Overview

Dataset statistics

Number of variables27
Number of observations4172
Missing cells36667
Missing cells (%)32.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory920.9 KiB
Average record size in memory226.0 B

Variable types

Categorical6
Numeric5
DateTime6
Text7
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),지정일자,민원종류명
Author마포구
URLhttps://data.seoul.go.kr/dataList/OA-19915/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
상세영업상태명 is highly imbalanced (55.5%)Imbalance
인허가취소일자 has 3728 (89.4%) missing valuesMissing
폐업일자 has 1189 (28.5%) missing valuesMissing
휴업시작일자 has 4098 (98.2%) missing valuesMissing
휴업종료일자 has 4098 (98.2%) missing valuesMissing
재개업일자 has 4172 (100.0%) missing valuesMissing
전화번호 has 1876 (45.0%) missing valuesMissing
소재지면적 has 4172 (100.0%) missing valuesMissing
소재지우편번호 has 3005 (72.0%) missing valuesMissing
지번주소 has 580 (13.9%) missing valuesMissing
도로명주소 has 573 (13.7%) missing valuesMissing
도로명우편번호 has 2804 (67.2%) missing valuesMissing
업태구분명 has 4172 (100.0%) missing valuesMissing
좌표정보(X) has 429 (10.3%) missing valuesMissing
좌표정보(Y) has 429 (10.3%) missing valuesMissing
지정일자 has 1342 (32.2%) missing valuesMissing
관리번호 is highly skewed (γ1 = 42.90214787)Skewed
관리번호 has unique valuesUnique
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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
상세영업상태코드 has 732 (17.5%) zerosZeros

Reproduction

Analysis started2024-04-06 12:58:49.013012
Analysis finished2024-04-06 12:58:51.602211
Duration2.59 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
3130000
4172 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3130000
2nd row3130000
3rd row3130000
4th row3130000
5th row3130000

Common Values

ValueCountFrequency (%)
3130000 4172
100.0%

Length

2024-04-06T21:58:51.740424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:51.950672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3130000 4172
100.0%

관리번호
Real number (ℝ)

SKEWED  UNIQUE 

Distinct4172
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0079015 × 1018
Minimum3.1301801 × 1014
Maximum9.999313 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.8 KiB
2024-04-06T21:58:52.180677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.1301801 × 1014
5-th percentile1.998313 × 1018
Q12.002313 × 1018
median2.007313 × 1018
Q32.014313 × 1018
95-th percentile2.021313 × 1018
Maximum9.999313 × 1018
Range9.999 × 1018
Interquartile range (IQR)1.2000004 × 1016

Descriptive statistics

Standard deviation1.3888619 × 1017
Coefficient of variation (CV)0.069169825
Kurtosis2667.8469
Mean2.0079015 × 1018
Median Absolute Deviation (MAD)6 × 1015
Skewness42.902148
Sum2.1430798 × 1018
Variance1.9289374 × 1034
MonotonicityStrictly increasing
2024-04-06T21:58:52.441162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
313018005600000 1
 
< 0.1%
2011313011805600081 1
 
< 0.1%
2011313011805600083 1
 
< 0.1%
2011313011805600084 1
 
< 0.1%
2011313011805600085 1
 
< 0.1%
2011313011805600086 1
 
< 0.1%
2011313011805600087 1
 
< 0.1%
2011313011805600088 1
 
< 0.1%
2011313011805600089 1
 
< 0.1%
2011313011805600090 1
 
< 0.1%
Other values (4162) 4162
99.8%
ValueCountFrequency (%)
313018005600000 1
< 0.1%
313018005600001 1
< 0.1%
313018005600003 1
< 0.1%
180313011805611000 1
< 0.1%
1087313018005600001 1
< 0.1%
1711313011805611111 1
< 0.1%
1966313011805600001 1
< 0.1%
1980313009905600001 1
< 0.1%
1981313009905600332 1
< 0.1%
1983313009905600001 1
< 0.1%
ValueCountFrequency (%)
9999313022505600000 1
< 0.1%
2024313025505600025 1
< 0.1%
2024313025505600024 1
< 0.1%
2024313025505600023 1
< 0.1%
2024313025505600022 1
< 0.1%
2024313025505600021 1
< 0.1%
2024313025505600020 1
< 0.1%
2024313025505600019 1
< 0.1%
2024313025505600018 1
< 0.1%
2024313025505600017 1
< 0.1%
Distinct2514
Distinct (%)60.3%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
Minimum1960-01-01 00:00:00
Maximum2024-04-03 00:00:00
2024-04-06T21:58:52.683671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:52.962459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

MISSING 

Distinct128
Distinct (%)28.8%
Missing3728
Missing (%)89.4%
Memory size32.7 KiB
Minimum2000-01-24 00:00:00
Maximum2024-01-31 00:00:00
2024-04-06T21:58:53.262330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:53.530176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
3
2984 
1
732 
4
453 
2
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 2984
71.5%
1 732
 
17.5%
4 453
 
10.9%
2 3
 
0.1%

Length

2024-04-06T21:58:53.799890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:54.040947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2984
71.5%
1 732
 
17.5%
4 453
 
10.9%
2 3
 
0.1%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
폐업
2984 
영업/정상
732 
취소/말소/만료/정지/중지
453 
휴업
 
3

Length

Max length14
Median length2
Mean length3.8293384
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2984
71.5%
영업/정상 732
 
17.5%
취소/말소/만료/정지/중지 453
 
10.9%
휴업 3
 
0.1%

Length

2024-04-06T21:58:54.315244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:54.555218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2984
71.5%
영업/정상 732
 
17.5%
취소/말소/만료/정지/중지 453
 
10.9%
휴업 3
 
0.1%

상세영업상태코드
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9046021
Minimum0
Maximum6
Zeros732
Zeros (%)17.5%
Negative0
Negative (%)0.0%
Memory size36.8 KiB
2024-04-06T21:58:55.154048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1800336
Coefficient of variation (CV)0.61956964
Kurtosis1.7188764
Mean1.9046021
Median Absolute Deviation (MAD)0
Skewness0.62213184
Sum7946
Variance1.3924794
MonotonicityNot monotonic
2024-04-06T21:58:55.357100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 2984
71.5%
0 732
 
17.5%
5 304
 
7.3%
3 143
 
3.4%
4 5
 
0.1%
1 3
 
0.1%
6 1
 
< 0.1%
ValueCountFrequency (%)
0 732
 
17.5%
1 3
 
0.1%
2 2984
71.5%
3 143
 
3.4%
4 5
 
0.1%
5 304
 
7.3%
6 1
 
< 0.1%
ValueCountFrequency (%)
6 1
 
< 0.1%
5 304
 
7.3%
4 5
 
0.1%
3 143
 
3.4%
2 2984
71.5%
1 3
 
0.1%
0 732
 
17.5%

상세영업상태명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
폐업처리
2984 
정상영업
732 
지정취소
304 
직권취소
 
143
임시소매기간만료
 
5
Other values (2)
 
4

Length

Max length8
Median length4
Mean length4.0047939
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 2984
71.5%
정상영업 732
 
17.5%
지정취소 304
 
7.3%
직권취소 143
 
3.4%
임시소매기간만료 5
 
0.1%
휴업처리 3
 
0.1%
영업정지 1
 
< 0.1%

Length

2024-04-06T21:58:55.625019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:58:55.882117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 2984
71.5%
정상영업 732
 
17.5%
지정취소 304
 
7.3%
직권취소 143
 
3.4%
임시소매기간만료 5
 
0.1%
휴업처리 3
 
0.1%
영업정지 1
 
< 0.1%

폐업일자
Text

MISSING 

Distinct2034
Distinct (%)68.2%
Missing1189
Missing (%)28.5%
Memory size32.7 KiB
2024-04-06T21:58:56.341707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.0616829
Min length8

Characters and Unicode

Total characters24048
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

Unique1382 ?
Unique (%)46.3%

Sample

1st row20151006
2nd row20161212
3rd row20151020
4th row20090401
5th row20160629
ValueCountFrequency (%)
20200610 13
 
0.4%
20031001 9
 
0.3%
20030329 8
 
0.3%
20200605 7
 
0.2%
20030804 7
 
0.2%
20040610 7
 
0.2%
20021202 6
 
0.2%
20071108 6
 
0.2%
20030923 6
 
0.2%
20200608 6
 
0.2%
Other values (2024) 2908
97.5%
2024-04-06T21:58:57.202736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8443
35.1%
2 5467
22.7%
1 4109
17.1%
3 1060
 
4.4%
4 817
 
3.4%
7 817
 
3.4%
6 812
 
3.4%
8 803
 
3.3%
9 787
 
3.3%
5 748
 
3.1%
Other values (2) 185
 
0.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 23863
99.2%
Dash Punctuation 184
 
0.8%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8443
35.4%
2 5467
22.9%
1 4109
17.2%
3 1060
 
4.4%
4 817
 
3.4%
7 817
 
3.4%
6 812
 
3.4%
8 803
 
3.4%
9 787
 
3.3%
5 748
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 184
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24048
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8443
35.1%
2 5467
22.7%
1 4109
17.1%
3 1060
 
4.4%
4 817
 
3.4%
7 817
 
3.4%
6 812
 
3.4%
8 803
 
3.3%
9 787
 
3.3%
5 748
 
3.1%
Other values (2) 185
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24048
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8443
35.1%
2 5467
22.7%
1 4109
17.1%
3 1060
 
4.4%
4 817
 
3.4%
7 817
 
3.4%
6 812
 
3.4%
8 803
 
3.3%
9 787
 
3.3%
5 748
 
3.1%
Other values (2) 185
 
0.8%

휴업시작일자
Date

MISSING 

Distinct58
Distinct (%)78.4%
Missing4098
Missing (%)98.2%
Memory size32.7 KiB
Minimum2007-10-24 00:00:00
Maximum2023-02-01 00:00:00
2024-04-06T21:58:57.475642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:57.846797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업종료일자
Date

MISSING 

Distinct57
Distinct (%)77.0%
Missing4098
Missing (%)98.2%
Memory size32.7 KiB
Minimum2007-11-13 00:00:00
Maximum2023-05-30 00:00:00
2024-04-06T21:58:58.089150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:58:58.333443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4172
Missing (%)100.0%
Memory size36.8 KiB

전화번호
Text

MISSING 

Distinct1621
Distinct (%)70.6%
Missing1876
Missing (%)45.0%
Memory size32.7 KiB
2024-04-06T21:58:58.905077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length8.2094948
Min length1

Characters and Unicode

Total characters18849
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

Unique1477 ?
Unique (%)64.3%

Sample

1st row02-711-6222
2nd row334-6946
3rd row02-717-2413
4th row333-0370
5th row7167938
ValueCountFrequency (%)
02 819
28.5%
11111111 105
 
3.7%
111111111111 44
 
1.5%
0211111111 18
 
0.6%
111 15
 
0.5%
1577-0711 13
 
0.5%
11111111111 13
 
0.5%
1111 12
 
0.4%
1111111 12
 
0.4%
111111111 7
 
0.2%
Other values (1614) 1817
63.2%
2024-04-06T21:58:59.907446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 3501
18.6%
2 2536
13.5%
3 2498
13.3%
0 2384
12.6%
7 1665
8.8%
- 1097
 
5.8%
4 1040
 
5.5%
6 1024
 
5.4%
5 895
 
4.7%
8 822
 
4.4%
Other values (5) 1387
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17167
91.1%
Dash Punctuation 1097
 
5.8%
Space Separator 581
 
3.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3501
20.4%
2 2536
14.8%
3 2498
14.6%
0 2384
13.9%
7 1665
9.7%
4 1040
 
6.1%
6 1024
 
6.0%
5 895
 
5.2%
8 822
 
4.8%
9 802
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1097
100.0%
Space Separator
ValueCountFrequency (%)
581
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
* 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18849
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3501
18.6%
2 2536
13.5%
3 2498
13.3%
0 2384
12.6%
7 1665
8.8%
- 1097
 
5.8%
4 1040
 
5.5%
6 1024
 
5.4%
5 895
 
4.7%
8 822
 
4.4%
Other values (5) 1387
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18849
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3501
18.6%
2 2536
13.5%
3 2498
13.3%
0 2384
12.6%
7 1665
8.8%
- 1097
 
5.8%
4 1040
 
5.5%
6 1024
 
5.4%
5 895
 
4.7%
8 822
 
4.4%
Other values (5) 1387
 
7.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4172
Missing (%)100.0%
Memory size36.8 KiB

소재지우편번호
Text

MISSING 

Distinct158
Distinct (%)13.5%
Missing3005
Missing (%)72.0%
Memory size32.7 KiB
2024-04-06T21:59:00.488502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0205656
Min length6

Characters and Unicode

Total characters7026
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

Unique44 ?
Unique (%)3.8%

Sample

1st row121883
2nd row121210
3rd row121813
4th row121820
5th row121080
ValueCountFrequency (%)
121210 106
 
9.1%
121270 80
 
6.9%
121040 49
 
4.2%
121230 48
 
4.1%
121220 43
 
3.7%
121200 42
 
3.6%
121080 36
 
3.1%
121110 35
 
3.0%
121020 34
 
2.9%
121250 33
 
2.8%
Other values (148) 661
56.6%
2024-04-06T21:59:01.357662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2681
38.2%
2 1711
24.4%
0 1181
16.8%
8 477
 
6.8%
7 213
 
3.0%
3 157
 
2.2%
9 143
 
2.0%
5 141
 
2.0%
4 139
 
2.0%
6 93
 
1.3%
Other values (2) 90
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6936
98.7%
Space Separator 66
 
0.9%
Dash Punctuation 24
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2681
38.7%
2 1711
24.7%
0 1181
17.0%
8 477
 
6.9%
7 213
 
3.1%
3 157
 
2.3%
9 143
 
2.1%
5 141
 
2.0%
4 139
 
2.0%
6 93
 
1.3%
Space Separator
ValueCountFrequency (%)
66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7026
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2681
38.2%
2 1711
24.4%
0 1181
16.8%
8 477
 
6.8%
7 213
 
3.0%
3 157
 
2.2%
9 143
 
2.0%
5 141
 
2.0%
4 139
 
2.0%
6 93
 
1.3%
Other values (2) 90
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7026
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2681
38.2%
2 1711
24.4%
0 1181
16.8%
8 477
 
6.8%
7 213
 
3.0%
3 157
 
2.2%
9 143
 
2.0%
5 141
 
2.0%
4 139
 
2.0%
6 93
 
1.3%
Other values (2) 90
 
1.3%

지번주소
Text

MISSING 

Distinct3176
Distinct (%)88.4%
Missing580
Missing (%)13.9%
Memory size32.7 KiB
2024-04-06T21:59:01.974201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length48
Mean length26.385022
Min length1

Characters and Unicode

Total characters94775
Distinct characters402
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

Unique2835 ?
Unique (%)78.9%

Sample

1st row서울특별시 마포구 합정동 91번지 11호
2nd row서울특별시 마포구 서교동 327번지 11호
3rd row서울특별시 마포구 염리동 106번지 2 호
4th row서울특별시 마포구 염리동 10번지 8호
5th row서울특별시 마포구 합정동 429번지 54호
ValueCountFrequency (%)
서울특별시 3588
 
17.9%
마포구 3587
 
17.9%
1층 559
 
2.8%
서교동 543
 
2.7%
1호 406
 
2.0%
392
 
2.0%
공덕동 312
 
1.6%
망원동 269
 
1.3%
상암동 261
 
1.3%
성산동 258
 
1.3%
Other values (2224) 9850
49.2%
2024-04-06T21:59:03.094088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19725
20.8%
4201
 
4.4%
1 4128
 
4.4%
3739
 
3.9%
3739
 
3.9%
3738
 
3.9%
3665
 
3.9%
3633
 
3.8%
3603
 
3.8%
3589
 
3.8%
Other values (392) 41015
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56661
59.8%
Space Separator 19725
 
20.8%
Decimal Number 17093
 
18.0%
Uppercase Letter 332
 
0.4%
Dash Punctuation 279
 
0.3%
Close Punctuation 274
 
0.3%
Open Punctuation 274
 
0.3%
Other Punctuation 74
 
0.1%
Lowercase Letter 47
 
< 0.1%
Math Symbol 10
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4201
 
7.4%
3739
 
6.6%
3739
 
6.6%
3738
 
6.6%
3665
 
6.5%
3633
 
6.4%
3603
 
6.4%
3589
 
6.3%
3588
 
6.3%
3457
 
6.1%
Other values (337) 19709
34.8%
Uppercase Letter
ValueCountFrequency (%)
B 51
15.4%
C 45
13.6%
D 35
10.5%
M 33
9.9%
K 26
7.8%
T 22
6.6%
S 20
 
6.0%
G 19
 
5.7%
I 17
 
5.1%
L 14
 
4.2%
Other values (10) 50
15.1%
Lowercase Letter
ValueCountFrequency (%)
e 9
19.1%
o 7
14.9%
r 6
12.8%
w 6
12.8%
t 3
 
6.4%
y 3
 
6.4%
i 3
 
6.4%
c 2
 
4.3%
u 2
 
4.3%
s 2
 
4.3%
Other values (3) 4
8.5%
Decimal Number
ValueCountFrequency (%)
1 4128
24.2%
3 2111
12.4%
2 2090
12.2%
4 1875
11.0%
5 1522
 
8.9%
6 1277
 
7.5%
0 1201
 
7.0%
7 1074
 
6.3%
8 975
 
5.7%
9 840
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 62
83.8%
@ 6
 
8.1%
. 4
 
5.4%
& 1
 
1.4%
/ 1
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 273
99.6%
[ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
19725
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 279
100.0%
Close Punctuation
ValueCountFrequency (%)
) 274
100.0%
Math Symbol
ValueCountFrequency (%)
~ 10
100.0%
Letter Number
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56661
59.8%
Common 37729
39.8%
Latin 385
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4201
 
7.4%
3739
 
6.6%
3739
 
6.6%
3738
 
6.6%
3665
 
6.5%
3633
 
6.4%
3603
 
6.4%
3589
 
6.3%
3588
 
6.3%
3457
 
6.1%
Other values (337) 19709
34.8%
Latin
ValueCountFrequency (%)
B 51
13.2%
C 45
11.7%
D 35
 
9.1%
M 33
 
8.6%
K 26
 
6.8%
T 22
 
5.7%
S 20
 
5.2%
G 19
 
4.9%
I 17
 
4.4%
L 14
 
3.6%
Other values (24) 103
26.8%
Common
ValueCountFrequency (%)
19725
52.3%
1 4128
 
10.9%
3 2111
 
5.6%
2 2090
 
5.5%
4 1875
 
5.0%
5 1522
 
4.0%
6 1277
 
3.4%
0 1201
 
3.2%
7 1074
 
2.8%
8 975
 
2.6%
Other values (11) 1751
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56661
59.8%
ASCII 38108
40.2%
Number Forms 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19725
51.8%
1 4128
 
10.8%
3 2111
 
5.5%
2 2090
 
5.5%
4 1875
 
4.9%
5 1522
 
4.0%
6 1277
 
3.4%
0 1201
 
3.2%
7 1074
 
2.8%
8 975
 
2.6%
Other values (44) 2130
 
5.6%
Hangul
ValueCountFrequency (%)
4201
 
7.4%
3739
 
6.6%
3739
 
6.6%
3738
 
6.6%
3665
 
6.5%
3633
 
6.4%
3603
 
6.4%
3589
 
6.3%
3588
 
6.3%
3457
 
6.1%
Other values (337) 19709
34.8%
Number Forms
ValueCountFrequency (%)
6
100.0%

도로명주소
Text

MISSING 

Distinct2852
Distinct (%)79.2%
Missing573
Missing (%)13.7%
Memory size32.7 KiB
2024-04-06T21:59:03.700187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length56
Mean length29.512642
Min length13

Characters and Unicode

Total characters106216
Distinct characters408
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

Unique2322 ?
Unique (%)64.5%

Sample

1st row서울특별시 마포구 대흥로 177-3 (대흥동)
2nd row서울특별시 마포구 광성로6길 22 (신수동)
3rd row서울특별시 마포구 독막로2길 9 (합정동)
4th row서울특별시 마포구 토정로2길 6-9 (합정동)
5th row서울특별시 마포구 마포대로11길 91 (염리동)
ValueCountFrequency (%)
서울특별시 3598
 
17.4%
마포구 3592
 
17.4%
1층 658
 
3.2%
서교동 332
 
1.6%
망원동 277
 
1.3%
성산동 242
 
1.2%
마포대로 216
 
1.0%
합정동 189
 
0.9%
월드컵북로 171
 
0.8%
공덕동 170
 
0.8%
Other values (2101) 11222
54.3%
2024-04-06T21:59:04.754605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17078
 
16.1%
1 4870
 
4.6%
4239
 
4.0%
4139
 
3.9%
4139
 
3.9%
4092
 
3.9%
( 3814
 
3.6%
) 3814
 
3.6%
3700
 
3.5%
3661
 
3.4%
Other values (398) 52670
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 63620
59.9%
Space Separator 17078
 
16.1%
Decimal Number 14708
 
13.8%
Open Punctuation 3814
 
3.6%
Close Punctuation 3814
 
3.6%
Other Punctuation 2448
 
2.3%
Uppercase Letter 341
 
0.3%
Dash Punctuation 326
 
0.3%
Lowercase Letter 40
 
< 0.1%
Math Symbol 18
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4239
 
6.7%
4139
 
6.5%
4139
 
6.5%
4092
 
6.4%
3700
 
5.8%
3661
 
5.8%
3647
 
5.7%
3601
 
5.7%
3598
 
5.7%
3381
 
5.3%
Other values (343) 25423
40.0%
Uppercase Letter
ValueCountFrequency (%)
B 93
27.3%
C 43
12.6%
K 28
 
8.2%
M 24
 
7.0%
D 22
 
6.5%
T 19
 
5.6%
S 19
 
5.6%
G 16
 
4.7%
I 16
 
4.7%
L 13
 
3.8%
Other values (11) 48
14.1%
Lowercase Letter
ValueCountFrequency (%)
e 9
22.5%
o 5
12.5%
r 4
10.0%
w 4
10.0%
s 2
 
5.0%
u 2
 
5.0%
b 2
 
5.0%
h 2
 
5.0%
i 2
 
5.0%
t 2
 
5.0%
Other values (4) 6
15.0%
Decimal Number
ValueCountFrequency (%)
1 4870
33.1%
2 2001
13.6%
3 1404
 
9.5%
0 1278
 
8.7%
4 1105
 
7.5%
5 896
 
6.1%
6 876
 
6.0%
7 781
 
5.3%
9 769
 
5.2%
8 728
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 2436
99.5%
. 7
 
0.3%
@ 4
 
0.2%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
17078
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3814
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3814
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 326
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%
Letter Number
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 63620
59.9%
Common 42206
39.7%
Latin 390
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4239
 
6.7%
4139
 
6.5%
4139
 
6.5%
4092
 
6.4%
3700
 
5.8%
3661
 
5.8%
3647
 
5.7%
3601
 
5.7%
3598
 
5.7%
3381
 
5.3%
Other values (343) 25423
40.0%
Latin
ValueCountFrequency (%)
B 93
23.8%
C 43
11.0%
K 28
 
7.2%
M 24
 
6.2%
D 22
 
5.6%
T 19
 
4.9%
S 19
 
4.9%
G 16
 
4.1%
I 16
 
4.1%
L 13
 
3.3%
Other values (26) 97
24.9%
Common
ValueCountFrequency (%)
17078
40.5%
1 4870
 
11.5%
( 3814
 
9.0%
) 3814
 
9.0%
, 2436
 
5.8%
2 2001
 
4.7%
3 1404
 
3.3%
0 1278
 
3.0%
4 1105
 
2.6%
5 896
 
2.1%
Other values (9) 3510
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 63620
59.9%
ASCII 42587
40.1%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17078
40.1%
1 4870
 
11.4%
( 3814
 
9.0%
) 3814
 
9.0%
, 2436
 
5.7%
2 2001
 
4.7%
3 1404
 
3.3%
0 1278
 
3.0%
4 1105
 
2.6%
5 896
 
2.1%
Other values (44) 3891
 
9.1%
Hangul
ValueCountFrequency (%)
4239
 
6.7%
4139
 
6.5%
4139
 
6.5%
4092
 
6.4%
3700
 
5.8%
3661
 
5.8%
3647
 
5.7%
3601
 
5.7%
3598
 
5.7%
3381
 
5.3%
Other values (343) 25423
40.0%
Number Forms
ValueCountFrequency (%)
9
100.0%

도로명우편번호
Text

MISSING 

Distinct387
Distinct (%)28.3%
Missing2804
Missing (%)67.2%
Memory size32.7 KiB
2024-04-06T21:59:05.528688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3274854
Min length5

Characters and Unicode

Total characters7288
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

Unique101 ?
Unique (%)7.4%

Sample

1st row04105
2nd row04096
3rd row04072
4th row04140
5th row04124
ValueCountFrequency (%)
03938 20
 
1.5%
04168 16
 
1.2%
121837 14
 
1.0%
04049 13
 
1.0%
121829 12
 
0.9%
04166 12
 
0.9%
04002 12
 
0.9%
03930 12
 
0.9%
03964 11
 
0.8%
121809 11
 
0.8%
Other values (377) 1235
90.3%
2024-04-06T21:59:06.586789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1633
22.4%
1 1415
19.4%
4 887
12.2%
2 734
10.1%
8 614
 
8.4%
9 597
 
8.2%
3 564
 
7.7%
7 300
 
4.1%
6 268
 
3.7%
5 264
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7276
99.8%
Dash Punctuation 12
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1633
22.4%
1 1415
19.4%
4 887
12.2%
2 734
10.1%
8 614
 
8.4%
9 597
 
8.2%
3 564
 
7.8%
7 300
 
4.1%
6 268
 
3.7%
5 264
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1633
22.4%
1 1415
19.4%
4 887
12.2%
2 734
10.1%
8 614
 
8.4%
9 597
 
8.2%
3 564
 
7.7%
7 300
 
4.1%
6 268
 
3.7%
5 264
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1633
22.4%
1 1415
19.4%
4 887
12.2%
2 734
10.1%
8 614
 
8.4%
9 597
 
8.2%
3 564
 
7.7%
7 300
 
4.1%
6 268
 
3.7%
5 264
 
3.6%
Distinct3184
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
2024-04-06T21:59:07.103362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length26
Mean length7.271093
Min length1

Characters and Unicode

Total characters30335
Distinct characters681
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

Unique2588 ?
Unique (%)62.0%

Sample

1st row담배가게
2nd row백광청과물직판장
3rd row성원
4th row제일슈퍼
5th row대현마트
ValueCountFrequency (%)
씨유 263
 
4.6%
gs25 216
 
3.8%
세븐일레븐 147
 
2.6%
훼미리마트 85
 
1.5%
미니스톱 72
 
1.3%
지에스25 62
 
1.1%
주)코리아세븐 56
 
1.0%
이마트24 43
 
0.8%
주식회사 27
 
0.5%
지에스(gs)25 25
 
0.4%
Other values (3122) 4726
82.6%
2024-04-06T21:59:07.901372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1578
 
5.2%
1558
 
5.1%
1077
 
3.6%
701
 
2.3%
2 592
 
2.0%
558
 
1.8%
516
 
1.7%
500
 
1.6%
485
 
1.6%
479
 
1.6%
Other values (671) 22291
73.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25410
83.8%
Space Separator 1558
 
5.1%
Decimal Number 1345
 
4.4%
Uppercase Letter 1175
 
3.9%
Close Punctuation 349
 
1.2%
Open Punctuation 345
 
1.1%
Lowercase Letter 110
 
0.4%
Other Punctuation 28
 
0.1%
Dash Punctuation 13
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1578
 
6.2%
1077
 
4.2%
701
 
2.8%
558
 
2.2%
516
 
2.0%
500
 
2.0%
485
 
1.9%
479
 
1.9%
433
 
1.7%
405
 
1.6%
Other values (604) 18678
73.5%
Uppercase Letter
ValueCountFrequency (%)
S 427
36.3%
G 374
31.8%
C 57
 
4.9%
M 33
 
2.8%
K 32
 
2.7%
L 26
 
2.2%
A 25
 
2.1%
D 24
 
2.0%
I 22
 
1.9%
B 17
 
1.4%
Other values (16) 138
 
11.7%
Lowercase Letter
ValueCountFrequency (%)
r 13
11.8%
a 12
10.9%
e 12
10.9%
t 10
9.1%
s 9
 
8.2%
o 9
 
8.2%
m 8
 
7.3%
y 5
 
4.5%
u 4
 
3.6%
f 4
 
3.6%
Other values (11) 24
21.8%
Decimal Number
ValueCountFrequency (%)
2 592
44.0%
5 474
35.2%
4 85
 
6.3%
6 48
 
3.6%
1 46
 
3.4%
3 37
 
2.8%
8 23
 
1.7%
7 16
 
1.2%
9 14
 
1.0%
0 10
 
0.7%
Other Punctuation
ValueCountFrequency (%)
& 10
35.7%
. 8
28.6%
: 7
25.0%
, 2
 
7.1%
' 1
 
3.6%
Space Separator
ValueCountFrequency (%)
1558
100.0%
Close Punctuation
ValueCountFrequency (%)
) 349
100.0%
Open Punctuation
ValueCountFrequency (%)
( 345
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25412
83.8%
Common 3638
 
12.0%
Latin 1285
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1578
 
6.2%
1077
 
4.2%
701
 
2.8%
558
 
2.2%
516
 
2.0%
500
 
2.0%
485
 
1.9%
479
 
1.9%
433
 
1.7%
405
 
1.6%
Other values (605) 18680
73.5%
Latin
ValueCountFrequency (%)
S 427
33.2%
G 374
29.1%
C 57
 
4.4%
M 33
 
2.6%
K 32
 
2.5%
L 26
 
2.0%
A 25
 
1.9%
D 24
 
1.9%
I 22
 
1.7%
B 17
 
1.3%
Other values (37) 248
19.3%
Common
ValueCountFrequency (%)
1558
42.8%
2 592
 
16.3%
5 474
 
13.0%
) 349
 
9.6%
( 345
 
9.5%
4 85
 
2.3%
6 48
 
1.3%
1 46
 
1.3%
3 37
 
1.0%
8 23
 
0.6%
Other values (9) 81
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25410
83.8%
ASCII 4923
 
16.2%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1578
 
6.2%
1077
 
4.2%
701
 
2.8%
558
 
2.2%
516
 
2.0%
500
 
2.0%
485
 
1.9%
479
 
1.9%
433
 
1.7%
405
 
1.6%
Other values (604) 18678
73.5%
ASCII
ValueCountFrequency (%)
1558
31.6%
2 592
 
12.0%
5 474
 
9.6%
S 427
 
8.7%
G 374
 
7.6%
) 349
 
7.1%
( 345
 
7.0%
4 85
 
1.7%
C 57
 
1.2%
6 48
 
1.0%
Other values (56) 614
 
12.5%
None
ValueCountFrequency (%)
2
100.0%
Distinct3184
Distinct (%)76.3%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
Minimum2007-07-12 18:10:44
Maximum2024-04-03 18:34:31
2024-04-06T21:59:08.158162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:59:08.398790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
I
3250 
U
922 

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 3250
77.9%
U 922
 
22.1%

Length

2024-04-06T21:59:08.573209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:59:08.732078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3250
77.9%
u 922
 
22.1%
Distinct640
Distinct (%)15.3%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:05:00
2024-04-06T21:59:08.938843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T21:59:09.189547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4172
Missing (%)100.0%
Memory size36.8 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1817
Distinct (%)48.5%
Missing429
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean193370.48
Minimum173751.2
Maximum196721.09
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.8 KiB
2024-04-06T21:59:09.432184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173751.2
5-th percentile190685.31
Q1192023.19
median193169.71
Q3194977.88
95-th percentile196079.44
Maximum196721.09
Range22969.888
Interquartile range (IQR)2954.6863

Descriptive statistics

Standard deviation1753.3933
Coefficient of variation (CV)0.0090675335
Kurtosis3.1648057
Mean193370.48
Median Absolute Deviation (MAD)1409.9468
Skewness-0.38009743
Sum7.237857 × 108
Variance3074388
MonotonicityNot monotonic
2024-04-06T21:59:09.647375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
193359.27190055 28
 
0.7%
190250.875091908 15
 
0.4%
192414.026879919 13
 
0.3%
192948.082935166 13
 
0.3%
194978.350112608 12
 
0.3%
190125.564768858 12
 
0.3%
191010.381048042 11
 
0.3%
195852.524254164 11
 
0.3%
195019.399817378 11
 
0.3%
194564.277152493 10
 
0.2%
Other values (1807) 3607
86.5%
(Missing) 429
 
10.3%
ValueCountFrequency (%)
173751.204337335 1
 
< 0.1%
188696.594570334 2
 
< 0.1%
189118.536648687 1
 
< 0.1%
189192.411433557 1
 
< 0.1%
189212.737535822 7
0.2%
189267.51449066 1
 
< 0.1%
189272.800655 1
 
< 0.1%
189282.58640148 5
0.1%
189286.651086068 2
 
< 0.1%
189315.310470024 1
 
< 0.1%
ValueCountFrequency (%)
196721.09277056 1
 
< 0.1%
196702.04987465 2
< 0.1%
196699.188309549 2
< 0.1%
196660.618569254 3
0.1%
196659.241554945 1
 
< 0.1%
196657.394765355 1
 
< 0.1%
196625.711759746 1
 
< 0.1%
196616.185721389 1
 
< 0.1%
196604.785527991 1
 
< 0.1%
196594.39064686 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1818
Distinct (%)48.6%
Missing429
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean450248.53
Minimum448116.64
Maximum458057.56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.8 KiB
2024-04-06T21:59:09.901703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum448116.64
5-th percentile448780.27
Q1449510.36
median450159.92
Q3450672.17
95-th percentile452667.98
Maximum458057.56
Range9940.9226
Interquartile range (IQR)1161.8098

Descriptive statistics

Standard deviation1059.7545
Coefficient of variation (CV)0.00235371
Kurtosis1.6524417
Mean450248.53
Median Absolute Deviation (MAD)595.44173
Skewness0.9966617
Sum1.6852803 × 109
Variance1123079.5
MonotonicityNot monotonic
2024-04-06T21:59:10.176704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
449831.533270543 26
 
0.6%
453017.867202928 15
 
0.4%
450340.205569676 13
 
0.3%
453090.149821248 12
 
0.3%
448487.374314355 12
 
0.3%
451328.488369456 11
 
0.3%
450075.489802 11
 
0.3%
448407.752664604 11
 
0.3%
448575.779442887 11
 
0.3%
451972.154018501 11
 
0.3%
Other values (1808) 3610
86.5%
(Missing) 429
 
10.3%
ValueCountFrequency (%)
448116.639953919 5
0.1%
448209.438670234 7
0.2%
448229.063825491 5
0.1%
448236.655548283 2
 
< 0.1%
448274.441478548 2
 
< 0.1%
448276.965250949 1
 
< 0.1%
448305.518618358 3
0.1%
448311.311124573 2
 
< 0.1%
448315.434477916 1
 
< 0.1%
448373.072155378 1
 
< 0.1%
ValueCountFrequency (%)
458057.562512175 1
 
< 0.1%
454136.901035 1
 
< 0.1%
453879.760075 1
 
< 0.1%
453872.42578746 3
0.1%
453764.989706 1
 
< 0.1%
453695.605496 1
 
< 0.1%
453685.545865753 2
< 0.1%
453647.349314742 1
 
< 0.1%
453647.190988422 1
 
< 0.1%
453618.0 1
 
< 0.1%

지정일자
Real number (ℝ)

MISSING 

Distinct1904
Distinct (%)67.3%
Missing1342
Missing (%)32.2%
Infinite0
Infinite (%)0.0%
Mean20088039
Minimum19600101
Maximum20220325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.8 KiB
2024-04-06T21:59:10.419363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19600101
5-th percentile19980303
Q120041021
median20090820
Q320140884
95-th percentile20190730
Maximum20220325
Range620224
Interquartile range (IQR)99863.25

Descriptive statistics

Standard deviation69615.73
Coefficient of variation (CV)0.0034655313
Kurtosis0.96107093
Mean20088039
Median Absolute Deviation (MAD)49985
Skewness-0.5627322
Sum5.6849152 × 1010
Variance4.8463499 × 109
MonotonicityNot monotonic
2024-04-06T21:59:10.672364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19900101 29
 
0.7%
19981103 15
 
0.4%
20090828 6
 
0.1%
19990120 6
 
0.1%
19900724 6
 
0.1%
20060322 6
 
0.1%
20021202 6
 
0.1%
20070607 6
 
0.1%
20090220 6
 
0.1%
19981121 6
 
0.1%
Other values (1894) 2738
65.6%
(Missing) 1342
32.2%
ValueCountFrequency (%)
19600101 1
 
< 0.1%
19660604 1
 
< 0.1%
19840125 1
 
< 0.1%
19860102 1
 
< 0.1%
19871012 1
 
< 0.1%
19890101 1
 
< 0.1%
19891116 1
 
< 0.1%
19900101 29
0.7%
19900205 1
 
< 0.1%
19900331 1
 
< 0.1%
ValueCountFrequency (%)
20220325 1
< 0.1%
20220316 1
< 0.1%
20220307 1
< 0.1%
20220303 2
< 0.1%
20220204 2
< 0.1%
20220107 1
< 0.1%
20211220 1
< 0.1%
20211216 1
< 0.1%
20211203 1
< 0.1%
20211202 1
< 0.1%

민원종류명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.7 KiB
2009년11월법개정전자료
1445 
<NA>
1343 
제7조의3제2항에따른경우
1118 
제7조의3제3항에따른경우
266 

Length

Max length14
Median length13
Mean length10.449185
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2009년11월법개정전자료
2nd row2009년11월법개정전자료
3rd row2009년11월법개정전자료
4th row2009년11월법개정전자료
5th row2009년11월법개정전자료

Common Values

ValueCountFrequency (%)
2009년11월법개정전자료 1445
34.6%
<NA> 1343
32.2%
제7조의3제2항에따른경우 1118
26.8%
제7조의3제3항에따른경우 266
 
6.4%

Length

2024-04-06T21:59:10.915915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T21:59:11.126583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2009년11월법개정전자료 1445
34.6%
na 1343
32.2%
제7조의3제2항에따른경우 1118
26.8%
제7조의3제3항에따른경우 266
 
6.4%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
0313000031301800560000020090831<NA>3폐업2폐업처리20151006<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 대흥로 177-3 (대흥동)04105담배가게2015-10-06 14:40:17I2018-08-31 23:59:59.0<NA>195135.479827450303.018844200908312009년11월법개정전자료
1313000031301800560000120151006<NA>3폐업2폐업처리201612122016010120160131<NA>02-711-6222<NA><NA><NA>서울특별시 마포구 광성로6길 22 (신수동)04096백광청과물직판장2016-12-12 10:40:50I2018-08-31 23:59:59.0<NA>194504.106753449623.764257201510062009년11월법개정전자료
2313000031301800560000320091001<NA>3폐업2폐업처리20151020<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 독막로2길 9 (합정동)04072성원2015-10-20 15:59:36I2018-08-31 23:59:59.0<NA>192401.948332449548.20566200910012009년11월법개정전자료
3313000018031301180561100020020304<NA>3폐업2폐업처리20090401<NA><NA><NA>334-6946<NA>121883서울특별시 마포구 합정동 91번지 11호서울특별시 마포구 토정로2길 6-9 (합정동)<NA>제일슈퍼2009-04-01 16:18:23I2018-08-31 23:59:59.0<NA>192225.763928449220.610111200203042009년11월법개정전자료
43130000108731301800560000119871012<NA>3폐업2폐업처리20160629<NA><NA><NA>02-717-2413<NA><NA><NA>서울특별시 마포구 마포대로11길 91 (염리동)04140대현마트2016-06-28 15:23:21I2018-08-31 23:59:59.0<NA>195450.049699449610.111387198710122009년11월법개정전자료
53130000171131301180561111119900724<NA>3폐업2폐업처리20160318<NA><NA><NA>333-0370<NA>121210서울특별시 마포구 서교동 327번지 11호서울특별시 마포구 와우산로 155 (서교동)<NA>타임스토어2016-03-17 13:01:27I2018-08-31 23:59:59.0<NA>193737.40776450291.097498199007242009년11월법개정전자료
63130000196631301180560000119660604202002134취소/말소/만료/정지/중지3직권취소<NA><NA><NA><NA>7167938<NA><NA>서울특별시 마포구 염리동 106번지 2 호서울특별시 마포구 백범로24길 19 (염리동)<NA>화남식품2020-02-14 09:48:47U2020-02-16 02:40:00.0<NA>195040.78739449306.827697196606042009년11월법개정전자료
73130000198031300990560000119800701<NA>3폐업2폐업처리20060809<NA><NA><NA>7160723<NA><NA>서울특별시 마포구 염리동 10번지 8호서울특별시 마포구 숭문16나길 20 (염리동)<NA>흥진사2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>195376.643877450305.982641<NA><NA>
83130000198131300990560033219810523<NA>3폐업2폐업처리20031224<NA><NA><NA>02<NA><NA>서울특별시 마포구 합정동 429번지 54호서울특별시 마포구 월드컵로7길 25 (합정동)<NA>한양상회2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>192031.639943450041.027326<NA><NA>
93130000198331300990560000119831217<NA>3폐업2폐업처리20060220<NA><NA><NA>1111 111<NA><NA>서울특별시 마포구 상수동 352번지 2호서울특별시 마포구 토정로9길 9 (상수동)<NA>한강식품2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>193216.915332449215.864683<NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
4162313000020243130255056000172024-03-06<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 482-178 난지2호서울특별시 마포구 마포나루길 216, 난지2호 (상암동)03900한강르네상스 난지2호점2024-03-12 09:23:34U2023-12-02 23:04:00.0<NA>189267.514491451403.485109<NA><NA>
4163313000020243130255056000182024-03-12<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 신수동 49-3서울특별시 마포구 독막로31길 12, 1층 (신수동)04096케이 할인마트2024-03-12 09:06:07I2023-12-02 23:04:00.0<NA>194561.529451449497.304712<NA><NA>
4164313000020243130255056000192024-03-18<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 35-1서울특별시 마포구 월드컵북로44길 49, 1층 (상암동)03930지에스25 상암본점2024-03-18 13:29:08I2023-12-02 22:00:00.0<NA>190631.655204452726.740427<NA><NA>
4165313000020243130255056000202024-03-21<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 1660 상암월드컵파크 7단지서울특별시 마포구 상암산로1길 92, 상가101호 (상암동, 상암월드컵파크 7단지)03903지에스(GS)25 상암7단지2024-03-21 16:49:53I2023-12-02 22:03:00.0<NA>189461.587934453279.956172<NA><NA>
4166313000020243130255056000212024-03-22<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 상암동 1647서울특별시 마포구 상암산로 34, B131호 (상암동)03909이마트24 상암디지털큐브점2024-03-22 16:31:42I2023-12-02 22:04:00.0<NA>190144.143204452658.525902<NA><NA>
4167313000020243130255056000222024-03-28<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 망원동 398-14 샬롬하우스서울특별시 마포구 희우정로12길 11, 1층 (망원동, 샬롬하우스)04015지에스(GS)25 망리단길2024-03-28 10:59:05I2023-12-02 21:00:00.0<NA>191417.268356450172.658073<NA><NA>
4168313000020243130255056000232024-03-28<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 공덕동 242-89서울특별시 마포구 만리재옛길 21, 1층 (공덕동)04210이정모바일2024-03-28 10:59:34I2023-12-02 21:00:00.0<NA>195979.237044449307.885514<NA><NA>
4169313000020243130255056000242024-04-02<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 아현동 700-6서울특별시 마포구 손기정로 25, 102호 (아현동)04198서울365VCPlus(가구단지점)2024-04-02 10:51:06I2023-12-04 00:04:00.0<NA>196530.474453450540.603799<NA><NA>
4170313000020243130255056000252024-04-03<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 창전동 145-17 광흥창역서울특별시 마포구 독막로 지하165, 광흥창역 (창전동)04099지에스25 S6광흥창역점2024-04-03 18:34:31I2023-12-04 00:05:00.0<NA>193961.576954449469.185406<NA><NA>
41713130000999931302250560000019600101201908284취소/말소/만료/정지/중지3직권취소<NA><NA><NA><NA><NA><NA><NA>서울특별시 마포구 염리동 148번지 32호서울특별시 마포구 숭문길 6 (염리동)04138우리식품2019-08-28 11:53:44I2019-08-30 02:22:32.0<NA>195117.261541449393.70909196001012009년11월법개정전자료