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

Description2021-02-01
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 04:05:15.495611
Analysis finished2024-04-17 04:05:15.831652
Duration0.34 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
2024-04-17T13:05:15.887539image/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
2024-04-17T13:05:15.990343image/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

2024-04-17T13:05:16.082119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:16.146112image/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

2024-04-17T13:05:16.212173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:16.277607image/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
2024-04-17T13:05:16.335518image/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
2024-04-17T13:05:16.435031image/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%
3320000 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
2024-04-17T13:05:16.548584image/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
2024-04-17T13:05:16.666431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2007340002506500001 1
 
1.1%
2015334008006500001 1
 
1.1%
2011336009406500003 1
 
1.1%
2011336010506500002 1
 
1.1%
2011336011906500001 1
 
1.1%
2014336010506500001 1
 
1.1%
2016336013606500002 1
 
1.1%
2016336013606500003 1
 
1.1%
2002336001306500002 1
 
1.1%
2008336006906500001 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
2024-04-17T13:05:16.782264image/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
2024-04-17T13:05:16.896006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19810516 2
 
2.2%
20110523 2
 
2.2%
20070515 1
 
1.1%
20150217 1
 
1.1%
20110419 1
 
1.1%
20110916 1
 
1.1%
20140619 1
 
1.1%
20160714 1
 
1.1%
20160818 1
 
1.1%
20020709 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 row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

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

Length

2024-04-17T13:05:17.002090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:17.077777image/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 row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

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

Length

2024-04-17T13:05:17.159751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:17.234288image/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 row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

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

Length

2024-04-17T13:05:17.313296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:17.628510image/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 row폐업
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

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

Length

2024-04-17T13:05:17.703353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:17.776493image/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
2024-04-17T13:05:17.872948image/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
2024-04-17T13:05:17.979458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
20071227 2
 
2.2%
20110930 1
 
1.1%
20130614 1
 
1.1%
20081120 1
 
1.1%
20080930 1
 
1.1%
20181221 1
 
1.1%
20040503 1
 
1.1%
20140721 1
 
1.1%
20080117 1
 
1.1%
20120518 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 row20200101
5th row<NA>

Common Values

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

Length

2024-04-17T13:05:18.110293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:18.211467image/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 row29990909
5th row<NA>

Common Values

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

Length

2024-04-17T13:05:18.316158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:18.413379image/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
2024-04-17T13:05:18.601084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.184783
Min length7

Characters and Unicode

Total characters1029
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 727 7500
2nd row051 727 5759
3rd row051 332 5820
4th row051 336 2000
5th row005102622744
ValueCountFrequency (%)
051 65
31.4%
315 3
 
1.4%
266 3
 
1.4%
262 3
 
1.4%
301 3
 
1.4%
728 3
 
1.4%
4517 3
 
1.4%
326 2
 
1.0%
972 2
 
1.0%
727 2
 
1.0%
Other values (116) 118
57.0%
2024-04-17T13:05:18.901773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 161
15.6%
1 159
15.5%
0 154
15.0%
119
11.6%
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 119
 
11.6%
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 (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1029
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 161
15.6%
1 159
15.5%
0 154
15.0%
119
11.6%
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 1029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 161
15.6%
1 159
15.5%
0 154
15.0%
119
11.6%
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
2024-04-17T13:05:19.012931image/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
2024-04-17T13:05:19.116298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
617805 3
 
3.2%
618280 3
 
3.2%
608080 2
 
2.2%
617020 2
 
2.2%
617844 2
 
2.2%
617843 2
 
2.2%
604836 2
 
2.2%
617841 1
 
1.1%
618819 1
 
1.1%
618410 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
2024-04-17T13:05:19.429884image/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 기장군 정관면 달산리 938번지
2nd row부산광역시 기장군 정관면 예림리 340번지
3rd row부산광역시 북구 덕천동 330번지 2 호
4th row부산광역시 북구 만덕동 산19번지 5 호
5th row부산광역시 사하구 구평동 178번지 11호
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%
남구 7
 
1.6%
감전동 7
 
1.6%
2호 6
 
1.4%
Other values (182) 253
57.5%
2024-04-17T13:05:19.879207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
362
17.9%
산 96
 
4.7%
동 96
 
4.7%
1 94
 
4.6%
부 93
 
4.6%
구 92
 
4.5%
시 90
 
4.4%
광 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 (%)
산 96
 
7.6%
동 96
 
7.6%
부 93
 
7.4%
구 92
 
7.3%
시 90
 
7.2%
광 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 (%)
산 96
 
7.6%
동 96
 
7.6%
부 93
 
7.4%
구 92
 
7.3%
시 90
 
7.2%
광 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 (%)
산 96
 
7.6%
동 96
 
7.6%
부 93
 
7.4%
구 92
 
7.3%
시 90
 
7.2%
광 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
2024-04-17T13:05:20.136225image/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 기장군 정관면 산단1로 56
2nd row부산광역시 기장군 정관면 예림1로 87-9
3rd row부산광역시 북구 금곡대로 35 (덕천동)
4th row부산광역시 북구 만덕대로 327 (만덕동)
5th row부산광역시 사하구 감천항로 153 (구평동)
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%
신평동 6
 
1.5%
감전동 6
 
1.5%
구평동 5
 
1.2%
Other values (188) 241
58.8%
2024-04-17T13:05:20.488217image/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%
Open Punctuation 76
 
3.8%
Close 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%
Open Punctuation
ValueCountFrequency (%)
( 76
100.0%
Close 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
2024-04-17T13:05:20.602648image/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
2024-04-17T13:05:20.715204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
617843 5
 
5.4%
604836 4
 
4.3%
618818 3
 
3.2%
604817 3
 
3.2%
617804 2
 
2.2%
618280 2
 
2.2%
604826 2
 
2.2%
617826 2
 
2.2%
619961 2
 
2.2%
604806 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
2024-04-17T13:05:20.915343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length7.9247312
Min length2

Characters and Unicode

Total characters737
Distinct characters145
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 row(주)정관전자공인계량소
2nd row우성자원계량소
3rd row구포계량증명업소
4th row(주)삼보계량증명업소
5th row동명계량사
ValueCountFrequency (%)
부산시 2
 
1.9%
계량증명업소 2
 
1.9%
주)정관전자공인계량소 1
 
1.0%
한국산업단지공단(녹산계량소 1
 
1.0%
화전계량사 1
 
1.0%
협동조합 1
 
1.0%
공업 1
 
1.0%
기계 1
 
1.0%
에스원아텍(주 1
 
1.0%
우성국제물류(주 1
 
1.0%
Other values (92) 92
88.5%
2024-04-17T13:05:21.250053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 65
 
8.8%
량 61
 
8.3%
업 42
 
5.7%
명 35
 
4.7%
소 34
 
4.6%
증 32
 
4.3%
사 30
 
4.1%
주 23
 
3.1%
( 18
 
2.4%
) 18
 
2.4%
Other values (135) 379
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 676
91.7%
Open Punctuation 18
 
2.4%
Close Punctuation 18
 
2.4%
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
 
9.6%
량 61
 
9.0%
업 42
 
6.2%
명 35
 
5.2%
소 34
 
5.0%
증 32
 
4.7%
사 30
 
4.4%
주 23
 
3.4%
산 16
 
2.4%
부 16
 
2.4%
Other values (123) 322
47.6%
Uppercase Letter
ValueCountFrequency (%)
N 2
20.0%
G 2
20.0%
E 2
20.0%
S 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%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 676
91.7%
Common 47
 
6.4%
Latin 14
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 65
 
9.6%
량 61
 
9.0%
업 42
 
6.2%
명 35
 
5.2%
소 34
 
5.0%
증 32
 
4.7%
사 30
 
4.4%
주 23
 
3.4%
산 16
 
2.4%
부 16
 
2.4%
Other values (123) 322
47.6%
Latin
ValueCountFrequency (%)
e 2
14.3%
N 2
14.3%
G 2
14.3%
E 2
14.3%
S 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 676
91.7%
ASCII 61
 
8.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 65
 
9.6%
량 61
 
9.0%
업 42
 
6.2%
명 35
 
5.2%
소 34
 
5.0%
증 32
 
4.7%
사 30
 
4.4%
주 23
 
3.4%
산 16
 
2.4%
부 16
 
2.4%
Other values (123) 322
47.6%
ASCII
ValueCountFrequency (%)
( 18
29.5%
) 18
29.5%
11
18.0%
e 2
 
3.3%
N 2
 
3.3%
G 2
 
3.3%
E 2
 
3.3%
S 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%
Mean2.0152447 × 1013
Minimum1.9801118 × 1013
Maximum2.0201214 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size969.0 B
2024-04-17T13:05:21.366570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.9801118 × 1013
5-th percentile2.009092 × 1013
Q12.0120206 × 1013
median2.0161004 × 1013
Q32.0200706 × 1013
95-th percentile2.0201057 × 1013
Maximum2.0201214 × 1013
Range4.0009619 × 1011
Interquartile range (IQR)8.0500061 × 1010

Descriptive statistics

Standard deviation5.3848612 × 1010
Coefficient of variation (CV)0.0026720632
Kurtosis18.412966
Mean2.0152447 × 1013
Median Absolute Deviation (MAD)3.9807963 × 1010
Skewness-3.0899741
Sum1.8741775 × 1015
Variance2.899673 × 1021
MonotonicityNot monotonic
2024-04-17T13:05:21.488156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20120201095710 1
 
1.1%
20150217130742 1
 
1.1%
20200814100359 1
 
1.1%
20200814100316 1
 
1.1%
20200812141224 1
 
1.1%
20200814100231 1
 
1.1%
20161111150618 1
 
1.1%
20200814100123 1
 
1.1%
20200819134121 1
 
1.1%
20201204105947 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 (%)
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%
20200814100608 1
1.1%
20200814100520 1
1.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size876.0 B
I
54 
U
39 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 54
58.1%
U 39
41.9%

Length

2024-04-17T13:05:21.593530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T13:05:21.674408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 54
58.1%
u 39
41.9%

데이터갱신일자
Categorical

Distinct21
Distinct (%)22.6%
Missing0
Missing (%)0.0%
Memory size876.0 B
2018-08-31 23:59:59.0
54 
2018-11-14 02:37:25.0
9 
2020-08-16 02:40:00.0
7 
2020-09-16 02:40:00.0
 
3
2020-08-13 02:40:00.0
 
2
Other values (16)
18 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique14 ?
Unique (%)15.1%

Sample

1st row2018-08-31 23:59:59.0
2nd row2018-08-31 23:59:59.0
3rd row2020-10-18 02:40:00.0
4th row2020-10-07 02:40:00.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 54
58.1%
2018-11-14 02:37:25.0 9
 
9.7%
2020-08-16 02:40:00.0 7
 
7.5%
2020-09-16 02:40:00.0 3
 
3.2%
2020-08-13 02:40:00.0 2
 
2.2%
2020-11-21 02:40:00.0 2
 
2.2%
2019-04-27 02:40:00.0 2
 
2.2%
2020-08-21 02:40:00.0 1
 
1.1%
2020-08-09 02:40:00.0 1
 
1.1%
2020-07-24 02:40:00.0 1
 
1.1%
Other values (11) 11
 
11.8%

Length

2024-04-17T13:05:21.744895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 54
29.0%
23:59:59.0 54
29.0%
02:40:00.0 30
16.1%
2018-11-14 9
 
4.8%
02:37:25.0 9
 
4.8%
2020-08-16 7
 
3.8%
2020-09-16 3
 
1.6%
2020-08-13 2
 
1.1%
2020-11-21 2
 
1.1%
2019-04-27 2
 
1.1%
Other values (14) 14
 
7.5%

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
2024-04-17T13:05:21.837755image/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
2024-04-17T13:05:21.941850image/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%
366756.770372749 1
 
1.1%
370083.902222437 1
 
1.1%
372204.225643134 1
 
1.1%
371953.608312036 1
 
1.1%
369129.311995 1
 
1.1%
385793.299310018 1
 
1.1%
367033.0 1
 
1.1%
356180.953841 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
2024-04-17T13:05:22.049891image/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
2024-04-17T13:05:22.166758image/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%
184524.029110792 1
 
1.1%
179300.229488675 1
 
1.1%
191022.817362669 1
 
1.1%
179983.353890829 1
 
1.1%
182844.063023 1
 
1.1%
180910.386635661 1
 
1.1%
175754.0 1
 
1.1%
266134.079826 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
2024-04-17T13:05:22.350112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.184783
Min length7

Characters and Unicode

Total characters1029
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 727 7500
2nd row051 727 5759
3rd row051 332 5820
4th row051 336 2000
5th row005102622744
ValueCountFrequency (%)
051 65
31.4%
315 3
 
1.4%
266 3
 
1.4%
262 3
 
1.4%
301 3
 
1.4%
728 3
 
1.4%
4517 3
 
1.4%
326 2
 
1.0%
972 2
 
1.0%
727 2
 
1.0%
Other values (116) 118
57.0%
2024-04-17T13:05:22.640193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 161
15.6%
1 159
15.5%
0 154
15.0%
119
11.6%
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 119
 
11.6%
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 (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1029
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 161
15.6%
1 159
15.5%
0 154
15.0%
119
11.6%
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 1029
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 161
15.6%
1 159
15.5%
0 154
15.0%
119
11.6%
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_P3400000200734000250650000120070515<NA>3폐업3폐업20091022<NA><NA><NA>051 727 7500<NA><NA>부산광역시 기장군 정관면 달산리 938번지부산광역시 기장군 정관면 산단1로 56619961(주)정관전자공인계량소20120201095710I2018-08-31 23:59:59.0<NA>397987.323586204006.570249051 727 7500<NA><NA>
12계량기증명업09_28_04_P3400000200634000250650000320061228<NA>3폐업3폐업20090225<NA><NA><NA>051 727 5759<NA><NA>부산광역시 기장군 정관면 예림리 340번지부산광역시 기장군 정관면 예림1로 87-9619961우성자원계량소20120201095831I2018-08-31 23:59:59.0<NA>400997.873851205560.000102051 727 5759<NA><NA>
23계량기증명업09_28_04_P3320000198133200000650000119810516<NA>3폐업3폐업20201015<NA><NA><NA>051 332 5820<NA><NA>부산광역시 북구 덕천동 330번지 2 호부산광역시 북구 금곡대로 35 (덕천동)616817구포계량증명업소20201016092224U2020-10-18 02:40:00.0<NA>382399.297462192271.133675051 332 5820<NA><NA>
34계량기증명업09_28_04_P3320000199033200000650001619900310<NA>3폐업3폐업202010052020010129990909<NA>051 336 2000<NA><NA>부산광역시 북구 만덕동 산19번지 5 호부산광역시 북구 만덕대로 327 (만덕동)616824(주)삼보계량증명업소20201005171439U2020-10-07 02:40:00.0<NA>385673.236619192353.375459051 336 2000<NA><NA>
45계량기증명업09_28_04_P3340000201233400800650000120120418<NA>3폐업3폐업20160930<NA><NA><NA>005102622744<NA>604060부산광역시 사하구 구평동 178번지 11호부산광역시 사하구 감천항로 153 (구평동)<NA>동명계량사20161004131223I2018-08-31 23:59:59.0<NA>381478.267312177391.455047005102622744<NA><NA>
56계량기증명업09_28_04_P3340000200633400660650000320060925<NA>3폐업3폐업20070418<NA><NA><NA>005102634771<NA><NA>부산광역시 사하구 장림동 312번지부산광역시 사하구 다대로 296 (장림동)604844극동스틸(주)20120206110413I2018-08-31 23:59:59.0<NA>380212.195225177000.001273005102634771<NA><NA>
67계량기증명업09_28_04_P3340000200433400170650000220040227<NA>3폐업3폐업20070221<NA><NA><NA>051 2913300<NA><NA>부산광역시 사하구 신평동 370번지 92호부산광역시 사하구 신산로 66 (신평동)604836월드계량증명업소20120206111628I2018-08-31 23:59:59.0<NA>378889.649674178496.185793051 2913300<NA><NA>
78계량기증명업09_28_04_P3340000200033400170650002119990902<NA>3폐업3폐업20090917<NA><NA><NA>2938984<NA>604804부산광역시 사하구 감천1동 441번지 6호<NA><NA>중앙계량사20090917171820I2018-08-31 23:59:59.0<NA>382075.921105177912.1567762938984<NA><NA>
89계량기증명업09_28_04_P3340000200033400170650001119891207<NA>3폐업3폐업20090921<NA><NA><NA>0512914195<NA>604858부산광역시 사하구 하단1동 892번지 1호<NA><NA>삼성계량사20090921170119I2018-08-31 23:59:59.0<NA>378609.597087180287.2682840512914195<NA><NA>
910계량기증명업09_28_04_P3340000200033400170650001719950728<NA>3폐업3폐업20001214<NA><NA><NA>051 263 4771<NA>604844부산광역시 사하구 장림1동 312번지부산광역시 사하구 다대로 296 (장림동)604844현대철강공업(주)20130118153357I2018-08-31 23:59:59.0<NA>380212.195225177000.001273051 263 4771<NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)사무소전화번호사업장전화번호Unnamed: 30
8384계량기증명업09_28_04_P3390000199633900150650003119960603<NA>1영업/정상1영업중<NA><NA><NA><NA>051 312 6759<NA>617841부산광역시 사상구 학장동 286번지 1 호부산광역시 사상구 가야대로 176 (학장동)617841오성계량사20181112145409U2018-11-14 02:37:25.0<NA>381445.571674185164.667279051 312 6759<NA><NA>
8485계량기증명업09_28_04_P3390000199633900150650003019961219<NA>1영업/정상1영업중<NA><NA><NA><NA>051 315 9682<NA><NA>부산광역시 사상구 감전동 957번지 44 호부산광역시 사상구 낙동대로902번길 61 (감전동)617805대건계량사20111102101024I2018-08-31 23:59:59.0<NA>379802.78143184190.423474051 315 9682<NA><NA>
8586계량기증명업09_28_04_P3390000199133900150650002719910926<NA>1영업/정상1영업중<NA><NA><NA><NA>051 311 5233<NA>617843부산광역시 사상구 학장동 731번지 1호부산광역시 사상구 장인로 80 (학장동)47026서림공인계량증명사20200807171013U2020-08-09 02:40:00.0<NA>380159.887634184293.415315051 311 5233<NA><NA>
8687계량기증명업09_28_04_P3390000198933900150650000419891229<NA>1영업/정상1영업중<NA><NA><NA><NA>051 971 3323<NA>617805부산광역시 사상구 감전동 506번지 1호부산광역시 사상구 낙동대로 900 (감전동)<NA>유신계량사20131001110052I2018-08-31 23:59:59.0<NA>379514.944525184200.556172051 971 3323<NA><NA>
8788계량기증명업09_28_04_P3390000198833900150650001219880310<NA>1영업/정상1영업중<NA><NA><NA><NA>051 326 5885<NA>617844부산광역시 사상구 학장동 264번지 15호부산광역시 사상구 대동로180번길 12 (학장동)617844함양계량증명업소20181112145535U2018-11-14 02:37:25.0<NA>380812.919738184462.721546051 326 5885<NA><NA>
8889계량기증명업09_28_04_P3390000198333900150650000219830926<NA>1영업/정상1영업중<NA><NA><NA><NA>051 301 7034<NA>617825부산광역시 사상구 삼락동 120번지 2호부산광역시 사상구 낙동대로 1438 (삼락동)617825삼락계량증명업소20181112152229U2018-11-14 02:37:25.0<NA>380185.259681189455.060978051 301 7034<NA><NA>
8990계량기증명업09_28_04_P3390000197933900150650001819790327<NA>1영업/정상1영업중<NA><NA><NA><NA>051 315 0435<NA>617843부산광역시 사상구 학장동 234번지 13호부산광역시 사상구 새벽로 36 (학장동)617843동원계량사20200109101511U2020-01-11 02:40:00.0<NA>380422.901711184585.1902051 315 0435<NA><NA>
9091계량기증명업09_28_04_P3310000200833100820650000120081125<NA>1영업/정상1영업중<NA><NA><NA><NA>051 638 3974<NA>608070부산광역시 남구 감만동 498번지 17호 외 77필지부산광역시 남구 우암로2번길 18 (감만동)608803내트럭하우스 부산사업소20190425215241U2019-04-27 02:40:00.0<NA>389703.194539180970.856108051 638 3974<NA><NA>
9192계량기증명업09_28_04_P3310000199233100000650000219920113<NA>1영업/정상1영업중<NA><NA><NA><NA>051 6227893<NA><NA>부산광역시 남구 용당동 479번지 1 호부산광역시 남구 신선로 414 (용당동)608830삼일컴퓨터계량사20120206112124I2018-08-31 23:59:59.0<NA>391291.88378182350.887086051 6227893<NA><NA>
9293계량기증명업09_28_04_P3310000201233100820650000120121120<NA>1영업/정상1영업중<NA><NA><NA><NA>931 8001<NA>608080부산광역시 남구 용당동 168번지 1호부산광역시 남구 신선로 261 (용당동)<NA>내트럭(주)부산용당사업소20190425215206U2019-04-27 02:40:00.0<NA>390807.6282181223.764822931 8001<NA><NA>