Overview

Dataset statistics

Number of variables48
Number of observations3140
Missing cells37700
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory414.0 B

Variable types

Numeric12
Categorical19
Text6
Unsupported9
DateTime1
Boolean1

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123111

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
업태구분명 has constant value ""Constant
위생업태명 has constant value ""Constant
전통업소지정번호 has constant value ""Constant
남성종사자수 is highly imbalanced (57.6%)Imbalance
영업장주변구분명 is highly imbalanced (52.6%)Imbalance
등급구분명 is highly imbalanced (57.3%)Imbalance
본사종업원수 is highly imbalanced (98.3%)Imbalance
공장사무직종업원수 is highly imbalanced (98.3%)Imbalance
공장판매직종업원수 is highly imbalanced (98.3%)Imbalance
공장생산직종업원수 is highly imbalanced (98.3%)Imbalance
보증액 is highly imbalanced (98.3%)Imbalance
월세액 is highly imbalanced (98.3%)Imbalance
다중이용업소여부 is highly imbalanced (87.8%)Imbalance
인허가취소일자 has 3140 (100.0%) missing valuesMissing
폐업일자 has 1172 (37.3%) missing valuesMissing
휴업시작일자 has 3140 (100.0%) missing valuesMissing
휴업종료일자 has 3140 (100.0%) missing valuesMissing
재개업일자 has 3140 (100.0%) missing valuesMissing
소재지전화 has 1121 (35.7%) missing valuesMissing
소재지면적 has 197 (6.3%) missing valuesMissing
소재지우편번호 has 49 (1.6%) missing valuesMissing
도로명전체주소 has 759 (24.2%) missing valuesMissing
도로명우편번호 has 787 (25.1%) missing valuesMissing
좌표정보(x) has 81 (2.6%) missing valuesMissing
좌표정보(y) has 81 (2.6%) missing valuesMissing
여성종사자수 has 2047 (65.2%) missing valuesMissing
총종업원수 has 3140 (100.0%) missing valuesMissing
건물소유구분명 has 3140 (100.0%) missing valuesMissing
전통업소지정번호 has 3139 (> 99.9%) missing valuesMissing
전통업소주된음식 has 3140 (100.0%) missing valuesMissing
홈페이지 has 3140 (100.0%) missing valuesMissing
Unnamed: 47 has 3140 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
총종업원수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
건물소유구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전통업소주된음식 is an unsupported type, check if it needs cleaning or further analysisUnsupported
홈페이지 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 47 is an unsupported type, check if it needs cleaning or further analysisUnsupported
여성종사자수 has 998 (31.8%) zerosZeros
시설총규모 has 229 (7.3%) zerosZeros

Reproduction

Analysis started2024-04-17 19:02:03.585247
Analysis finished2024-04-17 19:02:04.970294
Duration1.39 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct3140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1570.5
Minimum1
Maximum3140
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:05.023642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile157.95
Q1785.75
median1570.5
Q32355.25
95-th percentile2983.05
Maximum3140
Range3139
Interquartile range (IQR)1569.5

Descriptive statistics

Standard deviation906.58425
Coefficient of variation (CV)0.57725836
Kurtosis-1.2
Mean1570.5
Median Absolute Deviation (MAD)785
Skewness0
Sum4931370
Variance821895
MonotonicityStrictly increasing
2024-04-18T04:02:05.129625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2088 1
 
< 0.1%
2090 1
 
< 0.1%
2091 1
 
< 0.1%
2092 1
 
< 0.1%
2093 1
 
< 0.1%
2094 1
 
< 0.1%
2095 1
 
< 0.1%
2096 1
 
< 0.1%
2097 1
 
< 0.1%
Other values (3130) 3130
99.7%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
3140 1
< 0.1%
3139 1
< 0.1%
3138 1
< 0.1%
3137 1
< 0.1%
3136 1
< 0.1%
3135 1
< 0.1%
3134 1
< 0.1%
3133 1
< 0.1%
3132 1
< 0.1%
3131 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
제과점영업
3140 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 3140
100.0%

Length

2024-04-18T04:02:05.227808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:05.295634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 3140
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
07_22_18_P
3140 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row07_22_18_P
2nd row07_22_18_P
3rd row07_22_18_P
4th row07_22_18_P
5th row07_22_18_P

Common Values

ValueCountFrequency (%)
07_22_18_P 3140
100.0%

Length

2024-04-18T04:02:05.366526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:05.437547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
07_22_18_p 3140
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3327678.3
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:05.500901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13300000
median3330000
Q33350000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation38970.403
Coefficient of variation (CV)0.011710989
Kurtosis-0.73549886
Mean3327678.3
Median Absolute Deviation (MAD)30000
Skewness0.012051663
Sum1.044891 × 1010
Variance1.5186923 × 109
MonotonicityNot monotonic
2024-04-18T04:02:05.587249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3330000 443
14.1%
3290000 334
10.6%
3300000 287
9.1%
3340000 280
8.9%
3310000 226
 
7.2%
3350000 225
 
7.2%
3370000 209
 
6.7%
3320000 207
 
6.6%
3380000 183
 
5.8%
3390000 168
 
5.4%
Other values (6) 578
18.4%
ValueCountFrequency (%)
3250000 113
 
3.6%
3260000 92
 
2.9%
3270000 93
 
3.0%
3280000 73
 
2.3%
3290000 334
10.6%
3300000 287
9.1%
3310000 226
7.2%
3320000 207
6.6%
3330000 443
14.1%
3340000 280
8.9%
ValueCountFrequency (%)
3400000 122
 
3.9%
3390000 168
 
5.4%
3380000 183
5.8%
3370000 209
6.7%
3360000 85
 
2.7%
3350000 225
7.2%
3340000 280
8.9%
3330000 443
14.1%
3320000 207
6.6%
3310000 226
7.2%

관리번호
Text

UNIQUE 

Distinct3140
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
2024-04-18T04:02:05.751249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters69080
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

Unique3140 ?
Unique (%)100.0%

Sample

1st row3280000-121-1996-00003
2nd row3250000-121-2011-00006
3rd row3250000-121-2014-00003
4th row3250000-121-2014-00005
5th row3250000-121-2015-00003
ValueCountFrequency (%)
3280000-121-1996-00003 1
 
< 0.1%
3380000-121-1971-00405 1
 
< 0.1%
3380000-121-1994-00575 1
 
< 0.1%
3380000-121-2015-00003 1
 
< 0.1%
3380000-121-1980-00416 1
 
< 0.1%
3380000-121-1980-00423 1
 
< 0.1%
3380000-121-1991-00469 1
 
< 0.1%
3380000-121-1991-00538 1
 
< 0.1%
3380000-121-1991-00477 1
 
< 0.1%
3380000-121-1992-00485 1
 
< 0.1%
Other values (3130) 3130
99.7%
2024-04-18T04:02:06.005493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 27928
40.4%
1 9994
 
14.5%
- 9420
 
13.6%
2 7642
 
11.1%
3 6648
 
9.6%
9 2217
 
3.2%
4 1200
 
1.7%
5 1104
 
1.6%
8 1042
 
1.5%
7 1007
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59660
86.4%
Dash Punctuation 9420
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27928
46.8%
1 9994
 
16.8%
2 7642
 
12.8%
3 6648
 
11.1%
9 2217
 
3.7%
4 1200
 
2.0%
5 1104
 
1.9%
8 1042
 
1.7%
7 1007
 
1.7%
6 878
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 9420
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69080
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 27928
40.4%
1 9994
 
14.5%
- 9420
 
13.6%
2 7642
 
11.1%
3 6648
 
9.6%
9 2217
 
3.2%
4 1200
 
1.7%
5 1104
 
1.6%
8 1042
 
1.5%
7 1007
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69080
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 27928
40.4%
1 9994
 
14.5%
- 9420
 
13.6%
2 7642
 
11.1%
3 6648
 
9.6%
9 2217
 
3.2%
4 1200
 
1.7%
5 1104
 
1.6%
8 1042
 
1.5%
7 1007
 
1.5%

인허가일자
Real number (ℝ)

Distinct2461
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20076049
Minimum19631010
Maximum20210429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:06.125521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19631010
5-th percentile19870818
Q120020206
median20100326
Q320160302
95-th percentile20200416
Maximum20210429
Range579419
Interquartile range (IQR)140096

Descriptive statistics

Standard deviation101923.57
Coefficient of variation (CV)0.0050768739
Kurtosis0.64886845
Mean20076049
Median Absolute Deviation (MAD)65008.5
Skewness-0.98001767
Sum6.3038795 × 1010
Variance1.0388414 × 1010
MonotonicityNot monotonic
2024-04-18T04:02:06.228474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20090212 9
 
0.3%
20140410 6
 
0.2%
20181002 6
 
0.2%
20090120 5
 
0.2%
20100531 5
 
0.2%
20101027 5
 
0.2%
20110314 4
 
0.1%
20190207 4
 
0.1%
20120511 4
 
0.1%
20030725 4
 
0.1%
Other values (2451) 3088
98.3%
ValueCountFrequency (%)
19631010 2
0.1%
19651024 1
 
< 0.1%
19660916 1
 
< 0.1%
19680422 3
0.1%
19680716 1
 
< 0.1%
19691007 1
 
< 0.1%
19701031 1
 
< 0.1%
19711230 1
 
< 0.1%
19721220 1
 
< 0.1%
19730303 1
 
< 0.1%
ValueCountFrequency (%)
20210429 1
 
< 0.1%
20210428 1
 
< 0.1%
20210427 1
 
< 0.1%
20210423 1
 
< 0.1%
20210420 2
0.1%
20210415 1
 
< 0.1%
20210414 1
 
< 0.1%
20210413 1
 
< 0.1%
20210412 1
 
< 0.1%
20210409 4
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
3
1968 
1
1172 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
3 1968
62.7%
1 1172
37.3%

Length

2024-04-18T04:02:06.352911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:06.428521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1968
62.7%
1 1172
37.3%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
폐업
1968 
영업/정상
1172 

Length

Max length5
Median length2
Mean length3.1197452
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 1968
62.7%
영업/정상 1172
37.3%

Length

2024-04-18T04:02:06.505624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:06.581066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1968
62.7%
영업/정상 1172
37.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
2
1968 
1
1172 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
2 1968
62.7%
1 1172
37.3%

Length

2024-04-18T04:02:06.664859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:06.757153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1968
62.7%
1 1172
37.3%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
폐업
1968 
영업
1172 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1968
62.7%
영업 1172
37.3%

Length

2024-04-18T04:02:06.852981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:06.955242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1968
62.7%
영업 1172
37.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct1386
Distinct (%)70.4%
Missing1172
Missing (%)37.3%
Infinite0
Infinite (%)0.0%
Mean20137110
Minimum19950703
Maximum20210426
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:07.099896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950703
5-th percentile20060416
Q120100628
median20140423
Q320180129
95-th percentile20200872
Maximum20210426
Range259723
Interquartile range (IQR)79501.75

Descriptive statistics

Standard deviation45756.733
Coefficient of variation (CV)0.0022722592
Kurtosis-1.013466
Mean20137110
Median Absolute Deviation (MAD)39750
Skewness-0.22238904
Sum3.9629832 × 1010
Variance2.0936786 × 109
MonotonicityNot monotonic
2024-04-18T04:02:07.295978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20060216 31
 
1.0%
20170131 24
 
0.8%
20181220 16
 
0.5%
20060412 15
 
0.5%
20130607 14
 
0.4%
20130409 11
 
0.4%
20130614 9
 
0.3%
20170321 9
 
0.3%
20070126 7
 
0.2%
20190717 6
 
0.2%
Other values (1376) 1826
58.2%
(Missing) 1172
37.3%
ValueCountFrequency (%)
19950703 1
< 0.1%
19991221 1
< 0.1%
20050114 1
< 0.1%
20050805 1
< 0.1%
20050818 1
< 0.1%
20050920 1
< 0.1%
20050922 1
< 0.1%
20050930 1
< 0.1%
20051004 1
< 0.1%
20051027 1
< 0.1%
ValueCountFrequency (%)
20210426 1
 
< 0.1%
20210425 1
 
< 0.1%
20210423 3
0.1%
20210422 1
 
< 0.1%
20210419 1
 
< 0.1%
20210412 1
 
< 0.1%
20210410 1
 
< 0.1%
20210409 1
 
< 0.1%
20210408 2
0.1%
20210401 2
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

소재지전화
Text

MISSING 

Distinct1775
Distinct (%)87.9%
Missing1121
Missing (%)35.7%
Memory size24.7 KiB
2024-04-18T04:02:07.563618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.693413
Min length3

Characters and Unicode

Total characters21590
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

Unique1705 ?
Unique (%)84.4%

Sample

1st row051 4163857
2nd row051 4663202
3rd row02 26706546
4th row051 255 0771
5th row051 464 7007
ValueCountFrequency (%)
051 1789
39.1%
070 44
 
1.0%
727 20
 
0.4%
02 20
 
0.4%
728 12
 
0.3%
242 11
 
0.2%
255 10
 
0.2%
203 10
 
0.2%
330 9
 
0.2%
853 9
 
0.2%
Other values (1990) 2638
57.7%
2024-04-18T04:02:07.897883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3542
16.4%
5 3462
16.0%
1 3156
14.6%
2584
12.0%
2 1758
8.1%
7 1332
 
6.2%
3 1296
 
6.0%
8 1270
 
5.9%
6 1170
 
5.4%
4 1169
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19006
88.0%
Space Separator 2584
 
12.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3542
18.6%
5 3462
18.2%
1 3156
16.6%
2 1758
9.2%
7 1332
 
7.0%
3 1296
 
6.8%
8 1270
 
6.7%
6 1170
 
6.2%
4 1169
 
6.2%
9 851
 
4.5%
Space Separator
ValueCountFrequency (%)
2584
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21590
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3542
16.4%
5 3462
16.0%
1 3156
14.6%
2584
12.0%
2 1758
8.1%
7 1332
 
6.2%
3 1296
 
6.0%
8 1270
 
5.9%
6 1170
 
5.4%
4 1169
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3542
16.4%
5 3462
16.0%
1 3156
14.6%
2584
12.0%
2 1758
8.1%
7 1332
 
6.2%
3 1296
 
6.0%
8 1270
 
5.9%
6 1170
 
5.4%
4 1169
 
5.4%

소재지면적
Real number (ℝ)

MISSING 

Distinct2135
Distinct (%)72.5%
Missing197
Missing (%)6.3%
Infinite0
Infinite (%)0.0%
Mean53.2665
Minimum0
Maximum780.5
Zeros20
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:08.012891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile8.107
Q124.105
median39.16
Q365.93
95-th percentile138.433
Maximum780.5
Range780.5
Interquartile range (IQR)41.825

Descriptive statistics

Standard deviation52.959693
Coefficient of variation (CV)0.99424014
Kurtosis42.925503
Mean53.2665
Median Absolute Deviation (MAD)18.37
Skewness4.6966549
Sum156763.31
Variance2804.729
MonotonicityNot monotonic
2024-04-18T04:02:08.139061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
0.6%
24.0 17
 
0.5%
33.0 17
 
0.5%
20.0 13
 
0.4%
36.0 11
 
0.4%
26.0 11
 
0.4%
42.0 11
 
0.4%
25.0 11
 
0.4%
15.0 11
 
0.4%
30.0 10
 
0.3%
Other values (2125) 2811
89.5%
(Missing) 197
 
6.3%
ValueCountFrequency (%)
0.0 20
0.6%
0.25 1
 
< 0.1%
0.7 1
 
< 0.1%
0.9 1
 
< 0.1%
0.91 1
 
< 0.1%
1.0 5
 
0.2%
1.2 1
 
< 0.1%
1.21 2
 
0.1%
1.4 1
 
< 0.1%
1.49 1
 
< 0.1%
ValueCountFrequency (%)
780.5 1
< 0.1%
722.81 1
< 0.1%
695.26 1
< 0.1%
691.9 1
< 0.1%
605.0 1
< 0.1%
415.71 1
< 0.1%
395.77 1
< 0.1%
356.96 1
< 0.1%
335.04 1
< 0.1%
322.42 1
< 0.1%

소재지우편번호
Real number (ℝ)

MISSING 

Distinct653
Distinct (%)21.1%
Missing49
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean610907.48
Minimum600012
Maximum619953
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:08.255021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600012
5-th percentile601808
Q1607815
median611825
Q3614821.5
95-th percentile618200
Maximum619953
Range19941
Interquartile range (IQR)7006.5

Descriptive statistics

Standard deviation5005.9258
Coefficient of variation (CV)0.0081942454
Kurtosis-0.66047867
Mean610907.48
Median Absolute Deviation (MAD)3041
Skewness-0.32076951
Sum1.888315 × 109
Variance25059293
MonotonicityNot monotonic
2024-04-18T04:02:08.394155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
612020 97
 
3.1%
612824 31
 
1.0%
608832 28
 
0.9%
616852 28
 
0.9%
618200 27
 
0.9%
618814 25
 
0.8%
617808 25
 
0.8%
600017 25
 
0.8%
607815 24
 
0.8%
604851 23
 
0.7%
Other values (643) 2758
87.8%
(Missing) 49
 
1.6%
ValueCountFrequency (%)
600012 1
 
< 0.1%
600016 1
 
< 0.1%
600017 25
0.8%
600021 3
 
0.1%
600022 1
 
< 0.1%
600025 2
 
0.1%
600032 2
 
0.1%
600033 1
 
< 0.1%
600041 3
 
0.1%
600042 3
 
0.1%
ValueCountFrequency (%)
619953 3
 
0.1%
619952 4
 
0.1%
619951 3
 
0.1%
619913 1
 
< 0.1%
619912 8
0.3%
619911 2
 
0.1%
619906 3
 
0.1%
619905 15
0.5%
619904 1
 
< 0.1%
619903 13
0.4%
Distinct2821
Distinct (%)90.0%
Missing7
Missing (%)0.2%
Memory size24.7 KiB
2024-04-18T04:02:08.663264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length49
Mean length25.099585
Min length14

Characters and Unicode

Total characters78637
Distinct characters419
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

Unique2633 ?
Unique (%)84.0%

Sample

1st row부산광역시 영도구 남항동2가 271-1 272-3,274-2,274-3
2nd row부산광역시 중구 중앙동4가 36-14번지 (1층)
3rd row부산광역시 중구 창선동1가 12-1번지 1층 일부
4th row부산광역시 중구 중앙동7가 20-1 롯데몰마트시네마동롯데마트부산광복점지하1
5th row부산광역시 중구 부평동2가 45-13번지 1층
ValueCountFrequency (%)
부산광역시 3133
 
21.2%
해운대구 442
 
3.0%
부산진구 334
 
2.3%
동래구 287
 
1.9%
사하구 278
 
1.9%
남구 226
 
1.5%
금정구 225
 
1.5%
연제구 209
 
1.4%
북구 206
 
1.4%
수영구 183
 
1.2%
Other values (3701) 9242
62.6%
2024-04-18T04:02:09.057713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11641
 
14.8%
1 4054
 
5.2%
3840
 
4.9%
3771
 
4.8%
3723
 
4.7%
3245
 
4.1%
3227
 
4.1%
3158
 
4.0%
3107
 
4.0%
3074
 
3.9%
Other values (409) 35797
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47468
60.4%
Decimal Number 16091
 
20.5%
Space Separator 11641
 
14.8%
Dash Punctuation 2627
 
3.3%
Open Punctuation 217
 
0.3%
Close Punctuation 214
 
0.3%
Uppercase Letter 180
 
0.2%
Other Punctuation 172
 
0.2%
Lowercase Letter 18
 
< 0.1%
Math Symbol 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3840
 
8.1%
3771
 
7.9%
3723
 
7.8%
3245
 
6.8%
3227
 
6.8%
3158
 
6.7%
3107
 
6.5%
3074
 
6.5%
2707
 
5.7%
779
 
1.6%
Other values (358) 16837
35.5%
Uppercase Letter
ValueCountFrequency (%)
B 34
18.9%
A 26
14.4%
S 26
14.4%
G 18
10.0%
K 15
8.3%
C 13
 
7.2%
P 6
 
3.3%
T 5
 
2.8%
L 5
 
2.8%
E 4
 
2.2%
Other values (13) 28
15.6%
Decimal Number
ValueCountFrequency (%)
1 4054
25.2%
2 2121
13.2%
3 1665
10.3%
4 1472
 
9.1%
5 1428
 
8.9%
0 1299
 
8.1%
6 1097
 
6.8%
7 1078
 
6.7%
9 964
 
6.0%
8 913
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 146
84.9%
. 12
 
7.0%
@ 8
 
4.7%
/ 3
 
1.7%
· 2
 
1.2%
: 1
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
e 7
38.9%
s 4
22.2%
k 3
16.7%
l 3
16.7%
i 1
 
5.6%
Open Punctuation
ValueCountFrequency (%)
( 216
99.5%
[ 1
 
0.5%
Close Punctuation
ValueCountFrequency (%)
) 213
99.5%
] 1
 
0.5%
Space Separator
ValueCountFrequency (%)
11641
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2627
100.0%
Math Symbol
ValueCountFrequency (%)
~ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47468
60.4%
Common 30971
39.4%
Latin 198
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3840
 
8.1%
3771
 
7.9%
3723
 
7.8%
3245
 
6.8%
3227
 
6.8%
3158
 
6.7%
3107
 
6.5%
3074
 
6.5%
2707
 
5.7%
779
 
1.6%
Other values (358) 16837
35.5%
Latin
ValueCountFrequency (%)
B 34
17.2%
A 26
13.1%
S 26
13.1%
G 18
9.1%
K 15
 
7.6%
C 13
 
6.6%
e 7
 
3.5%
P 6
 
3.0%
T 5
 
2.5%
L 5
 
2.5%
Other values (18) 43
21.7%
Common
ValueCountFrequency (%)
11641
37.6%
1 4054
 
13.1%
- 2627
 
8.5%
2 2121
 
6.8%
3 1665
 
5.4%
4 1472
 
4.8%
5 1428
 
4.6%
0 1299
 
4.2%
6 1097
 
3.5%
7 1078
 
3.5%
Other values (13) 2489
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47468
60.4%
ASCII 31167
39.6%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11641
37.4%
1 4054
 
13.0%
- 2627
 
8.4%
2 2121
 
6.8%
3 1665
 
5.3%
4 1472
 
4.7%
5 1428
 
4.6%
0 1299
 
4.2%
6 1097
 
3.5%
7 1078
 
3.5%
Other values (40) 2685
 
8.6%
Hangul
ValueCountFrequency (%)
3840
 
8.1%
3771
 
7.9%
3723
 
7.8%
3245
 
6.8%
3227
 
6.8%
3158
 
6.7%
3107
 
6.5%
3074
 
6.5%
2707
 
5.7%
779
 
1.6%
Other values (358) 16837
35.5%
None
ValueCountFrequency (%)
· 2
100.0%

도로명전체주소
Text

MISSING 

Distinct2241
Distinct (%)94.1%
Missing759
Missing (%)24.2%
Memory size24.7 KiB
2024-04-18T04:02:09.358932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length58
Mean length32.433011
Min length20

Characters and Unicode

Total characters77223
Distinct characters449
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

Unique2170 ?
Unique (%)91.1%

Sample

1st row부산광역시 영도구 남항로 40-1 (남항동2가,272-3,274-2,274-3)
2nd row부산광역시 중구 해관로 65, 1층 (중앙동4가)
3rd row부산광역시 중구 광복로39번길 6 (창선동1가)
4th row부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데몰마트시네마동롯데마트부산광복점지하1)
5th row부산광역시 중구 보수대로 16, 1층 (부평동2가)
ValueCountFrequency (%)
부산광역시 2381
 
16.1%
1층 633
 
4.3%
해운대구 366
 
2.5%
부산진구 256
 
1.7%
사하구 211
 
1.4%
동래구 201
 
1.4%
남구 175
 
1.2%
금정구 161
 
1.1%
우동 156
 
1.1%
북구 148
 
1.0%
Other values (2770) 10121
68.3%
2024-04-18T04:02:09.779451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12442
 
16.1%
1 3593
 
4.7%
3160
 
4.1%
3065
 
4.0%
2885
 
3.7%
2606
 
3.4%
2546
 
3.3%
( 2418
 
3.1%
) 2414
 
3.1%
2401
 
3.1%
Other values (439) 39693
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 45606
59.1%
Space Separator 12442
 
16.1%
Decimal Number 11635
 
15.1%
Open Punctuation 2419
 
3.1%
Close Punctuation 2415
 
3.1%
Other Punctuation 2132
 
2.8%
Dash Punctuation 297
 
0.4%
Uppercase Letter 246
 
0.3%
Math Symbol 16
 
< 0.1%
Lowercase Letter 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3160
 
6.9%
3065
 
6.7%
2885
 
6.3%
2606
 
5.7%
2546
 
5.6%
2401
 
5.3%
2398
 
5.3%
2365
 
5.2%
1391
 
3.1%
1122
 
2.5%
Other values (388) 21667
47.5%
Uppercase Letter
ValueCountFrequency (%)
A 48
19.5%
B 40
16.3%
C 29
11.8%
S 26
10.6%
E 19
 
7.7%
P 19
 
7.7%
G 17
 
6.9%
K 13
 
5.3%
H 5
 
2.0%
T 4
 
1.6%
Other values (13) 26
10.6%
Decimal Number
ValueCountFrequency (%)
1 3593
30.9%
2 1625
14.0%
3 1151
 
9.9%
0 1050
 
9.0%
4 881
 
7.6%
5 842
 
7.2%
6 720
 
6.2%
7 691
 
5.9%
8 569
 
4.9%
9 513
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 2116
99.2%
. 9
 
0.4%
@ 4
 
0.2%
· 1
 
< 0.1%
/ 1
 
< 0.1%
* 1
 
< 0.1%
Lowercase Letter
ValueCountFrequency (%)
e 7
46.7%
s 3
20.0%
l 2
 
13.3%
k 2
 
13.3%
i 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 2418
> 99.9%
[ 1
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
) 2414
> 99.9%
] 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
12442
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 297
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 45606
59.1%
Common 31356
40.6%
Latin 261
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3160
 
6.9%
3065
 
6.7%
2885
 
6.3%
2606
 
5.7%
2546
 
5.6%
2401
 
5.3%
2398
 
5.3%
2365
 
5.2%
1391
 
3.1%
1122
 
2.5%
Other values (388) 21667
47.5%
Latin
ValueCountFrequency (%)
A 48
18.4%
B 40
15.3%
C 29
11.1%
S 26
10.0%
E 19
 
7.3%
P 19
 
7.3%
G 17
 
6.5%
K 13
 
5.0%
e 7
 
2.7%
H 5
 
1.9%
Other values (18) 38
14.6%
Common
ValueCountFrequency (%)
12442
39.7%
1 3593
 
11.5%
( 2418
 
7.7%
) 2414
 
7.7%
, 2116
 
6.7%
2 1625
 
5.2%
3 1151
 
3.7%
0 1050
 
3.3%
4 881
 
2.8%
5 842
 
2.7%
Other values (13) 2824
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 45606
59.1%
ASCII 31616
40.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12442
39.4%
1 3593
 
11.4%
( 2418
 
7.6%
) 2414
 
7.6%
, 2116
 
6.7%
2 1625
 
5.1%
3 1151
 
3.6%
0 1050
 
3.3%
4 881
 
2.8%
5 842
 
2.7%
Other values (40) 3084
 
9.8%
Hangul
ValueCountFrequency (%)
3160
 
6.9%
3065
 
6.7%
2885
 
6.3%
2606
 
5.7%
2546
 
5.6%
2401
 
5.3%
2398
 
5.3%
2365
 
5.2%
1391
 
3.1%
1122
 
2.5%
Other values (388) 21667
47.5%
None
ValueCountFrequency (%)
· 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct937
Distinct (%)39.8%
Missing787
Missing (%)25.1%
Infinite0
Infinite (%)0.0%
Mean47808.958
Minimum46002
Maximum49525
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:09.893222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46002
5-th percentile46225
Q147048
median47903
Q348503
95-th percentile49389
Maximum49525
Range3523
Interquartile range (IQR)1455

Descriptive statistics

Standard deviation983.34251
Coefficient of variation (CV)0.020568165
Kurtosis-0.94804637
Mean47808.958
Median Absolute Deviation (MAD)710
Skewness-0.074994308
Sum1.1249448 × 108
Variance966962.5
MonotonicityNot monotonic
2024-04-18T04:02:10.000482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
48058 69
 
2.2%
46726 25
 
0.8%
48944 24
 
0.8%
46291 22
 
0.7%
47285 20
 
0.6%
48735 20
 
0.6%
48515 19
 
0.6%
48060 18
 
0.6%
48059 14
 
0.4%
46970 13
 
0.4%
Other values (927) 2109
67.2%
(Missing) 787
 
25.1%
ValueCountFrequency (%)
46002 1
 
< 0.1%
46007 2
 
0.1%
46008 7
0.2%
46012 2
 
0.1%
46013 4
 
0.1%
46015 13
0.4%
46016 1
 
< 0.1%
46017 5
 
0.2%
46019 1
 
< 0.1%
46021 1
 
< 0.1%
ValueCountFrequency (%)
49525 1
 
< 0.1%
49524 2
 
0.1%
49521 1
 
< 0.1%
49520 6
0.2%
49519 8
0.3%
49518 3
 
0.1%
49515 1
 
< 0.1%
49511 2
 
0.1%
49509 1
 
< 0.1%
49505 3
 
0.1%
Distinct2543
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
2024-04-18T04:02:10.259676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length29
Mean length7.3538217
Min length2

Characters and Unicode

Total characters23091
Distinct characters689
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2256 ?
Unique (%)71.8%

Sample

1st row파리바게트 영도남항점
2nd row파리바게뜨
3rd row비엔씨제과광복점
4th row베이커리팩토리 광복점
5th row타임 베이커리
ValueCountFrequency (%)
파리바게뜨 112
 
2.8%
베이커리 106
 
2.6%
뚜레쥬르 75
 
1.8%
파리바게트 49
 
1.2%
몽블랑제 37
 
0.9%
과자점 33
 
0.8%
탑베이커리 25
 
0.6%
탑스베이커리 21
 
0.5%
크라운베이커리 16
 
0.4%
프레제 16
 
0.4%
Other values (2638) 3579
88.0%
2024-04-18T04:02:10.605962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1206
 
5.2%
1087
 
4.7%
929
 
4.0%
900
 
3.9%
655
 
2.8%
600
 
2.6%
462
 
2.0%
439
 
1.9%
408
 
1.8%
375
 
1.6%
Other values (679) 16030
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20229
87.6%
Space Separator 929
 
4.0%
Lowercase Letter 611
 
2.6%
Uppercase Letter 404
 
1.7%
Close Punctuation 343
 
1.5%
Open Punctuation 336
 
1.5%
Decimal Number 185
 
0.8%
Other Punctuation 42
 
0.2%
Dash Punctuation 7
 
< 0.1%
Letter Number 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1206
 
6.0%
1087
 
5.4%
900
 
4.4%
655
 
3.2%
600
 
3.0%
462
 
2.3%
439
 
2.2%
408
 
2.0%
375
 
1.9%
339
 
1.7%
Other values (608) 13758
68.0%
Lowercase Letter
ValueCountFrequency (%)
e 102
16.7%
a 66
 
10.8%
o 44
 
7.2%
r 42
 
6.9%
i 42
 
6.9%
s 38
 
6.2%
n 36
 
5.9%
t 26
 
4.3%
k 26
 
4.3%
l 24
 
3.9%
Other values (15) 165
27.0%
Uppercase Letter
ValueCountFrequency (%)
B 41
 
10.1%
S 34
 
8.4%
A 30
 
7.4%
E 30
 
7.4%
R 23
 
5.7%
O 22
 
5.4%
M 20
 
5.0%
T 20
 
5.0%
I 19
 
4.7%
N 19
 
4.7%
Other values (14) 146
36.1%
Decimal Number
ValueCountFrequency (%)
2 56
30.3%
1 38
20.5%
3 22
 
11.9%
0 18
 
9.7%
5 14
 
7.6%
7 11
 
5.9%
9 10
 
5.4%
4 8
 
4.3%
8 6
 
3.2%
6 2
 
1.1%
Other Punctuation
ValueCountFrequency (%)
& 16
38.1%
' 10
23.8%
. 9
21.4%
, 4
 
9.5%
? 2
 
4.8%
; 1
 
2.4%
Space Separator
ValueCountFrequency (%)
929
100.0%
Close Punctuation
ValueCountFrequency (%)
) 343
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Letter Number
ValueCountFrequency (%)
3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20222
87.6%
Common 1844
 
8.0%
Latin 1018
 
4.4%
Han 7
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1206
 
6.0%
1087
 
5.4%
900
 
4.5%
655
 
3.2%
600
 
3.0%
462
 
2.3%
439
 
2.2%
408
 
2.0%
375
 
1.9%
339
 
1.7%
Other values (602) 13751
68.0%
Latin
ValueCountFrequency (%)
e 102
 
10.0%
a 66
 
6.5%
o 44
 
4.3%
r 42
 
4.1%
i 42
 
4.1%
B 41
 
4.0%
s 38
 
3.7%
n 36
 
3.5%
S 34
 
3.3%
A 30
 
2.9%
Other values (40) 543
53.3%
Common
ValueCountFrequency (%)
929
50.4%
) 343
 
18.6%
( 336
 
18.2%
2 56
 
3.0%
1 38
 
2.1%
3 22
 
1.2%
0 18
 
1.0%
& 16
 
0.9%
5 14
 
0.8%
7 11
 
0.6%
Other values (11) 61
 
3.3%
Han
ValueCountFrequency (%)
2
28.6%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20222
87.6%
ASCII 2859
 
12.4%
CJK 6
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat Ideographs 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1206
 
6.0%
1087
 
5.4%
900
 
4.5%
655
 
3.2%
600
 
3.0%
462
 
2.3%
439
 
2.2%
408
 
2.0%
375
 
1.9%
339
 
1.7%
Other values (602) 13751
68.0%
ASCII
ValueCountFrequency (%)
929
32.5%
) 343
 
12.0%
( 336
 
11.8%
e 102
 
3.6%
a 66
 
2.3%
2 56
 
2.0%
o 44
 
1.5%
r 42
 
1.5%
i 42
 
1.5%
B 41
 
1.4%
Other values (60) 858
30.0%
Number Forms
ValueCountFrequency (%)
3
100.0%
CJK
ValueCountFrequency (%)
2
33.3%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
CJK Compat Ideographs
ValueCountFrequency (%)
1
100.0%

최종수정시점
Real number (ℝ)

Distinct2900
Distinct (%)92.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0139607 × 1013
Minimum1.9990303 × 1013
Maximum2.021043 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:10.727196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9990303 × 1013
5-th percentile2.0020802 × 1013
Q12.0100329 × 1013
median2.0160331 × 1013
Q32.0190819 × 1013
95-th percentile2.0210215 × 1013
Maximum2.021043 × 1013
Range2.2012721 × 1011
Interquartile range (IQR)9.0490221 × 1010

Descriptive statistics

Standard deviation6.0616246 × 1010
Coefficient of variation (CV)0.0030098029
Kurtosis-0.62579472
Mean2.0139607 × 1013
Median Absolute Deviation (MAD)4.0096956 × 1010
Skewness-0.70787844
Sum6.3238365 × 1016
Variance3.6743292 × 1021
MonotonicityNot monotonic
2024-04-18T04:02:10.841801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20061226000000 26
 
0.8%
20040823000000 14
 
0.4%
20050614000000 14
 
0.4%
19990318000000 14
 
0.4%
19990319000000 11
 
0.4%
20050615000000 11
 
0.4%
20020802000000 10
 
0.3%
19990317000000 9
 
0.3%
20050909000000 8
 
0.3%
20010803000000 8
 
0.3%
Other values (2890) 3015
96.0%
ValueCountFrequency (%)
19990303000000 1
 
< 0.1%
19990315000000 6
0.2%
19990316000000 5
 
0.2%
19990317000000 9
0.3%
19990318000000 14
0.4%
19990319000000 11
0.4%
19990323000000 2
 
0.1%
19990324000000 1
 
< 0.1%
19990511000000 4
 
0.1%
19990520000000 1
 
< 0.1%
ValueCountFrequency (%)
20210430205519 1
< 0.1%
20210430133820 1
< 0.1%
20210429182318 1
< 0.1%
20210429172601 1
< 0.1%
20210429153750 1
< 0.1%
20210429104527 1
< 0.1%
20210429094627 1
< 0.1%
20210428173834 1
< 0.1%
20210428145626 1
< 0.1%
20210428133933 1
< 0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
I
2145 
U
995 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 2145
68.3%
U 995
31.7%

Length

2024-04-18T04:02:10.937281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:11.241587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 2145
68.3%
u 995
31.7%
Distinct537
Distinct (%)17.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
Minimum2018-08-31 23:59:59
Maximum2021-05-02 02:40:00
2024-04-18T04:02:11.322163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T04:02:11.421700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
제과점영업
3140 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 3140
100.0%

Length

2024-04-18T04:02:11.511544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:11.584026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 3140
100.0%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct2324
Distinct (%)76.0%
Missing81
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean388339.3
Minimum364927.7
Maximum407434.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:11.663786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum364927.7
5-th percentile379287.5
Q1384142.15
median388831.51
Q3392157.73
95-th percentile398151.59
Maximum407434.69
Range42506.995
Interquartile range (IQR)8015.5888

Descriptive statistics

Standard deviation5877.2167
Coefficient of variation (CV)0.015134231
Kurtosis0.24743631
Mean388339.3
Median Absolute Deviation (MAD)3676.8053
Skewness-0.072802756
Sum1.1879299 × 109
Variance34541676
MonotonicityNot monotonic
2024-04-18T04:02:11.764439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
393952.264486105 63
 
2.0%
387271.299492377 25
 
0.8%
385590.814676765 23
 
0.7%
387539.767677801 21
 
0.7%
390120.394129863 15
 
0.5%
394482.139208377 13
 
0.4%
392474.578116018 13
 
0.4%
380225.635401772 12
 
0.4%
394083.501537578 12
 
0.4%
386163.228186082 12
 
0.4%
Other values (2314) 2850
90.8%
(Missing) 81
 
2.6%
ValueCountFrequency (%)
364927.696730227 1
< 0.1%
366829.531355754 1
< 0.1%
367205.763155348 1
< 0.1%
367397.014357092 1
< 0.1%
367451.087635496 1
< 0.1%
368045.907990854 1
< 0.1%
371173.90939644 1
< 0.1%
371211.777937641 1
< 0.1%
371278.227629686 1
< 0.1%
371290.690707476 1
< 0.1%
ValueCountFrequency (%)
407434.691805327 2
0.1%
407418.648415535 2
0.1%
407245.567193252 1
< 0.1%
407178.504808338 1
< 0.1%
407121.882187494 1
< 0.1%
405596.576299318 1
< 0.1%
405241.716598101 1
< 0.1%
404368.189766908 1
< 0.1%
403992.260361442 2
0.1%
403323.325916494 1
< 0.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct2325
Distinct (%)76.0%
Missing81
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean187272.28
Minimum170813.58
Maximum206353.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:11.877242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum170813.58
5-th percentile178482.04
Q1183633.94
median187456.38
Q3190982.23
95-th percentile196615.65
Maximum206353.86
Range35540.271
Interquartile range (IQR)7348.2848

Descriptive statistics

Standard deviation5847.7781
Coefficient of variation (CV)0.031226074
Kurtosis0.3410076
Mean187272.28
Median Absolute Deviation (MAD)3637.492
Skewness0.33299506
Sum5.7286591 × 108
Variance34196509
MonotonicityNot monotonic
2024-04-18T04:02:11.987272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
187602.933160728 63
 
2.0%
186099.137533193 25
 
0.8%
179553.867031936 23
 
0.7%
184402.96650913 21
 
0.7%
194600.671124104 15
 
0.5%
187606.035424193 13
 
0.4%
183052.21115244 13
 
0.4%
187707.586117775 12
 
0.4%
186791.519406736 12
 
0.4%
181532.301423753 12
 
0.4%
Other values (2315) 2850
90.8%
(Missing) 81
 
2.6%
ValueCountFrequency (%)
170813.584718477 1
 
< 0.1%
174096.498143437 1
 
< 0.1%
174097.616386311 1
 
< 0.1%
174140.916066183 1
 
< 0.1%
174156.617297535 1
 
< 0.1%
174173.508031304 1
 
< 0.1%
174211.496764498 1
 
< 0.1%
174289.976688419 1
 
< 0.1%
174307.148168245 1
 
< 0.1%
174422.480246459 3
0.1%
ValueCountFrequency (%)
206353.855586145 1
 
< 0.1%
206267.822551616 1
 
< 0.1%
206184.609573703 1
 
< 0.1%
206120.302153948 3
0.1%
206070.223360046 1
 
< 0.1%
206029.122466099 1
 
< 0.1%
206010.552884139 1
 
< 0.1%
205995.903772118 1
 
< 0.1%
205690.94819215 2
0.1%
205620.650144116 2
0.1%

위생업태명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
제과점영업
3140 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제과점영업 3140
100.0%

Length

2024-04-18T04:02:12.104406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:12.177919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제과점영업 3140
100.0%

남성종사자수
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
2052 
0
1002 
1
 
68
2
 
13
3
 
3

Length

Max length4
Median length4
Mean length2.9605096
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2052
65.4%
0 1002
31.9%
1 68
 
2.2%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%

Length

2024-04-18T04:02:12.258382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:12.345150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2052
65.4%
0 1002
31.9%
1 68
 
2.2%
2 13
 
0.4%
3 3
 
0.1%
4 2
 
0.1%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)0.5%
Missing2047
Missing (%)65.2%
Infinite0
Infinite (%)0.0%
Mean0.11436414
Minimum0
Maximum11
Zeros998
Zeros (%)31.8%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:12.423943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum11
Range11
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.50155845
Coefficient of variation (CV)4.3856271
Kurtosis211.86283
Mean0.11436414
Median Absolute Deviation (MAD)0
Skewness11.380325
Sum125
Variance0.25156088
MonotonicityNot monotonic
2024-04-18T04:02:12.498925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 998
31.8%
1 79
 
2.5%
2 12
 
0.4%
4 2
 
0.1%
3 1
 
< 0.1%
11 1
 
< 0.1%
(Missing) 2047
65.2%
ValueCountFrequency (%)
0 998
31.8%
1 79
 
2.5%
2 12
 
0.4%
3 1
 
< 0.1%
4 2
 
0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
11 1
 
< 0.1%
4 2
 
0.1%
3 1
 
< 0.1%
2 12
 
0.4%
1 79
 
2.5%
0 998
31.8%

영업장주변구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
2131 
기타
718 
주택가주변
 
149
아파트지역
 
100
유흥업소밀집지역
 
30
Other values (2)
 
12

Length

Max length8
Median length4
Mean length3.6751592
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2131
67.9%
기타 718
 
22.9%
주택가주변 149
 
4.7%
아파트지역 100
 
3.2%
유흥업소밀집지역 30
 
1.0%
학교정화(상대) 11
 
0.4%
결혼예식장주변 1
 
< 0.1%

Length

2024-04-18T04:02:12.590088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:12.674651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2131
67.9%
기타 718
 
22.9%
주택가주변 149
 
4.7%
아파트지역 100
 
3.2%
유흥업소밀집지역 30
 
1.0%
학교정화(상대 11
 
0.4%
결혼예식장주변 1
 
< 0.1%

등급구분명
Categorical

IMBALANCE 

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
2281 
기타
603 
자율
250 
우수
 
3
지도
 
2

Length

Max length4
Median length4
Mean length3.4528662
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 2281
72.6%
기타 603
 
19.2%
자율 250
 
8.0%
우수 3
 
0.1%
지도 2
 
0.1%
관리 1
 
< 0.1%

Length

2024-04-18T04:02:12.785589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:12.872360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 2281
72.6%
기타 603
 
19.2%
자율 250
 
8.0%
우수 3
 
0.1%
지도 2
 
0.1%
관리 1
 
< 0.1%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
상수도전용
1621 
<NA>
1516 
간이상수도
 
2
지하수전용
 
1

Length

Max length5
Median length5
Mean length4.5171975
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
상수도전용 1621
51.6%
<NA> 1516
48.3%
간이상수도 2
 
0.1%
지하수전용 1
 
< 0.1%

Length

2024-04-18T04:02:12.963216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:13.044786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상수도전용 1621
51.6%
na 1516
48.3%
간이상수도 2
 
0.1%
지하수전용 1
 
< 0.1%

총종업원수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

본사종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
3135 
0
 
5

Length

Max length4
Median length4
Mean length3.9952229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3135
99.8%
0 5
 
0.2%

Length

2024-04-18T04:02:13.160042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:13.239989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3135
99.8%
0 5
 
0.2%

공장사무직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
3135 
0
 
5

Length

Max length4
Median length4
Mean length3.9952229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3135
99.8%
0 5
 
0.2%

Length

2024-04-18T04:02:13.321409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:13.398223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3135
99.8%
0 5
 
0.2%

공장판매직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
3135 
0
 
5

Length

Max length4
Median length4
Mean length3.9952229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3135
99.8%
0 5
 
0.2%

Length

2024-04-18T04:02:13.476396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:13.552290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3135
99.8%
0 5
 
0.2%

공장생산직종업원수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
3135 
0
 
5

Length

Max length4
Median length4
Mean length3.9952229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3135
99.8%
0 5
 
0.2%

Length

2024-04-18T04:02:13.630259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:13.706858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3135
99.8%
0 5
 
0.2%

건물소유구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

보증액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
3135 
0
 
5

Length

Max length4
Median length4
Mean length3.9952229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3135
99.8%
0 5
 
0.2%

Length

2024-04-18T04:02:13.792470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:13.869877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3135
99.8%
0 5
 
0.2%

월세액
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size24.7 KiB
<NA>
3135 
0
 
5

Length

Max length4
Median length4
Mean length3.9952229
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 3135
99.8%
0 5
 
0.2%

Length

2024-04-18T04:02:13.951124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T04:02:14.028953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 3135
99.8%
0 5
 
0.2%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.2 KiB
False
3088 
True
 
52
ValueCountFrequency (%)
False 3088
98.3%
True 52
 
1.7%
2024-04-18T04:02:14.096113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

시설총규모
Real number (ℝ)

ZEROS 

Distinct2126
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.752936
Minimum0
Maximum780.5
Zeros229
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size27.7 KiB
2024-04-18T04:02:14.181199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120.975
median36.32
Q362.8525
95-th percentile134.2525
Maximum780.5
Range780.5
Interquartile range (IQR)41.8775

Descriptive statistics

Standard deviation52.943761
Coefficient of variation (CV)1.0641334
Kurtosis41.340465
Mean49.752936
Median Absolute Deviation (MAD)19.48
Skewness4.5382517
Sum156224.22
Variance2803.0418
MonotonicityNot monotonic
2024-04-18T04:02:14.298551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 229
 
7.3%
33.0 18
 
0.6%
24.0 17
 
0.5%
20.0 13
 
0.4%
42.0 11
 
0.4%
36.0 11
 
0.4%
25.0 11
 
0.4%
26.0 11
 
0.4%
15.0 11
 
0.4%
23.1 10
 
0.3%
Other values (2116) 2798
89.1%
ValueCountFrequency (%)
0.0 229
7.3%
0.25 1
 
< 0.1%
0.7 1
 
< 0.1%
0.9 1
 
< 0.1%
0.91 1
 
< 0.1%
1.0 5
 
0.2%
1.2 1
 
< 0.1%
1.21 2
 
0.1%
1.4 1
 
< 0.1%
1.49 1
 
< 0.1%
ValueCountFrequency (%)
780.5 1
< 0.1%
722.81 1
< 0.1%
695.26 1
< 0.1%
691.9 1
< 0.1%
605.0 1
< 0.1%
415.71 1
< 0.1%
395.77 1
< 0.1%
356.96 1
< 0.1%
335.04 1
< 0.1%
322.42 1
< 0.1%

전통업소지정번호
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing3139
Missing (%)> 99.9%
Memory size24.7 KiB
2024-04-18T04:02:14.366090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
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

Unique1 ?
Unique (%)100.0%

Sample

1st row-+
ValueCountFrequency (%)
1
100.0%
2024-04-18T04:02:14.503589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1
50.0%
+ 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Dash Punctuation 1
50.0%
Math Symbol 1
50.0%

Most frequent character per category

Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1
50.0%
+ 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1
50.0%
+ 1
50.0%

전통업소주된음식
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

홈페이지
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

Unnamed: 47
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3140
Missing (%)100.0%
Memory size27.7 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
01제과점영업07_22_18_P32800003280000-121-1996-0000319961118<NA>1영업/정상1영업<NA><NA><NA><NA>051 416385770.88606802부산광역시 영도구 남항동2가 271-1 272-3,274-2,274-3부산광역시 영도구 남항로 40-1 (남항동2가,272-3,274-2,274-3)49055파리바게트 영도남항점20201127140539U2020-11-29 02:40:00.0제과점영업386026.782302178511.723648제과점영업<NA><NA>기타기타상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N70.88<NA><NA><NA><NA>
12제과점영업07_22_18_P32500003250000-121-2011-0000620110728<NA>1영업/정상1영업<NA><NA><NA><NA>051 4663202111.0600815부산광역시 중구 중앙동4가 36-14번지 (1층)부산광역시 중구 해관로 65, 1층 (중앙동4가)48930파리바게뜨20130319111118I2018-08-31 23:59:59.0제과점영업385502.49232180297.579331제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N111.0<NA><NA><NA><NA>
23제과점영업07_22_18_P32500003250000-121-2014-0000320140320<NA>1영업/정상1영업<NA><NA><NA><NA><NA>85.95600051부산광역시 중구 창선동1가 12-1번지 1층 일부부산광역시 중구 광복로39번길 6 (창선동1가)48947비엔씨제과광복점20150413115934I2018-08-31 23:59:59.0제과점영업384993.660073179733.755299제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N85.95<NA><NA><NA><NA>
34제과점영업07_22_18_P32500003250000-121-2014-0000520140826<NA>1영업/정상1영업<NA><NA><NA><NA>02 2670654671.28600017부산광역시 중구 중앙동7가 20-1 롯데몰마트시네마동롯데마트부산광복점지하1부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데몰마트시네마동롯데마트부산광복점지하1)48944베이커리팩토리 광복점20201124163953U2020-11-26 02:40:00.0제과점영업385590.814677179553.867032제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y71.28<NA><NA><NA><NA>
45제과점영업07_22_18_P32500003250000-121-2015-0000320150706<NA>1영업/정상1영업<NA><NA><NA><NA>051 255 077133.04600807부산광역시 중구 부평동2가 45-13번지 1층부산광역시 중구 보수대로 16, 1층 (부평동2가)48980타임 베이커리20200317154332U2020-03-19 02:40:00.0제과점영업384614.3322179577.888166제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N33.04<NA><NA><NA><NA>
56제과점영업07_22_18_P32500003250000-121-2015-0000620151228<NA>1영업/정상1영업<NA><NA><NA><NA>051 464 700742.15600092부산광역시 중구 대청동2가 22-4번지 외1필지부산광역시 중구 대청로 90-1, 1층 (대청동2가)48947빵장수단팥빵20170210104844I2018-08-31 23:59:59.0제과점영업385002.672042180069.624291제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N42.15<NA><NA><NA><NA>
67제과점영업07_22_18_P32500003250000-121-2016-0000820161117<NA>1영업/정상1영업<NA><NA><NA><NA>051 612 422596.23600806부산광역시 중구 부평동2가 72-2번지부산광역시 중구 부평1길 49, 지하1층, 1층 (부평동2가)48977겐츠베이커리 부평시장점20161117143321I2018-08-31 23:59:59.0제과점영업384637.844483179947.236224제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N96.23<NA><NA><NA><NA>
78제과점영업07_22_18_P32500003250000-121-2017-0000220170330<NA>1영업/정상1영업<NA><NA><NA><NA>070 8815151211.44600017부산광역시 중구 중앙동7가 1-2번지부산광역시 중구 중앙대로 2, 지하1층 (중앙동7가, 롯데백화점광복점)48944대구근대골목단팥빵 광복롯데점20170417144912I2018-08-31 23:59:59.0제과점영업385649.488635179526.735317제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N11.44<NA><NA><NA><NA>
89제과점영업07_22_18_P32500003250000-121-2018-0000120180313<NA>1영업/정상1영업<NA><NA><NA><NA>051 6225300171.21600017부산광역시 중구 중앙동7가 20-1번지 롯데백화점광복점부산광역시 중구 중앙대로 2, 롯데백화점광복점 지상 4층 (중앙동7가)48944카페 아슬란20180313174733I2018-08-31 23:59:59.0제과점영업385590.814677179553.867032제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>Y171.21<NA><NA><NA><NA>
910제과점영업07_22_18_P32600003260000-121-2007-0005120021128<NA>1영업/정상1영업<NA><NA><NA><NA>051 257 222064.19602811부산광역시 서구 동대신동2가 331-2부산광역시 서구 구덕로 320 (동대신동2가)49217모젤과자점20210105164825U2021-01-07 02:40:00.0제과점영업383799.588946181106.417946제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N64.19<NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)위생업태명남성종사자수여성종사자수영업장주변구분명등급구분명급수시설구분명총종업원수본사종업원수공장사무직종업원수공장판매직종업원수공장생산직종업원수건물소유구분명보증액월세액다중이용업소여부시설총규모전통업소지정번호전통업소주된음식홈페이지Unnamed: 47
31303131제과점영업07_22_18_P33800003380000-121-2018-0001020181126<NA>3폐업2폐업20181226<NA><NA><NA><NA>58.41613831부산광역시 수영구 수영동 465-19번지부산광역시 수영구 연수로357번길 17-10, 1층 (수영동)48231꽃피는4월밀익는5월20181226172125U2018-12-28 02:40:00.0제과점영업392172.553354187922.020585제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N58.41<NA><NA><NA><NA>
31313132제과점영업07_22_18_P33100003310000-121-2018-0001820181120<NA>3폐업2폐업20201221<NA><NA><NA>051 611116143.6608090부산광역시 남구 용호동 954 더블유부산광역시 남구 분포로 145, 더블유스퀘어동 2층 2045호 (용호동, 더블유)48515오연당용호W20201221150925U2020-12-23 02:40:00.0제과점영업392495.046848183633.944535제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N43.6<NA><NA><NA><NA>
31323133제과점영업07_22_18_P33800003380000-121-2018-0001120181221<NA>3폐업2폐업20190410<NA><NA><NA><NA>32.8613832부산광역시 수영구 수영동 483-7번지부산광역시 수영구 구락로 61, 1층 (수영동)48225골든벨베이커리20190410163618U2019-04-12 02:40:00.0제과점영업392819.056323187998.552611제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N32.8<NA><NA><NA><NA>
31333134제과점영업07_22_18_P33100003310000-121-2018-0001620181112<NA>3폐업2폐업20191112<NA><NA><NA><NA>6.0608090부산광역시 남구 용호동 954번지 더블유부산광역시 남구 분포로 145, 1층 1201호 (용호동, 더블유)48515오브네20191112152113U2019-11-14 02:40:00.0제과점영업392495.046848183633.944535제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N6.0<NA><NA><NA><NA>
31343135제과점영업07_22_18_P33100003310000-121-2018-0001720181112<NA>3폐업2폐업20210215<NA><NA><NA><NA>12.08608090부산광역시 남구 용호동 954 더블유부산광역시 남구 분포로 145, 더블유스퀘어동 2층 2105호 (용호동, 더블유)48515이공이공(2020)20210215101432U2021-02-17 02:40:00.0제과점영업392495.046848183633.944535제과점영업<NA><NA><NA><NA>상수도전용<NA><NA><NA><NA><NA><NA><NA><NA>N12.08<NA><NA><NA><NA>
31353136제과점영업07_22_18_P33300003330000-121-2020-0002720201221<NA>3폐업2폐업20201225<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1495 신세계백화점센텀시티점부산광역시 해운대구 센텀남대로 35, 신세계백화점센텀시티점 지하1층 일부호 (우동)48058파티세리 몽슈슈 현대백화점 판교점20201226041508U2020-12-29 02:40:00.0제과점영업393952.264486187602.933161제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
31363137제과점영업07_22_18_P33300003330000-121-2020-0002820201221<NA>3폐업2폐업20201225<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1495 신세계백화점센텀시티점부산광역시 해운대구 센텀남대로 35, 신세계백화점센텀시티점 지하1층 일부호 (우동)48058움트20201226041508U2020-12-29 02:40:00.0제과점영업393952.264486187602.933161제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
31373138제과점영업07_22_18_P33300003330000-121-2020-0002420201202<NA>3폐업2폐업20201206<NA><NA><NA><NA><NA>612704부산광역시 해운대구 우동 1500 벡스코부산광역시 해운대구 APEC로 55, 벡스코 제1전시장 (우동)48060세자매바른빵20201207041509U2020-12-09 02:40:00.0제과점영업394482.139208187606.035424제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
31383139제과점영업07_22_18_P33300003330000-121-2020-0002920201222<NA>3폐업2폐업20201225<NA><NA><NA><NA><NA>612020부산광역시 해운대구 우동 1495 신세계백화점센텀시티점부산광역시 해운대구 센텀남대로 35, 신세계백화점센텀시티점 지하1층 일부호 (우동)48058더메나쥬리 센텀점20201226041508U2020-12-29 02:40:00.0제과점영업393952.264486187602.933161제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>
31393140제과점영업07_22_18_P32500003250000-121-2021-0000120210122<NA>3폐업2폐업20210128<NA><NA><NA><NA><NA>600017부산광역시 중구 중앙동7가 20-1 롯데백화점광복점부산광역시 중구 중앙대로 2, 롯데백화점광복점 지하1층 (중앙동7가)48944프띠르20210129041509U2021-01-31 02:40:00.0제과점영업385590.814677179553.867032제과점영업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N0.0<NA><NA><NA><NA>