Overview

Dataset statistics

Number of variables36
Number of observations4072
Missing cells38859
Missing cells (%)26.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory309.0 B

Variable types

Numeric14
Categorical9
Unsupported5
Text7
DateTime1

Dataset

Description6270000_대구광역시_09_30_08_P_대기오염물질배출시설설치사업장_7월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000048495&dataSetDetailId=DDI_0000048576&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
환경업무구분명 has constant value ""Constant
인허가일자 has 141 (3.5%) missing valuesMissing
인허가취소일자 has 4072 (100.0%) missing valuesMissing
폐업일자 has 2396 (58.8%) missing valuesMissing
휴업시작일자 has 4072 (100.0%) missing valuesMissing
휴업종료일자 has 4072 (100.0%) missing valuesMissing
재개업일자 has 4072 (100.0%) missing valuesMissing
소재지전화 has 644 (15.8%) missing valuesMissing
소재지면적 has 4072 (100.0%) missing valuesMissing
소재지우편번호 has 3139 (77.1%) missing valuesMissing
소재지전체주소 has 167 (4.1%) missing valuesMissing
도로명전체주소 has 1050 (25.8%) missing valuesMissing
도로명우편번호 has 2552 (62.7%) missing valuesMissing
업태구분명 has 1411 (34.7%) missing valuesMissing
좌표정보(X) has 939 (23.1%) missing valuesMissing
좌표정보(Y) has 939 (23.1%) missing valuesMissing
업종구분명 has 1411 (34.7%) missing valuesMissing
주생산품명 has 2744 (67.4%) missing valuesMissing
배출시설조업시간 has 56 (1.4%) missing valuesMissing
배출시설연간가동일수 has 59 (1.4%) missing valuesMissing
방지시설조업시간 has 431 (10.6%) missing valuesMissing
방지시설연간가동일수 has 420 (10.3%) missing valuesMissing
배출시설조업시간 is highly skewed (γ1 = 44.45752337)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설조업시간 has 1382 (33.9%) zerosZeros
배출시설연간가동일수 has 1396 (34.3%) zerosZeros
방지시설조업시간 has 1380 (33.9%) zerosZeros
방지시설연간가동일수 has 1387 (34.1%) zerosZeros

Reproduction

Analysis started2024-04-16 23:28:50.817660
Analysis finished2024-04-16 23:28:52.202543
Duration1.38 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct4072
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2036.5
Minimum1
Maximum4072
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:52.257555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile204.55
Q11018.75
median2036.5
Q33054.25
95-th percentile3868.45
Maximum4072
Range4071
Interquartile range (IQR)2035.5

Descriptive statistics

Standard deviation1175.6295
Coefficient of variation (CV)0.57727939
Kurtosis-1.2
Mean2036.5
Median Absolute Deviation (MAD)1018
Skewness0
Sum8292628
Variance1382104.7
MonotonicityStrictly increasing
2024-04-17T08:28:52.389866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
2721 1
 
< 0.1%
2708 1
 
< 0.1%
2709 1
 
< 0.1%
2710 1
 
< 0.1%
2711 1
 
< 0.1%
2712 1
 
< 0.1%
2713 1
 
< 0.1%
2714 1
 
< 0.1%
2715 1
 
< 0.1%
Other values (4062) 4062
99.8%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
4072 1
< 0.1%
4071 1
< 0.1%
4070 1
< 0.1%
4069 1
< 0.1%
4068 1
< 0.1%
4067 1
< 0.1%
4066 1
< 0.1%
4065 1
< 0.1%
4064 1
< 0.1%
4063 1
< 0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
대기오염물질배출시설설치사업장
4072 

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기오염물질배출시설설치사업장 4072
100.0%

Length

2024-04-17T08:28:52.493439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:52.564051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기오염물질배출시설설치사업장 4072
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
09_30_08_P
4072 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_08_P
2nd row09_30_08_P
3rd row09_30_08_P
4th row09_30_08_P
5th row09_30_08_P

Common Values

ValueCountFrequency (%)
09_30_08_P 4072
100.0%

Length

2024-04-17T08:28:52.637230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:52.706598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_08_p 4072
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3456426.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:52.772274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3430000
Q13430000
median3470000
Q33470000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation20656.804
Coefficient of variation (CV)0.0059763465
Kurtosis-1.3429693
Mean3456426.8
Median Absolute Deviation (MAD)10000
Skewness-0.5097429
Sum1.407457 × 1010
Variance4.2670356 × 108
MonotonicityIncreasing
2024-04-17T08:28:52.857825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 1662
40.8%
3430000 1075
26.4%
3480000 668
16.4%
3450000 374
 
9.2%
3420000 165
 
4.1%
3460000 79
 
1.9%
3410000 32
 
0.8%
3440000 17
 
0.4%
ValueCountFrequency (%)
3410000 32
 
0.8%
3420000 165
 
4.1%
3430000 1075
26.4%
3440000 17
 
0.4%
3450000 374
 
9.2%
3460000 79
 
1.9%
3470000 1662
40.8%
3480000 668
16.4%
ValueCountFrequency (%)
3480000 668
16.4%
3470000 1662
40.8%
3460000 79
 
1.9%
3450000 374
 
9.2%
3440000 17
 
0.4%
3430000 1075
26.4%
3420000 165
 
4.1%
3410000 32
 
0.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct4072
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.456427 × 1017
Minimum3.4100002 × 1017
Maximum3.4800002 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:52.961200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4100002 × 1017
5-th percentile3.4300002 × 1017
Q13.4300002 × 1017
median3.4700002 × 1017
Q33.4700002 × 1017
95-th percentile3.4800002 × 1017
Maximum3.4800002 × 1017
Range7 × 1015
Interquartile range (IQR)4 × 1015

Descriptive statistics

Standard deviation2.0656804 × 1015
Coefficient of variation (CV)0.0059763461
Kurtosis-1.3429693
Mean3.456427 × 1017
Median Absolute Deviation (MAD)1 × 1015
Skewness-0.5097429
Sum5.5045367 × 1018
Variance4.2670356 × 1030
MonotonicityNot monotonic
2024-04-17T08:28:53.093482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341000021201500007 1
 
< 0.1%
347000021199400029 1
 
< 0.1%
347000021199700016 1
 
< 0.1%
347000021199700017 1
 
< 0.1%
347000021199700018 1
 
< 0.1%
347000021199700019 1
 
< 0.1%
347000021199700020 1
 
< 0.1%
347000021199700021 1
 
< 0.1%
347000021199700022 1
 
< 0.1%
347000021199700023 1
 
< 0.1%
Other values (4062) 4062
99.8%
ValueCountFrequency (%)
341000021200400001 1
< 0.1%
341000021200400002 1
< 0.1%
341000021200700001 1
< 0.1%
341000021201400001 1
< 0.1%
341000021201500001 1
< 0.1%
341000021201500002 1
< 0.1%
341000021201500003 1
< 0.1%
341000021201500004 1
< 0.1%
341000021201500005 1
< 0.1%
341000021201500006 1
< 0.1%
ValueCountFrequency (%)
348000021201900018 1
< 0.1%
348000021201900017 1
< 0.1%
348000021201900016 1
< 0.1%
348000021201900015 1
< 0.1%
348000021201900014 1
< 0.1%
348000021201900013 1
< 0.1%
348000021201900012 1
< 0.1%
348000021201900011 1
< 0.1%
348000021201900010 1
< 0.1%
348000021201900009 1
< 0.1%

인허가일자
Real number (ℝ)

MISSING 

Distinct2500
Distinct (%)63.6%
Missing141
Missing (%)3.5%
Infinite0
Infinite (%)0.0%
Mean20029680
Minimum19010101
Maximum20190628
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:53.209841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19010101
5-th percentile19870320
Q119990729
median20040701
Q320120405
95-th percentile20170416
Maximum20190628
Range1180527
Interquartile range (IQR)129676

Descriptive statistics

Standard deviation148108.16
Coefficient of variation (CV)0.0073944345
Kurtosis27.283782
Mean20029680
Median Absolute Deviation (MAD)70219
Skewness-4.3603284
Sum7.8736672 × 1010
Variance2.1936026 × 1010
MonotonicityNot monotonic
2024-04-17T08:28:53.315961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20040701 76
 
1.9%
19010101 52
 
1.3%
20040702 48
 
1.2%
20040621 36
 
0.9%
20040628 25
 
0.6%
20040630 24
 
0.6%
20120322 23
 
0.6%
19940427 16
 
0.4%
19840210 14
 
0.3%
20040603 13
 
0.3%
Other values (2490) 3604
88.5%
(Missing) 141
 
3.5%
ValueCountFrequency (%)
19010101 52
1.3%
19240212 1
 
< 0.1%
19740905 1
 
< 0.1%
19760816 1
 
< 0.1%
19781004 1
 
< 0.1%
19781123 1
 
< 0.1%
19781205 1
 
< 0.1%
19781229 1
 
< 0.1%
19790220 6
 
0.1%
19790227 1
 
< 0.1%
ValueCountFrequency (%)
20190628 1
< 0.1%
20190626 1
< 0.1%
20190625 1
< 0.1%
20190624 1
< 0.1%
20190621 1
< 0.1%
20190620 2
< 0.1%
20190614 1
< 0.1%
20190531 1
< 0.1%
20190523 2
< 0.1%
20190516 2
< 0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4072
Missing (%)100.0%
Memory size35.9 KiB
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
3
1909 
1
1841 
4
313 
2
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 1909
46.9%
1 1841
45.2%
4 313
 
7.7%
2 9
 
0.2%

Length

2024-04-17T08:28:53.411000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:53.493052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1909
46.9%
1 1841
45.2%
4 313
 
7.7%
2 9
 
0.2%

영업상태명
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
폐업
1909 
영업/정상
1841 
취소/말소/만료/정지/중지
313 
휴업
 
9

Length

Max length14
Median length5
Mean length4.2787328
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1909
46.9%
영업/정상 1841
45.2%
취소/말소/만료/정지/중지 313
 
7.7%
휴업 9
 
0.2%

Length

2024-04-17T08:28:53.582239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:53.666085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1909
46.9%
영업/정상 1841
45.2%
취소/말소/만료/정지/중지 313
 
7.7%
휴업 9
 
0.2%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
2
1909 
11
1841 
4
313 
1
 
9

Length

Max length2
Median length1
Mean length1.452112
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
2 1909
46.9%
11 1841
45.2%
4 313
 
7.7%
1 9
 
0.2%

Length

2024-04-17T08:28:53.751886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:53.829638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1909
46.9%
11 1841
45.2%
4 313
 
7.7%
1 9
 
0.2%
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
폐업
1909 
영업
1841 
폐쇄
313 
휴업
 
9

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1909
46.9%
영업 1841
45.2%
폐쇄 313
 
7.7%
휴업 9
 
0.2%

Length

2024-04-17T08:28:53.908343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:53.988388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1909
46.9%
영업 1841
45.2%
폐쇄 313
 
7.7%
휴업 9
 
0.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct1039
Distinct (%)62.0%
Missing2396
Missing (%)58.8%
Infinite0
Infinite (%)0.0%
Mean20087259
Minimum19930721
Maximum20190630
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:54.089112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19930721
5-th percentile20030522
Q120050324
median20081006
Q320120109
95-th percentile20180620
Maximum20190630
Range259909
Interquartile range (IQR)69785.5

Descriptive statistics

Standard deviation47236.098
Coefficient of variation (CV)0.0023515453
Kurtosis-0.52700686
Mean20087259
Median Absolute Deviation (MAD)30684.5
Skewness0.60081367
Sum3.3666246 × 1010
Variance2.2312489 × 109
MonotonicityNot monotonic
2024-04-17T08:28:54.200528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20081118 69
 
1.7%
20081008 52
 
1.3%
20040701 38
 
0.9%
20081006 38
 
0.9%
20040907 21
 
0.5%
20091221 17
 
0.4%
20091216 11
 
0.3%
20091218 11
 
0.3%
20040630 10
 
0.2%
20040601 10
 
0.2%
Other values (1029) 1399
34.4%
(Missing) 2396
58.8%
ValueCountFrequency (%)
19930721 1
< 0.1%
19940225 1
< 0.1%
20001018 1
< 0.1%
20001108 1
< 0.1%
20001216 1
< 0.1%
20001219 1
< 0.1%
20010131 1
< 0.1%
20010205 1
< 0.1%
20010208 1
< 0.1%
20010310 1
< 0.1%
ValueCountFrequency (%)
20190630 1
< 0.1%
20190625 1
< 0.1%
20190617 1
< 0.1%
20190614 1
< 0.1%
20190607 1
< 0.1%
20190517 1
< 0.1%
20190515 1
< 0.1%
20190503 1
< 0.1%
20190501 1
< 0.1%
20190422 1
< 0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4072
Missing (%)100.0%
Memory size35.9 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4072
Missing (%)100.0%
Memory size35.9 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4072
Missing (%)100.0%
Memory size35.9 KiB

소재지전화
Text

MISSING 

Distinct3191
Distinct (%)93.1%
Missing644
Missing (%)15.8%
Memory size31.9 KiB
2024-04-17T08:28:54.411334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9.8363477
Min length3

Characters and Unicode

Total characters33719
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2980 ?
Unique (%)86.9%

Sample

1st row0534288900
2nd row053-609-1407
3rd row053-250-5555
4th row053-555-9204
5th row053-251-6019
ValueCountFrequency (%)
053 494
 
9.9%
581 121
 
2.4%
582 78
 
1.6%
583 67
 
1.3%
354 35
 
0.7%
562 25
 
0.5%
356 24
 
0.5%
567 23
 
0.5%
053615 23
 
0.5%
584 23
 
0.5%
Other values (3154) 4084
81.7%
2024-04-17T08:28:54.751251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 6997
20.8%
3 5006
14.8%
0 4945
14.7%
1 3090
9.2%
8 2562
 
7.6%
6 2416
 
7.2%
2 2036
 
6.0%
7 1613
 
4.8%
1582
 
4.7%
4 1557
 
4.6%
Other values (3) 1915
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 31616
93.8%
Space Separator 1582
 
4.7%
Dash Punctuation 520
 
1.5%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 6997
22.1%
3 5006
15.8%
0 4945
15.6%
1 3090
9.8%
8 2562
 
8.1%
6 2416
 
7.6%
2 2036
 
6.4%
7 1613
 
5.1%
4 1557
 
4.9%
9 1394
 
4.4%
Space Separator
ValueCountFrequency (%)
1582
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 520
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 33719
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 6997
20.8%
3 5006
14.8%
0 4945
14.7%
1 3090
9.2%
8 2562
 
7.6%
6 2416
 
7.2%
2 2036
 
6.0%
7 1613
 
4.8%
1582
 
4.7%
4 1557
 
4.6%
Other values (3) 1915
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33719
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 6997
20.8%
3 5006
14.8%
0 4945
14.7%
1 3090
9.2%
8 2562
 
7.6%
6 2416
 
7.2%
2 2036
 
6.0%
7 1613
 
4.8%
1582
 
4.7%
4 1557
 
4.6%
Other values (3) 1915
 
5.7%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4072
Missing (%)100.0%
Memory size35.9 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)12.5%
Missing3139
Missing (%)77.1%
Infinite0
Infinite (%)0.0%
Mean693143.49
Minimum4
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:54.861840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile701300
Q1704070
median704330
Q3704900
95-th percentile711855
Maximum711891
Range711887
Interquartile range (IQR)830

Descriptive statistics

Standard deviation91565.328
Coefficient of variation (CV)0.13210155
Kurtosis53.526363
Mean693143.49
Median Absolute Deviation (MAD)500
Skewness-7.4404284
Sum6.4670287 × 108
Variance8.3842093 × 109
MonotonicityNot monotonic
2024-04-17T08:28:54.964460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704190 63
 
1.5%
703830 58
 
1.4%
704900 57
 
1.4%
704330 39
 
1.0%
711855 39
 
1.0%
704801 37
 
0.9%
704400 36
 
0.9%
703833 35
 
0.9%
704170 35
 
0.9%
704070 32
 
0.8%
Other values (107) 502
 
12.3%
(Missing) 3139
77.1%
ValueCountFrequency (%)
4 1
 
< 0.1%
8 1
 
< 0.1%
704 14
0.3%
700761 1
 
< 0.1%
701040 1
 
< 0.1%
701050 2
 
< 0.1%
701130 1
 
< 0.1%
701140 1
 
< 0.1%
701180 1
 
< 0.1%
701190 1
 
< 0.1%
ValueCountFrequency (%)
711891 7
0.2%
711890 2
 
< 0.1%
711882 1
 
< 0.1%
711874 3
0.1%
711873 1
 
< 0.1%
711871 4
0.1%
711863 2
 
< 0.1%
711860 1
 
< 0.1%
711858 3
0.1%
711857 3
0.1%

소재지전체주소
Text

MISSING 

Distinct2916
Distinct (%)74.7%
Missing167
Missing (%)4.1%
Memory size31.9 KiB
2024-04-17T08:28:55.246362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length42
Mean length22.636108
Min length13

Characters and Unicode

Total characters88394
Distinct characters198
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2237 ?
Unique (%)57.3%

Sample

1st row대구광역시 중구 덕산동 110번지
2nd row대구광역시 중구 남일동 138-3번지 국민은행대구지점
3rd row대구광역시 중구 수창동 47번지
4th row대구광역시 중구 수창동 50-21번지
5th row대구광역시 중구 대봉동 111-1번지
ValueCountFrequency (%)
대구광역시 3905
23.5%
달서구 1454
 
8.7%
서구 1016
 
6.1%
달성군 823
 
5.0%
북구 368
 
2.2%
갈산동 366
 
2.2%
이현동 365
 
2.2%
비산동 342
 
2.1%
논공읍 325
 
2.0%
중리동 260
 
1.6%
Other values (2969) 7395
44.5%
2024-04-17T08:28:55.641379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16635
18.8%
7130
 
8.1%
4186
 
4.7%
3906
 
4.4%
3906
 
4.4%
3905
 
4.4%
3884
 
4.4%
3691
 
4.2%
3349
 
3.8%
1 3343
 
3.8%
Other values (188) 34459
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51351
58.1%
Decimal Number 16978
 
19.2%
Space Separator 16635
 
18.8%
Dash Punctuation 3003
 
3.4%
Uppercase Letter 153
 
0.2%
Close Punctuation 123
 
0.1%
Open Punctuation 106
 
0.1%
Other Punctuation 41
 
< 0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
7130
13.9%
4186
 
8.2%
3906
 
7.6%
3906
 
7.6%
3905
 
7.6%
3884
 
7.6%
3691
 
7.2%
3349
 
6.5%
2509
 
4.9%
2280
 
4.4%
Other values (168) 12605
24.5%
Decimal Number
ValueCountFrequency (%)
1 3343
19.7%
2 2280
13.4%
0 1956
11.5%
3 1908
11.2%
4 1556
9.2%
5 1292
 
7.6%
6 1246
 
7.3%
9 1208
 
7.1%
7 1167
 
6.9%
8 1022
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
B 81
52.9%
L 68
44.4%
A 3
 
2.0%
C 1
 
0.7%
Space Separator
ValueCountFrequency (%)
16635
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3003
100.0%
Close Punctuation
ValueCountFrequency (%)
) 123
100.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Lowercase Letter
ValueCountFrequency (%)
b 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 51351
58.1%
Common 36886
41.7%
Latin 157
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
7130
13.9%
4186
 
8.2%
3906
 
7.6%
3906
 
7.6%
3905
 
7.6%
3884
 
7.6%
3691
 
7.2%
3349
 
6.5%
2509
 
4.9%
2280
 
4.4%
Other values (168) 12605
24.5%
Common
ValueCountFrequency (%)
16635
45.1%
1 3343
 
9.1%
- 3003
 
8.1%
2 2280
 
6.2%
0 1956
 
5.3%
3 1908
 
5.2%
4 1556
 
4.2%
5 1292
 
3.5%
6 1246
 
3.4%
9 1208
 
3.3%
Other values (5) 2459
 
6.7%
Latin
ValueCountFrequency (%)
B 81
51.6%
L 68
43.3%
b 4
 
2.5%
A 3
 
1.9%
C 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 51351
58.1%
ASCII 37043
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16635
44.9%
1 3343
 
9.0%
- 3003
 
8.1%
2 2280
 
6.2%
0 1956
 
5.3%
3 1908
 
5.2%
4 1556
 
4.2%
5 1292
 
3.5%
6 1246
 
3.4%
9 1208
 
3.3%
Other values (10) 2616
 
7.1%
Hangul
ValueCountFrequency (%)
7130
13.9%
4186
 
8.2%
3906
 
7.6%
3906
 
7.6%
3905
 
7.6%
3884
 
7.6%
3691
 
7.2%
3349
 
6.5%
2509
 
4.9%
2280
 
4.4%
Other values (168) 12605
24.5%

도로명전체주소
Text

MISSING 

Distinct2629
Distinct (%)87.0%
Missing1050
Missing (%)25.8%
Memory size31.9 KiB
2024-04-17T08:28:55.937042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length44
Mean length25.55857
Min length19

Characters and Unicode

Total characters77238
Distinct characters287
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

Unique2321 ?
Unique (%)76.8%

Sample

1st row대구광역시 중구 달구벌대로 지하 2100 (덕산동, 반월당역)
2nd row대구광역시 중구 국채보상로 585 (사일동, 동성로파티)
3rd row대구광역시 중구 달구벌대로 2095 (덕산동)
4th row대구광역시 중구 국채보상로 지하 470 (대신동, 대신지하상가)
5th row대구광역시 중구 중앙대로 401, 국민은행대구지점 (남일동)
ValueCountFrequency (%)
대구광역시 3022
 
19.7%
달서구 999
 
6.5%
서구 809
 
5.3%
달성군 601
 
3.9%
북구 364
 
2.4%
논공읍 301
 
2.0%
이현동 274
 
1.8%
비산동 266
 
1.7%
갈산동 238
 
1.6%
중리동 230
 
1.5%
Other values (1565) 8228
53.7%
2024-04-17T08:28:56.349547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13067
 
16.9%
5708
 
7.4%
3548
 
4.6%
3035
 
3.9%
3027
 
3.9%
3025
 
3.9%
2941
 
3.8%
2876
 
3.7%
2843
 
3.7%
) 2518
 
3.3%
Other values (277) 34650
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 47021
60.9%
Space Separator 13067
 
16.9%
Decimal Number 11466
 
14.8%
Close Punctuation 2518
 
3.3%
Open Punctuation 2518
 
3.3%
Dash Punctuation 483
 
0.6%
Other Punctuation 141
 
0.2%
Uppercase Letter 24
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5708
 
12.1%
3548
 
7.5%
3035
 
6.5%
3027
 
6.4%
3025
 
6.4%
2941
 
6.3%
2876
 
6.1%
2843
 
6.0%
1992
 
4.2%
1976
 
4.2%
Other values (253) 16050
34.1%
Decimal Number
ValueCountFrequency (%)
1 2137
18.6%
2 1601
14.0%
3 1590
13.9%
5 1056
9.2%
4 1031
9.0%
6 965
8.4%
7 881
7.7%
9 788
 
6.9%
0 712
 
6.2%
8 705
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
B 9
37.5%
A 6
25.0%
K 2
 
8.3%
L 2
 
8.3%
T 1
 
4.2%
C 1
 
4.2%
E 1
 
4.2%
G 1
 
4.2%
S 1
 
4.2%
Space Separator
ValueCountFrequency (%)
13067
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2518
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2518
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 483
100.0%
Other Punctuation
ValueCountFrequency (%)
, 141
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 47021
60.9%
Common 30193
39.1%
Latin 24
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5708
 
12.1%
3548
 
7.5%
3035
 
6.5%
3027
 
6.4%
3025
 
6.4%
2941
 
6.3%
2876
 
6.1%
2843
 
6.0%
1992
 
4.2%
1976
 
4.2%
Other values (253) 16050
34.1%
Common
ValueCountFrequency (%)
13067
43.3%
) 2518
 
8.3%
( 2518
 
8.3%
1 2137
 
7.1%
2 1601
 
5.3%
3 1590
 
5.3%
5 1056
 
3.5%
4 1031
 
3.4%
6 965
 
3.2%
7 881
 
2.9%
Other values (5) 2829
 
9.4%
Latin
ValueCountFrequency (%)
B 9
37.5%
A 6
25.0%
K 2
 
8.3%
L 2
 
8.3%
T 1
 
4.2%
C 1
 
4.2%
E 1
 
4.2%
G 1
 
4.2%
S 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 47021
60.9%
ASCII 30217
39.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13067
43.2%
) 2518
 
8.3%
( 2518
 
8.3%
1 2137
 
7.1%
2 1601
 
5.3%
3 1590
 
5.3%
5 1056
 
3.5%
4 1031
 
3.4%
6 965
 
3.2%
7 881
 
2.9%
Other values (14) 2853
 
9.4%
Hangul
ValueCountFrequency (%)
5708
 
12.1%
3548
 
7.5%
3035
 
6.5%
3027
 
6.4%
3025
 
6.4%
2941
 
6.3%
2876
 
6.1%
2843
 
6.0%
1992
 
4.2%
1976
 
4.2%
Other values (253) 16050
34.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct315
Distinct (%)20.7%
Missing2552
Missing (%)62.7%
Infinite0
Infinite (%)0.0%
Mean461657.57
Minimum41007
Maximum711892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:56.461487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41007
5-th percentile41500
Q142719
median702872
Q3704900
95-th percentile711856
Maximum711892
Range670885
Interquartile range (IQR)662181

Descriptive statistics

Standard deviation319976.45
Coefficient of variation (CV)0.69310344
Kurtosis-1.7007455
Mean461657.57
Median Absolute Deviation (MAD)2159.5
Skewness-0.54881803
Sum7.0171951 × 108
Variance1.0238493 × 1011
MonotonicityNot monotonic
2024-04-17T08:28:56.564034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704900 89
 
2.2%
704801 80
 
2.0%
711855 46
 
1.1%
704190 43
 
1.1%
704833 43
 
1.1%
702815 42
 
1.0%
703830 40
 
1.0%
703825 36
 
0.9%
704920 29
 
0.7%
704901 28
 
0.7%
Other values (305) 1044
25.6%
(Missing) 2552
62.7%
ValueCountFrequency (%)
41007 1
 
< 0.1%
41052 1
 
< 0.1%
41060 1
 
< 0.1%
41061 1
 
< 0.1%
41074 1
 
< 0.1%
41078 10
0.2%
41079 3
 
0.1%
41081 4
 
0.1%
41082 1
 
< 0.1%
41097 1
 
< 0.1%
ValueCountFrequency (%)
711892 10
0.2%
711891 18
0.4%
711890 2
 
< 0.1%
711882 2
 
< 0.1%
711874 2
 
< 0.1%
711871 2
 
< 0.1%
711861 1
 
< 0.1%
711860 1
 
< 0.1%
711858 19
0.5%
711857 16
0.4%
Distinct3474
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
2024-04-17T08:28:56.771114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length7.2148821
Min length2

Characters and Unicode

Total characters29379
Distinct characters563
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2996 ?
Unique (%)73.6%

Sample

1st row메트로센터
2nd row동성로파티지원센터관리단
3rd row지알이전문투자형사모부동산투자신탁 제2호
4th row대신지하상가관리소
5th row(주)국민은행 대구지점
ValueCountFrequency (%)
주식회사 41
 
0.9%
대구공장 24
 
0.5%
제2공장 21
 
0.5%
2공장 12
 
0.3%
성서공장 10
 
0.2%
10
 
0.2%
대구지점 8
 
0.2%
비산공장 7
 
0.2%
태성산업 7
 
0.2%
삼일산업 6
 
0.1%
Other values (3561) 4279
96.7%
2024-04-17T08:28:57.101978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 1907
 
6.5%
) 1885
 
6.4%
1797
 
6.1%
954
 
3.2%
821
 
2.8%
782
 
2.7%
718
 
2.4%
612
 
2.1%
496
 
1.7%
458
 
1.6%
Other values (553) 18949
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24278
82.6%
Open Punctuation 1908
 
6.5%
Close Punctuation 1886
 
6.4%
Uppercase Letter 361
 
1.2%
Space Separator 353
 
1.2%
Other Punctuation 211
 
0.7%
Other Symbol 200
 
0.7%
Decimal Number 162
 
0.6%
Lowercase Letter 14
 
< 0.1%
Dash Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1797
 
7.4%
954
 
3.9%
821
 
3.4%
782
 
3.2%
718
 
3.0%
612
 
2.5%
496
 
2.0%
458
 
1.9%
454
 
1.9%
449
 
1.8%
Other values (497) 16737
68.9%
Uppercase Letter
ValueCountFrequency (%)
S 43
 
11.9%
C 33
 
9.1%
T 28
 
7.8%
E 25
 
6.9%
M 22
 
6.1%
K 21
 
5.8%
P 21
 
5.8%
O 20
 
5.5%
D 19
 
5.3%
A 17
 
4.7%
Other values (14) 112
31.0%
Lowercase Letter
ValueCountFrequency (%)
e 4
28.6%
h 2
14.3%
c 1
 
7.1%
m 1
 
7.1%
a 1
 
7.1%
r 1
 
7.1%
o 1
 
7.1%
t 1
 
7.1%
n 1
 
7.1%
g 1
 
7.1%
Decimal Number
ValueCountFrequency (%)
2 74
45.7%
1 55
34.0%
3 17
 
10.5%
8 6
 
3.7%
5 4
 
2.5%
6 3
 
1.9%
4 2
 
1.2%
9 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 98
46.4%
, 85
40.3%
& 16
 
7.6%
/ 7
 
3.3%
* 3
 
1.4%
2
 
0.9%
Open Punctuation
ValueCountFrequency (%)
( 1907
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1885
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
353
100.0%
Other Symbol
ValueCountFrequency (%)
200
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Math Symbol
ValueCountFrequency (%)
| 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24478
83.3%
Common 4526
 
15.4%
Latin 375
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1797
 
7.3%
954
 
3.9%
821
 
3.4%
782
 
3.2%
718
 
2.9%
612
 
2.5%
496
 
2.0%
458
 
1.9%
454
 
1.9%
449
 
1.8%
Other values (498) 16937
69.2%
Latin
ValueCountFrequency (%)
S 43
 
11.5%
C 33
 
8.8%
T 28
 
7.5%
E 25
 
6.7%
M 22
 
5.9%
K 21
 
5.6%
P 21
 
5.6%
O 20
 
5.3%
D 19
 
5.1%
A 17
 
4.5%
Other values (24) 126
33.6%
Common
ValueCountFrequency (%)
( 1907
42.1%
) 1885
41.6%
353
 
7.8%
. 98
 
2.2%
, 85
 
1.9%
2 74
 
1.6%
1 55
 
1.2%
3 17
 
0.4%
& 16
 
0.4%
/ 7
 
0.2%
Other values (11) 29
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24278
82.6%
ASCII 4899
 
16.7%
None 202
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 1907
38.9%
) 1885
38.5%
353
 
7.2%
. 98
 
2.0%
, 85
 
1.7%
2 74
 
1.5%
1 55
 
1.1%
S 43
 
0.9%
C 33
 
0.7%
T 28
 
0.6%
Other values (44) 338
 
6.9%
Hangul
ValueCountFrequency (%)
1797
 
7.4%
954
 
3.9%
821
 
3.4%
782
 
3.2%
718
 
3.0%
612
 
2.5%
496
 
2.0%
458
 
1.9%
454
 
1.9%
449
 
1.8%
Other values (497) 16737
68.9%
None
ValueCountFrequency (%)
200
99.0%
2
 
1.0%

최종수정시점
Real number (ℝ)

Distinct4070
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0127641 × 1013
Minimum2.0001018 × 1013
Maximum2.0190629 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:57.212855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0001018 × 1013
5-th percentile2.0040618 × 1013
Q12.0090221 × 1013
median2.0140612 × 1013
Q32.0170712 × 1013
95-th percentile2.0190318 × 1013
Maximum2.0190629 × 1013
Range1.8961092 × 1011
Interquartile range (IQR)8.0491063 × 1010

Descriptive statistics

Standard deviation4.9587781 × 1010
Coefficient of variation (CV)0.0024636658
Kurtosis-1.0032773
Mean2.0127641 × 1013
Median Absolute Deviation (MAD)3.9516508 × 1010
Skewness-0.48242926
Sum8.1959754 × 1016
Variance2.458948 × 1021
MonotonicityNot monotonic
2024-04-17T08:28:57.324498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160627095842 2
 
< 0.1%
20071123170427 2
 
< 0.1%
20151208204903 1
 
< 0.1%
20060208160124 1
 
< 0.1%
20081118152213 1
 
< 0.1%
20091222135850 1
 
< 0.1%
20151218150818 1
 
< 0.1%
20190313154906 1
 
< 0.1%
20180629181906 1
 
< 0.1%
20110922173536 1
 
< 0.1%
Other values (4060) 4060
99.7%
ValueCountFrequency (%)
20001018165055 1
< 0.1%
20010104114108 1
< 0.1%
20010131100554 1
< 0.1%
20010328174344 1
< 0.1%
20010511135104 1
< 0.1%
20010605181832 1
< 0.1%
20010605182545 1
< 0.1%
20010605193518 1
< 0.1%
20010605194306 1
< 0.1%
20010625143852 1
< 0.1%
ValueCountFrequency (%)
20190629085430 1
< 0.1%
20190628182242 1
< 0.1%
20190628182155 1
< 0.1%
20190628181422 1
< 0.1%
20190628163312 1
< 0.1%
20190628112939 1
< 0.1%
20190628112930 1
< 0.1%
20190628100424 1
< 0.1%
20190628094855 1
< 0.1%
20190627191938 1
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
I
3552 
U
520 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 3552
87.2%
U 520
 
12.8%

Length

2024-04-17T08:28:57.424032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:57.495950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 3552
87.2%
u 520
 
12.8%
Distinct219
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
Minimum2018-09-01 23:59:59
Maximum2019-07-02 02:21:40
2024-04-17T08:28:57.580301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T08:28:57.936415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Text

MISSING 

Distinct402
Distinct (%)15.1%
Missing1411
Missing (%)34.7%
Memory size31.9 KiB
2024-04-17T08:28:58.167858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length11.344607
Min length2

Characters and Unicode

Total characters30188
Distinct characters290
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)7.0%

Sample

1st row부동산 임대업
2nd row우편 및 소포 송달업
3rd row백화점
4th row주거용 부동산 관리업
5th row병원
ValueCountFrequency (%)
제조업 1337
 
16.0%
기타 831
 
10.0%
750
 
9.0%
자동차 314
 
3.8%
가공업 295
 
3.5%
염색 277
 
3.3%
섬유 257
 
3.1%
수리업 256
 
3.1%
조립금속제품 213
 
2.6%
그외 198
 
2.4%
Other values (539) 3614
43.3%
2024-04-17T08:28:58.508721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5683
18.8%
2713
 
9.0%
2342
 
7.8%
1700
 
5.6%
1177
 
3.9%
1024
 
3.4%
902
 
3.0%
816
 
2.7%
722
 
2.4%
644
 
2.1%
Other values (280) 12465
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24358
80.7%
Space Separator 5683
 
18.8%
Other Punctuation 124
 
0.4%
Decimal Number 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2713
 
11.1%
2342
 
9.6%
1700
 
7.0%
1177
 
4.8%
1024
 
4.2%
902
 
3.7%
816
 
3.4%
722
 
3.0%
644
 
2.6%
547
 
2.2%
Other values (275) 11771
48.3%
Other Punctuation
ValueCountFrequency (%)
, 113
91.1%
· 6
 
4.8%
; 5
 
4.0%
Space Separator
ValueCountFrequency (%)
5683
100.0%
Decimal Number
ValueCountFrequency (%)
1 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24358
80.7%
Common 5830
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2713
 
11.1%
2342
 
9.6%
1700
 
7.0%
1177
 
4.8%
1024
 
4.2%
902
 
3.7%
816
 
3.4%
722
 
3.0%
644
 
2.6%
547
 
2.2%
Other values (275) 11771
48.3%
Common
ValueCountFrequency (%)
5683
97.5%
, 113
 
1.9%
1 23
 
0.4%
· 6
 
0.1%
; 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24358
80.7%
ASCII 5824
 
19.3%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5683
97.6%
, 113
 
1.9%
1 23
 
0.4%
; 5
 
0.1%
Hangul
ValueCountFrequency (%)
2713
 
11.1%
2342
 
9.6%
1700
 
7.0%
1177
 
4.8%
1024
 
4.2%
902
 
3.7%
816
 
3.4%
722
 
3.0%
644
 
2.6%
547
 
2.2%
Other values (275) 11771
48.3%
None
ValueCountFrequency (%)
· 6
100.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct2432
Distinct (%)77.6%
Missing939
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean337761.15
Minimum324827.06
Maximum357474.36
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:58.615037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum324827.06
5-th percentile328459.42
Q1335009.97
median337458.94
Q3339806.13
95-th percentile348677.08
Maximum357474.36
Range32647.303
Interquartile range (IQR)4796.1587

Descriptive statistics

Standard deviation5704.0638
Coefficient of variation (CV)0.016887862
Kurtosis1.8439023
Mean337761.15
Median Absolute Deviation (MAD)2400.7221
Skewness0.86396688
Sum1.0582057 × 109
Variance32536344
MonotonicityNot monotonic
2024-04-17T08:28:58.718467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336344.302039 11
 
0.3%
336353.196287 8
 
0.2%
336366.064252 8
 
0.2%
338653.414866 7
 
0.2%
339163.824109 7
 
0.2%
336559.670287 7
 
0.2%
337148.956227 6
 
0.1%
339372.436369 6
 
0.1%
335898.647221 6
 
0.1%
338853.934043 6
 
0.1%
Other values (2422) 3061
75.2%
(Missing) 939
 
23.1%
ValueCountFrequency (%)
324827.061698 1
< 0.1%
325693.930075 1
< 0.1%
325695.119708 1
< 0.1%
325796.946031 1
< 0.1%
325797.948919 1
< 0.1%
325886.496212 1
< 0.1%
325928.444036 1
< 0.1%
325935.356421 1
< 0.1%
325962.159745 1
< 0.1%
325962.779943 1
< 0.1%
ValueCountFrequency (%)
357474.36475 1
 
< 0.1%
357249.517998 1
 
< 0.1%
357183.0049 1
 
< 0.1%
356288.780361 1
 
< 0.1%
355939.362329 1
 
< 0.1%
355715.873404 2
< 0.1%
355708.657238 1
 
< 0.1%
355569.867912 1
 
< 0.1%
355558.233247 3
0.1%
355557.42313 1
 
< 0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct2430
Distinct (%)77.6%
Missing939
Missing (%)23.1%
Infinite0
Infinite (%)0.0%
Mean261034.48
Minimum236283.75
Maximum278091.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:28:58.823787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum236283.75
5-th percentile248378.39
Q1259886.38
median262181.27
Q3265366.68
95-th percentile267823.61
Maximum278091.65
Range41807.907
Interquartile range (IQR)5480.2945

Descriptive statistics

Standard deviation6832.4594
Coefficient of variation (CV)0.026174547
Kurtosis2.6029759
Mean261034.48
Median Absolute Deviation (MAD)2775.7963
Skewness-1.6697985
Sum8.1782103 × 108
Variance46682502
MonotonicityNot monotonic
2024-04-17T08:28:58.923261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
261497.640906 11
 
0.3%
261562.315791 8
 
0.2%
261651.801477 8
 
0.2%
265188.870359 7
 
0.2%
261730.820003 7
 
0.2%
263466.441258 7
 
0.2%
263299.390649 6
 
0.1%
258962.00812 6
 
0.1%
260602.149585 6
 
0.1%
266176.21665 6
 
0.1%
Other values (2420) 3061
75.2%
(Missing) 939
 
23.1%
ValueCountFrequency (%)
236283.746887 1
< 0.1%
237677.093671 1
< 0.1%
237682.121457 1
< 0.1%
237686.085459 1
< 0.1%
237690.289797 1
< 0.1%
237692.765575 1
< 0.1%
237817.514628 1
< 0.1%
237831.890224 1
< 0.1%
237833.64806 1
< 0.1%
237835.998538 1
< 0.1%
ValueCountFrequency (%)
278091.653532 1
< 0.1%
277507.397404 1
< 0.1%
274498.743064 1
< 0.1%
274001.175164 1
< 0.1%
273857.356673 1
< 0.1%
273400.631796 1
< 0.1%
273237.600006 1
< 0.1%
272735.67566 1
< 0.1%
272669.414848 1
< 0.1%
271294.779784 1
< 0.1%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
대기배출업소관리
4072 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대기배출업소관리 4072
100.0%

Length

2024-04-17T08:28:59.013717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:59.083638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대기배출업소관리 4072
100.0%

업종구분명
Text

MISSING 

Distinct402
Distinct (%)15.1%
Missing1411
Missing (%)34.7%
Memory size31.9 KiB
2024-04-17T08:28:59.298618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length11.344607
Min length2

Characters and Unicode

Total characters30188
Distinct characters290
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)7.0%

Sample

1st row부동산 임대업
2nd row우편 및 소포 송달업
3rd row백화점
4th row주거용 부동산 관리업
5th row병원
ValueCountFrequency (%)
제조업 1337
 
16.0%
기타 831
 
10.0%
750
 
9.0%
자동차 314
 
3.8%
가공업 295
 
3.5%
염색 277
 
3.3%
섬유 257
 
3.1%
수리업 256
 
3.1%
조립금속제품 213
 
2.6%
그외 198
 
2.4%
Other values (539) 3614
43.3%
2024-04-17T08:28:59.649817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5683
18.8%
2713
 
9.0%
2342
 
7.8%
1700
 
5.6%
1177
 
3.9%
1024
 
3.4%
902
 
3.0%
816
 
2.7%
722
 
2.4%
644
 
2.1%
Other values (280) 12465
41.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24358
80.7%
Space Separator 5683
 
18.8%
Other Punctuation 124
 
0.4%
Decimal Number 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2713
 
11.1%
2342
 
9.6%
1700
 
7.0%
1177
 
4.8%
1024
 
4.2%
902
 
3.7%
816
 
3.4%
722
 
3.0%
644
 
2.6%
547
 
2.2%
Other values (275) 11771
48.3%
Other Punctuation
ValueCountFrequency (%)
, 113
91.1%
· 6
 
4.8%
; 5
 
4.0%
Space Separator
ValueCountFrequency (%)
5683
100.0%
Decimal Number
ValueCountFrequency (%)
1 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24358
80.7%
Common 5830
 
19.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2713
 
11.1%
2342
 
9.6%
1700
 
7.0%
1177
 
4.8%
1024
 
4.2%
902
 
3.7%
816
 
3.4%
722
 
3.0%
644
 
2.6%
547
 
2.2%
Other values (275) 11771
48.3%
Common
ValueCountFrequency (%)
5683
97.5%
, 113
 
1.9%
1 23
 
0.4%
· 6
 
0.1%
; 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24358
80.7%
ASCII 5824
 
19.3%
None 6
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5683
97.6%
, 113
 
1.9%
1 23
 
0.4%
; 5
 
0.1%
Hangul
ValueCountFrequency (%)
2713
 
11.1%
2342
 
9.6%
1700
 
7.0%
1177
 
4.8%
1024
 
4.2%
902
 
3.7%
816
 
3.4%
722
 
3.0%
644
 
2.6%
547
 
2.2%
Other values (275) 11771
48.3%
None
ValueCountFrequency (%)
· 6
100.0%

종별명
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size31.9 KiB
5종
2128 
4종
1312 
3종
 
212
2종
 
188
<NA>
 
187

Length

Max length4
Median length2
Mean length2.0918468
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4종
2nd row5종
3rd row4종
4th row5종
5th row5종

Common Values

ValueCountFrequency (%)
5종 2128
52.3%
4종 1312
32.2%
3종 212
 
5.2%
2종 188
 
4.6%
<NA> 187
 
4.6%
1종 45
 
1.1%

Length

2024-04-17T08:28:59.764575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T08:28:59.853998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5종 2128
52.3%
4종 1312
32.2%
3종 212
 
5.2%
2종 188
 
4.6%
na 187
 
4.6%
1종 45
 
1.1%

주생산품명
Text

MISSING 

Distinct836
Distinct (%)63.0%
Missing2744
Missing (%)67.4%
Memory size31.9 KiB
2024-04-17T08:29:00.063118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length5.8960843
Min length1

Characters and Unicode

Total characters7830
Distinct characters447
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique671 ?
Unique (%)50.5%

Sample

1st row전력,온수
2nd row자동차용고무제품
3rd row자동차종합정비
4th row
5th row수리된자동차
ValueCountFrequency (%)
자동차부품 166
 
9.7%
자동차 41
 
2.4%
37
 
2.2%
26
 
1.5%
안경테 23
 
1.3%
부품 21
 
1.2%
가공원단 19
 
1.1%
전자부품 18
 
1.1%
자동차정비 17
 
1.0%
고무시트 17
 
1.0%
Other values (862) 1321
77.4%
2024-04-17T08:29:00.429214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
470
 
6.0%
385
 
4.9%
378
 
4.8%
372
 
4.8%
333
 
4.3%
328
 
4.2%
156
 
2.0%
151
 
1.9%
129
 
1.6%
122
 
1.6%
Other values (437) 5006
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6861
87.6%
Space Separator 378
 
4.8%
Uppercase Letter 228
 
2.9%
Other Punctuation 135
 
1.7%
Lowercase Letter 78
 
1.0%
Open Punctuation 60
 
0.8%
Close Punctuation 60
 
0.8%
Decimal Number 25
 
0.3%
Dash Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
470
 
6.9%
385
 
5.6%
372
 
5.4%
333
 
4.9%
328
 
4.8%
156
 
2.3%
151
 
2.2%
129
 
1.9%
122
 
1.8%
108
 
1.6%
Other values (377) 4307
62.8%
Uppercase Letter
ValueCountFrequency (%)
P 43
18.9%
E 38
16.7%
C 19
8.3%
L 17
 
7.5%
D 17
 
7.5%
T 16
 
7.0%
I 14
 
6.1%
O 12
 
5.3%
R 9
 
3.9%
A 6
 
2.6%
Other values (12) 37
16.2%
Lowercase Letter
ValueCountFrequency (%)
o 9
11.5%
e 8
10.3%
r 8
10.3%
t 7
 
9.0%
l 6
 
7.7%
i 6
 
7.7%
a 5
 
6.4%
f 5
 
6.4%
n 3
 
3.8%
p 3
 
3.8%
Other values (11) 18
23.1%
Decimal Number
ValueCountFrequency (%)
1 6
24.0%
0 5
20.0%
6 4
16.0%
8 3
12.0%
2 2
 
8.0%
5 2
 
8.0%
4 1
 
4.0%
9 1
 
4.0%
7 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 121
89.6%
. 11
 
8.1%
/ 2
 
1.5%
& 1
 
0.7%
Space Separator
ValueCountFrequency (%)
378
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6861
87.6%
Common 663
 
8.5%
Latin 306
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
470
 
6.9%
385
 
5.6%
372
 
5.4%
333
 
4.9%
328
 
4.8%
156
 
2.3%
151
 
2.2%
129
 
1.9%
122
 
1.8%
108
 
1.6%
Other values (377) 4307
62.8%
Latin
ValueCountFrequency (%)
P 43
 
14.1%
E 38
 
12.4%
C 19
 
6.2%
L 17
 
5.6%
D 17
 
5.6%
T 16
 
5.2%
I 14
 
4.6%
O 12
 
3.9%
o 9
 
2.9%
R 9
 
2.9%
Other values (33) 112
36.6%
Common
ValueCountFrequency (%)
378
57.0%
, 121
 
18.3%
( 60
 
9.0%
) 60
 
9.0%
. 11
 
1.7%
1 6
 
0.9%
- 5
 
0.8%
0 5
 
0.8%
6 4
 
0.6%
8 3
 
0.5%
Other values (7) 10
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6861
87.6%
ASCII 969
 
12.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
470
 
6.9%
385
 
5.6%
372
 
5.4%
333
 
4.9%
328
 
4.8%
156
 
2.3%
151
 
2.2%
129
 
1.9%
122
 
1.8%
108
 
1.6%
Other values (377) 4307
62.8%
ASCII
ValueCountFrequency (%)
378
39.0%
, 121
 
12.5%
( 60
 
6.2%
) 60
 
6.2%
P 43
 
4.4%
E 38
 
3.9%
C 19
 
2.0%
L 17
 
1.8%
D 17
 
1.8%
T 16
 
1.7%
Other values (50) 200
20.6%

배출시설조업시간
Real number (ℝ)

MISSING  SKEWED  ZEROS 

Distinct33
Distinct (%)0.8%
Missing56
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean7.5668949
Minimum0
Maximum912
Zeros1382
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:29:00.562563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q38
95-th percentile24
Maximum912
Range912
Interquartile range (IQR)8

Descriptive statistics

Standard deviation16.076986
Coefficient of variation (CV)2.1246477
Kurtosis2495.4785
Mean7.5668949
Median Absolute Deviation (MAD)5
Skewness44.457523
Sum30388.65
Variance258.46946
MonotonicityNot monotonic
2024-04-17T08:29:00.669804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
8.0 1400
34.4%
0.0 1382
33.9%
24.0 425
 
10.4%
10.0 222
 
5.5%
6.0 85
 
2.1%
12.0 69
 
1.7%
5.0 61
 
1.5%
20.0 59
 
1.4%
4.0 52
 
1.3%
7.0 50
 
1.2%
Other values (23) 211
 
5.2%
(Missing) 56
 
1.4%
ValueCountFrequency (%)
0.0 1382
33.9%
1.0 10
 
0.2%
1.5 1
 
< 0.1%
2.0 12
 
0.3%
2.5 1
 
< 0.1%
3.0 21
 
0.5%
3.5 1
 
< 0.1%
4.0 52
 
1.3%
5.0 61
 
1.5%
6.0 85
 
2.1%
ValueCountFrequency (%)
912.0 1
 
< 0.1%
30.0 2
 
< 0.1%
25.0 2
 
< 0.1%
24.0 425
10.4%
22.0 12
 
0.3%
21.0 7
 
0.2%
20.0 59
 
1.4%
19.0 3
 
0.1%
18.0 5
 
0.1%
17.0 2
 
< 0.1%

배출시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct93
Distinct (%)2.3%
Missing59
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean191.02741
Minimum0
Maximum365
Zeros1396
Zeros (%)34.3%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:29:00.793212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median300
Q3300
95-th percentile312
Maximum365
Range365
Interquartile range (IQR)300

Descriptive statistics

Standard deviation143.18788
Coefficient of variation (CV)0.74956719
Kurtosis-1.6413523
Mean191.02741
Median Absolute Deviation (MAD)0
Skewness-0.53258189
Sum766593
Variance20502.769
MonotonicityNot monotonic
2024-04-17T08:29:00.905376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300 2028
49.8%
0 1396
34.3%
240 59
 
1.4%
365 53
 
1.3%
312 42
 
1.0%
264 30
 
0.7%
360 28
 
0.7%
180 27
 
0.7%
330 24
 
0.6%
280 23
 
0.6%
Other values (83) 303
 
7.4%
(Missing) 59
 
1.4%
ValueCountFrequency (%)
0 1396
34.3%
8 1
 
< 0.1%
24 3
 
0.1%
25 2
 
< 0.1%
30 3
 
0.1%
48 1
 
< 0.1%
52 1
 
< 0.1%
60 3
 
0.1%
80 1
 
< 0.1%
84 1
 
< 0.1%
ValueCountFrequency (%)
365 53
1.3%
362 1
 
< 0.1%
361 1
 
< 0.1%
360 28
0.7%
355 1
 
< 0.1%
352 2
 
< 0.1%
350 15
 
0.4%
340 13
 
0.3%
338 1
 
< 0.1%
336 14
 
0.3%

방지시설조업시간
Real number (ℝ)

MISSING  ZEROS 

Distinct33
Distinct (%)0.9%
Missing431
Missing (%)10.6%
Infinite0
Infinite (%)0.0%
Mean7.1473908
Minimum0
Maximum360
Zeros1380
Zeros (%)33.9%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:29:01.009826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q38
95-th percentile24
Maximum360
Range360
Interquartile range (IQR)8

Descriptive statistics

Standard deviation10.93901
Coefficient of variation (CV)1.5304899
Kurtosis413.20829
Mean7.1473908
Median Absolute Deviation (MAD)8
Skewness15.009504
Sum26023.65
Variance119.66193
MonotonicityNot monotonic
2024-04-17T08:29:01.128829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0.0 1380
33.9%
8.0 1251
30.7%
24.0 352
 
8.6%
10.0 181
 
4.4%
6.0 64
 
1.6%
5.0 56
 
1.4%
12.0 53
 
1.3%
20.0 47
 
1.2%
7.0 47
 
1.2%
4.0 40
 
1.0%
Other values (23) 170
 
4.2%
(Missing) 431
 
10.6%
ValueCountFrequency (%)
0.0 1380
33.9%
1.0 9
 
0.2%
2.0 9
 
0.2%
3.0 13
 
0.3%
4.0 40
 
1.0%
5.0 56
 
1.4%
6.0 64
 
1.6%
7.0 47
 
1.2%
7.5 2
 
< 0.1%
8.0 1251
30.7%
ValueCountFrequency (%)
360.0 1
 
< 0.1%
264.0 1
 
< 0.1%
210.0 1
 
< 0.1%
100.0 1
 
< 0.1%
34.0 1
 
< 0.1%
30.0 3
 
0.1%
25.0 2
 
< 0.1%
24.0 352
8.6%
22.0 11
 
0.3%
21.0 7
 
0.2%

방지시설연간가동일수
Real number (ℝ)

MISSING  ZEROS 

Distinct78
Distinct (%)2.1%
Missing420
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean183.31681
Minimum0
Maximum365
Zeros1387
Zeros (%)34.1%
Negative0
Negative (%)0.0%
Memory size35.9 KiB
2024-04-17T08:29:01.231103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median300
Q3300
95-th percentile306.45
Maximum365
Range365
Interquartile range (IQR)300

Descriptive statistics

Standard deviation145.77583
Coefficient of variation (CV)0.79521254
Kurtosis-1.7648745
Mean183.31681
Median Absolute Deviation (MAD)3
Skewness-0.42917627
Sum669473
Variance21250.592
MonotonicityNot monotonic
2024-04-17T08:29:01.338715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300 1818
44.6%
0 1387
34.1%
240 45
 
1.1%
312 41
 
1.0%
365 32
 
0.8%
360 23
 
0.6%
280 22
 
0.5%
264 21
 
0.5%
330 20
 
0.5%
250 20
 
0.5%
Other values (68) 223
 
5.5%
(Missing) 420
 
10.3%
ValueCountFrequency (%)
0 1387
34.1%
8 1
 
< 0.1%
24 1
 
< 0.1%
25 2
 
< 0.1%
30 2
 
< 0.1%
48 1
 
< 0.1%
52 1
 
< 0.1%
60 2
 
< 0.1%
84 1
 
< 0.1%
90 1
 
< 0.1%
ValueCountFrequency (%)
365 32
0.8%
362 1
 
< 0.1%
360 23
0.6%
355 1
 
< 0.1%
352 2
 
< 0.1%
350 14
0.3%
340 11
 
0.3%
338 1
 
< 0.1%
336 12
 
0.3%
335 3
 
0.1%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
01대기오염물질배출시설설치사업장09_30_08_P341000034100002120150000720151126<NA>1영업/정상11영업<NA><NA><NA><NA>0534288900<NA><NA><NA>대구광역시 중구 달구벌대로 지하 2100 (덕산동, 반월당역)41957메트로센터20151208204903I2018-10-04 11:12:49.0<NA>343838.339371264020.741504대기배출업소관리<NA>4종<NA>24.0120<NA><NA>
12대기오염물질배출시설설치사업장09_30_08_P341000034100002120150001320151209<NA>1영업/정상11영업<NA><NA><NA><NA>053-609-1407<NA><NA><NA>대구광역시 중구 국채보상로 585 (사일동, 동성로파티)41909동성로파티지원센터관리단20151228172104I2018-10-04 11:12:49.0<NA>343932.18838264630.944873대기배출업소관리<NA>5종<NA>3.0150<NA><NA>
23대기오염물질배출시설설치사업장09_30_08_P341000034100002120150001520151209<NA>1영업/정상11영업<NA><NA><NA><NA>053-250-5555<NA><NA>대구광역시 중구 덕산동 110번지대구광역시 중구 달구벌대로 2095 (덕산동)41936지알이전문투자형사모부동산투자신탁 제2호20180426174042I2018-10-04 11:12:49.0<NA>343787.134091264065.576741대기배출업소관리<NA>4종<NA>6.0196<NA><NA>
34대기오염물질배출시설설치사업장09_30_08_P341000034100002120150001620151211<NA>1영업/정상11영업<NA><NA><NA><NA>053-555-9204<NA><NA><NA>대구광역시 중구 국채보상로 지하 470 (대신동, 대신지하상가)41925대신지하상가관리소20170621115918I2018-10-04 11:12:49.0<NA>342791.972037264832.646106대기배출업소관리<NA>5종<NA>6.0180<NA><NA>
45대기오염물질배출시설설치사업장09_30_08_P341000034100002120150000620151120<NA>1영업/정상11영업<NA><NA><NA><NA>053-251-6019<NA><NA>대구광역시 중구 남일동 138-3번지 국민은행대구지점대구광역시 중구 중앙대로 401, 국민은행대구지점 (남일동)41935(주)국민은행 대구지점20180117134215I2018-10-04 11:12:49.0<NA>343836.000284264353.542698대기배출업소관리<NA>5종<NA>6.0180<NA><NA>
56대기오염물질배출시설설치사업장09_30_08_P341000034100002120150001720151217<NA>1영업/정상11영업<NA><NA><NA><NA>0534288984<NA><NA><NA>대구광역시 중구 국채보상로 611 (문화동, 대구시티센터)41913이지스티디에이치제32호사모부동사투자유한회사20151228172352I2018-10-04 11:12:49.0부동산 임대업344223.636477264597.611089대기배출업소관리부동산 임대업4종<NA>6.0240<NA><NA>
67대기오염물질배출시설설치사업장09_30_08_P341000034100002120150001820151217<NA>1영업/정상11영업<NA><NA><NA><NA>0532502000<NA><NA><NA>대구광역시 중구 경상감영길 80 (포정동, 대구우체국)41918대구우체국20151217130330I2018-10-04 11:12:49.0우편 및 소포 송달업343687.68301264634.313879대기배출업소관리우편 및 소포 송달업5종<NA>4.0100<NA><NA>
78대기오염물질배출시설설치사업장09_30_08_P341000034100002120150001920151217<NA>1영업/정상11영업<NA><NA><NA><NA>0532579663<NA><NA><NA>대구광역시 중구 달성로 37 (대신동, 계성빌딩)41927(학)계성학원20151217131009I2018-10-04 11:12:49.0<NA>342795.702037264290.451468대기배출업소관리<NA>5종<NA>3.0150<NA><NA>
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40624063대기오염물질배출시설설치사업장09_30_08_P348000034800002119910000119910714<NA>1영업/정상11영업<NA><NA><NA><NA>0536147755<NA><NA>대구광역시 달성군 논공읍 본리리 29-111번지대구광역시 달성군 논공읍 논공로91길 53-19<NA>(주)현대정밀20190115161505U2019-01-17 02:40:00.0기타 구조용 금속제품 제조업333161.480161249102.498367대기배출업소관리기타 구조용 금속제품 제조업5종경첩10.030010.0300
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40654066대기오염물질배출시설설치사업장09_30_08_P348000034800002119910000419910527<NA>3폐업2폐업20120720<NA><NA><NA>07082336770<NA><NA>대구광역시 달성군 논공읍 본리리 103-34번지대구광역시 달성군 논공읍 논공로87길 76<NA>금우단조공업20120723111807I2018-10-04 11:12:49.0기타 구조용 금속제품 제조업332950.852455248860.97539대기배출업소관리기타 구조용 금속제품 제조업5종기계부품8.0300<NA><NA>
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