Overview

Dataset statistics

Number of variables31
Number of observations93
Missing cells712
Missing cells (%)24.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.5 KiB
Average record size in memory269.4 B

Variable types

Numeric10
Categorical10
Unsupported6
Text5

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123136

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
휴업시작일자 is highly imbalanced (91.4%)Imbalance
휴업종료일자 is highly imbalanced (91.4%)Imbalance
인허가취소일자 has 93 (100.0%) missing valuesMissing
폐업일자 has 55 (59.1%) missing valuesMissing
재개업일자 has 93 (100.0%) missing valuesMissing
소재지전화 has 1 (1.1%) missing valuesMissing
소재지면적 has 93 (100.0%) missing valuesMissing
소재지우편번호 has 44 (47.3%) missing valuesMissing
소재지전체주소 has 4 (4.3%) missing valuesMissing
도로명전체주소 has 12 (12.9%) missing valuesMissing
도로명우편번호 has 27 (29.0%) missing valuesMissing
업태구분명 has 93 (100.0%) missing valuesMissing
좌표정보(x) has 5 (5.4%) missing valuesMissing
좌표정보(y) has 5 (5.4%) missing valuesMissing
사무소전화번호 has 1 (1.1%) missing valuesMissing
사업장전화번호 has 93 (100.0%) missing valuesMissing
Unnamed: 30 has 93 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
사업장명 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 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
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
사업장전화번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 30 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-17 04:04:41.966917
Analysis finished2024-04-17 04:04:42.328898
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47
Minimum1
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:42.383392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.6
Q124
median47
Q370
95-th percentile88.4
Maximum93
Range92
Interquartile range (IQR)46

Descriptive statistics

Standard deviation26.990739
Coefficient of variation (CV)0.57427105
Kurtosis-1.2
Mean47
Median Absolute Deviation (MAD)23
Skewness0
Sum4371
Variance728.5
MonotonicityStrictly increasing
2024-04-17T13:04:42.487876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
60 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
계량기증명업
93 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
계량기증명업 93
100.0%

Length

2024-04-17T13:04:42.582961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:42.651972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
계량기증명업 93
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size876.0 B
09_28_04_P
93 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_28_04_P
2nd row09_28_04_P
3rd row09_28_04_P
4th row09_28_04_P
5th row09_28_04_P

Common Values

ValueCountFrequency (%)
09_28_04_P 93
100.0%

Length

2024-04-17T13:04:42.730766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:42.812337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_28_04_p 93
100.0%

개방자치단체코드
Real number (ℝ)

Distinct14
Distinct (%)15.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3348709.7
Minimum3260000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:42.877557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3260000
5-th percentile3280000
Q13330000
median3350000
Q33390000
95-th percentile3400000
Maximum3400000
Range140000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation38199.3
Coefficient of variation (CV)0.01140717
Kurtosis-0.61689184
Mean3348709.7
Median Absolute Deviation (MAD)40000
Skewness-0.47155052
Sum3.1143 × 108
Variance1.4591865 × 109
MonotonicityNot monotonic
2024-04-17T13:04:42.968468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3390000 22
23.7%
3340000 21
22.6%
3360000 13
14.0%
3400000 7
 
7.5%
3310000 7
 
7.5%
3350000 5
 
5.4%
3300000 4
 
4.3%
3280000 3
 
3.2%
3290000 3
 
3.2%
3270000 2
 
2.2%
Other values (4) 6
 
6.5%
ValueCountFrequency (%)
3260000 2
 
2.2%
3270000 2
 
2.2%
3280000 3
 
3.2%
3290000 3
 
3.2%
3300000 4
 
4.3%
3310000 7
 
7.5%
3320000 2
 
2.2%
3330000 1
 
1.1%
3340000 21
22.6%
3350000 5
 
5.4%
ValueCountFrequency (%)
3400000 7
 
7.5%
3390000 22
23.7%
3370000 1
 
1.1%
3360000 13
14.0%
3350000 5
 
5.4%
3340000 21
22.6%
3330000 1
 
1.1%
3320000 2
 
2.2%
3310000 7
 
7.5%
3300000 4
 
4.3%

관리번호
Real number (ℝ)

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0019048 × 1018
Minimum1.979339 × 1018
Maximum2.018339 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:43.075442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.979339 × 1018
5-th percentile1.9819366 × 1018
Q11.999331 × 1018
median2.002326 × 1018
Q32.008331 × 1018
95-th percentile2.0163348 × 1018
Maximum2.018339 × 1018
Range3.9000008 × 1016
Interquartile range (IQR)9 × 1015

Descriptive statistics

Standard deviation9.6472293 × 1015
Coefficient of variation (CV)0.0048190251
Kurtosis-0.067504497
Mean2.0019048 × 1018
Median Absolute Deviation (MAD)5.0139976 × 1015
Skewness-0.61456023
Sum1.7097026 × 1018
Variance9.3069033 × 1031
MonotonicityNot monotonic
2024-04-17T13:04:43.197917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007336006906500001 1
 
1.1%
1985339001506500022 1
 
1.1%
2006335008706500003 1
 
1.1%
2006335001506500001 1
 
1.1%
1999336001306500001 1
 
1.1%
2005337001406500001 1
 
1.1%
1984339001506500029 1
 
1.1%
1998339001506500035 1
 
1.1%
2000339005606500040 1
 
1.1%
1980339001506500020 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
1979339001506500018 1
1.1%
1980333001506500001 1
1.1%
1980339001506500020 1
1.1%
1981332000006500001 1
1.1%
1981339001506500024 1
1.1%
1982335001506500003 1
1.1%
1983339001506500002 1
1.1%
1984331000006500001 1
1.1%
1984339001506500029 1
1.1%
1985339001506500022 1
1.1%
ValueCountFrequency (%)
2018339009106500002 1
1.1%
2018328009206500001 1
1.1%
2016340007206500001 1
1.1%
2016336013606500003 1
1.1%
2016336013606500002 1
1.1%
2016334008006500001 1
1.1%
2015340004406500001 1
1.1%
2015334008006500001 1
1.1%
2014339008306500001 1
1.1%
2014336010506500001 1
1.1%

인허가일자
Real number (ℝ)

Distinct91
Distinct (%)97.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19997150
Minimum19790327
Maximum20181123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:43.320947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19790327
5-th percentile19810516
Q119900310
median20010614
Q320081027
95-th percentile20160654
Maximum20181123
Range390796
Interquartile range (IQR)180717

Descriptive statistics

Standard deviation110001.83
Coefficient of variation (CV)0.0055008754
Kurtosis-1.0933203
Mean19997150
Median Absolute Deviation (MAD)89716
Skewness-0.25127597
Sum1.8597349 × 109
Variance1.2100402 × 1010
MonotonicityNot monotonic
2024-04-17T13:04:43.442015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20110523 2
 
2.2%
19810516 2
 
2.2%
20120418 1
 
1.1%
20060209 1
 
1.1%
20060123 1
 
1.1%
20060627 1
 
1.1%
20050416 1
 
1.1%
19841121 1
 
1.1%
19980928 1
 
1.1%
20000824 1
 
1.1%
Other values (81) 81
87.1%
ValueCountFrequency (%)
19790327 1
1.1%
19800227 1
1.1%
19800908 1
1.1%
19801118 1
1.1%
19810516 2
2.2%
19820622 1
1.1%
19830926 1
1.1%
19840817 1
1.1%
19841121 1
1.1%
19850423 1
1.1%
ValueCountFrequency (%)
20181123 1
1.1%
20180808 1
1.1%
20160930 1
1.1%
20160818 1
1.1%
20160714 1
1.1%
20160614 1
1.1%
20150730 1
1.1%
20150217 1
1.1%
20140822 1
1.1%
20140619 1
1.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
1
52 
3
40 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 52
55.9%
3 40
43.0%
2 1
 
1.1%

Length

2024-04-17T13:04:43.583195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:43.654292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 52
55.9%
3 40
43.0%
2 1
 
1.1%

영업상태명
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
영업/정상
52 
폐업
40 
휴업
 
1

Length

Max length5
Median length5
Mean length3.6774194
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 52
55.9%
폐업 40
43.0%
휴업 1
 
1.1%

Length

2024-04-17T13:04:43.734600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:43.812664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 52
55.9%
폐업 40
43.0%
휴업 1
 
1.1%

상세영업상태코드
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
1
52 
3
40 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 52
55.9%
3 40
43.0%
2 1
 
1.1%

Length

2024-04-17T13:04:43.889077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:43.957694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 52
55.9%
3 40
43.0%
2 1
 
1.1%

상세영업상태명
Categorical

Distinct3
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
영업중
52 
폐업
40 
휴업
 
1

Length

Max length3
Median length3
Mean length2.5591398
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row휴업
2nd row영업중
3rd row영업중
4th row영업중
5th row영업중

Common Values

ValueCountFrequency (%)
영업중 52
55.9%
폐업 40
43.0%
휴업 1
 
1.1%

Length

2024-04-17T13:04:44.277935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:44.351712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 52
55.9%
폐업 40
43.0%
휴업 1
 
1.1%

폐업일자
Real number (ℝ)

MISSING 

Distinct37
Distinct (%)97.4%
Missing55
Missing (%)59.1%
Infinite0
Infinite (%)0.0%
Mean20103444
Minimum20001214
Maximum20201015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:44.437592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001214
5-th percentile20019607
Q120071227
median20096120
Q320130493
95-th percentile20200751
Maximum20201015
Range199801
Interquartile range (IQR)59266.25

Descriptive statistics

Standard deviation49877.088
Coefficient of variation (CV)0.002481022
Kurtosis-0.13043224
Mean20103444
Median Absolute Deviation (MAD)25750.5
Skewness0.15737009
Sum7.6393089 × 108
Variance2.4877239 × 109
MonotonicityNot monotonic
2024-04-17T13:04:44.542347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20071227 2
 
2.2%
20021104 1
 
1.1%
20011126 1
 
1.1%
20201015 1
 
1.1%
20201005 1
 
1.1%
20040503 1
 
1.1%
20140721 1
 
1.1%
20110930 1
 
1.1%
20120529 1
 
1.1%
20091123 1
 
1.1%
Other values (27) 27
29.0%
(Missing) 55
59.1%
ValueCountFrequency (%)
20001214 1
1.1%
20011126 1
1.1%
20021104 1
1.1%
20040102 1
1.1%
20040503 1
1.1%
20061107 1
1.1%
20070221 1
1.1%
20070320 1
1.1%
20070418 1
1.1%
20071227 2
2.2%
ValueCountFrequency (%)
20201015 1
1.1%
20201005 1
1.1%
20200706 1
1.1%
20181221 1
1.1%
20161013 1
1.1%
20160930 1
1.1%
20151124 1
1.1%
20141114 1
1.1%
20140721 1
1.1%
20130614 1
1.1%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
92 
20200101
 
1

Length

Max length8
Median length4
Mean length4.0430108
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
98.9%
20200101 1
 
1.1%

Length

2024-04-17T13:04:44.652838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:44.733484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
98.9%
20200101 1
 
1.1%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
<NA>
92 
29990909
 
1

Length

Max length8
Median length4
Mean length4.0430108
Min length4

Unique

Unique1 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 92
98.9%
29990909 1
 
1.1%

Length

2024-04-17T13:04:44.814062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:44.889822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 92
98.9%
29990909 1
 
1.1%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

소재지전화
Text

MISSING 

Distinct91
Distinct (%)98.9%
Missing1
Missing (%)1.1%
Memory size876.0 B
2024-04-17T13:04:45.087224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.195652
Min length7

Characters and Unicode

Total characters1030
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

Unique90 ?
Unique (%)97.8%

Sample

1st row051 8315100
2nd row051 518 4555
3rd row051 728 5583
4th row051 7228702
5th row051 728 5579
ValueCountFrequency (%)
051 65
31.4%
728 3
 
1.4%
262 3
 
1.4%
301 3
 
1.4%
266 3
 
1.4%
315 3
 
1.4%
4517 3
 
1.4%
727 2
 
1.0%
941 2
 
1.0%
326 2
 
1.0%
Other values (116) 118
57.0%
2024-04-17T13:04:45.433819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 161
15.6%
1 159
15.4%
0 154
15.0%
120
11.7%
2 102
9.9%
3 83
8.1%
6 56
 
5.4%
8 56
 
5.4%
7 55
 
5.3%
4 46
 
4.5%
Other values (2) 38
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 908
88.2%
Space Separator 120
 
11.7%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 161
17.7%
1 159
17.5%
0 154
17.0%
2 102
11.2%
3 83
9.1%
6 56
 
6.2%
8 56
 
6.2%
7 55
 
6.1%
4 46
 
5.1%
9 36
 
4.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1030
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 161
15.6%
1 159
15.4%
0 154
15.0%
120
11.7%
2 102
9.9%
3 83
8.1%
6 56
 
5.4%
8 56
 
5.4%
7 55
 
5.3%
4 46
 
4.5%
Other values (2) 38
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 161
15.6%
1 159
15.4%
0 154
15.0%
120
11.7%
2 102
9.9%
3 83
8.1%
6 56
 
5.4%
8 56
 
5.4%
7 55
 
5.3%
4 46
 
4.5%
Other values (2) 38
 
3.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct40
Distinct (%)81.6%
Missing44
Missing (%)47.3%
Infinite0
Infinite (%)0.0%
Mean611764.88
Minimum601805
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:45.547346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum601805
5-th percentile602842
Q1604844
median611817
Q3617843
95-th percentile618374
Maximum619963
Range18158
Interquartile range (IQR)12999

Descriptive statistics

Standard deviation6334.0887
Coefficient of variation (CV)0.010353796
Kurtosis-1.7732978
Mean611764.88
Median Absolute Deviation (MAD)6027
Skewness-0.15442054
Sum29976479
Variance40120680
MonotonicityNot monotonic
2024-04-17T13:04:45.647332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
618280 3
 
3.2%
617805 3
 
3.2%
617020 2
 
2.2%
608080 2
 
2.2%
604836 2
 
2.2%
617843 2
 
2.2%
617844 2
 
2.2%
617825 1
 
1.1%
604804 1
 
1.1%
617841 1
 
1.1%
Other values (30) 30
32.3%
(Missing) 44
47.3%
ValueCountFrequency (%)
601805 1
1.1%
601837 1
1.1%
602030 1
1.1%
604060 1
1.1%
604804 1
1.1%
604806 1
1.1%
604817 1
1.1%
604826 1
1.1%
604827 1
1.1%
604836 2
2.2%
ValueCountFrequency (%)
619963 1
 
1.1%
618819 1
 
1.1%
618410 1
 
1.1%
618320 1
 
1.1%
618280 3
3.2%
618260 1
 
1.1%
618230 1
 
1.1%
617844 2
2.2%
617843 2
2.2%
617841 1
 
1.1%

소재지전체주소
Text

MISSING 

Distinct89
Distinct (%)100.0%
Missing4
Missing (%)4.3%
Memory size876.0 B
2024-04-17T13:04:45.913679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length33
Mean length22.741573
Min length12

Characters and Unicode

Total characters2024
Distinct characters112
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st row부산광역시 강서구 송정동 1540번지 2호
2nd row부산광역시 기장군 일광면 화전리 90-7번지
3rd row부산광역시 기장군 정관면 용수리 604번지 11호
4th row부산광역시 기장군 정관읍 달산리 148-13 정관농공단지입주기업체협의회
5th row부산광역시 사상구 감전동 500번지 26호
ValueCountFrequency (%)
부산광역시 88
 
20.0%
사상구 21
 
4.8%
사하구 20
 
4.5%
1호 11
 
2.5%
강서구 11
 
2.5%
학장동 9
 
2.0%
호 7
 
1.6%
감전동 7
 
1.6%
남구 7
 
1.6%
2호 6
 
1.4%
Other values (182) 253
57.5%
2024-04-17T13:04:46.293772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
362
17.9%
동 96
 
4.7%
산 96
 
4.7%
1 94
 
4.6%
부 93
 
4.6%
구 92
 
4.5%
광 90
 
4.4%
시 90
 
4.4%
역 89
 
4.4%
지 87
 
4.3%
Other values (102) 835
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1256
62.1%
Decimal Number 396
 
19.6%
Space Separator 362
 
17.9%
Dash Punctuation 10
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 96
 
7.6%
산 96
 
7.6%
부 93
 
7.4%
구 92
 
7.3%
광 90
 
7.2%
시 90
 
7.2%
역 89
 
7.1%
지 87
 
6.9%
번 83
 
6.6%
호 66
 
5.3%
Other values (90) 374
29.8%
Decimal Number
ValueCountFrequency (%)
1 94
23.7%
3 49
12.4%
2 40
10.1%
5 37
 
9.3%
7 34
 
8.6%
9 33
 
8.3%
4 31
 
7.8%
8 29
 
7.3%
6 28
 
7.1%
0 21
 
5.3%
Space Separator
ValueCountFrequency (%)
362
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1256
62.1%
Common 768
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 96
 
7.6%
산 96
 
7.6%
부 93
 
7.4%
구 92
 
7.3%
광 90
 
7.2%
시 90
 
7.2%
역 89
 
7.1%
지 87
 
6.9%
번 83
 
6.6%
호 66
 
5.3%
Other values (90) 374
29.8%
Common
ValueCountFrequency (%)
362
47.1%
1 94
 
12.2%
3 49
 
6.4%
2 40
 
5.2%
5 37
 
4.8%
7 34
 
4.4%
9 33
 
4.3%
4 31
 
4.0%
8 29
 
3.8%
6 28
 
3.6%
Other values (2) 31
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1256
62.1%
ASCII 768
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
362
47.1%
1 94
 
12.2%
3 49
 
6.4%
2 40
 
5.2%
5 37
 
4.8%
7 34
 
4.4%
9 33
 
4.3%
4 31
 
4.0%
8 29
 
3.8%
6 28
 
3.6%
Other values (2) 31
 
4.0%
Hangul
ValueCountFrequency (%)
동 96
 
7.6%
산 96
 
7.6%
부 93
 
7.4%
구 92
 
7.3%
광 90
 
7.2%
시 90
 
7.2%
역 89
 
7.1%
지 87
 
6.9%
번 83
 
6.6%
호 66
 
5.3%
Other values (90) 374
29.8%

도로명전체주소
Text

MISSING 

Distinct78
Distinct (%)96.3%
Missing12
Missing (%)12.9%
Memory size876.0 B
2024-04-17T13:04:46.562536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length29
Mean length24.851852
Min length20

Characters and Unicode

Total characters2013
Distinct characters139
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)92.6%

Sample

1st row부산광역시 강서구 송정길 26 (송정동)
2nd row부산광역시 기장군 장안읍 명례산단5로 93 ((주)현대철강)
3rd row부산광역시 기장군 장안읍 반룡로 68
4th row부산광역시 기장군 일광면 기장대로 996
5th row부산광역시 기장군 정관읍 용수로 94
ValueCountFrequency (%)
부산광역시 80
 
19.5%
사상구 21
 
5.1%
사하구 19
 
4.6%
강서구 10
 
2.4%
학장동 9
 
2.2%
기장군 7
 
1.7%
감천항로 6
 
1.5%
감전동 6
 
1.5%
신평동 6
 
1.5%
구평동 5
 
1.2%
Other values (188) 241
58.8%
2024-04-17T13:04:46.945570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
329
 
16.3%
산 96
 
4.8%
동 95
 
4.7%
부 83
 
4.1%
광 82
 
4.1%
시 82
 
4.1%
구 82
 
4.1%
역 81
 
4.0%
로 79
 
3.9%
) 76
 
3.8%
Other values (129) 928
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1264
62.8%
Space Separator 329
 
16.3%
Decimal Number 262
 
13.0%
Close Punctuation 76
 
3.8%
Open Punctuation 76
 
3.8%
Dash Punctuation 3
 
0.1%
Other Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 96
 
7.6%
동 95
 
7.5%
부 83
 
6.6%
광 82
 
6.5%
시 82
 
6.5%
구 82
 
6.5%
역 81
 
6.4%
로 79
 
6.2%
사 44
 
3.5%
대 33
 
2.6%
Other values (114) 507
40.1%
Decimal Number
ValueCountFrequency (%)
1 45
17.2%
6 32
12.2%
3 31
11.8%
2 30
11.5%
5 27
10.3%
9 24
9.2%
4 23
8.8%
7 20
7.6%
8 16
 
6.1%
0 14
 
5.3%
Space Separator
ValueCountFrequency (%)
329
100.0%
Close Punctuation
ValueCountFrequency (%)
) 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1264
62.8%
Common 749
37.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 96
 
7.6%
동 95
 
7.5%
부 83
 
6.6%
광 82
 
6.5%
시 82
 
6.5%
구 82
 
6.5%
역 81
 
6.4%
로 79
 
6.2%
사 44
 
3.5%
대 33
 
2.6%
Other values (114) 507
40.1%
Common
ValueCountFrequency (%)
329
43.9%
) 76
 
10.1%
( 76
 
10.1%
1 45
 
6.0%
6 32
 
4.3%
3 31
 
4.1%
2 30
 
4.0%
5 27
 
3.6%
9 24
 
3.2%
4 23
 
3.1%
Other values (5) 56
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1264
62.8%
ASCII 749
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
329
43.9%
) 76
 
10.1%
( 76
 
10.1%
1 45
 
6.0%
6 32
 
4.3%
3 31
 
4.1%
2 30
 
4.0%
5 27
 
3.6%
9 24
 
3.2%
4 23
 
3.1%
Other values (5) 56
 
7.5%
Hangul
ValueCountFrequency (%)
산 96
 
7.6%
동 95
 
7.5%
부 83
 
6.6%
광 82
 
6.5%
시 82
 
6.5%
구 82
 
6.5%
역 81
 
6.4%
로 79
 
6.2%
사 44
 
3.5%
대 33
 
2.6%
Other values (114) 507
40.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct48
Distinct (%)72.7%
Missing27
Missing (%)29.0%
Infinite0
Infinite (%)0.0%
Mean518395.76
Minimum41068
Maximum619961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:47.052818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41068
5-th percentile46212.75
Q1604817
median608820
Q3617843
95-th percentile619638.5
Maximum619961
Range578893
Interquartile range (IQR)13026

Descriptive statistics

Standard deviation212617.97
Coefficient of variation (CV)0.41014604
Kurtosis1.3874143
Mean518395.76
Median Absolute Deviation (MAD)9005.5
Skewness-1.8277146
Sum34214120
Variance4.5206401 × 1010
MonotonicityNot monotonic
2024-04-17T13:04:47.149963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
617843 5
 
5.4%
604836 4
 
4.3%
604817 3
 
3.2%
618818 3
 
3.2%
604826 2
 
2.2%
604844 2
 
2.2%
617826 2
 
2.2%
604806 2
 
2.2%
617804 2
 
2.2%
618280 2
 
2.2%
Other values (38) 39
41.9%
(Missing) 27
29.0%
ValueCountFrequency (%)
41068 1
1.1%
46004 1
1.1%
46020 1
1.1%
46028 1
1.1%
46767 1
1.1%
47026 1
1.1%
47027 1
1.1%
47030 1
1.1%
48936 1
1.1%
49048 1
1.1%
ValueCountFrequency (%)
619961 2
2.2%
619951 1
 
1.1%
619912 1
 
1.1%
618818 3
3.2%
618410 1
 
1.1%
618320 1
 
1.1%
618280 2
2.2%
618260 1
 
1.1%
618230 1
 
1.1%
617844 1
 
1.1%

사업장명
Text

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size876.0 B
2024-04-17T13:04:47.330327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length16
Mean length7.8924731
Min length2

Characters and Unicode

Total characters734
Distinct characters146
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)100.0%

Sample

1st row부산조선해양기자재공업협동조합
2nd row(주)현대철강
3rd row장안계량사
4th row신아시아드주유소
5th row정관계량증명업소
ValueCountFrequency (%)
계량증명업소 2
 
1.9%
부산시 2
 
1.9%
부산조선해양기자재공업협동조합 1
 
1.0%
부성자원 1
 
1.0%
우양비엔피산업(주 1
 
1.0%
남경eng 1
 
1.0%
남성계량증명업소 1
 
1.0%
대흥계량증명업소 1
 
1.0%
주)dsp 1
 
1.0%
대림계량증명업 1
 
1.0%
Other values (92) 92
88.5%
2024-04-17T13:04:47.633682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 65
 
8.9%
량 61
 
8.3%
업 42
 
5.7%
명 35
 
4.8%
소 34
 
4.6%
증 32
 
4.4%
사 30
 
4.1%
주 23
 
3.1%
) 18
 
2.5%
( 18
 
2.5%
Other values (136) 376
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 673
91.7%
Close Punctuation 18
 
2.5%
Open Punctuation 18
 
2.5%
Space Separator 11
 
1.5%
Uppercase Letter 10
 
1.4%
Lowercase Letter 4
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 65
 
9.7%
량 61
 
9.1%
업 42
 
6.2%
명 35
 
5.2%
소 34
 
5.1%
증 32
 
4.8%
사 30
 
4.5%
주 23
 
3.4%
부 15
 
2.2%
산 15
 
2.2%
Other values (124) 321
47.7%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
E 2
20.0%
N 2
20.0%
G 2
20.0%
P 1
10.0%
D 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
50.0%
l 1
25.0%
t 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 673
91.7%
Common 47
 
6.4%
Latin 14
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 65
 
9.7%
량 61
 
9.1%
업 42
 
6.2%
명 35
 
5.2%
소 34
 
5.1%
증 32
 
4.8%
사 30
 
4.5%
주 23
 
3.4%
부 15
 
2.2%
산 15
 
2.2%
Other values (124) 321
47.7%
Latin
ValueCountFrequency (%)
S 2
14.3%
E 2
14.3%
N 2
14.3%
G 2
14.3%
e 2
14.3%
P 1
7.1%
D 1
7.1%
l 1
7.1%
t 1
7.1%
Common
ValueCountFrequency (%)
) 18
38.3%
( 18
38.3%
11
23.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 673
91.7%
ASCII 61
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 65
 
9.7%
량 61
 
9.1%
업 42
 
6.2%
명 35
 
5.2%
소 34
 
5.1%
증 32
 
4.8%
사 30
 
4.5%
주 23
 
3.4%
부 15
 
2.2%
산 15
 
2.2%
Other values (124) 321
47.7%
ASCII
ValueCountFrequency (%)
) 18
29.5%
( 18
29.5%
11
18.0%
S 2
 
3.3%
E 2
 
3.3%
N 2
 
3.3%
G 2
 
3.3%
e 2
 
3.3%
P 1
 
1.6%
D 1
 
1.6%
Other values (2) 2
 
3.3%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct93
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0153187 × 1013
Minimum1.9801118 × 1013
Maximum2.0210413 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:47.752305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9801118 × 1013
5-th percentile2.009092 × 1013
Q12.0120206 × 1013
median2.0161014 × 1013
Q32.0200722 × 1013
95-th percentile2.0201119 × 1013
Maximum2.0210413 × 1013
Range4.0929509 × 1011
Interquartile range (IQR)8.0516063 × 1010

Descriptive statistics

Standard deviation5.4282507 × 1010
Coefficient of variation (CV)0.0026934949
Kurtosis17.928163
Mean2.0153187 × 1013
Median Absolute Deviation (MAD)3.979796 × 1010
Skewness-3.0391831
Sum1.8742464 × 1015
Variance2.9465905 × 1021
MonotonicityNot monotonic
2024-04-17T13:04:47.868133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200814095951 1
 
1.1%
20120705171745 1
 
1.1%
20130131095553 1
 
1.1%
20131230133838 1
 
1.1%
20111118171138 1
 
1.1%
20140724145557 1
 
1.1%
20181221131115 1
 
1.1%
20111101095941 1
 
1.1%
20111101095356 1
 
1.1%
20160510183654 1
 
1.1%
Other values (83) 83
89.2%
ValueCountFrequency (%)
19801118000000 1
1.1%
20070725155227 1
1.1%
20080117164214 1
1.1%
20080814114418 1
1.1%
20090917171820 1
1.1%
20090921170119 1
1.1%
20091029115104 1
1.1%
20101005145317 1
1.1%
20101005145603 1
1.1%
20111004155908 1
1.1%
ValueCountFrequency (%)
20210413093053 1
1.1%
20210315181411 1
1.1%
20201214194729 1
1.1%
20201204105947 1
1.1%
20201119141937 1
1.1%
20201119141903 1
1.1%
20201117175330 1
1.1%
20201016092224 1
1.1%
20201005171439 1
1.1%
20200819134121 1
1.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
I
53 
U
40 

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 53
57.0%
U 40
43.0%

Length

2024-04-17T13:04:47.969403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:04:48.034729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 53
57.0%
u 40
43.0%

데이터갱신일자
Categorical

Distinct23
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size876.0 B
2018-08-31 23:59:59.0
53 
2018-11-14 02:37:25.0
9 
2020-08-16 02:40:00.0
6 
2020-09-16 02:40:00.0
 
3
2020-08-13 02:40:00.0
 
2
Other values (18)
20 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique16 ?
Unique (%)17.2%

Sample

1st row2020-08-16 02:40:00.0
2nd row2018-08-31 23:59:59.0
3rd row2018-08-31 23:59:59.0
4th row2020-09-16 02:40:00.0
5th row2020-09-16 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 53
57.0%
2018-11-14 02:37:25.0 9
 
9.7%
2020-08-16 02:40:00.0 6
 
6.5%
2020-09-16 02:40:00.0 3
 
3.2%
2020-08-13 02:40:00.0 2
 
2.2%
2019-04-27 02:40:00.0 2
 
2.2%
2020-11-21 02:40:00.0 2
 
2.2%
2020-08-21 02:40:00.0 1
 
1.1%
2019-05-03 02:40:00.0 1
 
1.1%
2020-07-24 02:40:00.0 1
 
1.1%
Other values (13) 13
 
14.0%

Length

2024-04-17T13:04:48.106039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 53
28.5%
23:59:59.0 53
28.5%
02:40:00.0 31
16.7%
2018-11-14 9
 
4.8%
02:37:25.0 9
 
4.8%
2020-08-16 6
 
3.2%
2020-09-16 3
 
1.6%
2020-11-21 2
 
1.1%
2019-04-27 2
 
1.1%
2020-08-13 2
 
1.1%
Other values (16) 16
 
8.6%

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct86
Distinct (%)97.7%
Missing5
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean382680.72
Minimum356180.95
Maximum405026
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:48.199259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum356180.95
5-th percentile368040.76
Q1379223.52
median380804.28
Q3387851
95-th percentile398834.97
Maximum405026
Range48845.046
Interquartile range (IQR)8627.4838

Descriptive statistics

Standard deviation8719.8498
Coefficient of variation (CV)0.022786227
Kurtosis0.97756995
Mean382680.72
Median Absolute Deviation (MAD)2250.4096
Skewness0.16720759
Sum33675904
Variance76035781
MonotonicityNot monotonic
2024-04-17T13:04:48.306570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
380212.195224684 2
 
2.2%
371574.572711084 2
 
2.2%
385618.319280073 1
 
1.1%
379497.39588861 1
 
1.1%
391342.758998944 1
 
1.1%
390807.628200016 1
 
1.1%
379225.358306865 1
 
1.1%
380375.948275017 1
 
1.1%
380105.77662477 1
 
1.1%
380000.180418859 1
 
1.1%
Other values (76) 76
81.7%
(Missing) 5
 
5.4%
ValueCountFrequency (%)
356180.953841 1
1.1%
366505.223718151 1
1.1%
366756.770372749 1
1.1%
367033.0 1
1.1%
367778.41698672 1
1.1%
368527.963331981 1
1.1%
369129.311995 1
1.1%
370083.902222437 1
1.1%
371574.572711084 2
2.2%
371953.608312036 1
1.1%
ValueCountFrequency (%)
405026.0 1
1.1%
404550.0 1
1.1%
403131.751907109 1
1.1%
400997.873851 1
1.1%
399291.393107116 1
1.1%
397987.323586 1
1.1%
397574.08926 1
1.1%
393249.98642228 1
1.1%
392795.577237073 1
1.1%
391951.039359675 1
1.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct86
Distinct (%)97.7%
Missing5
Missing (%)5.4%
Infinite0
Infinite (%)0.0%
Mean185705.73
Minimum175030.02
Maximum266134.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:04:48.417308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum175030.02
5-th percentile176386.15
Q1178491.89
median183248.41
Q3188996.61
95-th percentile205274.77
Maximum266134.08
Range91104.056
Interquartile range (IQR)10504.716

Descriptive statistics

Standard deviation11820.892
Coefficient of variation (CV)0.063653887
Kurtosis24.160958
Mean185705.73
Median Absolute Deviation (MAD)4924.6712
Skewness4.0266696
Sum16342105
Variance1.3973348 × 108
MonotonicityNot monotonic
2024-04-17T13:04:48.525027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
177000.001272676 2
 
2.2%
179871.937472082 2
 
2.2%
178305.429213849 1
 
1.1%
183644.027908648 1
 
1.1%
189750.203631661 1
 
1.1%
181223.764821635 1
 
1.1%
183207.467245556 1
 
1.1%
184288.424663376 1
 
1.1%
184702.733602538 1
 
1.1%
188154.771634835 1
 
1.1%
Other values (76) 76
81.7%
(Missing) 5
 
5.4%
ValueCountFrequency (%)
175030.023901 1
1.1%
175754.0 1
1.1%
176007.256068992 1
1.1%
176020.721137134 1
1.1%
176179.218722146 1
1.1%
176770.441373371 1
1.1%
176872.911098378 1
1.1%
177000.001272676 2
2.2%
177391.455047097 1
1.1%
177406.33287069 1
1.1%
ValueCountFrequency (%)
266134.079826 1
1.1%
210223.0 1
1.1%
207644.0 1
1.1%
205869.798004 1
1.1%
205560.000102 1
1.1%
204745.058572184 1
1.1%
204006.570249 1
1.1%
200389.809025544 1
1.1%
196220.89085736 1
1.1%
195631.608104829 1
1.1%

사무소전화번호
Text

MISSING 

Distinct91
Distinct (%)98.9%
Missing1
Missing (%)1.1%
Memory size876.0 B
2024-04-17T13:04:48.741905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.195652
Min length7

Characters and Unicode

Total characters1030
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

Unique90 ?
Unique (%)97.8%

Sample

1st row051 8315100
2nd row051 518 4555
3rd row051 728 5583
4th row051 7228702
5th row051 728 5579
ValueCountFrequency (%)
051 65
31.4%
728 3
 
1.4%
262 3
 
1.4%
301 3
 
1.4%
266 3
 
1.4%
315 3
 
1.4%
4517 3
 
1.4%
727 2
 
1.0%
941 2
 
1.0%
326 2
 
1.0%
Other values (116) 118
57.0%
2024-04-17T13:04:49.064553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 161
15.6%
1 159
15.4%
0 154
15.0%
120
11.7%
2 102
9.9%
3 83
8.1%
6 56
 
5.4%
8 56
 
5.4%
7 55
 
5.3%
4 46
 
4.5%
Other values (2) 38
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 908
88.2%
Space Separator 120
 
11.7%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 161
17.7%
1 159
17.5%
0 154
17.0%
2 102
11.2%
3 83
9.1%
6 56
 
6.2%
8 56
 
6.2%
7 55
 
6.1%
4 46
 
5.1%
9 36
 
4.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1030
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 161
15.6%
1 159
15.4%
0 154
15.0%
120
11.7%
2 102
9.9%
3 83
8.1%
6 56
 
5.4%
8 56
 
5.4%
7 55
 
5.3%
4 46
 
4.5%
Other values (2) 38
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1030
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 161
15.6%
1 159
15.4%
0 154
15.0%
120
11.7%
2 102
9.9%
3 83
8.1%
6 56
 
5.4%
8 56
 
5.4%
7 55
 
5.3%
4 46
 
4.5%
Other values (2) 38
 
3.7%

사업장전화번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

Unnamed: 30
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing93
Missing (%)100.0%
Memory size969.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)사무소전화번호사업장전화번호Unnamed: 30
01계량기증명업09_28_04_P3360000200733600690650000120070504<NA>2휴업2휴업<NA><NA><NA><NA>051 8315100<NA><NA>부산광역시 강서구 송정동 1540번지 2호부산광역시 강서구 송정길 26 (송정동)618818부산조선해양기자재공업협동조합20200814095951U2020-08-16 02:40:00.0<NA>367778.416987179326.717807051 8315100<NA><NA>
12계량기증명업09_28_04_P3400000201634000720650000120160614<NA>1영업/정상1영업중<NA><NA><NA><NA>051 518 4555<NA><NA><NA>부산광역시 기장군 장안읍 명례산단5로 93 ((주)현대철강)46028(주)현대철강20160614152004I2018-08-31 23:59:59.0<NA>404550.0210223.0051 518 4555<NA><NA>
23계량기증명업09_28_04_P3400000201534000440650000120150730<NA>1영업/정상1영업중<NA><NA><NA><NA>051 728 5583<NA><NA><NA>부산광역시 기장군 장안읍 반룡로 68619951장안계량사20150731103946I2018-08-31 23:59:59.0<NA>405026.0207644.0051 728 5583<NA><NA>
34계량기증명업09_28_04_P3400000200634000250650000120060403<NA>1영업/정상1영업중<NA><NA><NA><NA>051 7228702<NA><NA>부산광역시 기장군 일광면 화전리 90-7번지부산광역시 기장군 일광면 기장대로 996619912신아시아드주유소20200812094007U2020-09-16 02:40:00.0<NA>403131.751907200389.809026051 7228702<NA><NA>
45계량기증명업09_28_04_P3400000200034000250650000219921007<NA>1영업/정상1영업중<NA><NA><NA><NA>051 728 5579<NA>619963부산광역시 기장군 정관면 용수리 604번지 11호부산광역시 기장군 정관읍 용수로 9446004정관계량증명업소20200812094156U2020-09-16 02:40:00.0<NA>397574.08926205869.798004051 728 5579<NA><NA>
56계량기증명업09_28_04_P3400000200034000250650000119890809<NA>1영업/정상1영업중<NA><NA><NA><NA>051 728 5276<NA><NA>부산광역시 기장군 정관읍 달산리 148-13 정관농공단지입주기업체협의회부산광역시 기장군 정관읍 농공길 4, 정관농공단지입주기업체협의회46020정관농공단지입주기업체협의회20200812094208U2020-09-16 02:40:00.0<NA>399291.393107204745.058572051 728 5276<NA><NA>
67계량기증명업09_28_04_P3390000201833900910650000220181123<NA>1영업/정상1영업중<NA><NA><NA><NA>051 324 7005<NA><NA>부산광역시 사상구 감전동 500번지 26호부산광역시 사상구 낙동대로915번길 12 (감전동)47030(주)한성산업20190501090558U2019-05-03 02:40:00.0<NA>379382.680087184392.114864051 324 7005<NA><NA>
78계량기증명업09_28_04_P3390000201433900830650000120140822<NA>1영업/정상1영업중<NA><NA><NA><NA>051 305 0805<NA><NA><NA>부산광역시 사상구 사상로531번길 61 (모라동)617819명성계량증명업소20180627132835I2018-08-31 23:59:59.0<NA>380834.666883189966.941519051 305 0805<NA><NA>
89계량기증명업09_28_04_P3390000201133900830650000120110201<NA>1영업/정상1영업중<NA><NA><NA><NA>051 301 5772<NA>617826부산광역시 사상구 삼락동 363번지 10호부산광역시 사상구 모덕로 33 (삼락동)617826동화스틸 계량증명업소20120925202924I2018-08-31 23:59:59.0<NA>380304.867604188843.788292051 301 5772<NA><NA>
910계량기증명업09_28_04_P3390000200433900150650000120040213<NA>1영업/정상1영업중<NA><NA><NA><NA>051 317 1553<NA><NA>부산광역시 사상구 감전동 169번지 1호부산광역시 사상구 낙동대로 1014 (감전동)47027삼용공인계량증명업소20200722174830U2020-07-24 02:40:00.0<NA>379686.146743185275.080605051 317 1553<NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)사무소전화번호사업장전화번호Unnamed: 30
8384계량기증명업09_28_04_P3300000200233000160650001919860118<NA>3폐업3폐업20120529<NA><NA><NA>8536342<NA>607801부산광역시 동래구 낙민동 82번지 12호부산광역시 동래구 온천천로 357 (낙민동)607801원일계량증명업소20120611104105I2018-08-31 23:59:59.0<NA>390496.578976190293.4167998536342<NA><NA>
8485계량기증명업09_28_04_P3300000200233000160650001819850617<NA>3폐업3폐업20021104<NA><NA><NA>051524 0123<NA><NA>부산광역시 동래구 안락동 751-8번지<NA><NA>부산계량증명업소20111118140942I2018-08-31 23:59:59.0<NA><NA><NA>051524 0123<NA><NA>
8586계량기증명업09_28_04_P3300000200033000160650000120001013<NA>3폐업3폐업20091123<NA><NA><NA>051 502 0509<NA><NA>부산광역시 동래구 사직동 129-7번지부산광역시 동래구 여고로 57 (사직동)607818대상컴퓨터계량사20111118141053I2018-08-31 23:59:59.0<NA>388466.826431190527.204667051 502 0509<NA><NA>
8687계량기증명업09_28_04_P3300000199733000160650000419971026<NA>3폐업3폐업20070320<NA><NA><NA>051 5232243<NA><NA>부산광역시 동래구 안락동 769-8번지부산광역시 동래구 충렬대로348번길 8 (안락동)607829안락계량증명업소20111118141147I2018-08-31 23:59:59.0<NA>390812.442909190703.989023051 5232243<NA><NA>
8788계량기증명업09_28_04_P3290000200032900130650000120000919<NA>3폐업3폐업20080117<NA><NA><NA>05106436143<NA><NA>부산광역시 부산진구 범천동 842-36번지<NA><NA>태창계량증명업20080117164214I2018-08-31 23:59:59.0<NA><NA><NA>05106436143<NA><NA>
8889계량기증명업09_28_04_P3290000200032900000650000119991216<NA>3폐업3폐업20040102<NA><NA><NA>051 805 9376<NA>614868부산광역시 부산진구 전포동 890번지 36호<NA><NA>전포계량사20080814114418I2018-08-31 23:59:59.0<NA><NA><NA>051 805 9376<NA><NA>
8990계량기증명업09_28_04_P3290000200132900130650000120010614<NA>3폐업3폐업20061107<NA><NA><NA>005108948801<NA><NA>부산광역시 부산진구 당감동 382번지부산광역시 부산진구 당감서로 49 (당감동)614821백선공인계량20111030150021I2018-08-31 23:59:59.0<NA>385498.889615186980.608282005108948801<NA><NA>
9091계량기증명업09_28_04_P3280000200032800150650000219910520<NA>3폐업3폐업20200706<NA><NA><NA>051 417 0269<NA>606823부산광역시 영도구 청학1동 345번지부산광역시 영도구 태종로292번길 9-6 (청학동)606823청학계량사20200706173012U2020-07-08 02:40:00.0<NA>387570.528593179533.948857051 417 0269<NA><NA>
9192계량기증명업09_28_04_P3270000200032700140650000219870214<NA>3폐업3폐업20151124<NA><NA><NA>0051 4647766<NA>601837부산광역시 동구 초량3동 1185번지 37호부산광역시 동구 충장대로 117 (초량동)601837우창계량증명업소20151125100906I2018-08-31 23:59:59.0<NA>386114.750206181232.2054830051 4647766<NA><NA>
9293계량기증명업09_28_04_P3260000200232600490650000220021207<NA>3폐업3폐업<NA><NA><NA><NA>005102562171<NA><NA>부산광역시 서구 동대신동1가 181번지부산광역시 서구 보수대로 169 (동대신동1가)<NA>동대주유소20180614134931I2018-08-31 23:59:59.0<NA>384257.687141180920.413448005102562171<NA><NA>