Overview

Dataset statistics

Number of variables27
Number of observations4098
Missing cells34980
Missing cells (%)31.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory908.6 KiB
Average record size in memory227.0 B

Variable types

Categorical7
Numeric5
Text9
DateTime3
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
Author관악구
URLhttps://data.seoul.go.kr/dataList/OA-19922/S/1/datasetView.do

Alerts

개방자치단체코드 has constant value ""Constant
인허가취소일자 has 3668 (89.5%) missing valuesMissing
폐업일자 has 1163 (28.4%) missing valuesMissing
휴업시작일자 has 3961 (96.7%) missing valuesMissing
휴업종료일자 has 3961 (96.7%) missing valuesMissing
재개업일자 has 4098 (100.0%) missing valuesMissing
전화번호 has 2271 (55.4%) missing valuesMissing
소재지면적 has 4098 (100.0%) missing valuesMissing
소재지우편번호 has 2844 (69.4%) missing valuesMissing
도로명주소 has 281 (6.9%) missing valuesMissing
도로명우편번호 has 2734 (66.7%) missing valuesMissing
업태구분명 has 4098 (100.0%) missing valuesMissing
좌표정보(X) has 122 (3.0%) missing valuesMissing
좌표정보(Y) has 122 (3.0%) missing valuesMissing
지정일자 has 1541 (37.6%) missing valuesMissing
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

Reproduction

Analysis started2024-04-17 19:15:58.906222
Analysis finished2024-04-17 19:15:59.855956
Duration0.95 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
3200000
4098 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3200000
2nd row3200000
3rd row3200000
4th row3200000
5th row3200000

Common Values

ValueCountFrequency (%)
3200000 4098
100.0%

Length

2024-04-18T04:15:59.900321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:15:59.988186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3200000 4098
100.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct4098
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0077058 × 1018
Minimum1.98032 × 1018
Maximum2.02432 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.1 KiB
2024-04-18T04:16:00.087001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.98032 × 1018
5-th percentile2.00032 × 1018
Q12.00032 × 1018
median2.00632 × 1018
Q32.01332 × 1018
95-th percentile2.02032 × 1018
Maximum2.02432 × 1018
Range4.4000014 × 1016
Interquartile range (IQR)1.3000011 × 1016

Descriptive statistics

Standard deviation7.0043985 × 1015
Coefficient of variation (CV)0.0034887574
Kurtosis-0.73903775
Mean2.0077058 × 1018
Median Absolute Deviation (MAD)6 × 1015
Skewness0.52105146
Sum3.3055588 × 1017
Variance4.9061599 × 1031
MonotonicityStrictly increasing
2024-04-18T04:16:00.195934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1980320008005610000 1
 
< 0.1%
2013320019105600026 1
 
< 0.1%
2010320019105600033 1
 
< 0.1%
2010320019105600034 1
 
< 0.1%
2010320019105600035 1
 
< 0.1%
2011320019105600001 1
 
< 0.1%
2011320019105600002 1
 
< 0.1%
2011320019105600003 1
 
< 0.1%
2011320019105600004 1
 
< 0.1%
2011320019105600005 1
 
< 0.1%
Other values (4088) 4088
99.8%
ValueCountFrequency (%)
1980320008005610000 1
< 0.1%
1980320013105600001 1
< 0.1%
1980320013105601000 1
< 0.1%
1989320008005600001 1
< 0.1%
1992320008005600001 1
< 0.1%
1993320010605601559 1
< 0.1%
1997320008005600001 1
< 0.1%
1999320008005601809 1
< 0.1%
2000320008005600001 1
< 0.1%
2000320008005600004 1
< 0.1%
ValueCountFrequency (%)
2024320022505600015 1
< 0.1%
2024320022505600014 1
< 0.1%
2024320022505600013 1
< 0.1%
2024320022505600012 1
< 0.1%
2024320022505600011 1
< 0.1%
2024320022505600010 1
< 0.1%
2024320022505600009 1
< 0.1%
2024320022505600008 1
< 0.1%
2024320022505600007 1
< 0.1%
2024320022505600006 1
< 0.1%
Distinct2059
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
2024-04-18T04:16:00.420103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.1083455
Min length8

Characters and Unicode

Total characters33228
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

Unique1308 ?
Unique (%)31.9%

Sample

1st row19801223
2nd row19801224
3rd row19801219
4th row19890401
5th row19920615
ValueCountFrequency (%)
19980101 918
 
22.4%
2020-09-04 9
 
0.2%
20041022 7
 
0.2%
20091015 6
 
0.1%
20010905 6
 
0.1%
20030121 6
 
0.1%
20031030 6
 
0.1%
20011023 6
 
0.1%
20201104 6
 
0.1%
20060922 5
 
0.1%
Other values (2049) 3123
76.2%
2024-04-18T04:16:00.759450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10681
32.1%
1 7272
21.9%
2 5562
16.7%
9 2883
 
8.7%
8 1744
 
5.2%
3 1178
 
3.5%
4 916
 
2.8%
5 863
 
2.6%
7 853
 
2.6%
6 832
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32784
98.7%
Dash Punctuation 444
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10681
32.6%
1 7272
22.2%
2 5562
17.0%
9 2883
 
8.8%
8 1744
 
5.3%
3 1178
 
3.6%
4 916
 
2.8%
5 863
 
2.6%
7 853
 
2.6%
6 832
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 444
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10681
32.1%
1 7272
21.9%
2 5562
16.7%
9 2883
 
8.7%
8 1744
 
5.2%
3 1178
 
3.5%
4 916
 
2.8%
5 863
 
2.6%
7 853
 
2.6%
6 832
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10681
32.1%
1 7272
21.9%
2 5562
16.7%
9 2883
 
8.7%
8 1744
 
5.2%
3 1178
 
3.5%
4 916
 
2.8%
5 863
 
2.6%
7 853
 
2.6%
6 832
 
2.5%

인허가취소일자
Real number (ℝ)

MISSING 

Distinct128
Distinct (%)29.8%
Missing3668
Missing (%)89.5%
Infinite0
Infinite (%)0.0%
Mean20132493
Minimum20010406
Maximum20221020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.1 KiB
2024-04-18T04:16:00.882873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20010406
5-th percentile20020710
Q120070946
median20140826
Q320201005
95-th percentile20201130
Maximum20221020
Range210614
Interquartile range (IQR)130058.5

Descriptive statistics

Standard deviation69702.679
Coefficient of variation (CV)0.0034621981
Kurtosis-1.1410733
Mean20132493
Median Absolute Deviation (MAD)60179
Skewness-0.54577513
Sum8.6569719 × 109
Variance4.8584634 × 109
MonotonicityNot monotonic
2024-04-18T04:16:00.994195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020710 31
 
0.8%
20201119 30
 
0.7%
20200915 29
 
0.7%
20201109 19
 
0.5%
20201020 18
 
0.4%
20140826 18
 
0.4%
20101025 17
 
0.4%
20201005 15
 
0.4%
20010914 14
 
0.3%
20201130 12
 
0.3%
Other values (118) 227
 
5.5%
(Missing) 3668
89.5%
ValueCountFrequency (%)
20010406 3
 
0.1%
20010418 2
 
< 0.1%
20010914 14
0.3%
20020304 1
 
< 0.1%
20020710 31
0.8%
20020716 7
 
0.2%
20020726 4
 
0.1%
20020801 1
 
< 0.1%
20020802 1
 
< 0.1%
20021121 2
 
< 0.1%
ValueCountFrequency (%)
20221020 1
< 0.1%
20220825 1
< 0.1%
20220530 1
< 0.1%
20220526 1
< 0.1%
20220506 1
< 0.1%
20220425 2
< 0.1%
20210812 1
< 0.1%
20210712 1
< 0.1%
20210706 1
< 0.1%
20210705 1
< 0.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
3
2935 
1
706 
4
453 
2
 
4

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 2935
71.6%
1 706
 
17.2%
4 453
 
11.1%
2 4
 
0.1%

Length

2024-04-18T04:16:01.091113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:16:01.171389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 2935
71.6%
1 706
 
17.2%
4 453
 
11.1%
2 4
 
0.1%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
폐업
2935 
영업/정상
706 
취소/말소/만료/정지/중지
453 
휴업
 
4

Length

Max length14
Median length2
Mean length3.8433382
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 2935
71.6%
영업/정상 706
 
17.2%
취소/말소/만료/정지/중지 453
 
11.1%
휴업 4
 
0.1%

Length

2024-04-18T04:16:01.265937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:16:01.353323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 2935
71.6%
영업/정상 706
 
17.2%
취소/말소/만료/정지/중지 453
 
11.1%
휴업 4
 
0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
2
2935 
0
706 
5
 
266
3
 
187
1
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 2935
71.6%
0 706
 
17.2%
5 266
 
6.5%
3 187
 
4.6%
1 4
 
0.1%

Length

2024-04-18T04:16:01.459617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:16:01.543648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 2935
71.6%
0 706
 
17.2%
5 266
 
6.5%
3 187
 
4.6%
1 4
 
0.1%
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
폐업처리
2935 
정상영업
706 
지정취소
 
266
직권취소
 
187
휴업처리
 
4

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업처리 2935
71.6%
정상영업 706
 
17.2%
지정취소 266
 
6.5%
직권취소 187
 
4.6%
휴업처리 4
 
0.1%

Length

2024-04-18T04:16:01.629105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:16:01.708164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업처리 2935
71.6%
정상영업 706
 
17.2%
지정취소 266
 
6.5%
직권취소 187
 
4.6%
휴업처리 4
 
0.1%

폐업일자
Date

MISSING 

Distinct2187
Distinct (%)74.5%
Missing1163
Missing (%)28.4%
Memory size32.1 KiB
Minimum2000-12-29 00:00:00
Maximum2024-04-11 00:00:00
2024-04-18T04:16:01.809179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:16:01.917511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Text

MISSING 

Distinct123
Distinct (%)89.8%
Missing3961
Missing (%)96.7%
Memory size32.1 KiB
2024-04-18T04:16:02.156882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2627737
Min length8

Characters and Unicode

Total characters1132
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

Unique112 ?
Unique (%)81.8%

Sample

1st row20081008
2nd row20080325
3rd row20110704
4th row20210717
5th row20080202
ValueCountFrequency (%)
20170201 3
 
2.2%
20121128 3
 
2.2%
20180201 3
 
2.2%
20110704 2
 
1.5%
20180416 2
 
1.5%
20180424 2
 
1.5%
20140225 2
 
1.5%
20150629 2
 
1.5%
20150720 2
 
1.5%
20110224 2
 
1.5%
Other values (113) 114
83.2%
2024-04-18T04:16:02.534708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 339
29.9%
2 272
24.0%
1 233
20.6%
3 43
 
3.8%
7 41
 
3.6%
8 40
 
3.5%
4 36
 
3.2%
- 36
 
3.2%
9 32
 
2.8%
6 30
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1096
96.8%
Dash Punctuation 36
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 339
30.9%
2 272
24.8%
1 233
21.3%
3 43
 
3.9%
7 41
 
3.7%
8 40
 
3.6%
4 36
 
3.3%
9 32
 
2.9%
6 30
 
2.7%
5 30
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1132
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 339
29.9%
2 272
24.0%
1 233
20.6%
3 43
 
3.8%
7 41
 
3.6%
8 40
 
3.5%
4 36
 
3.2%
- 36
 
3.2%
9 32
 
2.8%
6 30
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 339
29.9%
2 272
24.0%
1 233
20.6%
3 43
 
3.8%
7 41
 
3.6%
8 40
 
3.5%
4 36
 
3.2%
- 36
 
3.2%
9 32
 
2.8%
6 30
 
2.7%

휴업종료일자
Text

MISSING 

Distinct122
Distinct (%)89.1%
Missing3961
Missing (%)96.7%
Memory size32.1 KiB
2024-04-18T04:16:02.803951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length8.2627737
Min length8

Characters and Unicode

Total characters1132
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

Unique110 ?
Unique (%)80.3%

Sample

1st row20081107
2nd row20080725
3rd row20110803
4th row20210815
5th row20080301
ValueCountFrequency (%)
20180228 3
 
2.2%
20121227 3
 
2.2%
20170228 3
 
2.2%
20140324 2
 
1.5%
20180811 2
 
1.5%
20140630 2
 
1.5%
20110323 2
 
1.5%
20180515 2
 
1.5%
20150819 2
 
1.5%
20120630 2
 
1.5%
Other values (112) 114
83.2%
2024-04-18T04:16:03.175675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 326
28.8%
2 281
24.8%
1 215
19.0%
3 72
 
6.4%
8 57
 
5.0%
4 37
 
3.3%
- 36
 
3.2%
5 32
 
2.8%
7 31
 
2.7%
9 24
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1096
96.8%
Dash Punctuation 36
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 326
29.7%
2 281
25.6%
1 215
19.6%
3 72
 
6.6%
8 57
 
5.2%
4 37
 
3.4%
5 32
 
2.9%
7 31
 
2.8%
9 24
 
2.2%
6 21
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1132
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 326
28.8%
2 281
24.8%
1 215
19.0%
3 72
 
6.4%
8 57
 
5.0%
4 37
 
3.3%
- 36
 
3.2%
5 32
 
2.8%
7 31
 
2.7%
9 24
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 326
28.8%
2 281
24.8%
1 215
19.0%
3 72
 
6.4%
8 57
 
5.0%
4 37
 
3.3%
- 36
 
3.2%
5 32
 
2.8%
7 31
 
2.7%
9 24
 
2.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4098
Missing (%)100.0%
Memory size36.1 KiB

전화번호
Text

MISSING 

Distinct1580
Distinct (%)86.5%
Missing2271
Missing (%)55.4%
Memory size32.1 KiB
2024-04-18T04:16:03.414806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length9.5188834
Min length1

Characters and Unicode

Total characters17391
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

Unique1400 ?
Unique (%)76.6%

Sample

1st row02 8992232
2nd row887-5190
3rd row863-7775
4th row02 8387963
5th row02 8658223
ValueCountFrequency (%)
02 1126
37.3%
1577-0711 15
 
0.5%
031 10
 
0.3%
2671-1188 9
 
0.3%
8888888 7
 
0.2%
02-2225-6392 6
 
0.2%
886 5
 
0.2%
1111111 5
 
0.2%
8893607 5
 
0.2%
8721786 4
 
0.1%
Other values (1595) 1825
60.5%
2024-04-18T04:16:03.746674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 3186
18.3%
2 2374
13.7%
0 2318
13.3%
7 1509
8.7%
5 1217
 
7.0%
1195
 
6.9%
6 1136
 
6.5%
3 1077
 
6.2%
1 1036
 
6.0%
4 925
 
5.3%
Other values (5) 1418
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15584
89.6%
Space Separator 1195
 
6.9%
Dash Punctuation 608
 
3.5%
Close Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 3186
20.4%
2 2374
15.2%
0 2318
14.9%
7 1509
9.7%
5 1217
 
7.8%
6 1136
 
7.3%
3 1077
 
6.9%
1 1036
 
6.6%
4 925
 
5.9%
9 806
 
5.2%
Space Separator
ValueCountFrequency (%)
1195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 608
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 17391
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
8 3186
18.3%
2 2374
13.7%
0 2318
13.3%
7 1509
8.7%
5 1217
 
7.0%
1195
 
6.9%
6 1136
 
6.5%
3 1077
 
6.2%
1 1036
 
6.0%
4 925
 
5.3%
Other values (5) 1418
8.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 17391
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8 3186
18.3%
2 2374
13.7%
0 2318
13.3%
7 1509
8.7%
5 1217
 
7.0%
1195
 
6.9%
6 1136
 
6.5%
3 1077
 
6.2%
1 1036
 
6.0%
4 925
 
5.3%
Other values (5) 1418
8.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4098
Missing (%)100.0%
Memory size36.1 KiB

소재지우편번호
Text

MISSING 

Distinct207
Distinct (%)16.5%
Missing2844
Missing (%)69.4%
Memory size32.1 KiB
2024-04-18T04:16:03.985862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0215311
Min length5

Characters and Unicode

Total characters7551
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

Unique81 ?
Unique (%)6.5%

Sample

1st row151897
2nd row000
3rd row000
4th row151015
5th row151863
ValueCountFrequency (%)
151050 162
 
12.9%
151015 153
 
12.2%
151010 91
 
7.3%
151891 19
 
1.5%
151895 18
 
1.4%
151843 14
 
1.1%
151856 14
 
1.1%
151830 14
 
1.1%
151858 14
 
1.1%
151811 13
 
1.0%
Other values (196) 742
59.2%
2024-04-18T04:16:04.320111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2915
38.6%
5 1753
23.2%
0 990
 
13.1%
8 785
 
10.4%
9 249
 
3.3%
7 215
 
2.8%
3 162
 
2.1%
2 162
 
2.1%
4 139
 
1.8%
6 114
 
1.5%
Other values (2) 67
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7484
99.1%
Space Separator 35
 
0.5%
Dash Punctuation 32
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2915
38.9%
5 1753
23.4%
0 990
 
13.2%
8 785
 
10.5%
9 249
 
3.3%
7 215
 
2.9%
3 162
 
2.2%
2 162
 
2.2%
4 139
 
1.9%
6 114
 
1.5%
Space Separator
ValueCountFrequency (%)
35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7551
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2915
38.6%
5 1753
23.2%
0 990
 
13.1%
8 785
 
10.4%
9 249
 
3.3%
7 215
 
2.8%
3 162
 
2.1%
2 162
 
2.1%
4 139
 
1.8%
6 114
 
1.5%
Other values (2) 67
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2915
38.6%
5 1753
23.2%
0 990
 
13.1%
8 785
 
10.4%
9 249
 
3.3%
7 215
 
2.8%
3 162
 
2.1%
2 162
 
2.1%
4 139
 
1.8%
6 114
 
1.5%
Other values (2) 67
 
0.9%
Distinct3541
Distinct (%)86.8%
Missing18
Missing (%)0.4%
Memory size32.1 KiB
2024-04-18T04:16:04.618671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length48
Mean length26.007353
Min length17

Characters and Unicode

Total characters106110
Distinct characters309
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3125 ?
Unique (%)76.6%

Sample

1st row서울특별시 관악구 신림동 484번지 35호
2nd row서울특별시 관악구 대학동 1559번지 20호
3rd row서울특별시 관악구 신림동 704번지 42호 26통 2반
4th row서울특별시 관악구 신림동 산104번지 7호
5th row서울특별시 관악구 신림동 654번지 39호
ValueCountFrequency (%)
서울특별시 4080
18.2%
관악구 4079
18.2%
신림동 1930
 
8.6%
봉천동 1425
 
6.4%
746
 
3.3%
1층 492
 
2.2%
1호 428
 
1.9%
2호 122
 
0.5%
남현동 114
 
0.5%
1 111
 
0.5%
Other values (2062) 8884
39.6%
2024-04-18T04:16:05.028783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
22644
21.3%
1 5865
 
5.5%
4215
 
4.0%
4188
 
3.9%
4126
 
3.9%
4118
 
3.9%
4115
 
3.9%
4111
 
3.9%
4087
 
3.9%
4086
 
3.9%
Other values (299) 44555
42.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60576
57.1%
Space Separator 22644
 
21.3%
Decimal Number 22306
 
21.0%
Dash Punctuation 296
 
0.3%
Uppercase Letter 118
 
0.1%
Other Punctuation 54
 
0.1%
Close Punctuation 51
 
< 0.1%
Open Punctuation 51
 
< 0.1%
Math Symbol 11
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4215
 
7.0%
4188
 
6.9%
4126
 
6.8%
4118
 
6.8%
4115
 
6.8%
4111
 
6.8%
4087
 
6.7%
4086
 
6.7%
4081
 
6.7%
4081
 
6.7%
Other values (267) 19368
32.0%
Uppercase Letter
ValueCountFrequency (%)
B 71
60.2%
A 20
 
16.9%
K 7
 
5.9%
S 5
 
4.2%
D 4
 
3.4%
T 3
 
2.5%
C 2
 
1.7%
G 2
 
1.7%
M 2
 
1.7%
I 1
 
0.8%
Decimal Number
ValueCountFrequency (%)
1 5865
26.3%
2 2378
10.7%
6 2238
 
10.0%
5 2158
 
9.7%
4 2002
 
9.0%
3 1804
 
8.1%
0 1713
 
7.7%
7 1410
 
6.3%
8 1399
 
6.3%
9 1339
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 49
90.7%
@ 3
 
5.6%
/ 2
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
e 1
50.0%
a 1
50.0%
Space Separator
ValueCountFrequency (%)
22644
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 296
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Math Symbol
ValueCountFrequency (%)
~ 11
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60576
57.1%
Common 45414
42.8%
Latin 120
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4215
 
7.0%
4188
 
6.9%
4126
 
6.8%
4118
 
6.8%
4115
 
6.8%
4111
 
6.8%
4087
 
6.7%
4086
 
6.7%
4081
 
6.7%
4081
 
6.7%
Other values (267) 19368
32.0%
Common
ValueCountFrequency (%)
22644
49.9%
1 5865
 
12.9%
2 2378
 
5.2%
6 2238
 
4.9%
5 2158
 
4.8%
4 2002
 
4.4%
3 1804
 
4.0%
0 1713
 
3.8%
7 1410
 
3.1%
8 1399
 
3.1%
Other values (9) 1803
 
4.0%
Latin
ValueCountFrequency (%)
B 71
59.2%
A 20
 
16.7%
K 7
 
5.8%
S 5
 
4.2%
D 4
 
3.3%
T 3
 
2.5%
C 2
 
1.7%
G 2
 
1.7%
M 2
 
1.7%
e 1
 
0.8%
Other values (3) 3
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60576
57.1%
ASCII 45534
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22644
49.7%
1 5865
 
12.9%
2 2378
 
5.2%
6 2238
 
4.9%
5 2158
 
4.7%
4 2002
 
4.4%
3 1804
 
4.0%
0 1713
 
3.8%
7 1410
 
3.1%
8 1399
 
3.1%
Other values (22) 1923
 
4.2%
Hangul
ValueCountFrequency (%)
4215
 
7.0%
4188
 
6.9%
4126
 
6.8%
4118
 
6.8%
4115
 
6.8%
4111
 
6.8%
4087
 
6.7%
4086
 
6.7%
4081
 
6.7%
4081
 
6.7%
Other values (267) 19368
32.0%

도로명주소
Text

MISSING 

Distinct2696
Distinct (%)70.6%
Missing281
Missing (%)6.9%
Memory size32.1 KiB
2024-04-18T04:16:05.296452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length66
Median length56
Mean length27.446162
Min length17

Characters and Unicode

Total characters104762
Distinct characters323
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1999 ?
Unique (%)52.4%

Sample

1st row서울특별시 관악구 남부순환로163길 13 (신림동)
2nd row서울특별시 관악구 호암로20길 1 (신림동)
3rd row서울특별시 관악구 난곡로31길 15 (신림동)
4th row서울특별시 관악구 난곡로16길 19 (신림동)
5th row서울특별시 관악구 난곡로63길 60 (신림동)
ValueCountFrequency (%)
서울특별시 3817
18.2%
관악구 3805
18.1%
신림동 1915
 
9.1%
봉천동 1376
 
6.6%
1층 781
 
3.7%
남부순환로 336
 
1.6%
신림로 199
 
0.9%
봉천로 148
 
0.7%
관악로 145
 
0.7%
난곡로 135
 
0.6%
Other values (1781) 8321
39.7%
2024-04-18T04:16:05.676186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
17221
 
16.4%
1 4788
 
4.6%
4214
 
4.0%
4116
 
3.9%
4031
 
3.8%
3923
 
3.7%
3863
 
3.7%
3860
 
3.7%
) 3847
 
3.7%
( 3847
 
3.7%
Other values (313) 51052
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 62134
59.3%
Space Separator 17221
 
16.4%
Decimal Number 15430
 
14.7%
Close Punctuation 3847
 
3.7%
Open Punctuation 3847
 
3.7%
Other Punctuation 1896
 
1.8%
Dash Punctuation 253
 
0.2%
Uppercase Letter 120
 
0.1%
Math Symbol 13
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4214
 
6.8%
4116
 
6.6%
4031
 
6.5%
3923
 
6.3%
3863
 
6.2%
3860
 
6.2%
3838
 
6.2%
3818
 
6.1%
3817
 
6.1%
2881
 
4.6%
Other values (284) 23773
38.3%
Decimal Number
ValueCountFrequency (%)
1 4788
31.0%
2 2068
13.4%
3 1667
 
10.8%
4 1242
 
8.0%
6 1151
 
7.5%
0 1147
 
7.4%
5 1117
 
7.2%
7 814
 
5.3%
8 750
 
4.9%
9 686
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
B 78
65.0%
A 14
 
11.7%
K 8
 
6.7%
S 5
 
4.2%
T 4
 
3.3%
C 3
 
2.5%
D 3
 
2.5%
M 2
 
1.7%
G 2
 
1.7%
P 1
 
0.8%
Other Punctuation
ValueCountFrequency (%)
, 1893
99.8%
@ 2
 
0.1%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
17221
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3847
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3847
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 253
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 62134
59.3%
Common 42507
40.6%
Latin 121
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4214
 
6.8%
4116
 
6.6%
4031
 
6.5%
3923
 
6.3%
3863
 
6.2%
3860
 
6.2%
3838
 
6.2%
3818
 
6.1%
3817
 
6.1%
2881
 
4.6%
Other values (284) 23773
38.3%
Common
ValueCountFrequency (%)
17221
40.5%
1 4788
 
11.3%
) 3847
 
9.1%
( 3847
 
9.1%
2 2068
 
4.9%
, 1893
 
4.5%
3 1667
 
3.9%
4 1242
 
2.9%
6 1151
 
2.7%
0 1147
 
2.7%
Other values (8) 3636
 
8.6%
Latin
ValueCountFrequency (%)
B 78
64.5%
A 14
 
11.6%
K 8
 
6.6%
S 5
 
4.1%
T 4
 
3.3%
C 3
 
2.5%
D 3
 
2.5%
M 2
 
1.7%
G 2
 
1.7%
e 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 62134
59.3%
ASCII 42628
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17221
40.4%
1 4788
 
11.2%
) 3847
 
9.0%
( 3847
 
9.0%
2 2068
 
4.9%
, 1893
 
4.4%
3 1667
 
3.9%
4 1242
 
2.9%
6 1151
 
2.7%
0 1147
 
2.7%
Other values (19) 3757
 
8.8%
Hangul
ValueCountFrequency (%)
4214
 
6.8%
4116
 
6.6%
4031
 
6.5%
3923
 
6.3%
3863
 
6.2%
3860
 
6.2%
3838
 
6.2%
3818
 
6.1%
3817
 
6.1%
2881
 
4.6%
Other values (284) 23773
38.3%

도로명우편번호
Text

MISSING 

Distinct287
Distinct (%)21.0%
Missing2734
Missing (%)66.7%
Memory size32.1 KiB
2024-04-18T04:16:05.947203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4589443
Min length5

Characters and Unicode

Total characters7446
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

Unique82 ?
Unique (%)6.0%

Sample

1st row151015
2nd row151863
3rd row151881
4th row151881
5th row151861
ValueCountFrequency (%)
151015 154
 
11.3%
151050 123
 
9.0%
08793 21
 
1.5%
08826 19
 
1.4%
08819 16
 
1.2%
08788 14
 
1.0%
08784 14
 
1.0%
08813 14
 
1.0%
08852 13
 
1.0%
151891 12
 
0.9%
Other values (277) 964
70.7%
2024-04-18T04:16:06.568641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1600
21.5%
0 1461
19.6%
8 1461
19.6%
5 1151
15.5%
7 693
9.3%
9 246
 
3.3%
6 213
 
2.9%
4 209
 
2.8%
3 199
 
2.7%
2 191
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7424
99.7%
Dash Punctuation 22
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1600
21.6%
0 1461
19.7%
8 1461
19.7%
5 1151
15.5%
7 693
9.3%
9 246
 
3.3%
6 213
 
2.9%
4 209
 
2.8%
3 199
 
2.7%
2 191
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7446
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1600
21.5%
0 1461
19.6%
8 1461
19.6%
5 1151
15.5%
7 693
9.3%
9 246
 
3.3%
6 213
 
2.9%
4 209
 
2.8%
3 199
 
2.7%
2 191
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1600
21.5%
0 1461
19.6%
8 1461
19.6%
5 1151
15.5%
7 693
9.3%
9 246
 
3.3%
6 213
 
2.9%
4 209
 
2.8%
3 199
 
2.7%
2 191
 
2.6%
Distinct3163
Distinct (%)77.2%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
2024-04-18T04:16:06.788700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length6.6337238
Min length1

Characters and Unicode

Total characters27185
Distinct characters660
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2689 ?
Unique (%)65.6%

Sample

1st row현슈퍼
2nd row현대식품
3rd row충남슈퍼
4th row새충복슈퍼
5th row충남슈퍼
ValueCountFrequency (%)
씨유 198
 
3.9%
gs25 106
 
2.1%
세븐일레븐 104
 
2.0%
주)코리아세븐 55
 
1.1%
지에스25 55
 
1.1%
미니스톱 40
 
0.8%
이마트24 34
 
0.7%
전자담배 20
 
0.4%
지에스(gs)25 20
 
0.4%
훼미리마트 19
 
0.4%
Other values (3093) 4464
87.3%
2024-04-18T04:16:07.110284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1177
 
4.3%
1031
 
3.8%
861
 
3.2%
813
 
3.0%
688
 
2.5%
548
 
2.0%
546
 
2.0%
516
 
1.9%
497
 
1.8%
2 459
 
1.7%
Other values (650) 20049
73.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23478
86.4%
Space Separator 1041
 
3.8%
Decimal Number 1002
 
3.7%
Uppercase Letter 904
 
3.3%
Close Punctuation 307
 
1.1%
Open Punctuation 305
 
1.1%
Lowercase Letter 113
 
0.4%
Other Punctuation 18
 
0.1%
Dash Punctuation 16
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1177
 
5.0%
861
 
3.7%
813
 
3.5%
688
 
2.9%
548
 
2.3%
546
 
2.3%
516
 
2.2%
497
 
2.1%
430
 
1.8%
417
 
1.8%
Other values (581) 16985
72.3%
Uppercase Letter
ValueCountFrequency (%)
S 280
31.0%
G 279
30.9%
C 68
 
7.5%
U 49
 
5.4%
K 23
 
2.5%
A 20
 
2.2%
E 20
 
2.2%
L 19
 
2.1%
T 19
 
2.1%
M 16
 
1.8%
Other values (15) 111
 
12.3%
Lowercase Letter
ValueCountFrequency (%)
e 19
16.8%
a 12
10.6%
c 9
 
8.0%
o 8
 
7.1%
t 8
 
7.1%
s 7
 
6.2%
l 6
 
5.3%
y 6
 
5.3%
p 6
 
5.3%
r 6
 
5.3%
Other values (11) 26
23.0%
Decimal Number
ValueCountFrequency (%)
2 459
45.8%
5 397
39.6%
4 80
 
8.0%
3 20
 
2.0%
6 15
 
1.5%
1 13
 
1.3%
7 7
 
0.7%
8 5
 
0.5%
9 3
 
0.3%
0 3
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 9
50.0%
, 3
 
16.7%
? 2
 
11.1%
& 1
 
5.6%
! 1
 
5.6%
: 1
 
5.6%
1
 
5.6%
Space Separator
ValueCountFrequency (%)
1031
99.0%
  10
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 307
100.0%
Open Punctuation
ValueCountFrequency (%)
( 305
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23475
86.4%
Common 2690
 
9.9%
Latin 1017
 
3.7%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1177
 
5.0%
861
 
3.7%
813
 
3.5%
688
 
2.9%
548
 
2.3%
546
 
2.3%
516
 
2.2%
497
 
2.1%
430
 
1.8%
417
 
1.8%
Other values (578) 16982
72.3%
Latin
ValueCountFrequency (%)
S 280
27.5%
G 279
27.4%
C 68
 
6.7%
U 49
 
4.8%
K 23
 
2.3%
A 20
 
2.0%
E 20
 
2.0%
L 19
 
1.9%
T 19
 
1.9%
e 19
 
1.9%
Other values (36) 221
21.7%
Common
ValueCountFrequency (%)
1031
38.3%
2 459
17.1%
5 397
 
14.8%
) 307
 
11.4%
( 305
 
11.3%
4 80
 
3.0%
3 20
 
0.7%
- 16
 
0.6%
6 15
 
0.6%
1 13
 
0.5%
Other values (13) 47
 
1.7%
Han
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23475
86.4%
ASCII 3696
 
13.6%
None 11
 
< 0.1%
CJK 3
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1177
 
5.0%
861
 
3.7%
813
 
3.5%
688
 
2.9%
548
 
2.3%
546
 
2.3%
516
 
2.2%
497
 
2.1%
430
 
1.8%
417
 
1.8%
Other values (578) 16982
72.3%
ASCII
ValueCountFrequency (%)
1031
27.9%
2 459
12.4%
5 397
 
10.7%
) 307
 
8.3%
( 305
 
8.3%
S 280
 
7.6%
G 279
 
7.5%
4 80
 
2.2%
C 68
 
1.8%
U 49
 
1.3%
Other values (57) 441
11.9%
None
ValueCountFrequency (%)
  10
90.9%
1
 
9.1%
CJK
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Distinct2910
Distinct (%)71.0%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
Minimum2007-07-03 14:56:45
Maximum2024-04-12 10:13:51
2024-04-18T04:16:07.236667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:16:07.350392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
I
3290 
U
808 

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 3290
80.3%
U 808
 
19.7%

Length

2024-04-18T04:16:07.443580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:16:07.515437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3290
80.3%
u 808
 
19.7%
Distinct611
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-04 00:04:00
2024-04-18T04:16:07.597673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:16:07.704130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4098
Missing (%)100.0%
Memory size36.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1852
Distinct (%)46.6%
Missing122
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean194368.39
Minimum191123.21
Maximum198793.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.1 KiB
2024-04-18T04:16:07.812990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum191123.21
5-th percentile192074.91
Q1193212.96
median194254.89
Q3195521.6
95-th percentile196966.68
Maximum198793.03
Range7669.813
Interquartile range (IQR)2308.6341

Descriptive statistics

Standard deviation1538.7068
Coefficient of variation (CV)0.0079164456
Kurtosis-0.52435743
Mean194368.39
Median Absolute Deviation (MAD)1154.4064
Skewness0.26535477
Sum7.7280871 × 108
Variance2367618.5
MonotonicityNot monotonic
2024-04-18T04:16:07.921721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196139.864969792 31
 
0.8%
193746.833837509 16
 
0.4%
193957.944323928 12
 
0.3%
193578.742465284 12
 
0.3%
195045.515107949 12
 
0.3%
192861.778605245 11
 
0.3%
194879.596231677 10
 
0.2%
192766.551228288 10
 
0.2%
195337.004655221 9
 
0.2%
194255.560048876 9
 
0.2%
Other values (1842) 3844
93.8%
(Missing) 122
 
3.0%
ValueCountFrequency (%)
191123.213681016 1
 
< 0.1%
191126.690175551 1
 
< 0.1%
191182.000480527 2
< 0.1%
191193.948424131 2
< 0.1%
191196.893533157 1
 
< 0.1%
191228.411082685 2
< 0.1%
191237.262245059 1
 
< 0.1%
191264.654358325 2
< 0.1%
191268.385525368 3
0.1%
191270.737527797 2
< 0.1%
ValueCountFrequency (%)
198793.026677087 1
 
< 0.1%
198374.473281221 1
 
< 0.1%
198351.367148646 2
 
< 0.1%
198315.174254041 9
0.2%
198297.240031378 1
 
< 0.1%
198284.487350496 2
 
< 0.1%
198284.078546351 2
 
< 0.1%
198279.354654344 3
 
0.1%
198278.931088754 2
 
< 0.1%
198274.871752809 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1853
Distinct (%)46.6%
Missing122
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean441872.76
Minimum439023.17
Maximum443547.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.1 KiB
2024-04-18T04:16:08.031099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum439023.17
5-th percentile440379.98
Q1441353.06
median442004.18
Q3442492.23
95-th percentile443013.18
Maximum443547.05
Range4523.8826
Interquartile range (IQR)1139.1766

Descriptive statistics

Standard deviation816.59285
Coefficient of variation (CV)0.0018480271
Kurtosis0.2473216
Mean441872.76
Median Absolute Deviation (MAD)555.68022
Skewness-0.64754902
Sum1.7568861 × 109
Variance666823.89
MonotonicityNot monotonic
2024-04-18T04:16:08.142743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
439023.167125842 31
 
0.8%
442510.775085572 16
 
0.4%
441437.774867372 12
 
0.3%
443547.049696825 12
 
0.3%
443011.455007816 12
 
0.3%
442492.234475461 11
 
0.3%
442483.131081868 10
 
0.2%
442362.093852471 10
 
0.2%
440362.815100863 9
 
0.2%
441476.617056563 9
 
0.2%
Other values (1843) 3844
93.8%
(Missing) 122
 
3.0%
ValueCountFrequency (%)
439023.167125842 31
0.8%
439483.359820012 1
 
< 0.1%
439488.324186803 1
 
< 0.1%
439515.769575137 1
 
< 0.1%
439687.506761882 2
 
< 0.1%
439787.715563055 2
 
< 0.1%
439796.106926076 1
 
< 0.1%
439797.323116345 1
 
< 0.1%
439809.669640911 3
 
0.1%
439816.999224208 3
 
0.1%
ValueCountFrequency (%)
443547.049696825 12
0.3%
443507.348695928 1
 
< 0.1%
443437.692580028 5
0.1%
443381.921429128 1
 
< 0.1%
443381.288614319 1
 
< 0.1%
443369.29506954 1
 
< 0.1%
443344.373525343 1
 
< 0.1%
443341.379446435 4
 
0.1%
443332.522660073 4
 
0.1%
443325.157422878 1
 
< 0.1%

지정일자
Real number (ℝ)

MISSING 

Distinct1528
Distinct (%)59.8%
Missing1541
Missing (%)37.6%
Infinite0
Infinite (%)0.0%
Mean20086786
Minimum19801219
Maximum20220325
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size36.1 KiB
2024-04-18T04:16:08.247969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19801219
5-th percentile19980101
Q120040603
median20090825
Q320140501
95-th percentile20190543
Maximum20220325
Range419106
Interquartile range (IQR)99898

Descriptive statistics

Standard deviation66221.252
Coefficient of variation (CV)0.003296757
Kurtosis-0.68845155
Mean20086786
Median Absolute Deviation (MAD)49891
Skewness-0.16657215
Sum5.1361912 × 1010
Variance4.3852542 × 109
MonotonicityNot monotonic
2024-04-18T04:16:08.356912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19980101 344
 
8.4%
20201104 6
 
0.1%
20091015 6
 
0.1%
20090813 5
 
0.1%
20120702 5
 
0.1%
20110103 5
 
0.1%
20031030 5
 
0.1%
20100407 5
 
0.1%
20060921 4
 
0.1%
20111111 4
 
0.1%
Other values (1518) 2168
52.9%
(Missing) 1541
37.6%
ValueCountFrequency (%)
19801219 1
 
< 0.1%
19801224 1
 
< 0.1%
19920620 1
 
< 0.1%
19931127 1
 
< 0.1%
19980101 344
8.4%
19981113 1
 
< 0.1%
19981126 1
 
< 0.1%
19981215 1
 
< 0.1%
19990105 1
 
< 0.1%
19990130 1
 
< 0.1%
ValueCountFrequency (%)
20220325 1
 
< 0.1%
20220310 1
 
< 0.1%
20220223 1
 
< 0.1%
20220217 3
0.1%
20220215 1
 
< 0.1%
20220211 1
 
< 0.1%
20220210 1
 
< 0.1%
20220126 1
 
< 0.1%
20220124 1
 
< 0.1%
20220110 1
 
< 0.1%

민원종류명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size32.1 KiB
<NA>
1541 
제7조의3제2항에따른경우
1251 
2009년11월법개정전자료
1189 
제7조의3제3항에따른경우
 
117

Length

Max length14
Median length13
Mean length9.9058077
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row2009년11월법개정전자료
3rd row2009년11월법개정전자료
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1541
37.6%
제7조의3제2항에따른경우 1251
30.5%
2009년11월법개정전자료 1189
29.0%
제7조의3제3항에따른경우 117
 
2.9%

Length

2024-04-18T04:16:08.453123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:16:08.531883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1541
37.6%
제7조의3제2항에따른경우 1251
30.5%
2009년11월법개정전자료 1189
29.0%
제7조의3제3항에따른경우 117
 
2.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
03200000198032000800561000019801223<NA>3폐업2폐업처리20050829<NA><NA><NA>02 8992232<NA><NA>서울특별시 관악구 신림동 484번지 35호서울특별시 관악구 남부순환로163길 13 (신림동)<NA>현슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>192977.874673442473.745484<NA><NA>
13200000198032001310560000119801224<NA>3폐업2폐업처리20110718<NA><NA><NA>887-5190<NA>151897서울특별시 관악구 대학동 1559번지 20호서울특별시 관악구 호암로20길 1 (신림동)<NA>현대식품2011-07-18 11:17:57I2018-08-31 23:59:59.0<NA>193929.848705440626.328356198012242009년11월법개정전자료
23200000198032001310560100019801219<NA>3폐업2폐업처리20100311<NA><NA><NA>863-7775<NA>000서울특별시 관악구 신림동 704번지 42호 26통 2반서울특별시 관악구 난곡로31길 15 (신림동)<NA>충남슈퍼2010-03-11 16:20:56I2018-08-31 23:59:59.0<NA>192771.108322441000.526126198012192009년11월법개정전자료
33200000198932000800560000119890401<NA>3폐업2폐업처리20031127<NA><NA><NA>02 8387963<NA><NA>서울특별시 관악구 신림동 산104번지 7호<NA><NA>새충복슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA>
43200000199232000800560000119920615<NA>3폐업2폐업처리20031110<NA><NA><NA>02 8658223<NA><NA>서울특별시 관악구 신림동 654번지 39호서울특별시 관악구 난곡로16길 19 (신림동)<NA>충남슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>192997.487458440512.510197<NA><NA>
53200000199332001060560155919931127<NA>1영업/정상0정상영업<NA><NA><NA><NA>862-5865<NA>000서울특별시 관악구 신림동 1484번지 4호 11통 2반서울특별시 관악구 난곡로63길 60 (신림동)<NA>금성슈퍼2014-09-02 18:10:39I2018-08-31 23:59:59.0<NA>192086.290303442052.845153199311272009년11월법개정전자료
63200000199732000800560000119970422<NA>3폐업2폐업처리20021031<NA><NA><NA>02 5332377<NA><NA>서울특별시 관악구 신림동 1489호<NA><NA>없음2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA><NA><NA><NA><NA>
73200000199932000800560180919990510<NA>3폐업2폐업처리20011228<NA><NA><NA>02 8888888<NA><NA>서울특별시 관악구 신림동 396번지 6호서울특별시 관악구 양산길 21 (신림동)<NA>미도슈퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>193925.605983441281.84106<NA><NA>
83200000200032000800560000119980101<NA>3폐업2폐업처리20011031<NA><NA><NA>8640919<NA><NA>서울특별시 관악구 신림동 1659번지 32호서울특별시 관악구 조원로10길 61 (신림동)<NA>지훈수퍼2008-02-21 00:00:00I2018-08-31 23:59:59.0<NA>191466.456353442106.064181<NA><NA>
93200000200032000800560000419980101<NA>3폐업2폐업처리20170612<NA><NA><NA>8776593<NA><NA>서울특별시 관악구 봉천동 944번지 29호서울특별시 관악구 남부순환로 1713-7 (봉천동)<NA>동해식품2017-06-12 16:41:53I2018-08-31 23:59:59.0<NA>194700.12235442356.55213419980101제7조의3제2항에따른경우
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)지정일자민원종류명
4088320000020243200225056000062024-02-13<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 932-1서울특별시 관악구 봉천로31길 6, 103, 104, 105호 (봉천동)08750지에스25뉴봉천한아름2024-02-13 10:39:50I2023-12-01 23:05:00.0<NA>194762.666317442428.312037<NA><NA>
4089320000020243200225056000072024-02-29<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 108-80서울특별시 관악구 복은4길 56, 1층, 2층 (신림동)08837지에스(GS)25신림으뜸점2024-02-29 10:37:40I2023-12-03 00:02:00.0<NA>194348.667097441193.877483<NA><NA>
4090320000020243200225056000082024-03-04<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 704-13 성수빌딩서울특별시 관악구 난곡로 181, 성수빌딩 1층 (신림동)08858주식회사 지에스25남강학사2024-04-02 21:14:41U2023-12-04 00:04:00.0<NA>192805.58529441017.414873<NA><NA>
4091320000020243200225056000092024-03-04<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1712-1 관악드림타운아파트서울특별시 관악구 구암길 98, 관악드림타운아파트 제분산상가동 1층 105호, 106호, 109호, 110호 (봉천동)08725지에스25 관악드림타운점2024-03-28 13:02:39U2023-12-02 21:00:00.0<NA>195345.358939443273.487218<NA><NA>
4092320000020243200225056000102024-03-07<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 1524-4서울특별시 관악구 신림로23길 22, 1층 (신림동)08812서울관악지역자활센터 gs25 신림대학점2024-03-07 17:22:58I2023-12-03 00:09:00.0<NA>194152.312898440870.699504<NA><NA>
4093320000020243200225056000112024-03-08<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 1637-28서울특별시 관악구 인헌길 18, 1층 일부호 (봉천동)08793씨유 뉴낙성인헌점2024-03-08 10:54:01I2023-12-02 23:00:00.0<NA>196985.516902441400.383614<NA><NA>
4094320000020243200225056000122024-03-11<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 1587-24서울특별시 관악구 관천로 29-1, 1층 (신림동)08774세븐일레븐 신림별빛거리점2024-03-11 13:28:06I2023-12-02 23:03:00.0<NA>193515.13814442244.468814<NA><NA>
4095320000020243200225056000132024-03-14<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 870-13 신원메트로빌서울특별시 관악구 남부순환로 1811, 신원메트로빌 101호 (봉천동)08758주식회사 지에스25봉천메트로2024-03-14 10:47:15I2023-12-02 23:06:00.0<NA>195635.738009442172.892033<NA><NA>
4096320000020243200225056000142024-03-14<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 신림동 674-1서울특별시 관악구 난향7길 2, 1층 (신림동)08859GS25 난향타운점2024-03-14 10:48:12I2023-12-02 23:06:00.0<NA>192491.848849440038.244391<NA><NA>
4097320000020243200225056000152024-03-27<NA>1영업/정상0정상영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 관악구 봉천동 956-2서울특별시 관악구 은천로 24, 1층 (봉천동)08749씨유 관악은천로점2024-03-27 16:18:10I2023-12-02 22:09:00.0<NA>194437.43024442656.933126<NA><NA>