separator
ValueCountFrequency (%)
1790
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6033
62.8%
Common 3551
37.0%
Latin 24
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 416
 
6.9%
송 399
 
6.6%
동 380
 
6.3%
시 371
 
6.1%
서 370
 
6.1%
울 362
 
6.0%
구 361
 
6.0%
별 361
 
6.0%
특 361
 
6.0%
지 291
 
4.8%
Other values (205) 2361
39.1%
Latin
ValueCountFrequency (%)
T 5
20.8%
A 3
12.5%
E 2
 
8.3%
R 2
 
8.3%
S 2
 
8.3%
K 2
 
8.3%
Q 1
 
4.2%
G 1
 
4.2%
O 1
 
4.2%
L 1
 
4.2%
Other values (4) 4
16.7%
Common
ValueCountFrequency (%)
1790
50.4%
* 1670
47.0%
- 75
 
2.1%
) 4
 
0.1%
( 4
 
0.1%
, 3
 
0.1%
1 2
 
0.1%
~ 1
 
< 0.1%
3 1
 
< 0.1%
7 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6032
62.8%
ASCII 3575
37.2%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1790
50.1%
* 1670
46.7%
- 75
 
2.1%
T 5
 
0.1%
) 4
 
0.1%
( 4
 
0.1%
A 3
 
0.1%
, 3
 
0.1%
1 2
 
0.1%
E 2
 
0.1%
Other values (14) 17
 
0.5%
Hangul
ValueCountFrequency (%)
파 416
 
6.9%
송 399
 
6.6%
동 380
 
6.3%
시 371
 
6.2%
서 370
 
6.1%
울 362
 
6.0%
구 361
 
6.0%
별 361
 
6.0%
특 361
 
6.0%
지 291
 
4.8%
Other values (204) 2360
39.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명주소
Text

MISSING 

Distinct329
Distinct (%)91.6%
Missing51
Missing (%)12.4%
Memory size3.3 KiB
2024-05-11T02:26:45.678376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length78
Median length54
Mean length33.963788
Min length21

Characters and Unicode

Total characters12193
Distinct characters247
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique307 ?
Unique (%)85.5%

Sample

1st row서울특별시 송파구 올림픽로 *** (방이동,대우유토피아*층)
2nd row서울특별시 송파구 가락로 *** (방이동)
3rd row서울특별시 송파구 백제고분로 *** (삼전동,삼전빌딩*층***호)
4th row서울특별시 송파구 오금로**길 ** (방이동,신동아타워*층)
5th row서울특별시 송파구 오금로**길 ** (방이동,***)
ValueCountFrequency (%)
368
16.9%
서울특별시 359
16.5%
송파구 358
16.4%
층 100
 
4.6%
호 93
 
4.3%
문정동 47
 
2.2%
가락동 46
 
2.1%
송파대로**길 39
 
1.8%
방이동 28
 
1.3%
백제고분로**길 28
 
1.3%
Other values (301) 712
32.7%
2024-05-11T02:26:46.953830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 2004
 
16.4%
1932
 
15.8%
파 484
 
4.0%
송 469
 
3.8%
동 414
 
3.4%
서 368
 
3.0%
시 367
 
3.0%
, 367
 
3.0%
로 361
 
3.0%
) 359
 
2.9%
Other values (237) 5068
41.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7054
57.9%
Other Punctuation 2372
 
19.5%
Space Separator 1932
 
15.8%
Close Punctuation 359
 
2.9%
Open Punctuation 359
 
2.9%
Dash Punctuation 59
 
0.5%
Uppercase Letter 56
 
0.5%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 484
 
6.9%
송 469
 
6.6%
동 414
 
5.9%
서 368
 
5.2%
시 367
 
5.2%
로 361
 
5.1%
구 359
 
5.1%
울 359
 
5.1%
특 359
 
5.1%
별 359
 
5.1%
Other values (211) 3155
44.7%
Uppercase Letter
ValueCountFrequency (%)
T 8
14.3%
A 7
12.5%
K 6
10.7%
C 5
8.9%
S 5
8.9%
B 5
8.9%
F 3
 
5.4%
H 2
 
3.6%
D 2
 
3.6%
N 2
 
3.6%
Other values (8) 11
19.6%
Other Punctuation
ValueCountFrequency (%)
* 2004
84.5%
, 367
 
15.5%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1932
100.0%
Close Punctuation
ValueCountFrequency (%)
) 359
100.0%
Open Punctuation
ValueCountFrequency (%)
( 359
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 59
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7054
57.9%
Common 5083
41.7%
Latin 56
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 484
 
6.9%
송 469
 
6.6%
동 414
 
5.9%
서 368
 
5.2%
시 367
 
5.2%
로 361
 
5.1%
구 359
 
5.1%
울 359
 
5.1%
특 359
 
5.1%
별 359
 
5.1%
Other values (211) 3155
44.7%
Latin
ValueCountFrequency (%)
T 8
14.3%
A 7
12.5%
K 6
10.7%
C 5
8.9%
S 5
8.9%
B 5
8.9%
F 3
 
5.4%
H 2
 
3.6%
D 2
 
3.6%
N 2
 
3.6%
Other values (8) 11
19.6%
Common
ValueCountFrequency (%)
* 2004
39.4%
1932
38.0%
, 367
 
7.2%
) 359
 
7.1%
( 359
 
7.1%
- 59
 
1.2%
~ 2
 
< 0.1%
/ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7054
57.9%
ASCII 5139
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 2004
39.0%
1932
37.6%
, 367
 
7.1%
) 359
 
7.0%
( 359
 
7.0%
- 59
 
1.1%
T 8
 
0.2%
A 7
 
0.1%
K 6
 
0.1%
C 5
 
0.1%
Other values (16) 33
 
0.6%
Hangul
ValueCountFrequency (%)
파 484
 
6.9%
송 469
 
6.6%
동 414
 
5.9%
서 368
 
5.2%
시 367
 
5.2%
로 361
 
5.1%
구 359
 
5.1%
울 359
 
5.1%
특 359
 
5.1%
별 359
 
5.1%
Other values (211) 3155
44.7%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct95
Distinct (%)54.3%
Missing235
Missing (%)57.3%
Infinite0
Infinite (%)0.0%
Mean50517.291
Minimum5503
Maximum138960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:47.557949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5503
5-th percentile5544.4
Q15682
median5836
Q3138170
95-th percentile138848.9
Maximum138960
Range133457
Interquartile range (IQR)132488

Descriptive statistics

Standard deviation62985.52
Coefficient of variation (CV)1.2468111
Kurtosis-1.5345985
Mean50517.291
Median Absolute Deviation (MAD)223
Skewness0.69499134
Sum8840526
Variance3.9671757 × 109
MonotonicityNot monotonic
2024-05-11T02:26:48.148189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5836 15
 
3.7%
138160 7
 
1.7%
5854 6
 
1.5%
5838 5
 
1.2%
138847 5
 
1.2%
5855 5
 
1.2%
5548 5
 
1.2%
138240 4
 
1.0%
5717 4
 
1.0%
5510 4
 
1.0%
Other values (85) 115
28.0%
(Missing) 235
57.3%
ValueCountFrequency (%)
5503 1
 
0.2%
5510 4
1.0%
5538 1
 
0.2%
5542 2
 
0.5%
5543 1
 
0.2%
5545 2
 
0.5%
5548 5
1.2%
5549 1
 
0.2%
5551 1
 
0.2%
5557 1
 
0.2%
ValueCountFrequency (%)
138960 3
0.7%
138956 1
 
0.2%
138951 1
 
0.2%
138922 1
 
0.2%
138907 1
 
0.2%
138872 1
 
0.2%
138851 1
 
0.2%
138848 1
 
0.2%
138847 5
1.2%
138845 2
 
0.5%

사업장명
Text

Distinct404
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-05-11T02:26:49.046207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length15
Mean length7.8341463
Min length2

Characters and Unicode

Total characters3212
Distinct characters392
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

Unique398 ?
Unique (%)97.1%

Sample

1st row(주)이엠정보교육원
2nd row도서출판 성일
3rd row(주)온누리서비스
4th row도서출판대광
5th row(주)해마컴
ValueCountFrequency (%)
주식회사 76
 
13.8%
주 19
 
3.5%
㈜ 5
 
0.9%
서울지점 3
 
0.5%
주)오아수피부과학 2
 
0.4%
월드텔레콤 2
 
0.4%
베스트모바일 2
 
0.4%
하남통신 2
 
0.4%
솔루션 2
 
0.4%
창연 2
 
0.4%
Other values (431) 434
79.1%
2024-05-11T02:26:50.417332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 218
 
6.8%
) 150
 
4.7%
141
 
4.4%
( 139
 
4.3%
이 129
 
4.0%
사 99
 
3.1%
스 87
 
2.7%
회 81
 
2.5%
식 79
 
2.5%
에 59
 
1.8%
Other values (382) 2030
63.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2621
81.6%
Close Punctuation 150
 
4.7%
Space Separator 141
 
4.4%
Open Punctuation 139
 
4.3%
Uppercase Letter 94
 
2.9%
Lowercase Letter 36
 
1.1%
Other Symbol 10
 
0.3%
Other Punctuation 10
 
0.3%
Decimal Number 7
 
0.2%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 218
 
8.3%
이 129
 
4.9%
사 99
 
3.8%
스 87
 
3.3%
회 81
 
3.1%
식 79
 
3.0%
에 59
 
2.3%
신 43
 
1.6%
아 40
 
1.5%
씨 37
 
1.4%
Other values (328) 1749
66.7%
Uppercase Letter
ValueCountFrequency (%)
S 12
 
12.8%
A 8
 
8.5%
I 8
 
8.5%
M 7
 
7.4%
N 6
 
6.4%
C 5
 
5.3%
R 5
 
5.3%
T 5
 
5.3%
E 4
 
4.3%
B 4
 
4.3%
Other values (13) 30
31.9%
Lowercase Letter
ValueCountFrequency (%)
e 5
13.9%
r 5
13.9%
s 4
11.1%
o 4
11.1%
c 2
 
5.6%
n 2
 
5.6%
i 2
 
5.6%
p 2
 
5.6%
l 2
 
5.6%
t 2
 
5.6%
Other values (6) 6
16.7%
Decimal Number
ValueCountFrequency (%)
1 2
28.6%
6 1
14.3%
5 1
14.3%
3 1
14.3%
2 1
14.3%
4 1
14.3%
Other Punctuation
ValueCountFrequency (%)
. 5
50.0%
& 4
40.0%
, 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 150
100.0%
Space Separator
ValueCountFrequency (%)
141
100.0%
Open Punctuation
ValueCountFrequency (%)
( 139
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2631
81.9%
Common 451
 
14.0%
Latin 130
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 218
 
8.3%
이 129
 
4.9%
사 99
 
3.8%
스 87
 
3.3%
회 81
 
3.1%
식 79
 
3.0%
에 59
 
2.2%
신 43
 
1.6%
아 40
 
1.5%
씨 37
 
1.4%
Other values (329) 1759
66.9%
Latin
ValueCountFrequency (%)
S 12
 
9.2%
A 8
 
6.2%
I 8
 
6.2%
M 7
 
5.4%
N 6
 
4.6%
e 5
 
3.8%
C 5
 
3.8%
r 5
 
3.8%
R 5
 
3.8%
T 5
 
3.8%
Other values (29) 64
49.2%
Common
ValueCountFrequency (%)
) 150
33.3%
141
31.3%
( 139
30.8%
. 5
 
1.1%
& 4
 
0.9%
- 3
 
0.7%
1 2
 
0.4%
+ 1
 
0.2%
6 1
 
0.2%
5 1
 
0.2%
Other values (4) 4
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2621
81.6%
ASCII 581
 
18.1%
None 10
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 218
 
8.3%
이 129
 
4.9%
사 99
 
3.8%
스 87
 
3.3%
회 81
 
3.1%
식 79
 
3.0%
에 59
 
2.3%
신 43
 
1.6%
아 40
 
1.5%
씨 37
 
1.4%
Other values (328) 1749
66.7%
ASCII
ValueCountFrequency (%)
) 150
25.8%
141
24.3%
( 139
23.9%
S 12
 
2.1%
A 8
 
1.4%
I 8
 
1.4%
M 7
 
1.2%
N 6
 
1.0%
e 5
 
0.9%
C 5
 
0.9%
Other values (43) 100
17.2%
None
ValueCountFrequency (%)
㈜ 10
100.0%

최종수정일자
Date

UNIQUE 

Distinct410
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2008-04-30 11:46:24
Maximum2024-04-25 13:58:13
2024-05-11T02:26:50.870413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:51.333699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
I
361 
U
49 

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 361
88.0%
U 49
 
12.0%

Length

2024-05-11T02:26:51.748542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T02:26:52.084255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 361
88.0%
u 49
 
12.0%

데이터갱신일자
Date

Distinct88
Distinct (%)21.5%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-03 23:08:00
2024-05-11T02:26:52.699695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T02:26:53.100223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing410
Missing (%)100.0%
Memory size3.7 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct257
Distinct (%)72.0%
Missing53
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean209958.04
Minimum201438.15
Maximum213977.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:53.570774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201438.15
5-th percentile207308.33
Q1209281.16
median210081.93
Q3210768.56
95-th percentile212121.14
Maximum213977.36
Range12539.207
Interquartile range (IQR)1487.404

Descriptive statistics

Standard deviation1378.1231
Coefficient of variation (CV)0.0065638022
Kurtosis3.8514192
Mean209958.04
Median Absolute Deviation (MAD)772.77477
Skewness-0.73555726
Sum74955021
Variance1899223.2
MonotonicityNot monotonic
2024-05-11T02:26:54.030797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
210694.766184172 15
 
3.7%
209338.128679752 12
 
2.9%
210986.460698452 6
 
1.5%
209140.885315651 5
 
1.2%
210236.0 5
 
1.2%
209427.410217251 4
 
1.0%
209248.063694462 3
 
0.7%
210480.282018702 3
 
0.7%
210342.206068429 3
 
0.7%
209193.653248336 3
 
0.7%
Other values (247) 298
72.7%
(Missing) 53
 
12.9%
ValueCountFrequency (%)
201438.14880655 1
0.2%
206908.348523164 1
0.2%
206914.005245094 1
0.2%
206932.357872339 1
0.2%
206989.715895815 1
0.2%
206990.685929503 1
0.2%
207048.638189411 1
0.2%
207055.16119649 1
0.2%
207099.557340127 2
0.5%
207106.032236098 1
0.2%
ValueCountFrequency (%)
213977.355937651 1
0.2%
213658.586176433 1
0.2%
213276.0219815 1
0.2%
213199.012090172 1
0.2%
213008.308132846 1
0.2%
212959.73484683 2
0.5%
212852.620762184 1
0.2%
212703.408548258 1
0.2%
212664.976994997 1
0.2%
212597.675932013 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct257
Distinct (%)72.0%
Missing53
Missing (%)12.9%
Infinite0
Infinite (%)0.0%
Mean444495.27
Minimum441725.29
Maximum448318.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:54.516740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441725.29
5-th percentile442391.4
Q1443681.68
median444557.21
Q3445451.59
95-th percentile446042.59
Maximum448318.05
Range6592.7566
Interquartile range (IQR)1769.9055

Descriptive statistics

Standard deviation1215.7646
Coefficient of variation (CV)0.0027351576
Kurtosis-0.034839648
Mean444495.27
Median Absolute Deviation (MAD)894.24962
Skewness-0.14483703
Sum1.5868481 × 108
Variance1478083.6
MonotonicityNot monotonic
2024-05-11T02:26:55.158411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443754.398132722 15
 
3.7%
445745.524217446 12
 
2.9%
441725.293491662 6
 
1.5%
446042.592367722 5
 
1.2%
442574.0 5
 
1.2%
445829.725943441 4
 
1.0%
446061.439207259 3
 
0.7%
441833.16323518 3
 
0.7%
445296.361565108 3
 
0.7%
445134.148720751 3
 
0.7%
Other values (247) 298
72.7%
(Missing) 53
 
12.9%
ValueCountFrequency (%)
441725.293491662 6
1.5%
441833.16323518 3
0.7%
441996.227705236 1
 
0.2%
442026.988783 2
 
0.5%
442070.575741668 2
 
0.5%
442307.508632528 1
 
0.2%
442311.216622559 1
 
0.2%
442367.024660277 1
 
0.2%
442377.0 1
 
0.2%
442395.0 1
 
0.2%
ValueCountFrequency (%)
448318.0500626 1
 
0.2%
448172.806593699 1
 
0.2%
448019.855857682 1
 
0.2%
447905.543738759 1
 
0.2%
447302.640257779 1
 
0.2%
447224.169191476 1
 
0.2%
446299.352775446 2
0.5%
446147.977949052 1
 
0.2%
446061.439207259 3
0.7%
446048.260013091 2
0.5%

자산규모
Real number (ℝ)

MISSING  ZEROS 

Distinct91
Distinct (%)47.2%
Missing217
Missing (%)52.9%
Infinite0
Infinite (%)0.0%
Mean6.4468767 × 1010
Minimum0
Maximum7.4607052 × 1012
Zeros23
Zeros (%)5.6%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:55.638889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q112859637
median50000000
Q35 × 108
95-th percentile5.4523911 × 109
Maximum7.4607052 × 1012
Range7.4607052 × 1012
Interquartile range (IQR)4.8714036 × 108

Descriptive statistics

Standard deviation6.2945463 × 1011
Coefficient of variation (CV)9.7637144
Kurtosis113.92469
Mean6.4468767 × 1010
Median Absolute Deviation (MAD)50000000
Skewness10.511026
Sum1.2442472 × 1013
Variance3.9621313 × 1023
MonotonicityNot monotonic
2024-05-11T02:26:56.123730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 38
 
9.3%
0 23
 
5.6%
500000 11
 
2.7%
500000000 7
 
1.7%
60000000 7
 
1.7%
10000000 7
 
1.7%
70000000 6
 
1.5%
5000000 3
 
0.7%
20000000 3
 
0.7%
200000000 3
 
0.7%
Other values (81) 85
 
20.7%
(Missing) 217
52.9%
ValueCountFrequency (%)
0 23
5.6%
30000 1
 
0.2%
500000 11
2.7%
1000000 1
 
0.2%
5000000 3
 
0.7%
10000000 7
 
1.7%
11000000 1
 
0.2%
11520000 1
 
0.2%
12859637 1
 
0.2%
13351475 1
 
0.2%
ValueCountFrequency (%)
7460705190126 1
0.2%
4603903488718 1
0.2%
72500000000 1
0.2%
66175710052 1
0.2%
56154387175 1
0.2%
51231818904 1
0.2%
33361937648 1
0.2%
16714803939 1
0.2%
6765000000 1
0.2%
6130977704 1
0.2%

부채총액
Real number (ℝ)

MISSING  ZEROS 

Distinct68
Distinct (%)35.2%
Missing217
Missing (%)52.9%
Infinite0
Infinite (%)0.0%
Mean2.1165044 × 1010
Minimum0
Maximum3.1212653 × 1012
Zeros123
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size3.7 KiB
2024-05-11T02:26:56.589897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31.04671 × 108
95-th percentile2.8046153 × 109
Maximum3.1212653 × 1012
Range3.1212653 × 1012
Interquartile range (IQR)1.04671 × 108

Descriptive statistics

Standard deviation2.3209543 × 1011
Coefficient of variation (CV)10.965979
Kurtosis168.77731
Mean2.1165044 × 1010
Median Absolute Deviation (MAD)0
Skewness12.761066
Sum4.0848534 × 1012
Variance5.3868287 × 1022
MonotonicityNot monotonic
2024-05-11T02:26:57.276198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 123
30.0%
10000000 3
 
0.7%
100000000 2
 
0.5%
12107159912 1
 
0.2%
104671000 1
 
0.2%
86006248 1
 
0.2%
13129913 1
 
0.2%
880109874 1
 
0.2%
26230066 1
 
0.2%
448977389 1
 
0.2%
Other values (58) 58
 
14.1%
(Missing) 217
52.9%
ValueCountFrequency (%)
0 123
30.0%
3383084 1
 
0.2%
3492303 1
 
0.2%
3694634 1
 
0.2%
6867808 1
 
0.2%
10000000 3
 
0.7%
13129913 1
 
0.2%
15657520 1
 
0.2%
15779867 1
 
0.2%
18494860 1
 
0.2%
ValueCountFrequency (%)
3121265294664 1
0.2%
826988458311 1
0.2%
46414953221 1
0.2%
17148989993 1
0.2%
13600000000 1
0.2%
12107159912 1
0.2%
9781018820 1
0.2%
4623273000 1
0.2%
4557353427 1
0.2%
3378190047 1
0.2%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct67
Distinct (%)34.5%
Missing216
Missing (%)52.7%
Infinite0
Infinite (%)0.0%
Mean4.2399773 × 1010
Minimum-5.7655194 × 108
Maximum4.3394399 × 1012
Zeros12
Zeros (%)2.9%
Negative1
Negative (%)0.2%
Memory size3.7 KiB
2024-05-11T02:26:57.845014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-5.7655194 × 108
5-th percentile0
Q120000000
median50000000
Q32 × 108
95-th percentile2.398264 × 109
Maximum4.3394399 × 1012
Range4.3400165 × 1012
Interquartile range (IQR)1.8 × 108

Descriptive statistics

Standard deviation4.0712236 × 1011
Coefficient of variation (CV)9.6019938
Kurtosis97.127946
Mean4.2399773 × 1010
Median Absolute Deviation (MAD)48887610
Skewness9.8707029
Sum8.225556 × 1012
Variance1.6574861 × 1023
MonotonicityNot monotonic
2024-05-11T02:26:58.336156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 50
 
12.2%
0 12
 
2.9%
10000000 11
 
2.7%
500000 11
 
2.7%
100000000 9
 
2.2%
60000000 8
 
2.0%
500000000 7
 
1.7%
200000000 5
 
1.2%
150000000 5
 
1.2%
70000000 5
 
1.2%
Other values (57) 71
 
17.3%
(Missing) 216
52.7%
ValueCountFrequency (%)
-576551940 1
 
0.2%
0 12
2.9%
30000 1
 
0.2%
100000 1
 
0.2%
500000 11
2.7%
1000000 2
 
0.5%
1224781 1
 
0.2%
2000000 1
 
0.2%
3000000 1
 
0.2%
5000000 4
 
1.0%
ValueCountFrequency (%)
4339439935463 1
0.2%
3674071270014 1
0.2%
77065900000 1
0.2%
41450800084 1
0.2%
21254777736 1
0.2%
20598356625 1
0.2%
9739433954 1
0.2%
5000000000 1
0.2%
4500000000 1
0.2%
2915040000 1
0.2%

판매방식명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing410
Missing (%)100.0%
Memory size3.7 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
03230000200232301312420073120020731<NA>3폐업3폐업처리20040830<NA><NA><NA>3431-4543<NA>138050서울특별시 송파구 방이동 **번지 대우유토피아*층서울특별시 송파구 올림픽로 *** (방이동,대우유토피아*층)<NA>(주)이엠정보교육원2008-04-30 11:46:24I2018-08-31 23:59:59.0<NA>209430.450574445913.08891250000000050000000<NA>
13230000200232301312420082220020822<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>200208222202-7174<NA>138050서울특별시 송파구 방이동 ***번지 *호서울특별시 송파구 가락로 *** (방이동)<NA>도서출판 성일2010-06-03 11:31:32I2018-08-31 23:59:59.0<NA>210509.435147445549.755691<NA><NA><NA><NA>
23230000200232301312420082620020826<NA>3폐업3폐업처리20030415<NA><NA>20020826412-0048<NA><NA>서울특별시 송파구 잠실동 ***-** *층<NA><NA>(주)온누리서비스2008-04-30 11:56:47I2018-08-31 23:59:59.0<NA><NA><NA>000<NA>
33230000200232301312420082820020828<NA>3폐업3폐업처리20130705<NA><NA>200208282202-5146<NA>138180서울특별시 송파구 삼전동 ***번지 **호 삼전빌딩*층***호서울특별시 송파구 백제고분로 *** (삼전동,삼전빌딩*층***호)<NA>도서출판대광2013-07-05 16:28:06I2018-08-31 23:59:59.0<NA>208216.655492444536.271852<NA><NA><NA><NA>
43230000200232301312420090320020903<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>200209032105-5622<NA><NA>서울특별시 송파구 잠실동 ***-** 두성빌딩 *,*층<NA><NA>(주)해마컴2010-06-03 11:33:47I2018-08-31 23:59:59.0<NA><NA><NA>5000000000500000000<NA>
53230000200232301312420091620020916<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>20020916417-3223<NA>138050서울특별시 송파구 방이동 **번지 *호 신동아타워*층서울특별시 송파구 오금로**길 ** (방이동,신동아타워*층)<NA>(주)디엠디이십일2010-06-03 11:30:27I2018-08-31 23:59:59.0<NA>209708.127928445937.5434565000000000500000000<NA>
63230000200232301312420091720020917<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>200209173432-0731<NA>138050서울특별시 송파구 방이동 **번지 *호 ***서울특별시 송파구 오금로**길 ** (방이동,***)<NA>(주)Mors Sola2010-06-03 11:29:55I2018-08-31 23:59:59.0<NA>209550.894135445815.81193350000000050000000<NA>
73230000200232301312420101420021014<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>200210142203-1125<NA>138050서울특별시 송파구 방이동 **번지 *호 신동아타워*층***서울특별시 송파구 오금로**길 ** (방이동,신동아타워*층***)<NA>포라이프아이엔티(주)2010-06-03 11:31:04I2018-08-31 23:59:59.0<NA>209708.127928445937.5434565000000000500000000<NA>
83230000200232301312420102220021022<NA>3폐업3폐업처리20090820<NA><NA>20021022412-8762<NA>138170서울특별시 송파구 송파동 **번지 *호 남경빌딩*층 *서울특별시 송파구 백제고분로 *** (송파동,남경빌딩*층 *)<NA>족보나라2009-08-20 17:03:09I2018-08-31 23:59:59.0<NA>209452.341133444866.772986<NA><NA><NA><NA>
93230000200232301312420110220021102<NA>4취소/말소/만료/정지/중지7직권말소<NA><NA><NA>20021102406-7501<NA>138200서울특별시 송파구 문정동 **번지 *호 동호빌딩 신관***호서울특별시 송파구 문정로*길 ** (문정동,동호빌딩 신관***호)<NA>일간스포츠GNB2010-06-03 11:29:17I2018-08-31 23:59:59.0<NA>211074.735618442480.543457<NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)자산규모부채총액자본금판매방식명
400323000020233230291242000082023-08-29<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-6426-0104<NA><NA>서울특별시 송파구 신천동 **-* 새마을 교통회관서울특별시 송파구 올림픽로 ***, *층 (신천동)5510(주)씨에스2023-08-29 15:59:40I2022-12-07 21:01:00.0<NA>209243.16935445935.092531<NA><NA><NA><NA>
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403323000020233230291242000112023-12-19<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-1644-0273<NA><NA>서울특별시 송파구 문정동 **-* *층 ***-***호서울특별시 송파구 송파대로**길 *-**, *층 ***-***호 (문정동)5807주식회사 메가멤버스2024-04-24 16:16:08U2023-12-03 22:06:00.0<NA>210983.587452442438.127125<NA><NA><NA><NA>
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406323000020243230291242000032024-03-07<NA>1영업/정상1정상영업<NA><NA><NA><NA>02-569-2031<NA><NA>서울특별시 송파구 문정동 *** 송파 테라타워*서울특별시 송파구 송파대로 ***, 송파 테라타워* 비동 **층 ****호 (문정동)5854주식회사 마이컴즈2024-03-07 11:17:14I2023-12-03 00:09:00.0<NA><NA><NA><NA><NA><NA><NA>
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