Overview

Dataset statistics

Number of variables29
Number of observations226
Missing cells1638
Missing cells (%)25.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory52.7 KiB
Average record size in memory238.6 B

Variable types

Numeric5
Categorical9
Text7
DateTime8

Dataset

Description24년03월_6270000_대구광역시_08_25_01_P_대규모점포
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000106680&dataSetDetailId=DDI_0000106692&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
인허가취소일자 has constant value ""Constant
인허가취소일자 has 225 (99.6%) missing valuesMissing
폐업일자 has 180 (79.6%) missing valuesMissing
휴업시작일자 has 224 (99.1%) missing valuesMissing
휴업종료일자 has 224 (99.1%) missing valuesMissing
재개업일자 has 220 (97.3%) missing valuesMissing
소재지전화 has 9 (4.0%) missing valuesMissing
소재지면적 has 63 (27.9%) missing valuesMissing
소재지우편번호 has 161 (71.2%) missing valuesMissing
소재지전체주소 has 5 (2.2%) missing valuesMissing
도로명전체주소 has 63 (27.9%) missing valuesMissing
도로명우편번호 has 142 (62.8%) missing valuesMissing
좌표정보(X) has 61 (27.0%) missing valuesMissing
좌표정보(Y) has 61 (27.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
소재지면적 has 28 (12.4%) zerosZeros

Reproduction

Analysis started2024-04-29 12:37:24.135202
Analysis finished2024-04-29 12:37:24.917390
Duration0.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct226
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean113.5
Minimum1
Maximum226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-29T21:37:24.990950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile12.25
Q157.25
median113.5
Q3169.75
95-th percentile214.75
Maximum226
Range225
Interquartile range (IQR)112.5

Descriptive statistics

Standard deviation65.384759
Coefficient of variation (CV)0.57607717
Kurtosis-1.2
Mean113.5
Median Absolute Deviation (MAD)56.5
Skewness0
Sum25651
Variance4275.1667
MonotonicityStrictly increasing
2024-04-29T21:37:25.100613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
171 1
 
0.4%
145 1
 
0.4%
146 1
 
0.4%
147 1
 
0.4%
148 1
 
0.4%
149 1
 
0.4%
150 1
 
0.4%
151 1
 
0.4%
152 1
 
0.4%
Other values (216) 216
95.6%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
226 1
0.4%
225 1
0.4%
224 1
0.4%
223 1
0.4%
222 1
0.4%
221 1
0.4%
220 1
0.4%
219 1
0.4%
218 1
0.4%
217 1
0.4%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
대규모점포
226 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대규모점포 226
100.0%

Length

2024-04-29T21:37:25.217181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:25.305296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대규모점포 226
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
08_25_01_P
226 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row08_25_01_P
2nd row08_25_01_P
3rd row08_25_01_P
4th row08_25_01_P
5th row08_25_01_P

Common Values

ValueCountFrequency (%)
08_25_01_P 226
100.0%

Length

2024-04-29T21:37:25.387906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:25.460866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
08_25_01_p 226
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3443849.6
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-29T21:37:25.529140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3450000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21964.708
Coefficient of variation (CV)0.0063779521
Kurtosis-1.3280721
Mean3443849.6
Median Absolute Deviation (MAD)20000
Skewness-0.32393151
Sum7.7831 × 108
Variance4.8244838 × 108
MonotonicityIncreasing
2024-04-29T21:37:25.624094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3450000 45
19.9%
3460000 44
19.5%
3470000 43
19.0%
3410000 39
17.3%
3430000 28
12.4%
3420000 21
9.3%
3440000 3
 
1.3%
3480000 3
 
1.3%
ValueCountFrequency (%)
3410000 39
17.3%
3420000 21
9.3%
3430000 28
12.4%
3440000 3
 
1.3%
3450000 45
19.9%
3460000 44
19.5%
3470000 43
19.0%
3480000 3
 
1.3%
ValueCountFrequency (%)
3480000 3
 
1.3%
3470000 43
19.0%
3460000 44
19.5%
3450000 45
19.9%
3440000 3
 
1.3%
3430000 28
12.4%
3420000 21
9.3%
3410000 39
17.3%

관리번호
Text

UNIQUE 

Distinct226
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-29T21:37:25.812641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters4294
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

Unique226 ?
Unique (%)100.0%

Sample

1st row2019341013007500001
2nd row1977341004607500002
3rd row2024341016307500001
4th row2006341001307500002
5th row2001341001307500012
ValueCountFrequency (%)
2019341013007500001 1
 
0.4%
2001346005507500021 1
 
0.4%
2011346011707500006 1
 
0.4%
1981346005507500009 1
 
0.4%
1981346014007500001 1
 
0.4%
1982 1
 
0.4%
46005507500010 1
 
0.4%
1983346005507500011 1
 
0.4%
1983346005507500012 1
 
0.4%
1986346005507500013 1
 
0.4%
Other values (217) 217
95.6%
2024-04-29T21:37:26.112351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1895
44.1%
1 477
 
11.1%
5 372
 
8.7%
7 371
 
8.6%
3 320
 
7.5%
2 294
 
6.8%
4 287
 
6.7%
9 119
 
2.8%
6 99
 
2.3%
8 59
 
1.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4293
> 99.9%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1895
44.1%
1 477
 
11.1%
5 372
 
8.7%
7 371
 
8.6%
3 320
 
7.5%
2 294
 
6.8%
4 287
 
6.7%
9 119
 
2.8%
6 99
 
2.3%
8 59
 
1.4%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4294
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1895
44.1%
1 477
 
11.1%
5 372
 
8.7%
7 371
 
8.6%
3 320
 
7.5%
2 294
 
6.8%
4 287
 
6.7%
9 119
 
2.8%
6 99
 
2.3%
8 59
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4294
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1895
44.1%
1 477
 
11.1%
5 372
 
8.7%
7 371
 
8.6%
3 320
 
7.5%
2 294
 
6.8%
4 287
 
6.7%
9 119
 
2.8%
6 99
 
2.3%
8 59
 
1.4%
Distinct191
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1960-10-27 00:00:00
Maximum2024-03-21 00:00:00
2024-04-29T21:37:26.251562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:26.558182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing225
Missing (%)99.6%
Memory size1.9 KiB
Minimum2020-10-08 00:00:00
Maximum2020-10-08 00:00:00
2024-04-29T21:37:26.655249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:26.736769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
157 
3
46 
2
22 
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row1
2nd row1
3rd row1
4th row4
5th row3

Common Values

ValueCountFrequency (%)
1 157
69.5%
3 46
 
20.4%
2 22
 
9.7%
4 1
 
0.4%

Length

2024-04-29T21:37:26.849786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:26.942111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 157
69.5%
3 46
 
20.4%
2 22
 
9.7%
4 1
 
0.4%

영업상태명
Categorical

Distinct4
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
영업/정상
157 
폐업
46 
휴업
22 
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length4.1371681
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row취소/말소/만료/정지/중지
5th row폐업

Common Values

ValueCountFrequency (%)
영업/정상 157
69.5%
폐업 46
 
20.4%
휴업 22
 
9.7%
취소/말소/만료/정지/중지 1
 
0.4%

Length

2024-04-29T21:37:27.038073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:27.135132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 157
69.5%
폐업 46
 
20.4%
휴업 22
 
9.7%
취소/말소/만료/정지/중지 1
 
0.4%
Distinct6
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
1
152 
3
46 
2
22 
5
 
3
BBBB
 
2

Length

Max length4
Median length1
Mean length1.0265487
Min length1

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row1
2nd row1
3rd row5
4th row4
5th row3

Common Values

ValueCountFrequency (%)
1 152
67.3%
3 46
 
20.4%
2 22
 
9.7%
5 3
 
1.3%
BBBB 2
 
0.9%
4 1
 
0.4%

Length

2024-04-29T21:37:27.238824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:27.330077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 152
67.3%
3 46
 
20.4%
2 22
 
9.7%
5 3
 
1.3%
bbbb 2
 
0.9%
4 1
 
0.4%
Distinct6
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
정상영업
152 
폐업처리
46 
휴업처리
22 
영업개시전
 
3
<NA>
 
2

Length

Max length5
Median length4
Mean length4.0132743
Min length4

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row정상영업
2nd row정상영업
3rd row영업개시전
4th row직권취소
5th row폐업처리

Common Values

ValueCountFrequency (%)
정상영업 152
67.3%
폐업처리 46
 
20.4%
휴업처리 22
 
9.7%
영업개시전 3
 
1.3%
<NA> 2
 
0.9%
직권취소 1
 
0.4%

Length

2024-04-29T21:37:27.429900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:27.521966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상영업 152
67.3%
폐업처리 46
 
20.4%
휴업처리 22
 
9.7%
영업개시전 3
 
1.3%
na 2
 
0.9%
직권취소 1
 
0.4%

폐업일자
Date

MISSING 

Distinct39
Distinct (%)84.8%
Missing180
Missing (%)79.6%
Memory size1.9 KiB
Minimum2000-01-21 00:00:00
Maximum2023-02-28 00:00:00
2024-04-29T21:37:27.635649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:27.756247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)

휴업시작일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing224
Missing (%)99.1%
Memory size1.9 KiB
Minimum2021-09-15 00:00:00
Maximum2022-05-17 00:00:00
2024-04-29T21:37:27.851439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:27.928575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

휴업종료일자
Date

MISSING 

Distinct2
Distinct (%)100.0%
Missing224
Missing (%)99.1%
Memory size1.9 KiB
Minimum2022-09-14 00:00:00
Maximum2025-01-01 00:00:00
2024-04-29T21:37:28.009415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:28.097163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

재개업일자
Date

MISSING 

Distinct5
Distinct (%)83.3%
Missing220
Missing (%)97.3%
Memory size1.9 KiB
Minimum2006-10-12 00:00:00
Maximum2019-04-15 00:00:00
2024-04-29T21:37:28.182492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:28.282902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

소재지전화
Text

MISSING 

Distinct214
Distinct (%)98.6%
Missing9
Missing (%)4.0%
Memory size1.9 KiB
2024-04-29T21:37:28.553424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.041475
Min length7

Characters and Unicode

Total characters2396
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

Unique211 ?
Unique (%)97.2%

Sample

1st row053-766-1860
2nd row053-257-3562
3rd row053 421 9323
4th row02 6373 1117
5th row053 421 5658
ValueCountFrequency (%)
053 107
28.9%
02 3
 
0.8%
421 3
 
0.8%
428 3
 
0.8%
8545 3
 
0.8%
053-213-5225 2
 
0.5%
3000 2
 
0.5%
350 2
 
0.5%
1052 2
 
0.5%
8124 2
 
0.5%
Other values (239) 241
65.1%
2024-04-29T21:37:28.968994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 434
18.1%
5 415
17.3%
3 321
13.4%
1 190
7.9%
2 181
7.6%
6 163
 
6.8%
157
 
6.6%
4 132
 
5.5%
- 118
 
4.9%
7 112
 
4.7%
Other values (3) 173
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2120
88.5%
Space Separator 157
 
6.6%
Dash Punctuation 118
 
4.9%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 434
20.5%
5 415
19.6%
3 321
15.1%
1 190
9.0%
2 181
8.5%
6 163
 
7.7%
4 132
 
6.2%
7 112
 
5.3%
8 99
 
4.7%
9 73
 
3.4%
Space Separator
ValueCountFrequency (%)
157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 118
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 434
18.1%
5 415
17.3%
3 321
13.4%
1 190
7.9%
2 181
7.6%
6 163
 
6.8%
157
 
6.6%
4 132
 
5.5%
- 118
 
4.9%
7 112
 
4.7%
Other values (3) 173
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 434
18.1%
5 415
17.3%
3 321
13.4%
1 190
7.9%
2 181
7.6%
6 163
 
6.8%
157
 
6.6%
4 132
 
5.5%
- 118
 
4.9%
7 112
 
4.7%
Other values (3) 173
 
7.2%

소재지면적
Real number (ℝ)

MISSING  ZEROS 

Distinct126
Distinct (%)77.3%
Missing63
Missing (%)27.9%
Infinite0
Infinite (%)0.0%
Mean7095.2545
Minimum0
Maximum105538.69
Zeros28
Zeros (%)12.4%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-29T21:37:29.107383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1281.1
median2534.6
Q310932.36
95-th percentile21943.052
Maximum105538.69
Range105538.69
Interquartile range (IQR)10651.26

Descriptive statistics

Standard deviation11320.74
Coefficient of variation (CV)1.5955369
Kurtosis35.592766
Mean7095.2545
Median Absolute Deviation (MAD)2534.6
Skewness4.744352
Sum1156526.5
Variance1.2815916 × 108
MonotonicityNot monotonic
2024-04-29T21:37:29.246983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 28
 
12.4%
9375.95 3
 
1.3%
16272.6 2
 
0.9%
4680.75 2
 
0.9%
7675.0 2
 
0.9%
200.0 2
 
0.9%
8651.61 2
 
0.9%
735.0 2
 
0.9%
14022.0 2
 
0.9%
13089.0 2
 
0.9%
Other values (116) 116
51.3%
(Missing) 63
27.9%
ValueCountFrequency (%)
0.0 28
12.4%
8.0 1
 
0.4%
136.4 1
 
0.4%
152.4 1
 
0.4%
186.1 1
 
0.4%
189.0 1
 
0.4%
200.0 2
 
0.9%
200.49 1
 
0.4%
211.24 1
 
0.4%
213.6 1
 
0.4%
ValueCountFrequency (%)
105538.69 1
0.4%
46625.73 1
0.4%
36820.0 1
0.4%
34827.86 1
0.4%
34772.76 1
0.4%
27231.15 1
0.4%
25448.82 1
0.4%
25138.34 1
0.4%
22026.27 1
0.4%
21194.09 1
0.4%

소재지우편번호
Text

MISSING 

Distinct58
Distinct (%)89.2%
Missing161
Missing (%)71.2%
Memory size1.9 KiB
2024-04-29T21:37:29.473933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters455
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

Unique54 ?
Unique (%)83.1%

Sample

1st row700-711
2nd row700-739
3rd row700-717
4th row700-808
5th row700-823
ValueCountFrequency (%)
702-250 4
 
6.2%
702-062 3
 
4.6%
706-130 2
 
3.1%
704-371 2
 
3.1%
704-131 1
 
1.5%
706-838 1
 
1.5%
706-777 1
 
1.5%
706-080 1
 
1.5%
706-170 1
 
1.5%
706-092 1
 
1.5%
Other values (48) 48
73.8%
2024-04-29T21:37:29.795536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 109
24.0%
7 89
19.6%
- 65
14.3%
2 34
 
7.5%
1 33
 
7.3%
8 27
 
5.9%
3 25
 
5.5%
4 25
 
5.5%
6 23
 
5.1%
5 13
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 390
85.7%
Dash Punctuation 65
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 109
27.9%
7 89
22.8%
2 34
 
8.7%
1 33
 
8.5%
8 27
 
6.9%
3 25
 
6.4%
4 25
 
6.4%
6 23
 
5.9%
5 13
 
3.3%
9 12
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 455
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 109
24.0%
7 89
19.6%
- 65
14.3%
2 34
 
7.5%
1 33
 
7.3%
8 27
 
5.9%
3 25
 
5.5%
4 25
 
5.5%
6 23
 
5.1%
5 13
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 455
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 109
24.0%
7 89
19.6%
- 65
14.3%
2 34
 
7.5%
1 33
 
7.3%
8 27
 
5.9%
3 25
 
5.5%
4 25
 
5.5%
6 23
 
5.1%
5 13
 
2.9%

소재지전체주소
Text

MISSING 

Distinct204
Distinct (%)92.3%
Missing5
Missing (%)2.2%
Memory size1.9 KiB
2024-04-29T21:37:30.151296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length33
Mean length23.361991
Min length7

Characters and Unicode

Total characters5163
Distinct characters179
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

Unique191 ?
Unique (%)86.4%

Sample

1st row대구광역시 중구 공평동 58번지 6호
2nd row대구광역시 중구 대신동 115-30 동산상가
3rd row대구광역시 중구 수창동 178 대구역 제일풍경채 위너스카이
4th row대구광역시 중구 삼덕동1가 5번지 2 호
5th row대구광역시 중구 문화동 11번지 1호
ValueCountFrequency (%)
대구광역시 219
 
20.3%
북구 44
 
4.1%
수성구 43
 
4.0%
달서구 42
 
3.9%
중구 36
 
3.3%
32
 
3.0%
서구 28
 
2.6%
1호 23
 
2.1%
동구 21
 
1.9%
3호 13
 
1.2%
Other values (363) 580
53.7%
2024-04-29T21:37:30.653670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1157
22.4%
442
 
8.6%
258
 
5.0%
239
 
4.6%
227
 
4.4%
221
 
4.3%
1 220
 
4.3%
219
 
4.2%
178
 
3.4%
156
 
3.0%
Other values (169) 1846
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3019
58.5%
Space Separator 1157
 
22.4%
Decimal Number 946
 
18.3%
Dash Punctuation 31
 
0.6%
Other Punctuation 4
 
0.1%
Uppercase Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
442
14.6%
258
 
8.5%
239
 
7.9%
227
 
7.5%
221
 
7.3%
219
 
7.3%
178
 
5.9%
156
 
5.2%
136
 
4.5%
86
 
2.8%
Other values (150) 857
28.4%
Decimal Number
ValueCountFrequency (%)
1 220
23.3%
2 117
12.4%
3 100
10.6%
5 94
9.9%
6 93
9.8%
4 70
 
7.4%
9 69
 
7.3%
8 67
 
7.1%
0 61
 
6.4%
7 55
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
K 1
25.0%
S 1
25.0%
M 1
25.0%
W 1
25.0%
Math Symbol
ValueCountFrequency (%)
~ 1
50.0%
+ 1
50.0%
Space Separator
ValueCountFrequency (%)
1157
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3019
58.5%
Common 2140
41.4%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
442
14.6%
258
 
8.5%
239
 
7.9%
227
 
7.5%
221
 
7.3%
219
 
7.3%
178
 
5.9%
156
 
5.2%
136
 
4.5%
86
 
2.8%
Other values (150) 857
28.4%
Common
ValueCountFrequency (%)
1157
54.1%
1 220
 
10.3%
2 117
 
5.5%
3 100
 
4.7%
5 94
 
4.4%
6 93
 
4.3%
4 70
 
3.3%
9 69
 
3.2%
8 67
 
3.1%
0 61
 
2.9%
Other values (5) 92
 
4.3%
Latin
ValueCountFrequency (%)
K 1
25.0%
S 1
25.0%
M 1
25.0%
W 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3019
58.5%
ASCII 2144
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1157
54.0%
1 220
 
10.3%
2 117
 
5.5%
3 100
 
4.7%
5 94
 
4.4%
6 93
 
4.3%
4 70
 
3.3%
9 69
 
3.2%
8 67
 
3.1%
0 61
 
2.8%
Other values (9) 96
 
4.5%
Hangul
ValueCountFrequency (%)
442
14.6%
258
 
8.5%
239
 
7.9%
227
 
7.5%
221
 
7.3%
219
 
7.3%
178
 
5.9%
156
 
5.2%
136
 
4.5%
86
 
2.8%
Other values (150) 857
28.4%

도로명전체주소
Text

MISSING 

Distinct144
Distinct (%)88.3%
Missing63
Missing (%)27.9%
Memory size1.9 KiB
2024-04-29T21:37:30.963335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length69
Median length50
Mean length26.656442
Min length19

Characters and Unicode

Total characters4345
Distinct characters201
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

Unique130 ?
Unique (%)79.8%

Sample

1st row대구광역시 중구 동성로6길 61 (공평동)
2nd row대구광역시 중구 큰장로26길 65, 동산상가 (대신동)
3rd row대구광역시 중구 달성로26길 70, 상가동 106호, 108~110호 (수창동, 대구역 제일풍경채 위너스카이)
4th row대구광역시 중구 동성로5길 25 (삼덕동1가)
5th row대구광역시 중구 국채보상로 611 (문화동)
ValueCountFrequency (%)
대구광역시 162
 
18.4%
북구 41
 
4.7%
달서구 33
 
3.8%
수성구 30
 
3.4%
중구 27
 
3.1%
동구 14
 
1.6%
서구 12
 
1.4%
달구벌대로 12
 
1.4%
산격동 12
 
1.4%
상인동 9
 
1.0%
Other values (356) 527
60.0%
2024-04-29T21:37:31.357293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
718
 
16.5%
348
 
8.0%
223
 
5.1%
210
 
4.8%
174
 
4.0%
166
 
3.8%
164
 
3.8%
162
 
3.7%
) 161
 
3.7%
( 161
 
3.7%
Other values (191) 1858
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2625
60.4%
Space Separator 718
 
16.5%
Decimal Number 609
 
14.0%
Close Punctuation 161
 
3.7%
Open Punctuation 161
 
3.7%
Other Punctuation 50
 
1.2%
Dash Punctuation 12
 
0.3%
Math Symbol 6
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
348
 
13.3%
223
 
8.5%
210
 
8.0%
174
 
6.6%
166
 
6.3%
164
 
6.2%
162
 
6.2%
81
 
3.1%
61
 
2.3%
58
 
2.2%
Other values (171) 978
37.3%
Decimal Number
ValueCountFrequency (%)
1 140
23.0%
2 99
16.3%
3 76
12.5%
0 61
10.0%
9 45
 
7.4%
5 44
 
7.2%
4 44
 
7.2%
6 41
 
6.7%
7 31
 
5.1%
8 28
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
A 1
33.3%
W 1
33.3%
Math Symbol
ValueCountFrequency (%)
~ 5
83.3%
+ 1
 
16.7%
Space Separator
ValueCountFrequency (%)
718
100.0%
Close Punctuation
ValueCountFrequency (%)
) 161
100.0%
Open Punctuation
ValueCountFrequency (%)
( 161
100.0%
Other Punctuation
ValueCountFrequency (%)
, 50
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2625
60.4%
Common 1717
39.5%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
348
 
13.3%
223
 
8.5%
210
 
8.0%
174
 
6.6%
166
 
6.3%
164
 
6.2%
162
 
6.2%
81
 
3.1%
61
 
2.3%
58
 
2.2%
Other values (171) 978
37.3%
Common
ValueCountFrequency (%)
718
41.8%
) 161
 
9.4%
( 161
 
9.4%
1 140
 
8.2%
2 99
 
5.8%
3 76
 
4.4%
0 61
 
3.6%
, 50
 
2.9%
9 45
 
2.6%
5 44
 
2.6%
Other values (7) 162
 
9.4%
Latin
ValueCountFrequency (%)
M 1
33.3%
A 1
33.3%
W 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2625
60.4%
ASCII 1720
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
718
41.7%
) 161
 
9.4%
( 161
 
9.4%
1 140
 
8.1%
2 99
 
5.8%
3 76
 
4.4%
0 61
 
3.5%
, 50
 
2.9%
9 45
 
2.6%
5 44
 
2.6%
Other values (10) 165
 
9.6%
Hangul
ValueCountFrequency (%)
348
 
13.3%
223
 
8.5%
210
 
8.0%
174
 
6.6%
166
 
6.3%
164
 
6.2%
162
 
6.2%
81
 
3.1%
61
 
2.3%
58
 
2.2%
Other values (171) 978
37.3%

도로명우편번호
Text

MISSING 

Distinct77
Distinct (%)91.7%
Missing142
Missing (%)62.8%
Memory size1.9 KiB
2024-04-29T21:37:31.586104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length6.1904762
Min length5

Characters and Unicode

Total characters520
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

Unique70 ?
Unique (%)83.3%

Sample

1st row41938
2nd row41926
3rd row41920
4th row700-716
5th row41909
ValueCountFrequency (%)
701-847 2
 
2.4%
702-062 2
 
2.4%
42124 2
 
2.4%
41083 2
 
2.4%
706-803 2
 
2.4%
706-130 2
 
2.4%
41926 2
 
2.4%
42653 1
 
1.2%
42809 1
 
1.2%
704-912 1
 
1.2%
Other values (67) 67
79.8%
2024-04-29T21:37:31.938822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 93
17.9%
7 72
13.8%
4 61
11.7%
1 55
10.6%
- 50
9.6%
8 47
9.0%
2 43
8.3%
3 29
 
5.6%
5 25
 
4.8%
6 24
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 470
90.4%
Dash Punctuation 50
 
9.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 93
19.8%
7 72
15.3%
4 61
13.0%
1 55
11.7%
8 47
10.0%
2 43
9.1%
3 29
 
6.2%
5 25
 
5.3%
6 24
 
5.1%
9 21
 
4.5%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 520
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 93
17.9%
7 72
13.8%
4 61
11.7%
1 55
10.6%
- 50
9.6%
8 47
9.0%
2 43
8.3%
3 29
 
5.6%
5 25
 
4.8%
6 24
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 520
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 93
17.9%
7 72
13.8%
4 61
11.7%
1 55
10.6%
- 50
9.6%
8 47
9.0%
2 43
8.3%
3 29
 
5.6%
5 25
 
4.8%
6 24
 
4.6%
Distinct217
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2024-04-29T21:37:32.216327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length9.3318584
Min length3

Characters and Unicode

Total characters2109
Distinct characters248
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

Unique209 ?
Unique (%)92.5%

Sample

1st row태왕스파크
2nd row동산상가
3rd rowGS THE FRESH 대구역풍경채점
4th row유플러스
5th row대구밀리오레
ValueCountFrequency (%)
홈플러스(주 11
 
3.1%
대구점 9
 
2.5%
익스프레스 8
 
2.2%
주)이마트 7
 
1.9%
주)지에스리테일 6
 
1.7%
홈플러스 6
 
1.7%
gs수퍼 6
 
1.7%
대구종합유통단지 6
 
1.7%
롯데쇼핑(주)롯데슈퍼 6
 
1.7%
롯데슈퍼 5
 
1.4%
Other values (238) 290
80.6%
2024-04-29T21:37:32.672511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
135
 
6.4%
99
 
4.7%
88
 
4.2%
78
 
3.7%
68
 
3.2%
) 64
 
3.0%
64
 
3.0%
( 64
 
3.0%
61
 
2.9%
61
 
2.9%
Other values (238) 1327
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1727
81.9%
Space Separator 135
 
6.4%
Uppercase Letter 90
 
4.3%
Close Punctuation 64
 
3.0%
Open Punctuation 64
 
3.0%
Lowercase Letter 15
 
0.7%
Decimal Number 12
 
0.6%
Dash Punctuation 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
99
 
5.7%
88
 
5.1%
78
 
4.5%
68
 
3.9%
64
 
3.7%
61
 
3.5%
61
 
3.5%
42
 
2.4%
39
 
2.3%
36
 
2.1%
Other values (202) 1091
63.2%
Uppercase Letter
ValueCountFrequency (%)
S 17
18.9%
E 11
12.2%
G 11
12.2%
T 8
8.9%
H 8
8.9%
R 7
7.8%
O 4
 
4.4%
M 4
 
4.4%
F 4
 
4.4%
A 3
 
3.3%
Other values (8) 13
14.4%
Lowercase Letter
ValueCountFrequency (%)
l 4
26.7%
t 2
13.3%
e 2
13.3%
o 2
13.3%
u 1
 
6.7%
a 1
 
6.7%
k 1
 
6.7%
c 1
 
6.7%
h 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 7
58.3%
1 3
25.0%
4 1
 
8.3%
5 1
 
8.3%
Space Separator
ValueCountFrequency (%)
135
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1727
81.9%
Common 277
 
13.1%
Latin 105
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
99
 
5.7%
88
 
5.1%
78
 
4.5%
68
 
3.9%
64
 
3.7%
61
 
3.5%
61
 
3.5%
42
 
2.4%
39
 
2.3%
36
 
2.1%
Other values (202) 1091
63.2%
Latin
ValueCountFrequency (%)
S 17
16.2%
E 11
10.5%
G 11
10.5%
T 8
 
7.6%
H 8
 
7.6%
R 7
 
6.7%
O 4
 
3.8%
l 4
 
3.8%
M 4
 
3.8%
F 4
 
3.8%
Other values (17) 27
25.7%
Common
ValueCountFrequency (%)
135
48.7%
) 64
23.1%
( 64
23.1%
2 7
 
2.5%
1 3
 
1.1%
- 1
 
0.4%
4 1
 
0.4%
5 1
 
0.4%
+ 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1727
81.9%
ASCII 382
 
18.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
135
35.3%
) 64
16.8%
( 64
16.8%
S 17
 
4.5%
E 11
 
2.9%
G 11
 
2.9%
T 8
 
2.1%
H 8
 
2.1%
2 7
 
1.8%
R 7
 
1.8%
Other values (26) 50
 
13.1%
Hangul
ValueCountFrequency (%)
99
 
5.7%
88
 
5.1%
78
 
4.5%
68
 
3.9%
64
 
3.7%
61
 
3.5%
61
 
3.5%
42
 
2.4%
39
 
2.3%
36
 
2.1%
Other values (202) 1091
63.2%
Distinct149
Distinct (%)65.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2007-06-30 11:12:41
Maximum2024-03-30 17:43:54
2024-04-29T21:37:32.818116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:32.954572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct2
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
I
140 
U
86 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 140
61.9%
U 86
38.1%

Length

2024-04-29T21:37:33.063622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:33.143507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 140
61.9%
u 86
38.1%
Distinct81
Distinct (%)35.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2018-08-31 23:59:59
Maximum2024-04-01 02:40:00
2024-04-29T21:37:33.234514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-29T21:37:33.354769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

Distinct9
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
그 밖의 대규모점포
112 
대형마트
60 
쇼핑센터
13 
구분없음
 
11
시장
 
11
Other values (4)
19 

Length

Max length10
Median length5
Mean length6.8584071
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

1st row그 밖의 대규모점포
2nd row그 밖의 대규모점포
3rd row구분없음
4th row전문점
5th row그 밖의 대규모점포

Common Values

ValueCountFrequency (%)
그 밖의 대규모점포 112
49.6%
대형마트 60
26.5%
쇼핑센터 13
 
5.8%
구분없음 11
 
4.9%
시장 11
 
4.9%
복합쇼핑몰 7
 
3.1%
전문점 6
 
2.7%
백화점 5
 
2.2%
<NA> 1
 
0.4%

Length

2024-04-29T21:37:33.474860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:33.581627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
112
24.9%
밖의 112
24.9%
대규모점포 112
24.9%
대형마트 60
13.3%
쇼핑센터 13
 
2.9%
구분없음 11
 
2.4%
시장 11
 
2.4%
복합쇼핑몰 7
 
1.6%
전문점 6
 
1.3%
백화점 5
 
1.1%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct145
Distinct (%)87.9%
Missing61
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean342619.56
Minimum199145.32
Maximum356223.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-29T21:37:33.717599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199145.32
5-th percentile337115.9
Q1339735.1
median343820.41
Q3346013.65
95-th percentile352962.98
Maximum356223.24
Range157077.92
Interquartile range (IQR)6278.5488

Descriptive statistics

Standard deviation12202.735
Coefficient of variation (CV)0.03561599
Kurtosis117.91278
Mean342619.56
Median Absolute Deviation (MAD)3102.1541
Skewness-9.9830441
Sum56532227
Variance1.4890674 × 108
MonotonicityNot monotonic
2024-04-29T21:37:33.848552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343510.573192364 4
 
1.8%
341860.419648281 3
 
1.3%
349426.805402323 2
 
0.9%
338560.694882634 2
 
0.9%
353893.90529968 2
 
0.9%
352335.045028381 2
 
0.9%
347420.400131212 2
 
0.9%
347757.985568431 2
 
0.9%
345973.900997038 2
 
0.9%
338898.15784325 2
 
0.9%
Other values (135) 142
62.8%
(Missing) 61
27.0%
ValueCountFrequency (%)
199145.32420106 1
0.4%
328501.384301002 1
0.4%
330601.335825737 1
0.4%
332209.678232161 1
0.4%
334682.626097655 1
0.4%
335707.743212212 1
0.4%
335728.273516917 1
0.4%
336343.945542934 1
0.4%
337097.037439529 1
0.4%
337191.345792727 1
0.4%
ValueCountFrequency (%)
356223.244084316 1
0.4%
355939.362329351 1
0.4%
355857.357218327 1
0.4%
355855.955513013 1
0.4%
354859.878411554 1
0.4%
353893.90529968 2
0.9%
353326.345101284 1
0.4%
352986.591397707 1
0.4%
352868.53664899 1
0.4%
352335.045028381 2
0.9%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct145
Distinct (%)87.9%
Missing61
Missing (%)27.0%
Infinite0
Infinite (%)0.0%
Mean264994.98
Minimum240739.94
Maximum451040.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.1 KiB
2024-04-29T21:37:33.978610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240739.94
5-th percentile258524.26
Q1261625.05
median264105.41
Q3266134.26
95-th percentile271593.9
Maximum451040.43
Range210300.49
Interquartile range (IQR)4509.2079

Descriptive statistics

Standard deviation15251.676
Coefficient of variation (CV)0.057554585
Kurtosis137.0735
Mean264994.98
Median Absolute Deviation (MAD)2272.4417
Skewness11.146722
Sum43724171
Variance2.3261362 × 108
MonotonicityNot monotonic
2024-04-29T21:37:34.102080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
266134.259920881 4
 
1.8%
264004.459308992 3
 
1.3%
266377.854783573 2
 
0.9%
261656.240623114 2
 
0.9%
261327.132869664 2
 
0.9%
260158.750203679 2
 
0.9%
259103.97403926 2
 
0.9%
264692.744180043 2
 
0.9%
262874.677491731 2
 
0.9%
271593.897503132 2
 
0.9%
Other values (135) 142
62.8%
(Missing) 61
27.0%
ValueCountFrequency (%)
240739.938522968 1
0.4%
244543.552402647 1
0.4%
244660.404545869 1
0.4%
257347.594572499 1
0.4%
257587.994732084 1
0.4%
258136.225468779 1
0.4%
258171.802787206 1
0.4%
258241.360670906 1
0.4%
258512.316695219 1
0.4%
258572.019825526 1
0.4%
ValueCountFrequency (%)
451040.432662092 1
0.4%
272735.675659876 2
0.9%
272659.975074019 2
0.9%
272394.00290408 1
0.4%
271944.939697366 1
0.4%
271647.094222276 1
0.4%
271593.897503132 2
0.9%
271557.940207262 1
0.4%
271332.920191127 1
0.4%
271331.088251183 1
0.4%

점포구분명
Categorical

Distinct3
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
<NA>
99 
대규모점포
84 
준대규모점포
43 

Length

Max length6
Median length5
Mean length4.7522124
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 99
43.8%
대규모점포 84
37.2%
준대규모점포 43
19.0%

Length

2024-04-29T21:37:34.439099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-29T21:37:34.534078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 99
43.8%
대규모점포 84
37.2%
준대규모점포 43
19.0%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
01대규모점포08_25_01_P341000020193410130075000012019-09-25<NA>1영업/정상1정상영업<NA><NA><NA><NA>053-766-186013179.89<NA>대구광역시 중구 공평동 58번지 6호대구광역시 중구 동성로6길 61 (공평동)41938태왕스파크2020-07-09 10:07:21U2020-07-11 02:40:00그 밖의 대규모점포344317.219568264349.485186대규모점포
12대규모점포08_25_01_P341000019773410046075000021977-12-14<NA>1영업/정상1정상영업<NA><NA><NA><NA>053-257-356210799.72<NA>대구광역시 중구 대신동 115-30 동산상가대구광역시 중구 큰장로26길 65, 동산상가 (대신동)41926동산상가2023-04-14 09:23:42U2023-04-16 02:40:00그 밖의 대규모점포342780.445665264345.364396대규모점포
23대규모점포08_25_01_P341000020243410163075000012024-01-17<NA>1영업/정상5영업개시전<NA><NA><NA><NA><NA>136.4<NA>대구광역시 중구 수창동 178 대구역 제일풍경채 위너스카이대구광역시 중구 달성로26길 70, 상가동 106호, 108~110호 (수창동, 대구역 제일풍경채 위너스카이)41920GS THE FRESH 대구역풍경채점2024-01-17 11:46:42I2024-01-19 00:16:25구분없음<NA><NA>준대규모점포
34대규모점포08_25_01_P341000020063410013075000022006-09-152020-10-084취소/말소/만료/정지/중지4직권취소<NA><NA><NA><NA>053 421 93233804.08<NA>대구광역시 중구 삼덕동1가 5번지 2 호대구광역시 중구 동성로5길 25 (삼덕동1가)<NA>유플러스2020-10-08 17:57:24U2020-10-10 02:40:00전문점344075.953606264266.216087대규모점포
45대규모점포08_25_01_P341000020013410013075000122001-08-20<NA>3폐업3폐업처리2007-09-04<NA><NA><NA>02 6373 11170.0<NA>대구광역시 중구 문화동 11번지 1호대구광역시 중구 국채보상로 611 (문화동)<NA>대구밀리오레2010-11-02 14:59:06I2018-08-31 23:59:59그 밖의 대규모점포344223.636477264597.611089<NA>
56대규모점포08_25_01_P341000020003410051075000012000-12-07<NA>3폐업3폐업처리2010-05-10<NA><NA><NA>053 421 56580.0<NA>대구광역시 중구 동성로2가 88-22호<NA><NA>한일밀라노존2011-03-11 15:07:22I2018-08-31 23:59:59전문점<NA><NA><NA>
67대규모점포08_25_01_P341000019983410105075000011998-03-30<NA>3폐업3폐업처리2022-02-232021-09-152022-09-14<NA>053423123422026.27<NA><NA>대구광역시 중구 동성로 30 (동성로2가)700-716대구백화점2022-02-23 13:10:49U2022-02-25 02:40:00백화점344047.979265264405.128696대규모점포
78대규모점포08_25_01_P341000020013410013075200112001-07-04<NA>3폐업3폐업처리2007-02-07<NA><NA><NA>053 428 43000.0<NA>대구광역시 중구 공평동 55번지 54 호대구광역시 중구 동성로6길 36 (공평동)<NA>이스테이션2010-11-02 15:13:35I2018-08-31 23:59:59그 밖의 대규모점포344182.117576264325.505092<NA>
89대규모점포08_25_01_P341000020073410071075000012007-08-23<NA>3폐업3폐업처리2020-12-18<NA><NA><NA>053 609 140015668.17<NA>대구광역시 중구 사일동 15번지 1호 동성로파티대구광역시 중구 국채보상로 585 (사일동)41909동성로 파티2020-12-18 17:16:32U2020-12-20 02:40:00쇼핑센터343932.18838264630.944873대규모점포
910대규모점포08_25_01_P341000020103410071075000011997-08-26<NA>3폐업3폐업처리2021-12-30<NA><NA><NA>053 429 42309364.27700-711대구광역시 중구 동문동 20번지 4호 외 6필지대구광역시 중구 경상감영길 171 (동문동,외 6필지)<NA>동아아울렛 동문본점2021-12-31 11:08:20U2022-01-02 02:40:00백화점344148.352033264812.35373대규모점포
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)점포구분명
216217대규모점포08_25_01_P347000020143470117075000052011-07-21<NA>3폐업3폐업처리2017-10-24<NA><NA><NA>643-0631676.0704-758대구광역시 달서구 상인동 1475번지대구광역시 달서구 상화북로 160, A동 101호 (상인동, 백조아파트상가)704-758(주)지에스리테일 GS수퍼 대구상인점2017-10-26 13:47:20I2018-08-31 23:59:59대형마트<NA><NA>준대규모점포
217218대규모점포08_25_01_P347000020143470117075000062011-07-21<NA>3폐업3폐업처리2017-10-24<NA><NA><NA>716-8003718.0704-819대구광역시 달서구 상인동 1595번지대구광역시 달서구 조암남로 17, 101~103호 (상인동)704-819(주)지에스리테일 GS수퍼 대구월서점2017-10-26 13:47:40I2018-08-31 23:59:59대형마트338300.745101259066.123688준대규모점포
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