Overview

Dataset statistics

Number of variables36
Number of observations151
Missing cells1867
Missing cells (%)34.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.7 KiB
Average record size in memory309.9 B

Variable types

Numeric10
Categorical9
Unsupported9
Text7
DateTime1

Dataset

Description2021-06-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123130

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
영업상태구분코드 has constant value ""Constant
영업상태명 has constant value ""Constant
상세영업상태코드 has constant value ""Constant
상세영업상태명 has constant value ""Constant
목재생산업구분코드명 has constant value ""Constant
상태구분명 has constant value ""Constant
인허가취소일자 has 151 (100.0%) missing valuesMissing
폐업일자 has 151 (100.0%) missing valuesMissing
휴업시작일자 has 151 (100.0%) missing valuesMissing
휴업종료일자 has 151 (100.0%) missing valuesMissing
재개업일자 has 151 (100.0%) missing valuesMissing
소재지전화 has 35 (23.2%) missing valuesMissing
소재지면적 has 151 (100.0%) missing valuesMissing
소재지우편번호 has 151 (100.0%) missing valuesMissing
소재지전체주소 has 64 (42.4%) missing valuesMissing
도로명전체주소 has 6 (4.0%) missing valuesMissing
도로명우편번호 has 71 (47.0%) missing valuesMissing
업태구분명 has 151 (100.0%) missing valuesMissing
좌표정보(x) has 3 (2.0%) missing valuesMissing
좌표정보(y) has 3 (2.0%) missing valuesMissing
목재생산업종류명 has 149 (98.7%) missing valuesMissing
취급목재제품 has 6 (4.0%) missing valuesMissing
인력보유현황 has 122 (80.8%) missing valuesMissing
년간생산량 has 22 (14.6%) missing valuesMissing
자본금 has 27 (17.9%) missing valuesMissing
Unnamed: 35 has 151 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐업일자 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
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 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
Unnamed: 35 is an unsupported type, check if it needs cleaning or further analysisUnsupported
자본금 has 2 (1.3%) zerosZeros

Reproduction

Analysis started2024-04-16 06:20:33.434574
Analysis finished2024-04-16 06:20:33.948783
Duration0.51 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76
Minimum1
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:34.004509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.5
Q138.5
median76
Q3113.5
95-th percentile143.5
Maximum151
Range150
Interquartile range (IQR)75

Descriptive statistics

Standard deviation43.734045
Coefficient of variation (CV)0.57544796
Kurtosis-1.2
Mean76
Median Absolute Deviation (MAD)38
Skewness0
Sum11476
Variance1912.6667
MonotonicityStrictly increasing
2024-04-16T15:20:34.132726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
105 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
106 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
목재수입유통업
151 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목재수입유통업 151
100.0%

Length

2024-04-16T15:20:34.250262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:34.334435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목재수입유통업 151
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
09_27_01_P
151 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_27_01_P
2nd row09_27_01_P
3rd row09_27_01_P
4th row09_27_01_P
5th row09_27_01_P

Common Values

ValueCountFrequency (%)
09_27_01_P 151
100.0%

Length

2024-04-16T15:20:34.618321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:34.690387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_27_01_p 151
100.0%

개방자치단체코드
Real number (ℝ)

Distinct15
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3340993.4
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:34.755211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3250000
Q13320000
median3360000
Q33360000
95-th percentile3390000
Maximum3400000
Range150000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation41693.404
Coefficient of variation (CV)0.012479344
Kurtosis-0.31207497
Mean3340993.4
Median Absolute Deviation (MAD)20000
Skewness-0.77857294
Sum5.0449 × 108
Variance1.73834 × 109
MonotonicityIncreasing
2024-04-16T15:20:34.843395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3360000 48
31.8%
3390000 22
14.6%
3340000 21
13.9%
3270000 10
 
6.6%
3250000 9
 
6.0%
3290000 9
 
6.0%
3330000 8
 
5.3%
3310000 6
 
4.0%
3400000 5
 
3.3%
3320000 3
 
2.0%
Other values (5) 10
 
6.6%
ValueCountFrequency (%)
3250000 9
6.0%
3260000 1
 
0.7%
3270000 10
6.6%
3280000 1
 
0.7%
3290000 9
6.0%
3310000 6
 
4.0%
3320000 3
 
2.0%
3330000 8
 
5.3%
3340000 21
13.9%
3350000 3
 
2.0%
ValueCountFrequency (%)
3400000 5
 
3.3%
3390000 22
14.6%
3380000 3
 
2.0%
3370000 2
 
1.3%
3360000 48
31.8%
3350000 3
 
2.0%
3340000 21
13.9%
3330000 8
 
5.3%
3320000 3
 
2.0%
3310000 6
 
4.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3409943 × 1017
Minimum3.2500009 × 1017
Maximum3.4000009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:34.946875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2500009 × 1017
5-th percentile3.2500009 × 1017
Q13.3200009 × 1017
median3.3600009 × 1017
Q33.3600009 × 1017
95-th percentile3.3900009 × 1017
Maximum3.4000009 × 1017
Range1.5 × 1016
Interquartile range (IQR)4 × 1015

Descriptive statistics

Standard deviation4.1693404 × 1015
Coefficient of variation (CV)0.01247934
Kurtosis-0.31207497
Mean3.3409943 × 1017
Median Absolute Deviation (MAD)2 × 1015
Skewness-0.77857294
Sum-4.8912186 × 1018
Variance1.73834 × 1031
MonotonicityNot monotonic
2024-04-16T15:20:35.056889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
325000090201900001 1
 
0.7%
336000090201900010 1
 
0.7%
336000090201800004 1
 
0.7%
336000090201900002 1
 
0.7%
336000090201900003 1
 
0.7%
336000090201900007 1
 
0.7%
336000090201900005 1
 
0.7%
336000090201900008 1
 
0.7%
336000090201900009 1
 
0.7%
336000090201900011 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
325000090201400002 1
0.7%
325000090201400003 1
0.7%
325000090201400004 1
0.7%
325000090201500001 1
0.7%
325000090201500002 1
0.7%
325000090201500003 1
0.7%
325000090201700001 1
0.7%
325000090201800002 1
0.7%
325000090201900001 1
0.7%
326000090201700001 1
0.7%
ValueCountFrequency (%)
340000090202000001 1
0.7%
340000090201900002 1
0.7%
340000090201900001 1
0.7%
340000090201300002 1
0.7%
340000090201300001 1
0.7%
339000090202000003 1
0.7%
339000090202000002 1
0.7%
339000090202000001 1
0.7%
339000090201900004 1
0.7%
339000090201900003 1
0.7%

인허가일자
Real number (ℝ)

Distinct120
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20165574
Minimum20130910
Maximum20210408
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:35.167035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20130910
5-th percentile20131128
Q120140318
median20170329
Q320190706
95-th percentile20200929
Maximum20210408
Range79498
Interquartile range (IQR)50388

Descriptive statistics

Standard deviation26071.978
Coefficient of variation (CV)0.0012928954
Kurtosis-1.4575519
Mean20165574
Median Absolute Deviation (MAD)29399
Skewness0.042382137
Sum3.0450016 × 109
Variance6.7974803 × 108
MonotonicityNot monotonic
2024-04-16T15:20:35.279780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131213 6
 
4.0%
20131123 3
 
2.0%
20190711 3
 
2.0%
20131211 3
 
2.0%
20131203 3
 
2.0%
20140114 2
 
1.3%
20200929 2
 
1.3%
20161011 2
 
1.3%
20191107 2
 
1.3%
20140220 2
 
1.3%
Other values (110) 123
81.5%
ValueCountFrequency (%)
20130910 1
 
0.7%
20131121 2
1.3%
20131122 1
 
0.7%
20131123 3
2.0%
20131128 2
1.3%
20131129 2
1.3%
20131203 3
2.0%
20131204 1
 
0.7%
20131209 2
1.3%
20131211 3
2.0%
ValueCountFrequency (%)
20210408 1
0.7%
20210331 1
0.7%
20210315 1
0.7%
20210309 1
0.7%
20201214 1
0.7%
20201112 1
0.7%
20201030 1
0.7%
20200929 2
1.3%
20200916 1
0.7%
20200904 1
0.7%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

영업상태구분코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
151 

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 (%)
1 151
100.0%

Length

2024-04-16T15:20:35.391538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:35.477715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 151
100.0%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업/정상
151 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 151
100.0%

Length

2024-04-16T15:20:35.564813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:35.655551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 151
100.0%

상세영업상태코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
151 

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 (%)
1 151
100.0%

Length

2024-04-16T15:20:35.730093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:35.813552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 151
100.0%

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
정상
151 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 151
100.0%

Length

2024-04-16T15:20:35.886873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:35.957213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 151
100.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

소재지전화
Text

MISSING 

Distinct107
Distinct (%)92.2%
Missing35
Missing (%)23.2%
Memory size1.3 KiB
2024-04-16T15:20:36.156941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.37931
Min length1

Characters and Unicode

Total characters1320
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

Unique98 ?
Unique (%)84.5%

Sample

1st row051-462-0345
2nd row0514648501
3rd row051-253-8653
4th row0514414011
5th row0514690052
ValueCountFrequency (%)
051-972-0188 2
 
1.7%
051-941-3140 2
 
1.7%
051-714-4744 2
 
1.7%
051-203-3700 2
 
1.7%
051-262-5555 2
 
1.7%
051-464-2280 2
 
1.7%
0553395651 2
 
1.7%
051-469-5945 2
 
1.7%
051-831-6363 2
 
1.7%
051-714-3638 1
 
0.9%
Other values (97) 97
83.6%
2024-04-16T15:20:36.471294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 221
16.7%
0 196
14.8%
- 181
13.7%
5 180
13.6%
3 100
7.6%
4 94
7.1%
2 87
 
6.6%
8 74
 
5.6%
6 73
 
5.5%
7 66
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1139
86.3%
Dash Punctuation 181
 
13.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 221
19.4%
0 196
17.2%
5 180
15.8%
3 100
8.8%
4 94
8.3%
2 87
 
7.6%
8 74
 
6.5%
6 73
 
6.4%
7 66
 
5.8%
9 48
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 181
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1320
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 221
16.7%
0 196
14.8%
- 181
13.7%
5 180
13.6%
3 100
7.6%
4 94
7.1%
2 87
 
6.6%
8 74
 
5.6%
6 73
 
5.5%
7 66
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 221
16.7%
0 196
14.8%
- 181
13.7%
5 180
13.6%
3 100
7.6%
4 94
7.1%
2 87
 
6.6%
8 74
 
5.6%
6 73
 
5.5%
7 66
 
5.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

소재지전체주소
Text

MISSING 

Distinct79
Distinct (%)90.8%
Missing64
Missing (%)42.4%
Memory size1.3 KiB
2024-04-16T15:20:36.706867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length23.781609
Min length17

Characters and Unicode

Total characters2069
Distinct characters130
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)82.8%

Sample

1st row부산광역시 중구 중앙동6가 66-3번지 부산데파트
2nd row부산광역시 중구 중앙동4가 36-14번지
3rd row부산광역시 동구 초량동 1211-7번지
4th row부산광역시 동구 초량동 1211-1번지
5th row부산광역시 동구 범일동 110-8번지
ValueCountFrequency (%)
부산광역시 86
22.0%
강서구 37
 
9.5%
사하구 17
 
4.3%
송정동 16
 
4.1%
하단동 7
 
1.8%
사상구 7
 
1.8%
동구 7
 
1.8%
대저2동 7
 
1.8%
초량동 6
 
1.5%
부산진구 6
 
1.5%
Other values (149) 195
49.9%
2024-04-16T15:20:37.024725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
304
 
14.7%
1 129
 
6.2%
동 99
 
4.8%
부 95
 
4.6%
산 94
 
4.5%
시 87
 
4.2%
광 86
 
4.2%
역 86
 
4.2%
구 83
 
4.0%
지 73
 
3.5%
Other values (120) 933
45.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1243
60.1%
Decimal Number 450
 
21.7%
Space Separator 304
 
14.7%
Dash Punctuation 69
 
3.3%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 99
 
8.0%
부 95
 
7.6%
산 94
 
7.6%
시 87
 
7.0%
광 86
 
6.9%
역 86
 
6.9%
구 83
 
6.7%
지 73
 
5.9%
번 66
 
5.3%
강 40
 
3.2%
Other values (105) 434
34.9%
Decimal Number
ValueCountFrequency (%)
1 129
28.7%
2 54
12.0%
6 45
 
10.0%
5 43
 
9.6%
4 38
 
8.4%
7 37
 
8.2%
3 33
 
7.3%
0 31
 
6.9%
8 26
 
5.8%
9 14
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
A 1
33.3%
Space Separator
ValueCountFrequency (%)
304
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1243
60.1%
Common 823
39.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 99
 
8.0%
부 95
 
7.6%
산 94
 
7.6%
시 87
 
7.0%
광 86
 
6.9%
역 86
 
6.9%
구 83
 
6.7%
지 73
 
5.9%
번 66
 
5.3%
강 40
 
3.2%
Other values (105) 434
34.9%
Common
ValueCountFrequency (%)
304
36.9%
1 129
15.7%
- 69
 
8.4%
2 54
 
6.6%
6 45
 
5.5%
5 43
 
5.2%
4 38
 
4.6%
7 37
 
4.5%
3 33
 
4.0%
0 31
 
3.8%
Other values (2) 40
 
4.9%
Latin
ValueCountFrequency (%)
B 1
33.3%
E 1
33.3%
A 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1243
60.1%
ASCII 826
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
304
36.8%
1 129
15.6%
- 69
 
8.4%
2 54
 
6.5%
6 45
 
5.4%
5 43
 
5.2%
4 38
 
4.6%
7 37
 
4.5%
3 33
 
4.0%
0 31
 
3.8%
Other values (5) 43
 
5.2%
Hangul
ValueCountFrequency (%)
동 99
 
8.0%
부 95
 
7.6%
산 94
 
7.6%
시 87
 
7.0%
광 86
 
6.9%
역 86
 
6.9%
구 83
 
6.7%
지 73
 
5.9%
번 66
 
5.3%
강 40
 
3.2%
Other values (105) 434
34.9%

도로명전체주소
Text

MISSING 

Distinct135
Distinct (%)93.1%
Missing6
Missing (%)4.0%
Memory size1.3 KiB
2024-04-16T15:20:37.323914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length39
Mean length30.227586
Min length20

Characters and Unicode

Total characters4383
Distinct characters200
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)86.2%

Sample

1st row부산광역시 중구 중앙대로 21, 부산데파트 4층 513-1호 (중앙동6가)
2nd row부산광역시 중구 충장대로9번길 16 (중앙동4가)
3rd row부산광역시 중구 중앙대로 26 (중앙동6가)
4th row부산광역시 중구 해관로 65, 402호 (중앙동4가)
5th row부산광역시 중구 대청로 91-6, 703동 (대청동2가)
ValueCountFrequency (%)
부산광역시 144
 
16.8%
강서구 45
 
5.3%
사상구 21
 
2.5%
사하구 20
 
2.3%
송정동 17
 
2.0%
중앙대로 12
 
1.4%
괘법동 10
 
1.2%
동구 10
 
1.2%
중구 9
 
1.1%
괘감로 9
 
1.1%
Other values (366) 559
65.3%
2024-04-16T15:20:37.778755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
711
 
16.2%
산 193
 
4.4%
동 192
 
4.4%
부 157
 
3.6%
광 149
 
3.4%
시 147
 
3.4%
역 144
 
3.3%
( 140
 
3.2%
구 140
 
3.2%
) 140
 
3.2%
Other values (190) 2270
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2573
58.7%
Space Separator 711
 
16.2%
Decimal Number 709
 
16.2%
Open Punctuation 140
 
3.2%
Close Punctuation 140
 
3.2%
Other Punctuation 85
 
1.9%
Dash Punctuation 19
 
0.4%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 193
 
7.5%
동 192
 
7.5%
부 157
 
6.1%
광 149
 
5.8%
시 147
 
5.7%
역 144
 
5.6%
구 140
 
5.4%
로 136
 
5.3%
대 69
 
2.7%
강 52
 
2.0%
Other values (172) 1194
46.4%
Decimal Number
ValueCountFrequency (%)
1 136
19.2%
2 108
15.2%
3 84
11.8%
0 75
10.6%
7 64
9.0%
6 62
8.7%
4 59
8.3%
5 45
 
6.3%
8 43
 
6.1%
9 33
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
B 2
33.3%
E 1
 
16.7%
Space Separator
ValueCountFrequency (%)
711
100.0%
Open Punctuation
ValueCountFrequency (%)
( 140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 140
100.0%
Other Punctuation
ValueCountFrequency (%)
, 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2573
58.7%
Common 1804
41.2%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 193
 
7.5%
동 192
 
7.5%
부 157
 
6.1%
광 149
 
5.8%
시 147
 
5.7%
역 144
 
5.6%
구 140
 
5.4%
로 136
 
5.3%
대 69
 
2.7%
강 52
 
2.0%
Other values (172) 1194
46.4%
Common
ValueCountFrequency (%)
711
39.4%
( 140
 
7.8%
) 140
 
7.8%
1 136
 
7.5%
2 108
 
6.0%
, 85
 
4.7%
3 84
 
4.7%
0 75
 
4.2%
7 64
 
3.5%
6 62
 
3.4%
Other values (5) 199
 
11.0%
Latin
ValueCountFrequency (%)
A 3
50.0%
B 2
33.3%
E 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2573
58.7%
ASCII 1810
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
711
39.3%
( 140
 
7.7%
) 140
 
7.7%
1 136
 
7.5%
2 108
 
6.0%
, 85
 
4.7%
3 84
 
4.6%
0 75
 
4.1%
7 64
 
3.5%
6 62
 
3.4%
Other values (8) 205
 
11.3%
Hangul
ValueCountFrequency (%)
산 193
 
7.5%
동 192
 
7.5%
부 157
 
6.1%
광 149
 
5.8%
시 147
 
5.7%
역 144
 
5.6%
구 140
 
5.4%
로 136
 
5.3%
대 69
 
2.7%
강 52
 
2.0%
Other values (172) 1194
46.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct63
Distinct (%)78.8%
Missing71
Missing (%)47.0%
Infinite0
Infinite (%)0.0%
Mean75044.288
Minimum17600
Maximum618200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:37.892543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17600
5-th percentile46307.05
Q146728.5
median46977
Q348567.75
95-th percentile77251.75
Maximum618200
Range600600
Interquartile range (IQR)1839.25

Descriptive statistics

Standard deviation123000.38
Coefficient of variation (CV)1.6390372
Kurtosis16.096919
Mean75044.288
Median Absolute Deviation (MAD)274
Skewness4.2039375
Sum6003543
Variance1.5129094 × 1010
MonotonicityNot monotonic
2024-04-16T15:20:38.021379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46755 5
 
3.3%
48792 4
 
2.6%
46729 3
 
2.0%
46721 2
 
1.3%
46754 2
 
1.3%
46731 2
 
1.3%
604041 2
 
1.3%
46977 2
 
1.3%
46982 2
 
1.3%
49305 2
 
1.3%
Other values (53) 54
35.8%
(Missing) 71
47.0%
ValueCountFrequency (%)
17600 1
0.7%
46008 1
0.7%
46018 1
0.7%
46080 1
0.7%
46319 1
0.7%
46332 1
0.7%
46614 1
0.7%
46700 1
0.7%
46702 1
0.7%
46704 1
0.7%
ValueCountFrequency (%)
618200 1
0.7%
604051 1
0.7%
604041 2
1.3%
49526 1
0.7%
49437 1
0.7%
49430 1
0.7%
49418 1
0.7%
49324 1
0.7%
49307 1
0.7%
49305 2
1.3%

사업장명
Text

Distinct126
Distinct (%)83.4%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-16T15:20:38.212012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.4172185
Min length2

Characters and Unicode

Total characters969
Distinct characters180
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)80.8%

Sample

1st row(주)골드웨이트레이딩
2nd row효동선박
3rd row코보데크
4th row(주)보경인터내셔날
5th row(주)알케이글로벌
ValueCountFrequency (%)
23
 
13.9%
주식회사 9
 
5.5%
주)보경인터내셔날 2
 
1.2%
주)글로발코리아 2
 
1.2%
주)쉽맨코 2
 
1.2%
주)도호 2
 
1.2%
영웅에너지참숯무역 1
 
0.6%
주)한성글로벌 1
 
0.6%
주)금호창호 1
 
0.6%
김한섭 1
 
0.6%
Other values (121) 121
73.3%
2024-04-16T15:20:38.502970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 85
 
8.8%
) 75
 
7.7%
( 74
 
7.6%
* 69
 
7.1%
재 24
 
2.5%
목 22
 
2.3%
이 19
 
2.0%
사 17
 
1.8%
아 16
 
1.7%
산 16
 
1.7%
Other values (170) 552
57.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 722
74.5%
Close Punctuation 75
 
7.7%
Open Punctuation 74
 
7.6%
Other Punctuation 70
 
7.2%
Space Separator 14
 
1.4%
Uppercase Letter 11
 
1.1%
Lowercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 85
 
11.8%
재 24
 
3.3%
목 22
 
3.0%
이 19
 
2.6%
사 17
 
2.4%
아 16
 
2.2%
산 16
 
2.2%
우 16
 
2.2%
인 15
 
2.1%
식 14
 
1.9%
Other values (155) 478
66.2%
Uppercase Letter
ValueCountFrequency (%)
B 3
27.3%
C 3
27.3%
N 1
 
9.1%
M 1
 
9.1%
J 1
 
9.1%
R 1
 
9.1%
E 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
x 1
33.3%
t 1
33.3%
s 1
33.3%
Other Punctuation
ValueCountFrequency (%)
* 69
98.6%
. 1
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 74
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 722
74.5%
Common 233
 
24.0%
Latin 14
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 85
 
11.8%
재 24
 
3.3%
목 22
 
3.0%
이 19
 
2.6%
사 17
 
2.4%
아 16
 
2.2%
산 16
 
2.2%
우 16
 
2.2%
인 15
 
2.1%
식 14
 
1.9%
Other values (155) 478
66.2%
Latin
ValueCountFrequency (%)
B 3
21.4%
C 3
21.4%
N 1
 
7.1%
M 1
 
7.1%
J 1
 
7.1%
R 1
 
7.1%
E 1
 
7.1%
x 1
 
7.1%
t 1
 
7.1%
s 1
 
7.1%
Common
ValueCountFrequency (%)
) 75
32.2%
( 74
31.8%
* 69
29.6%
14
 
6.0%
. 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 722
74.5%
ASCII 247
 
25.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 85
 
11.8%
재 24
 
3.3%
목 22
 
3.0%
이 19
 
2.6%
사 17
 
2.4%
아 16
 
2.2%
산 16
 
2.2%
우 16
 
2.2%
인 15
 
2.1%
식 14
 
1.9%
Other values (155) 478
66.2%
ASCII
ValueCountFrequency (%)
) 75
30.4%
( 74
30.0%
* 69
27.9%
14
 
5.7%
B 3
 
1.2%
C 3
 
1.2%
. 1
 
0.4%
N 1
 
0.4%
M 1
 
0.4%
J 1
 
0.4%
Other values (5) 5
 
2.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0172518 × 1013
Minimum2.0131121 × 1013
Maximum2.0210422 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:38.615754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0131121 × 1013
5-th percentile2.0131166 × 1013
Q12.0141028 × 1013
median2.0180323 × 1013
Q32.0200108 × 1013
95-th percentile2.0201223 × 1013
Maximum2.0210422 × 1013
Range7.9300948 × 1010
Interquartile range (IQR)5.908055 × 1010

Descriptive statistics

Standard deviation2.6460177 × 1010
Coefficient of variation (CV)0.0013116943
Kurtosis-1.3847886
Mean2.0172518 × 1013
Median Absolute Deviation (MAD)2.0301049 × 1010
Skewness-0.32108716
Sum3.0460502 × 1015
Variance7.0014094 × 1020
MonotonicityNot monotonic
2024-04-16T15:20:38.729460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20191209090701 1
 
0.7%
20191119094613 1
 
0.7%
20180717174552 1
 
0.7%
20200210142827 1
 
0.7%
20190507110606 1
 
0.7%
20190923184633 1
 
0.7%
20190702094535 1
 
0.7%
20191107092850 1
 
0.7%
20191107095153 1
 
0.7%
20191119095205 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
20131121203143 1
0.7%
20131121203806 1
0.7%
20131125164648 1
0.7%
20131125172116 1
0.7%
20131125181917 1
0.7%
20131126174357 1
0.7%
20131129095138 1
0.7%
20131129100959 1
0.7%
20131203151816 1
0.7%
20131204151456 1
0.7%
ValueCountFrequency (%)
20210422151630 1
0.7%
20210408090345 1
0.7%
20210407150809 1
0.7%
20210401120600 1
0.7%
20210315155404 1
0.7%
20210309095204 1
0.7%
20210205192424 1
0.7%
20201231090619 1
0.7%
20201215102739 1
0.7%
20201214180136 1
0.7%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
125 
U
26 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 125
82.8%
U 26
 
17.2%

Length

2024-04-16T15:20:38.838815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:38.919679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 125
82.8%
u 26
 
17.2%

데이터갱신일자
Date

Distinct66
Distinct (%)43.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2021-04-24 02:40:00
2024-04-16T15:20:39.003898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T15:20:39.113587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct126
Distinct (%)85.1%
Missing3
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean380288.68
Minimum221015.89
Maximum407807.19
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:39.214058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum221015.89
5-th percentile369538.49
Q1375469.86
median380291.66
Q3386093.67
95-th percentile394055.85
Maximum407807.19
Range186791.3
Interquartile range (IQR)10623.812

Descriptive statistics

Standard deviation15565.231
Coefficient of variation (CV)0.040930039
Kurtosis74.893369
Mean380288.68
Median Absolute Deviation (MAD)5777.4526
Skewness-7.264644
Sum56282725
Variance2.4227641 × 108
MonotonicityNot monotonic
2024-04-16T15:20:39.320005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
380291.656000926 8
 
5.3%
386093.674147239 4
 
2.6%
378522.007200069 3
 
2.0%
371774.0 2
 
1.3%
369659.990965637 2
 
1.3%
380090.057997493 2
 
1.3%
377612.120854748 2
 
1.3%
385603.815595631 2
 
1.3%
373006.154295793 2
 
1.3%
387869.134317928 2
 
1.3%
Other values (116) 119
78.8%
(Missing) 3
 
2.0%
ValueCountFrequency (%)
221015.890785944 1
0.7%
366573.694551617 1
0.7%
367979.894335724 1
0.7%
368294.938398231 1
0.7%
369396.906545409 2
1.3%
369493.32063271 1
0.7%
369518.386773504 1
0.7%
369575.824367534 1
0.7%
369624.999837451 1
0.7%
369628.797801081 1
0.7%
ValueCountFrequency (%)
407807.189985213 1
0.7%
402171.576043541 1
0.7%
400923.754261714 1
0.7%
400575.125464 1
0.7%
397650.317430573 1
0.7%
397553.652369772 1
0.7%
397288.512367137 1
0.7%
394085.659790124 1
0.7%
394000.476393582 1
0.7%
393696.083565618 1
0.7%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct125
Distinct (%)84.5%
Missing3
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean185404.36
Minimum173969.72
Maximum384662.91
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:39.434125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173969.72
5-th percentile177251.53
Q1179759.1
median183669.3
Q3186845.16
95-th percentile193056.09
Maximum384662.91
Range210693.19
Interquartile range (IQR)7086.0595

Descriptive statistics

Standard deviation17447.138
Coefficient of variation (CV)0.094103174
Kurtosis117.55378
Mean185404.36
Median Absolute Deviation (MAD)3509.542
Skewness10.292731
Sum27439845
Variance3.0440264 × 108
MonotonicityNot monotonic
2024-04-16T15:20:39.559822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186303.922053702 8
 
5.3%
182068.358104572 4
 
2.6%
180909.306630124 3
 
2.0%
178315.004400424 2
 
1.3%
178312.481999126 2
 
1.3%
176504.955138913 2
 
1.3%
174355.708212487 2
 
1.3%
183728.0 2
 
1.3%
191768.970144673 2
 
1.3%
177655.476042346 2
 
1.3%
Other values (115) 119
78.8%
(Missing) 3
 
2.0%
ValueCountFrequency (%)
173969.719902491 1
0.7%
174355.708212487 2
1.3%
174582.583885409 1
0.7%
176504.955138913 2
1.3%
176823.187442523 1
0.7%
177108.0404076 1
0.7%
177518.0 1
0.7%
177643.699590984 1
0.7%
177655.476042346 2
1.3%
177995.407107721 1
0.7%
ValueCountFrequency (%)
384662.912788779 1
0.7%
206309.213371059 1
0.7%
205400.208795236 1
0.7%
204881.782325 1
0.7%
204205.798524297 1
0.7%
195361.118531762 1
0.7%
193652.804635603 1
0.7%
193088.225321286 1
0.7%
192996.408501857 1
0.7%
192962.357980296 1
0.7%

목재생산업구분코드명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
목재수입유통업
151 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
목재수입유통업 151
100.0%

Length

2024-04-16T15:20:39.656729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:39.737787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
목재수입유통업 151
100.0%

목재생산업종류명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing149
Missing (%)98.7%
Memory size1.3 KiB
2024-04-16T15:20:39.820674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters3
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row1종
2nd row2종
ValueCountFrequency (%)
1종 1
50.0%
2종 1
50.0%
2024-04-16T15:20:40.043947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
종 2
50.0%
1 1
25.0%
2 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
50.0%
Decimal Number 2
50.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Other Letter
ValueCountFrequency (%)
종 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
50.0%
Common 2
50.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Hangul
ValueCountFrequency (%)
종 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
50.0%
ASCII 2
50.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
종 2
100.0%
ASCII
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%

취급목재제품
Text

MISSING 

Distinct87
Distinct (%)60.0%
Missing6
Missing (%)4.0%
Memory size1.3 KiB
2024-04-16T15:20:40.236456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length24
Mean length7.5310345
Min length1

Characters and Unicode

Total characters1092
Distinct characters127
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

Unique72 ?
Unique (%)49.7%

Sample

1st row목탄
2nd row목재펠릿
3rd row목재펠릿
4th row목재펠릿
5th row우드펠렛
ValueCountFrequency (%)
제재목 33
 
12.6%
합판 32
 
12.3%
목재펠릿 17
 
6.5%
원목 13
 
5.0%
목탄 11
 
4.2%
우드펠릿 11
 
4.2%
톱밥 9
 
3.4%
집성재 9
 
3.4%
숯 8
 
3.1%
성형목탄 6
 
2.3%
Other values (81) 112
42.9%
2024-04-16T15:20:40.527788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
목 131
 
12.0%
116
 
10.6%
, 112
 
10.3%
재 102
 
9.3%
판 47
 
4.3%
합 42
 
3.8%
제 38
 
3.5%
펠 36
 
3.3%
릿 36
 
3.3%
탄 33
 
3.0%
Other values (117) 399
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 802
73.4%
Space Separator 116
 
10.6%
Other Punctuation 113
 
10.3%
Uppercase Letter 29
 
2.7%
Open Punctuation 16
 
1.5%
Close Punctuation 16
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
목 131
16.3%
재 102
 
12.7%
판 47
 
5.9%
합 42
 
5.2%
제 38
 
4.7%
펠 36
 
4.5%
릿 36
 
4.5%
탄 33
 
4.1%
드 27
 
3.4%
성 24
 
3.0%
Other values (100) 286
35.7%
Uppercase Letter
ValueCountFrequency (%)
B 5
17.2%
O 4
13.8%
P 3
10.3%
L 2
 
6.9%
S 2
 
6.9%
G 2
 
6.9%
E 2
 
6.9%
M 2
 
6.9%
D 2
 
6.9%
F 2
 
6.9%
Other values (2) 3
10.3%
Other Punctuation
ValueCountFrequency (%)
, 112
99.1%
/ 1
 
0.9%
Space Separator
ValueCountFrequency (%)
116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 802
73.4%
Common 261
 
23.9%
Latin 29
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
목 131
16.3%
재 102
 
12.7%
판 47
 
5.9%
합 42
 
5.2%
제 38
 
4.7%
펠 36
 
4.5%
릿 36
 
4.5%
탄 33
 
4.1%
드 27
 
3.4%
성 24
 
3.0%
Other values (100) 286
35.7%
Latin
ValueCountFrequency (%)
B 5
17.2%
O 4
13.8%
P 3
10.3%
L 2
 
6.9%
S 2
 
6.9%
G 2
 
6.9%
E 2
 
6.9%
M 2
 
6.9%
D 2
 
6.9%
F 2
 
6.9%
Other values (2) 3
10.3%
Common
ValueCountFrequency (%)
116
44.4%
, 112
42.9%
( 16
 
6.1%
) 16
 
6.1%
/ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 802
73.4%
ASCII 290
 
26.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
목 131
16.3%
재 102
 
12.7%
판 47
 
5.9%
합 42
 
5.2%
제 38
 
4.7%
펠 36
 
4.5%
릿 36
 
4.5%
탄 33
 
4.1%
드 27
 
3.4%
성 24
 
3.0%
Other values (100) 286
35.7%
ASCII
ValueCountFrequency (%)
116
40.0%
, 112
38.6%
( 16
 
5.5%
) 16
 
5.5%
B 5
 
1.7%
O 4
 
1.4%
P 3
 
1.0%
L 2
 
0.7%
S 2
 
0.7%
G 2
 
0.7%
Other values (7) 12
 
4.1%

인력보유현황
Text

MISSING 

Distinct17
Distinct (%)58.6%
Missing122
Missing (%)80.8%
Memory size1.3 KiB
2024-04-16T15:20:40.653247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length1
Mean length3.3103448
Min length1

Characters and Unicode

Total characters96
Distinct characters50
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)44.8%

Sample

1st row2
2nd row보유
3rd row직원 2인 트럭 등 장비 1식
4th row3
5th row2명
ValueCountFrequency (%)
1 6
 
15.8%
2 5
 
13.2%
3 3
 
7.9%
1명 3
 
7.9%
대표자1인 1
 
2.6%
김기범 1
 
2.6%
수료 1
 
2.6%
교육 1
 
2.6%
목재생산업(제재업1종 1
 
2.6%
4 1
 
2.6%
Other values (15) 15
39.5%
2024-04-16T15:20:41.100653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
 
12.5%
9
 
9.4%
2 7
 
7.3%
명 5
 
5.2%
3 3
 
3.1%
업 3
 
3.1%
산 3
 
3.1%
) 3
 
3.1%
( 3
 
3.1%
공 2
 
2.1%
Other values (40) 46
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55
57.3%
Decimal Number 25
26.0%
Space Separator 9
 
9.4%
Close Punctuation 3
 
3.1%
Open Punctuation 3
 
3.1%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 5
 
9.1%
업 3
 
5.5%
산 3
 
5.5%
공 2
 
3.6%
장 2
 
3.6%
인 2
 
3.6%
기 2
 
3.6%
대 2
 
3.6%
재 2
 
3.6%
표 2
 
3.6%
Other values (30) 30
54.5%
Decimal Number
ValueCountFrequency (%)
1 12
48.0%
2 7
28.0%
3 3
 
12.0%
4 1
 
4.0%
0 1
 
4.0%
6 1
 
4.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55
57.3%
Common 41
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
명 5
 
9.1%
업 3
 
5.5%
산 3
 
5.5%
공 2
 
3.6%
장 2
 
3.6%
인 2
 
3.6%
기 2
 
3.6%
대 2
 
3.6%
재 2
 
3.6%
표 2
 
3.6%
Other values (30) 30
54.5%
Common
ValueCountFrequency (%)
1 12
29.3%
9
22.0%
2 7
17.1%
3 3
 
7.3%
) 3
 
7.3%
( 3
 
7.3%
4 1
 
2.4%
- 1
 
2.4%
0 1
 
2.4%
6 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55
57.3%
ASCII 41
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
29.3%
9
22.0%
2 7
17.1%
3 3
 
7.3%
) 3
 
7.3%
( 3
 
7.3%
4 1
 
2.4%
- 1
 
2.4%
0 1
 
2.4%
6 1
 
2.4%
Hangul
ValueCountFrequency (%)
명 5
 
9.1%
업 3
 
5.5%
산 3
 
5.5%
공 2
 
3.6%
장 2
 
3.6%
인 2
 
3.6%
기 2
 
3.6%
대 2
 
3.6%
재 2
 
3.6%
표 2
 
3.6%
Other values (30) 30
54.5%

년간생산량
Real number (ℝ)

MISSING 

Distinct65
Distinct (%)50.4%
Missing22
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean26135.612
Minimum1
Maximum884696
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:41.211257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile100
Q11000
median5000
Q321440
95-th percentile81329.6
Maximum884696
Range884695
Interquartile range (IQR)20440

Descriptive statistics

Standard deviation90952.366
Coefficient of variation (CV)3.4800167
Kurtosis68.05671
Mean26135.612
Median Absolute Deviation (MAD)4900
Skewness7.8441743
Sum3371494
Variance8.272333 × 109
MonotonicityNot monotonic
2024-04-16T15:20:41.312036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000 11
 
7.3%
30000 10
 
6.6%
3000 7
 
4.6%
2000 6
 
4.0%
10000 5
 
3.3%
1000 5
 
3.3%
5000 5
 
3.3%
500 4
 
2.6%
200 4
 
2.6%
50000 3
 
2.0%
Other values (55) 69
45.7%
(Missing) 22
 
14.6%
ValueCountFrequency (%)
1 1
 
0.7%
6 1
 
0.7%
10 1
 
0.7%
30 1
 
0.7%
50 1
 
0.7%
100 3
2.0%
125 1
 
0.7%
200 4
2.6%
250 1
 
0.7%
300 2
1.3%
ValueCountFrequency (%)
884696 1
 
0.7%
500000 1
 
0.7%
178200 1
 
0.7%
120000 1
 
0.7%
100000 2
1.3%
92216 1
 
0.7%
65000 1
 
0.7%
50000 3
2.0%
45000 1
 
0.7%
36000 1
 
0.7%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct41
Distinct (%)33.1%
Missing27
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean1613950.5
Minimum0
Maximum1 × 108
Zeros2
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T15:20:41.412884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q150
median150
Q3400
95-th percentile6593.35
Maximum1 × 108
Range1 × 108
Interquartile range (IQR)350

Descriptive statistics

Standard deviation12648148
Coefficient of variation (CV)7.8367633
Kurtosis59.434
Mean1613950.5
Median Absolute Deviation (MAD)120
Skewness7.7766003
Sum2.0012986 × 108
Variance1.5997564 × 1014
MonotonicityNot monotonic
2024-04-16T15:20:41.518432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
100 16
 
10.6%
50 15
 
9.9%
200 11
 
7.3%
300 10
 
6.6%
30 10
 
6.6%
20 5
 
3.3%
10 5
 
3.3%
400 4
 
2.6%
500 4
 
2.6%
1000 3
 
2.0%
Other values (31) 41
27.2%
(Missing) 27
17.9%
ValueCountFrequency (%)
0 2
 
1.3%
1 1
 
0.7%
5 2
 
1.3%
10 5
 
3.3%
20 5
 
3.3%
30 10
6.6%
45 1
 
0.7%
50 15
9.9%
80 2
 
1.3%
100 16
10.6%
ValueCountFrequency (%)
100000000 2
1.3%
58298 1
 
0.7%
10000 3
2.0%
7051 1
 
0.7%
4000 1
 
0.7%
2000 1
 
0.7%
1550 1
 
0.7%
1500 1
 
0.7%
1287 1
 
0.7%
1244 1
 
0.7%

상태구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업
151 

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 (%)
영업 151
100.0%

Length

2024-04-16T15:20:41.618731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T15:20:41.693501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 151
100.0%

Unnamed: 35
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)목재생산업구분코드명목재생산업종류명취급목재제품인력보유현황년간생산량자본금상태구분명Unnamed: 35
01목재수입유통업09_27_01_P325000032500009020190000120191007<NA>1영업/정상1정상<NA><NA><NA><NA><NA><NA><NA>부산광역시 중구 중앙동6가 66-3번지 부산데파트부산광역시 중구 중앙대로 21, 부산데파트 4층 513-1호 (중앙동6가)<NA>(주)골드웨이트레이딩20191209090701U2019-12-11 02:40:00.0<NA>385601.609225179713.921731목재수입유통업<NA>목탄2100010영업<NA>
12목재수입유통업09_27_01_P325000032500009020140000320140804<NA>1영업/정상1정상<NA><NA><NA><NA>051-462-0345<NA><NA><NA>부산광역시 중구 충장대로9번길 16 (중앙동4가)<NA>효동선박20140804111418I2018-08-31 23:59:59.0<NA>385717.476671180525.499101목재수입유통업<NA>목재펠릿보유36000900영업<NA>
23목재수입유통업09_27_01_P325000032500009020140000220140516<NA>1영업/정상1정상<NA><NA><NA><NA>0514648501<NA><NA><NA>부산광역시 중구 중앙대로 26 (중앙동6가)<NA>코보데크20140516154214I2018-08-31 23:59:59.0<NA>385666.280865179774.158396목재수입유통업<NA>목재펠릿<NA>5000200영업<NA>
34목재수입유통업09_27_01_P325000032500009020140000420141124<NA>1영업/정상1정상<NA><NA><NA><NA>051-253-8653<NA><NA>부산광역시 중구 중앙동4가 36-14번지부산광역시 중구 해관로 65, 402호 (중앙동4가)<NA>(주)보경인터내셔날20141125132800I2018-08-31 23:59:59.0<NA>385502.49232180297.579331목재수입유통업<NA>목재펠릿<NA>500200영업<NA>
45목재수입유통업09_27_01_P325000032500009020150000120150422<NA>1영업/정상1정상<NA><NA><NA><NA>0514414011<NA><NA><NA>부산광역시 중구 대청로 91-6, 703동 (대청동2가)<NA>(주)알케이글로벌20150422101940I2018-08-31 23:59:59.0<NA>385032.076933180119.953454목재수입유통업<NA>우드펠렛<NA>300002000영업<NA>
56목재수입유통업09_27_01_P325000032500009020150000220150514<NA>1영업/정상1정상<NA><NA><NA><NA>0514690052<NA><NA><NA>부산광역시 중구 중앙대로 70, 14층 (중앙동4가)<NA>모이주식회사20150514135545I2018-08-31 23:59:59.0<NA>385637.167035180199.557791목재수입유통업<NA>목탄,브리켓,펠릿,원목,고사목 등<NA>480100영업<NA>
67목재수입유통업09_27_01_P325000032500009020150000320150717<NA>1영업/정상1정상<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 중구 중앙대로98번길 102, 17층 (중앙동4가)<NA>(주) stx마린서비스20150717170404I2018-08-31 23:59:59.0<NA><NA><NA>목재수입유통업<NA>목재펠릿<NA>1000010000영업<NA>
78목재수입유통업09_27_01_P325000032500009020170000120170929<NA>1영업/정상1정상<NA><NA><NA><NA>051-468-0482<NA><NA><NA>부산광역시 중구 동영로 41 (영주동)<NA>아이엘디자인20170929145350I2018-08-31 23:59:59.0<NA>385379.730646181233.261129목재수입유통업<NA>목탄직원 2인 트럭 등 장비 1식52830영업<NA>
89목재수입유통업09_27_01_P325000032500009020180000220181207<NA>1영업/정상1정상<NA><NA><NA><NA>0514684456<NA><NA><NA>부산광역시 중구 해관로 89, 805호 (대창동1가)48924조경수20181207140034I2018-12-09 02:20:10.0<NA>385507.64053180548.792612목재수입유통업<NA>목재팰릿330000100영업<NA>
910목재수입유통업09_27_01_P326000032600009020170000120170329<NA>1영업/정상1정상<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 서구 부용로 26-2 (서대신동1가)<NA>태광목탄20170329173953I2018-08-31 23:59:59.0<NA>383863.350935180611.184301목재수입유통업<NA>목탄(숯)<NA>2000758영업<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)목재생산업구분코드명목재생산업종류명취급목재제품인력보유현황년간생산량자본금상태구분명Unnamed: 35
141142목재수입유통업09_27_01_P339000033900009020190000320190523<NA>1영업/정상1정상<NA><NA><NA><NA>0518174341<NA><NA><NA>부산광역시 사상구 장인로 80 (학장동)47026***20190523172401I2019-05-25 02:20:54.0<NA>380159.887634184293.415315목재수입유통업<NA>합판(하드보드)<NA><NA><NA>영업<NA>
142143목재수입유통업09_27_01_P339000033900009020190000420191111<NA>1영업/정상1정상<NA><NA><NA><NA>315-1619<NA><NA><NA>부산광역시 사상구 낙동대로 830, 원일목재 (감전동)47029***20191111165715I2019-11-13 00:23:24.0<NA>379669.082866183529.113297목재수입유통업<NA>합판<NA><NA><NA>영업<NA>
143144목재수입유통업09_27_01_P339000033900009020200000120200107<NA>1영업/정상1정상<NA><NA><NA><NA>051-327-2022<NA><NA><NA>부산광역시 사상구 낙동대로1002번길 63, 동창종합건재(주) (감전동)47027동창종합건재(주)20200107175055I2020-01-09 00:23:25.0<NA>379906.568484185154.78147목재수입유통업<NA>합판<NA>70020영업<NA>
144145목재수입유통업09_27_01_P339000033900009020200000220200916<NA>1영업/정상1정상<NA><NA><NA><NA><NA><NA><NA>부산광역시 사상구 덕포동 419-11 해피궁부산광역시 사상구 사상로 309, 해피궁 (덕포동)46948***20200916092510I2020-09-18 00:23:12.0<NA>380596.604679187712.825739목재수입유통업<NA>백탄, 검탄110050영업<NA>
145146목재수입유통업09_27_01_P339000033900009020200000320201112<NA>1영업/정상1정상<NA><NA><NA><NA>328-0350<NA><NA><NA>부산광역시 사상구 괘감로 131, 삼주오피스텔 607호 (감전동)46982***20201112170521I2020-11-14 00:23:08.0<NA>381144.366063185965.490068목재수입유통업<NA>원목13000300영업<NA>
146147목재수입유통업09_27_01_P340000034000009020190000220191204<NA>1영업/정상1정상<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 정관읍 모전리 689-15번지부산광역시 기장군 정관읍 모전1길 7246008예랑차콜20191204170235I2019-12-06 00:23:27.0<NA>397288.512367206309.213371목재수입유통업<NA>목탄1400100영업<NA>
147148목재수입유통업09_27_01_P340000034000009020190000120191028<NA>1영업/정상1정상<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 청강리 146-2번지부산광역시 기장군 기장읍 청강로 5846080정태하20191028134335I2019-10-30 00:23:03.0<NA>402171.576044195361.118532목재수입유통업<NA>우드펠릿210영업<NA>
148149목재수입유통업09_27_01_P340000034000009020200000120200929<NA>1영업/정상1정상<NA><NA><NA><NA>051-996-7773<NA><NA>부산광역시 기장군 정관읍 매학리 168-11부산광역시 기장군 정관읍 매곡길 4146018정석우드텍20201231090619U2021-01-02 02:40:00.0<NA>397553.65237204205.798524목재수입유통업<NA>합판/원목목재생산업(제재업1종) 교육 수료104230영업<NA>
149150목재수입유통업09_27_01_P340000034000009020130000120131129<NA>1영업/정상1정상<NA><NA><NA><NA>051-722-0442<NA><NA><NA>부산광역시 기장군 정관면 산단7로 7-25<NA>(주)배성목재20140219141923I2018-08-31 23:59:59.0<NA>400575.125464204881.782325목재수입유통업<NA>제재목김기범 과장(임산가공산업기사)30000150영업<NA>
150151목재수입유통업09_27_01_P340000034000009020130000220131129<NA>1영업/정상1정상<NA><NA><NA><NA>051-506-3768<NA><NA><NA>부산광역시 기장군 장안읍 길천길 65<NA>가람아성(주)20201005133957U2020-10-07 02:40:00.0<NA>407807.189985205400.208795목재수입유통업<NA>합판<NA>5400100영업<NA>